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• Published: 04 June 2021

Coronavirus disease (COVID-19) pandemic: an overview of systematic reviews

• Israel Júnior Borges do Nascimento 1 , 2 ,
• Dónal P. O’Mathúna 3 , 4 ,
• Thilo Caspar von Groote 5 ,
• Hebatullah Mohamed Abdulazeem 6 ,
• Ishanka Weerasekara 7 , 8 ,
• Ana Marusic 9 ,
• Livia Puljak   ORCID: orcid.org/0000-0002-8467-6061 10 ,
• Vinicius Tassoni Civile 11 ,
• Irena Zakarija-Grkovic 9 ,
• Tina Poklepovic Pericic 9 ,
• Alvaro Nagib Atallah 11 ,
• Santino Filoso 12 ,
• Nicola Luigi Bragazzi 13 &
• Milena Soriano Marcolino 1

On behalf of the International Network of Coronavirus Disease 2019 (InterNetCOVID-19)

BMC Infectious Diseases volume  21 , Article number:  525 ( 2021 ) Cite this article

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Navigating the rapidly growing body of scientific literature on the SARS-CoV-2 pandemic is challenging, and ongoing critical appraisal of this output is essential. We aimed to summarize and critically appraise systematic reviews of coronavirus disease (COVID-19) in humans that were available at the beginning of the pandemic.

Nine databases (Medline, EMBASE, Cochrane Library, CINAHL, Web of Sciences, PDQ-Evidence, WHO’s Global Research, LILACS, and Epistemonikos) were searched from December 1, 2019, to March 24, 2020. Systematic reviews analyzing primary studies of COVID-19 were included. Two authors independently undertook screening, selection, extraction (data on clinical symptoms, prevalence, pharmacological and non-pharmacological interventions, diagnostic test assessment, laboratory, and radiological findings), and quality assessment (AMSTAR 2). A meta-analysis was performed of the prevalence of clinical outcomes.

Eighteen systematic reviews were included; one was empty (did not identify any relevant study). Using AMSTAR 2, confidence in the results of all 18 reviews was rated as “critically low”. Identified symptoms of COVID-19 were (range values of point estimates): fever (82–95%), cough with or without sputum (58–72%), dyspnea (26–59%), myalgia or muscle fatigue (29–51%), sore throat (10–13%), headache (8–12%) and gastrointestinal complaints (5–9%). Severe symptoms were more common in men. Elevated C-reactive protein and lactate dehydrogenase, and slightly elevated aspartate and alanine aminotransferase, were commonly described. Thrombocytopenia and elevated levels of procalcitonin and cardiac troponin I were associated with severe disease. A frequent finding on chest imaging was uni- or bilateral multilobar ground-glass opacity. A single review investigated the impact of medication (chloroquine) but found no verifiable clinical data. All-cause mortality ranged from 0.3 to 13.9%.

Conclusions

In this overview of systematic reviews, we analyzed evidence from the first 18 systematic reviews that were published after the emergence of COVID-19. However, confidence in the results of all reviews was “critically low”. Thus, systematic reviews that were published early on in the pandemic were of questionable usefulness. Even during public health emergencies, studies and systematic reviews should adhere to established methodological standards.

Peer Review reports

The spread of the “Severe Acute Respiratory Coronavirus 2” (SARS-CoV-2), the causal agent of COVID-19, was characterized as a pandemic by the World Health Organization (WHO) in March 2020 and has triggered an international public health emergency [ 1 ]. The numbers of confirmed cases and deaths due to COVID-19 are rapidly escalating, counting in millions [ 2 ], causing massive economic strain, and escalating healthcare and public health expenses [ 3 , 4 ].

The research community has responded by publishing an impressive number of scientific reports related to COVID-19. The world was alerted to the new disease at the beginning of 2020 [ 1 ], and by mid-March 2020, more than 2000 articles had been published on COVID-19 in scholarly journals, with 25% of them containing original data [ 5 ]. The living map of COVID-19 evidence, curated by the Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-Centre), contained more than 40,000 records by February 2021 [ 6 ]. More than 100,000 records on PubMed were labeled as “SARS-CoV-2 literature, sequence, and clinical content” by February 2021 [ 7 ].

Due to publication speed, the research community has voiced concerns regarding the quality and reproducibility of evidence produced during the COVID-19 pandemic, warning of the potential damaging approach of “publish first, retract later” [ 8 ]. It appears that these concerns are not unfounded, as it has been reported that COVID-19 articles were overrepresented in the pool of retracted articles in 2020 [ 9 ]. These concerns about inadequate evidence are of major importance because they can lead to poor clinical practice and inappropriate policies [ 10 ].

Systematic reviews are a cornerstone of today’s evidence-informed decision-making. By synthesizing all relevant evidence regarding a particular topic, systematic reviews reflect the current scientific knowledge. Systematic reviews are considered to be at the highest level in the hierarchy of evidence and should be used to make informed decisions. However, with high numbers of systematic reviews of different scope and methodological quality being published, overviews of multiple systematic reviews that assess their methodological quality are essential [ 11 , 12 , 13 ]. An overview of systematic reviews helps identify and organize the literature and highlights areas of priority in decision-making.

In this overview of systematic reviews, we aimed to summarize and critically appraise systematic reviews of coronavirus disease (COVID-19) in humans that were available at the beginning of the pandemic.

Methodology

Research question.

This overview’s primary objective was to summarize and critically appraise systematic reviews that assessed any type of primary clinical data from patients infected with SARS-CoV-2. Our research question was purposefully broad because we wanted to analyze as many systematic reviews as possible that were available early following the COVID-19 outbreak.

Study design

We conducted an overview of systematic reviews. The idea for this overview originated in a protocol for a systematic review submitted to PROSPERO (CRD42020170623), which indicated a plan to conduct an overview.

Overviews of systematic reviews use explicit and systematic methods for searching and identifying multiple systematic reviews addressing related research questions in the same field to extract and analyze evidence across important outcomes. Overviews of systematic reviews are in principle similar to systematic reviews of interventions, but the unit of analysis is a systematic review [ 14 , 15 , 16 ].

We used the overview methodology instead of other evidence synthesis methods to allow us to collate and appraise multiple systematic reviews on this topic, and to extract and analyze their results across relevant topics [ 17 ]. The overview and meta-analysis of systematic reviews allowed us to investigate the methodological quality of included studies, summarize results, and identify specific areas of available or limited evidence, thereby strengthening the current understanding of this novel disease and guiding future research [ 13 ].

A reporting guideline for overviews of reviews is currently under development, i.e., Preferred Reporting Items for Overviews of Reviews (PRIOR) [ 18 ]. As the PRIOR checklist is still not published, this study was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 statement [ 19 ]. The methodology used in this review was adapted from the Cochrane Handbook for Systematic Reviews of Interventions and also followed established methodological considerations for analyzing existing systematic reviews [ 14 ].

Approval of a research ethics committee was not necessary as the study analyzed only publicly available articles.

Eligibility criteria

Systematic reviews were included if they analyzed primary data from patients infected with SARS-CoV-2 as confirmed by RT-PCR or another pre-specified diagnostic technique. Eligible reviews covered all topics related to COVID-19 including, but not limited to, those that reported clinical symptoms, diagnostic methods, therapeutic interventions, laboratory findings, or radiological results. Both full manuscripts and abbreviated versions, such as letters, were eligible.

No restrictions were imposed on the design of the primary studies included within the systematic reviews, the last search date, whether the review included meta-analyses or language. Reviews related to SARS-CoV-2 and other coronaviruses were eligible, but from those reviews, we analyzed only data related to SARS-CoV-2.

No consensus definition exists for a systematic review [ 20 ], and debates continue about the defining characteristics of a systematic review [ 21 ]. Cochrane’s guidance for overviews of reviews recommends setting pre-established criteria for making decisions around inclusion [ 14 ]. That is supported by a recent scoping review about guidance for overviews of systematic reviews [ 22 ].

Thus, for this study, we defined a systematic review as a research report which searched for primary research studies on a specific topic using an explicit search strategy, had a detailed description of the methods with explicit inclusion criteria provided, and provided a summary of the included studies either in narrative or quantitative format (such as a meta-analysis). Cochrane and non-Cochrane systematic reviews were considered eligible for inclusion, with or without meta-analysis, and regardless of the study design, language restriction and methodology of the included primary studies. To be eligible for inclusion, reviews had to be clearly analyzing data related to SARS-CoV-2 (associated or not with other viruses). We excluded narrative reviews without those characteristics as these are less likely to be replicable and are more prone to bias.

Scoping reviews and rapid reviews were eligible for inclusion in this overview if they met our pre-defined inclusion criteria noted above. We included reviews that addressed SARS-CoV-2 and other coronaviruses if they reported separate data regarding SARS-CoV-2.

Information sources

Nine databases were searched for eligible records published between December 1, 2019, and March 24, 2020: Cochrane Database of Systematic Reviews via Cochrane Library, PubMed, EMBASE, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Sciences, LILACS (Latin American and Caribbean Health Sciences Literature), PDQ-Evidence, WHO’s Global Research on Coronavirus Disease (COVID-19), and Epistemonikos.

The comprehensive search strategy for each database is provided in Additional file 1 and was designed and conducted in collaboration with an information specialist. All retrieved records were primarily processed in EndNote, where duplicates were removed, and records were then imported into the Covidence platform [ 23 ]. In addition to database searches, we screened reference lists of reviews included after screening records retrieved via databases.

Study selection

All searches, screening of titles and abstracts, and record selection, were performed independently by two investigators using the Covidence platform [ 23 ]. Articles deemed potentially eligible were retrieved for full-text screening carried out independently by two investigators. Discrepancies at all stages were resolved by consensus. During the screening, records published in languages other than English were translated by a native/fluent speaker.

Data collection process

We custom designed a data extraction table for this study, which was piloted by two authors independently. Data extraction was performed independently by two authors. Conflicts were resolved by consensus or by consulting a third researcher.

We extracted the following data: article identification data (authors’ name and journal of publication), search period, number of databases searched, population or settings considered, main results and outcomes observed, and number of participants. From Web of Science (Clarivate Analytics, Philadelphia, PA, USA), we extracted journal rank (quartile) and Journal Impact Factor (JIF).

We categorized the following as primary outcomes: all-cause mortality, need for and length of mechanical ventilation, length of hospitalization (in days), admission to intensive care unit (yes/no), and length of stay in the intensive care unit.

The following outcomes were categorized as exploratory: diagnostic methods used for detection of the virus, male to female ratio, clinical symptoms, pharmacological and non-pharmacological interventions, laboratory findings (full blood count, liver enzymes, C-reactive protein, d-dimer, albumin, lipid profile, serum electrolytes, blood vitamin levels, glucose levels, and any other important biomarkers), and radiological findings (using radiography, computed tomography, magnetic resonance imaging or ultrasound).

We also collected data on reporting guidelines and requirements for the publication of systematic reviews and meta-analyses from journal websites where included reviews were published.

Quality assessment in individual reviews

Two researchers independently assessed the reviews’ quality using the “A MeaSurement Tool to Assess Systematic Reviews 2 (AMSTAR 2)”. We acknowledge that the AMSTAR 2 was created as “a critical appraisal tool for systematic reviews that include randomized or non-randomized studies of healthcare interventions, or both” [ 24 ]. However, since AMSTAR 2 was designed for systematic reviews of intervention trials, and we included additional types of systematic reviews, we adjusted some AMSTAR 2 ratings and reported these in Additional file 2 .

Adherence to each item was rated as follows: yes, partial yes, no, or not applicable (such as when a meta-analysis was not conducted). The overall confidence in the results of the review is rated as “critically low”, “low”, “moderate” or “high”, according to the AMSTAR 2 guidance based on seven critical domains, which are items 2, 4, 7, 9, 11, 13, 15 as defined by AMSTAR 2 authors [ 24 ]. We reported our adherence ratings for transparency of our decision with accompanying explanations, for each item, in each included review.

One of the included systematic reviews was conducted by some members of this author team [ 25 ]. This review was initially assessed independently by two authors who were not co-authors of that review to prevent the risk of bias in assessing this study.

Synthesis of results

For data synthesis, we prepared a table summarizing each systematic review. Graphs illustrating the mortality rate and clinical symptoms were created. We then prepared a narrative summary of the methods, findings, study strengths, and limitations.

For analysis of the prevalence of clinical outcomes, we extracted data on the number of events and the total number of patients to perform proportional meta-analysis using RStudio© software, with the “meta” package (version 4.9–6), using the “metaprop” function for reviews that did not perform a meta-analysis, excluding case studies because of the absence of variance. For reviews that did not perform a meta-analysis, we presented pooled results of proportions with their respective confidence intervals (95%) by the inverse variance method with a random-effects model, using the DerSimonian-Laird estimator for τ 2 . We adjusted data using Freeman-Tukey double arcosen transformation. Confidence intervals were calculated using the Clopper-Pearson method for individual studies. We created forest plots using the RStudio© software, with the “metafor” package (version 2.1–0) and “forest” function.

Managing overlapping systematic reviews

Some of the included systematic reviews that address the same or similar research questions may include the same primary studies in overviews. Including such overlapping reviews may introduce bias when outcome data from the same primary study are included in the analyses of an overview multiple times. Thus, in summaries of evidence, multiple-counting of the same outcome data will give data from some primary studies too much influence [ 14 ]. In this overview, we did not exclude overlapping systematic reviews because, according to Cochrane’s guidance, it may be appropriate to include all relevant reviews’ results if the purpose of the overview is to present and describe the current body of evidence on a topic [ 14 ]. To avoid any bias in summary estimates associated with overlapping reviews, we generated forest plots showing data from individual systematic reviews, but the results were not pooled because some primary studies were included in multiple reviews.

Our search retrieved 1063 publications, of which 175 were duplicates. Most publications were excluded after the title and abstract analysis ( n = 860). Among the 28 studies selected for full-text screening, 10 were excluded for the reasons described in Additional file 3 , and 18 were included in the final analysis (Fig. 1 ) [ 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ]. Reference list screening did not retrieve any additional systematic reviews.

PRISMA flow diagram

Characteristics of included reviews

Summary features of 18 systematic reviews are presented in Table 1 . They were published in 14 different journals. Only four of these journals had specific requirements for systematic reviews (with or without meta-analysis): European Journal of Internal Medicine, Journal of Clinical Medicine, Ultrasound in Obstetrics and Gynecology, and Clinical Research in Cardiology . Two journals reported that they published only invited reviews ( Journal of Medical Virology and Clinica Chimica Acta ). Three systematic reviews in our study were published as letters; one was labeled as a scoping review and another as a rapid review (Table 2 ).

All reviews were published in English, in first quartile (Q1) journals, with JIF ranging from 1.692 to 6.062. One review was empty, meaning that its search did not identify any relevant studies; i.e., no primary studies were included [ 36 ]. The remaining 17 reviews included 269 unique studies; the majority ( N = 211; 78%) were included in only a single review included in our study (range: 1 to 12). Primary studies included in the reviews were published between December 2019 and March 18, 2020, and comprised case reports, case series, cohorts, and other observational studies. We found only one review that included randomized clinical trials [ 38 ]. In the included reviews, systematic literature searches were performed from 2019 (entire year) up to March 9, 2020. Ten systematic reviews included meta-analyses. The list of primary studies found in the included systematic reviews is shown in Additional file 4 , as well as the number of reviews in which each primary study was included.

Population and study designs

Most of the reviews analyzed data from patients with COVID-19 who developed pneumonia, acute respiratory distress syndrome (ARDS), or any other correlated complication. One review aimed to evaluate the effectiveness of using surgical masks on preventing transmission of the virus [ 36 ], one review was focused on pediatric patients [ 34 ], and one review investigated COVID-19 in pregnant women [ 37 ]. Most reviews assessed clinical symptoms, laboratory findings, or radiological results.

Systematic review findings

The summary of findings from individual reviews is shown in Table 2 . Overall, all-cause mortality ranged from 0.3 to 13.9% (Fig. 2 ).

A meta-analysis of the prevalence of mortality

Clinical symptoms

Seven reviews described the main clinical manifestations of COVID-19 [ 26 , 28 , 29 , 34 , 35 , 39 , 41 ]. Three of them provided only a narrative discussion of symptoms [ 26 , 34 , 35 ]. In the reviews that performed a statistical analysis of the incidence of different clinical symptoms, symptoms in patients with COVID-19 were (range values of point estimates): fever (82–95%), cough with or without sputum (58–72%), dyspnea (26–59%), myalgia or muscle fatigue (29–51%), sore throat (10–13%), headache (8–12%), gastrointestinal disorders, such as diarrhea, nausea or vomiting (5.0–9.0%), and others (including, in one study only: dizziness 12.1%) (Figs. 3 , 4 , 5 , 6 , 7 , 8 and 9 ). Three reviews assessed cough with and without sputum together; only one review assessed sputum production itself (28.5%).

A meta-analysis of the prevalence of fever

A meta-analysis of the prevalence of cough

A meta-analysis of the prevalence of dyspnea

A meta-analysis of the prevalence of fatigue or myalgia

A meta-analysis of the prevalence of headache

A meta-analysis of the prevalence of gastrointestinal disorders

A meta-analysis of the prevalence of sore throat

Diagnostic aspects

Three reviews described methodologies, protocols, and tools used for establishing the diagnosis of COVID-19 [ 26 , 34 , 38 ]. The use of respiratory swabs (nasal or pharyngeal) or blood specimens to assess the presence of SARS-CoV-2 nucleic acid using RT-PCR assays was the most commonly used diagnostic method mentioned in the included studies. These diagnostic tests have been widely used, but their precise sensitivity and specificity remain unknown. One review included a Chinese study with clinical diagnosis with no confirmation of SARS-CoV-2 infection (patients were diagnosed with COVID-19 if they presented with at least two symptoms suggestive of COVID-19, together with laboratory and chest radiography abnormalities) [ 34 ].

Therapeutic possibilities

Pharmacological and non-pharmacological interventions (supportive therapies) used in treating patients with COVID-19 were reported in five reviews [ 25 , 27 , 34 , 35 , 38 ]. Antivirals used empirically for COVID-19 treatment were reported in seven reviews [ 25 , 27 , 34 , 35 , 37 , 38 , 41 ]; most commonly used were protease inhibitors (lopinavir, ritonavir, darunavir), nucleoside reverse transcriptase inhibitor (tenofovir), nucleotide analogs (remdesivir, galidesivir, ganciclovir), and neuraminidase inhibitors (oseltamivir). Umifenovir, a membrane fusion inhibitor, was investigated in two studies [ 25 , 35 ]. Possible supportive interventions analyzed were different types of oxygen supplementation and breathing support (invasive or non-invasive ventilation) [ 25 ]. The use of antibiotics, both empirically and to treat secondary pneumonia, was reported in six studies [ 25 , 26 , 27 , 34 , 35 , 38 ]. One review specifically assessed evidence on the efficacy and safety of the anti-malaria drug chloroquine [ 27 ]. It identified 23 ongoing trials investigating the potential of chloroquine as a therapeutic option for COVID-19, but no verifiable clinical outcomes data. The use of mesenchymal stem cells, antifungals, and glucocorticoids were described in four reviews [ 25 , 34 , 35 , 38 ].

Laboratory and radiological findings

Of the 18 reviews included in this overview, eight analyzed laboratory parameters in patients with COVID-19 [ 25 , 29 , 30 , 32 , 33 , 34 , 35 , 39 ]; elevated C-reactive protein levels, associated with lymphocytopenia, elevated lactate dehydrogenase, as well as slightly elevated aspartate and alanine aminotransferase (AST, ALT) were commonly described in those eight reviews. Lippi et al. assessed cardiac troponin I (cTnI) [ 25 ], procalcitonin [ 32 ], and platelet count [ 33 ] in COVID-19 patients. Elevated levels of procalcitonin [ 32 ] and cTnI [ 30 ] were more likely to be associated with a severe disease course (requiring intensive care unit admission and intubation). Furthermore, thrombocytopenia was frequently observed in patients with complicated COVID-19 infections [ 33 ].

Chest imaging (chest radiography and/or computed tomography) features were assessed in six reviews, all of which described a frequent pattern of local or bilateral multilobar ground-glass opacity [ 25 , 34 , 35 , 39 , 40 , 41 ]. Those six reviews showed that septal thickening, bronchiectasis, pleural and cardiac effusions, halo signs, and pneumothorax were observed in patients suffering from COVID-19.

Quality of evidence in individual systematic reviews

Table 3 shows the detailed results of the quality assessment of 18 systematic reviews, including the assessment of individual items and summary assessment. A detailed explanation for each decision in each review is available in Additional file 5 .

Using AMSTAR 2 criteria, confidence in the results of all 18 reviews was rated as “critically low” (Table 3 ). Common methodological drawbacks were: omission of prospective protocol submission or publication; use of inappropriate search strategy: lack of independent and dual literature screening and data-extraction (or methodology unclear); absence of an explanation for heterogeneity among the studies included; lack of reasons for study exclusion (or rationale unclear).

Risk of bias assessment, based on a reported methodological tool, and quality of evidence appraisal, in line with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) method, were reported only in one review [ 25 ]. Five reviews presented a table summarizing bias, using various risk of bias tools [ 25 , 29 , 39 , 40 , 41 ]. One review analyzed “study quality” [ 37 ]. One review mentioned the risk of bias assessment in the methodology but did not provide any related analysis [ 28 ].

This overview of systematic reviews analyzed the first 18 systematic reviews published after the onset of the COVID-19 pandemic, up to March 24, 2020, with primary studies involving more than 60,000 patients. Using AMSTAR-2, we judged that our confidence in all those reviews was “critically low”. Ten reviews included meta-analyses. The reviews presented data on clinical manifestations, laboratory and radiological findings, and interventions. We found no systematic reviews on the utility of diagnostic tests.

Symptoms were reported in seven reviews; most of the patients had a fever, cough, dyspnea, myalgia or muscle fatigue, and gastrointestinal disorders such as diarrhea, nausea, or vomiting. Olfactory dysfunction (anosmia or dysosmia) has been described in patients infected with COVID-19 [ 43 ]; however, this was not reported in any of the reviews included in this overview. During the SARS outbreak in 2002, there were reports of impairment of the sense of smell associated with the disease [ 44 , 45 ].

The reported mortality rates ranged from 0.3 to 14% in the included reviews. Mortality estimates are influenced by the transmissibility rate (basic reproduction number), availability of diagnostic tools, notification policies, asymptomatic presentations of the disease, resources for disease prevention and control, and treatment facilities; variability in the mortality rate fits the pattern of emerging infectious diseases [ 46 ]. Furthermore, the reported cases did not consider asymptomatic cases, mild cases where individuals have not sought medical treatment, and the fact that many countries had limited access to diagnostic tests or have implemented testing policies later than the others. Considering the lack of reviews assessing diagnostic testing (sensitivity, specificity, and predictive values of RT-PCT or immunoglobulin tests), and the preponderance of studies that assessed only symptomatic individuals, considerable imprecision around the calculated mortality rates existed in the early stage of the COVID-19 pandemic.

Few reviews included treatment data. Those reviews described studies considered to be at a very low level of evidence: usually small, retrospective studies with very heterogeneous populations. Seven reviews analyzed laboratory parameters; those reviews could have been useful for clinicians who attend patients suspected of COVID-19 in emergency services worldwide, such as assessing which patients need to be reassessed more frequently.

All systematic reviews scored poorly on the AMSTAR 2 critical appraisal tool for systematic reviews. Most of the original studies included in the reviews were case series and case reports, impacting the quality of evidence. Such evidence has major implications for clinical practice and the use of these reviews in evidence-based practice and policy. Clinicians, patients, and policymakers can only have the highest confidence in systematic review findings if high-quality systematic review methodologies are employed. The urgent need for information during a pandemic does not justify poor quality reporting.

We acknowledge that there are numerous challenges associated with analyzing COVID-19 data during a pandemic [ 47 ]. High-quality evidence syntheses are needed for decision-making, but each type of evidence syntheses is associated with its inherent challenges.

The creation of classic systematic reviews requires considerable time and effort; with massive research output, they quickly become outdated, and preparing updated versions also requires considerable time. A recent study showed that updates of non-Cochrane systematic reviews are published a median of 5 years after the publication of the previous version [ 48 ].

Authors may register a review and then abandon it [ 49 ], but the existence of a public record that is not updated may lead other authors to believe that the review is still ongoing. A quarter of Cochrane review protocols remains unpublished as completed systematic reviews 8 years after protocol publication [ 50 ].

Rapid reviews can be used to summarize the evidence, but they involve methodological sacrifices and simplifications to produce information promptly, with inconsistent methodological approaches [ 51 ]. However, rapid reviews are justified in times of public health emergencies, and even Cochrane has resorted to publishing rapid reviews in response to the COVID-19 crisis [ 52 ]. Rapid reviews were eligible for inclusion in this overview, but only one of the 18 reviews included in this study was labeled as a rapid review.

Ideally, COVID-19 evidence would be continually summarized in a series of high-quality living systematic reviews, types of evidence synthesis defined as “ a systematic review which is continually updated, incorporating relevant new evidence as it becomes available ” [ 53 ]. However, conducting living systematic reviews requires considerable resources, calling into question the sustainability of such evidence synthesis over long periods [ 54 ].

Research reports about COVID-19 will contribute to research waste if they are poorly designed, poorly reported, or simply not necessary. In principle, systematic reviews should help reduce research waste as they usually provide recommendations for further research that is needed or may advise that sufficient evidence exists on a particular topic [ 55 ]. However, systematic reviews can also contribute to growing research waste when they are not needed, or poorly conducted and reported. Our present study clearly shows that most of the systematic reviews that were published early on in the COVID-19 pandemic could be categorized as research waste, as our confidence in their results is critically low.

Our study has some limitations. One is that for AMSTAR 2 assessment we relied on information available in publications; we did not attempt to contact study authors for clarifications or additional data. In three reviews, the methodological quality appraisal was challenging because they were published as letters, or labeled as rapid communications. As a result, various details about their review process were not included, leading to AMSTAR 2 questions being answered as “not reported”, resulting in low confidence scores. Full manuscripts might have provided additional information that could have led to higher confidence in the results. In other words, low scores could reflect incomplete reporting, not necessarily low-quality review methods. To make their review available more rapidly and more concisely, the authors may have omitted methodological details. A general issue during a crisis is that speed and completeness must be balanced. However, maintaining high standards requires proper resourcing and commitment to ensure that the users of systematic reviews can have high confidence in the results.

Furthermore, we used adjusted AMSTAR 2 scoring, as the tool was designed for critical appraisal of reviews of interventions. Some reviews may have received lower scores than actually warranted in spite of these adjustments.

Another limitation of our study may be the inclusion of multiple overlapping reviews, as some included reviews included the same primary studies. According to the Cochrane Handbook, including overlapping reviews may be appropriate when the review’s aim is “ to present and describe the current body of systematic review evidence on a topic ” [ 12 ], which was our aim. To avoid bias with summarizing evidence from overlapping reviews, we presented the forest plots without summary estimates. The forest plots serve to inform readers about the effect sizes for outcomes that were reported in each review.

Several authors from this study have contributed to one of the reviews identified [ 25 ]. To reduce the risk of any bias, two authors who did not co-author the review in question initially assessed its quality and limitations.

Finally, we note that the systematic reviews included in our overview may have had issues that our analysis did not identify because we did not analyze their primary studies to verify the accuracy of the data and information they presented. We give two examples to substantiate this possibility. Lovato et al. wrote a commentary on the review of Sun et al. [ 41 ], in which they criticized the authors’ conclusion that sore throat is rare in COVID-19 patients [ 56 ]. Lovato et al. highlighted that multiple studies included in Sun et al. did not accurately describe participants’ clinical presentations, warning that only three studies clearly reported data on sore throat [ 56 ].

In another example, Leung [ 57 ] warned about the review of Li, L.Q. et al. [ 29 ]: “ it is possible that this statistic was computed using overlapped samples, therefore some patients were double counted ”. Li et al. responded to Leung that it is uncertain whether the data overlapped, as they used data from published articles and did not have access to the original data; they also reported that they requested original data and that they plan to re-do their analyses once they receive them; they also urged readers to treat the data with caution [ 58 ]. This points to the evolving nature of evidence during a crisis.

Our study’s strength is that this overview adds to the current knowledge by providing a comprehensive summary of all the evidence synthesis about COVID-19 available early after the onset of the pandemic. This overview followed strict methodological criteria, including a comprehensive and sensitive search strategy and a standard tool for methodological appraisal of systematic reviews.

In conclusion, in this overview of systematic reviews, we analyzed evidence from the first 18 systematic reviews that were published after the emergence of COVID-19. However, confidence in the results of all the reviews was “critically low”. Thus, systematic reviews that were published early on in the pandemic could be categorized as research waste. Even during public health emergencies, studies and systematic reviews should adhere to established methodological standards to provide patients, clinicians, and decision-makers trustworthy evidence.

Availability of data and materials

All data collected and analyzed within this study are available from the corresponding author on reasonable request.

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Acknowledgments

We thank Catherine Henderson DPhil from Swanscoe Communications for pro bono medical writing and editing support. We acknowledge support from the Covidence Team, specifically Anneliese Arno. We thank the whole International Network of Coronavirus Disease 2019 (InterNetCOVID-19) for their commitment and involvement. Members of the InterNetCOVID-19 are listed in Additional file 6 . We thank Pavel Cerny and Roger Crosthwaite for guiding the team supervisor (IJBN) on human resources management.

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Israel Júnior Borges do Nascimento & Milena Soriano Marcolino

Medical College of Wisconsin, Milwaukee, WI, USA

Israel Júnior Borges do Nascimento

Helene Fuld Health Trust National Institute for Evidence-based Practice in Nursing and Healthcare, College of Nursing, The Ohio State University, Columbus, OH, USA

Dónal P. O’Mathúna

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Thilo Caspar von Groote

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Livia Puljak

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IJBN conceived the research idea and worked as a project coordinator. DPOM, TCVG, HMA, IW, AM, LP, VTC, IZG, TPP, ANA, SF, NLB and MSM were involved in data curation, formal analysis, investigation, methodology, and initial draft writing. All authors revised the manuscript critically for the content. The author(s) read and approved the final manuscript.

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Supplementary Information

Additional file 1: appendix 1..

Search strategies used in the study.

Additional file 2: Appendix 2.

Adjusted scoring of AMSTAR 2 used in this study for systematic reviews of studies that did not analyze interventions.

Additional file 3: Appendix 3.

List of excluded studies, with reasons.

Additional file 4: Appendix 4.

Table of overlapping studies, containing the list of primary studies included, their visual overlap in individual systematic reviews, and the number in how many reviews each primary study was included.

Additional file 5: Appendix 5.

A detailed explanation of AMSTAR scoring for each item in each review.

Additional file 6: Appendix 6.

List of members and affiliates of International Network of Coronavirus Disease 2019 (InterNetCOVID-19).

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Borges do Nascimento, I.J., O’Mathúna, D.P., von Groote, T.C. et al. Coronavirus disease (COVID-19) pandemic: an overview of systematic reviews. BMC Infect Dis 21 , 525 (2021). https://doi.org/10.1186/s12879-021-06214-4

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MINI REVIEW article

Covid-19: emergence, spread, possible treatments, and global burden.

• 1 Department of Pharmacology, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India
• 2 Department of Health Sciences, School of Education and Health, Cape Breton University, Sydney, NS, Canada

The Coronavirus (CoV) is a large family of viruses known to cause illnesses ranging from the common cold to acute respiratory tract infection. The severity of the infection may be visible as pneumonia, acute respiratory syndrome, and even death. Until the outbreak of SARS, this group of viruses was greatly overlooked. However, since the SARS and MERS outbreaks, these viruses have been studied in greater detail, propelling the vaccine research. On December 31, 2019, mysterious cases of pneumonia were detected in the city of Wuhan in China's Hubei Province. On January 7, 2020, the causative agent was identified as a new coronavirus (2019-nCoV), and the disease was later named as COVID-19 by the WHO. The virus spread extensively in the Wuhan region of China and has gained entry to over 210 countries and territories. Though experts suspected that the virus is transmitted from animals to humans, there are mixed reports on the origin of the virus. There are no treatment options available for the virus as such, limited to the use of anti-HIV drugs and/or other antivirals such as Remdesivir and Galidesivir. For the containment of the virus, it is recommended to quarantine the infected and to follow good hygiene practices. The virus has had a significant socio-economic impact globally. Economically, China is likely to experience a greater setback than other countries from the pandemic due to added trade war pressure, which have been discussed in this paper.

Introduction

Coronaviridae is a family of viruses with a positive-sense RNA that possess an outer viral coat. When looked at with the help of an electron microscope, there appears to be a unique corona around it. This family of viruses mainly cause respiratory diseases in humans, in the forms of common cold or pneumonia as well as respiratory infections. These viruses can infect animals as well ( 1 , 2 ). Up until the year 2003, coronavirus (CoV) had attracted limited interest from researchers. However, after the SARS (severe acute respiratory syndrome) outbreak caused by the SARS-CoV, the coronavirus was looked at with renewed interest ( 3 , 4 ). This also happened to be the first epidemic of the 21st century originating in the Guangdong province of China. Almost 10 years later, there was a MERS (Middle East respiratory syndrome) outbreak in 2012, which was caused by the MERS-CoV ( 5 , 6 ). Both SARS and MERS have a zoonotic origin and originated from bats. A unique feature of these viruses is the ability to mutate rapidly and adapt to a new host. The zoonotic origin of these viruses allows them to jump from host to host. Coronaviruses are known to use the angiotensin-converting enzyme-2 (ACE-2) receptor or the dipeptidyl peptidase IV (DPP-4) protein to gain entry into cells for replication ( 7 – 10 ).

In December 2019, almost seven years after the MERS 2012 outbreak, a novel Coronavirus (2019-nCoV) surfaced in Wuhan in the Hubei region of China. The outbreak rapidly grew and spread to neighboring countries. However, rapid communication of information and the increasing scale of events led to quick quarantine and screening of travelers, thus containing the spread of the infection. The major part of the infection was restricted to China, and a second cluster was found on a cruise ship called the Diamond Princess docked in Japan ( 11 , 12 ).

The new virus was identified to be a novel Coronavirus and was thus initially named 2019-nCoV; later, it was renamed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ( 13 ), and the disease it causes is now referred to as Coronavirus Disease-2019 (COVID-19) by the WHO. The virus was suspected to have begun its spread in the Huanan seafood wholesale market in the Wuhan region. It is possible that an animal that was carrying the virus was brought into or sold in the market, causing the spread of the virus in the crowded marketplace. One of the first claims made was in an article published in the Journal of Medical Virology ( 14 ), which identified snakes as the possible host. A second possibility was that pangolins could be the wild host of SARS-CoV-2 ( 15 ), though the most likely possibility is that the virus originated from bats ( 13 , 16 – 19 ). Increasing evidence and experts are now collectively concluding the virus had a natural origin in bats, as with previous such respiratory viruses ( 2 , 20 – 24 ).

Similarly, SARS and MERS were also suspected to originate from bats. In the case of MERS, the dromedary camel is an intermediate host ( 5 , 10 ). Bats have been known to harbor coronaviruses for quite some time now. Just as in the case of avian flu, SARS, MERS, and possibly even HIV, with increasing selection and ecological pressure due to human activities, the virus made the jump from animal to man. Humans have been encroaching increasingly into forests, and this is true over much of China, as in Africa. Combined with additional ecological pressure due to climate change, such zoonotic spillovers are now more common than ever. It is likely that the next disease X will also have such an origin ( 25 ). We have learned the importance of identification of the source organism due to the Ebola virus pandemic. Viruses are unstable organisms genetically, constantly mutating by genetic shift or drift. It is not possible to predict when a cross-species jump may occur and when a seemingly harmless variant form of the virus may turn into a deadly strain. Such an incident occurred in Reston, USA, with the Reston virus ( 26 ), an alarming reminder of this possibility. The identification of the original host helps us to contain future spreads as well as to learn about the mechanism of transmission of viruses. Until the virus is isolated from a wild animal host, in this case, mostly bats, the zoonotic origin will remain hypothetical, though likely. It should further be noted that the virus has acquired several mutations, as noted by a group in China, indicating that there are more than two strains of the virus, which may have had an impact on its pathogenicity. However, this claim remains unproven, and many experts have argued otherwise; data proving this are not yet available ( 27 ). A similar finding was reported from Italy and India independently, where they found two strains ( 28 , 29 ). These findings need to be further cross-verified by similar analyses globally. If true, this finding could effectively explain why some nations are more affected than others.

Transmission

When the spread of COVID-19 began ( Figure 1 ), the virus appeared to be contained within China and the cruise ship “Diamond Princess,” which formed the major clusters of the virus. However, as of April 2020, over 210 countries and territories are affected by the virus, with Europe, the USA, and Iran forming the new cluster of the virus. The USA ( Figure 2 ) has the highest number of confirmed COVID-19 cases, whereas India and China, despite being among the most population-dense countries in the world, have managed to constrain the infection rate by the implementation of a complete lockdown with arrangements in place to manage the confirmed cases. Similarly, the UK has also managed to maintain a low curve of the graph by implementing similar measures, though it was not strictly enforced. Reports have indicated that the presence of different strains or strands of the virus may have had an effect on the management of the infection rate of the virus ( 27 – 29 ). The disease is spread by droplet transmission. As of April 2020, the total number of infected individuals stands at around 3 million, with ~200,000 deaths and more than 1 million recoveries globally ( 30 , 34 ). The virus thus has a fatality rate of around 2% and an R 0 of 3 based on current data. However, a more recent report from the CDC, Atlanta, USA, claims that the R 0 could be as high as 5.7 ( 35 ). It has also been observed from data available from China and India that individuals likely to be infected by the virus from both these countries belong to the age groups of 20–50 years ( 36 , 37 ). In both of these countries, the working class mostly belongs to this age group, making exposure more likely. Germany and Singapore are great examples of countries with a high number of cases but low fatalities as compared to their immediate neighbors. Singapore is one of the few countries that had developed a detailed plan of action after the previous SARS outbreak to deal with a similar situation in the future, and this worked in their favor during this outbreak. Both countries took swift action after the outbreak began, with Singapore banning Chinese travelers and implementing screening and quarantine measures at a time when the WHO recommended none. They ordered the elderly and the vulnerable to strictly stay at home, and they ensured that lifesaving equipment and large-scale testing facilities were available immediately ( 38 , 39 ). Germany took similar measures by ramping up testing capacity quite early and by ensuring that all individuals had equal opportunity to get tested. This meant that young, old, and at-risk people all got tested, thus ensuring positive results early during disease progression and that most cases were mild like in Singapore, thus maintaining a lower death percentage ( 40 ). It allowed infected individuals to be identified and quarantined before they even had symptoms. Testing was carried out at multiple labs, reducing the load and providing massive scale, something which countries such as the USA did quite late and India restricted to select government and private labs. The German government also banned large gatherings and advocated social distancing to further reduce the spread, though unlike India and the USA, this was done quite late. South Korea is another example of how a nation has managed to contain the spread and transmission of the infection. South Korea and the USA both reported their first COVID-19 cases on the same day; however, the US administration downplayed the risks of the disease, unlike South Korean officials, who constantly informed their citizens about the developments of the disease using the media and a centralized messaging system. They also employed the Trace, Test, and Treat protocol to identify and isolate patients fast, whereas the USA restricted this to patients with severe infection and only later broadened this criterion, like many European countries as well as India. Unlike the USA, South Korea also has universal healthcare, ensuring free diagnostic testing.

Figure 1 . Timeline of COVID-19 progression ( 30 – 32 ).

Figure 2 . Total confirmed COVID 19 cases as of May 2020 ( 33 ).

The main mode of transmission of 2019-nCoV is human to human. As of now, animal-to-human transfer has not yet been confirmed. Asymptomatic carriers of the virus are at major risk of being superinfectors with this disease, as all those infected may not develop the disease ( 41 ). This is a concern that has been raised by nations globally, with the Indian government raising concerns on how to identify and contain asymptomatic carriers, who could account for 80% of those infected ( 42 ). Since current resources are directed towards understanding the hospitalized individuals showing symptoms, there is still a vast amount of information about asymptomatic individuals that has yet to be studied. For example, some questions that need to be answered include: Do asymptomatic individuals develop the disease at any point in time at all? Do they eventually develop antibodies? How long do they shed the virus for? Can any tissue of these individuals store the virus in a dormant state? Asymptomatic transmission is a gray area that encompasses major unknowns in COVID-19.

The main route of human-to-human transmission is by droplets, which are generated during coughing, talking, or sneezing and are then inhaled by a healthy individual. They can also be indirectly transmitted to a person when they land on surfaces that are touched by a healthy individual who may then touch their nose, mouth, or eyes, allowing the virus entry into the body. Fomites are also a common issue in such diseases ( 43 ).

Aerosol-based transmission of the virus has not yet been confirmed ( 43 ). Stool-based transmission via the fecal-oral route may also be possible since the SARS-CoV-2 has been found in patient feces ( 44 , 45 ). Some patients with COVID-19 tend to develop diarrhea, which can become a major route of transmission if proper sanitation and personal hygiene needs are not met. There is no evidence currently available to suggest intrauterine vertical transmission of the disease in pregnant women ( 46 ).

More investigation is necessary of whether climate has played any role in the containment of the infection in countries such as India, Singapore, China, and Israel, as these are significantly warmer countries as compared with the UK, the USA, and Canada ( Figure 2 ). Ideally, a warm climate should prevent the virus from surviving for longer periods of time on surfaces, reducing transmissibility.

Pathophysiology

On gaining entry via any of the mucus membranes, the single-stranded RNA-based virus enters the host cell using type 2 transmembrane serine protease (TMPRSS2) and ACE2 receptor protein, leading to fusion and endocytosis with the host cell ( 47 – 49 ). The uncoated RNA is then translated, and viral proteins are synthesized. With the help of RNA-dependant RNA polymerase, new RNA is produced for the new virions. The cell then undergoes lysis, releasing a load of new virions into the patients' body. The resultant infection causes a massive release of pro-inflammatory cytokines that causes a cytokine storm.

Clinical Presentation

The clinical presentation of the disease resembles beta coronavirus infections. The virus has an incubation time of 2–14 days, which is the reason why most patients suspected to have the illness or contact with an individual having the illness remain in quarantine for the said amount of time. Infection with SARS-CoV-2 causes severe pneumonia, intermittent fever, and cough ( 50 , 51 ). Symptoms of rhinorrhoea, pharyngitis, and sneezing have been less commonly seen. Patients often develop acute respiratory distress syndrome within 2 days of hospital admission, requiring ventilatory support. It has been observed that during this phase, the mortality tends to be high. Chest CT will show indicators of pneumonia and ground-glass opacity, a feature that has helped to improve the preliminary diagnosis ( 51 ). The primary method of diagnosis for SARS-CoV-2 is with the help of PCR. For the PCR testing, the US CDC recommends testing for the N gene, whereas the Chinese CDC recommends the use of ORF lab and N gene of the viral genome for testing. Some also rely on the radiological findings for preliminary screening ( 52 ). Additionally, immunodiagnostic tests based on the presence of antibodies can also play a role in testing. While the WHO recommends the use of these tests for research use, many countries have pre-emptively deployed the use of these tests in the hope of ramping up the rate and speed of testing ( 52 – 54 ). Later, they noticed variations among the results, causing them to stop the use of such kits; there was also debate among the experts about the sensitivity and specificity of the tests. For immunological tests, it is beneficial to test for antibodies against the virus produced by the body rather than to test for the presence of the viral proteins, since the antibodies can be present in larger titers for a longer span of time. However, the cross-reactivity of these tests with other coronavirus antibodies is something that needs verification. Biochemical parameters such as D-dimer, C-reactive protein, and variations in neutrophil and lymphocyte counts are some other parameters that can be used to make a preliminary diagnosis; however, these parameters vary in a number of diseases and thus cannot be relied upon conclusively ( 51 ). Patients with pre-existing diseases such as asthma or similar lung disorder are at higher risk, requiring life support, as are those with other diseases such as diabetes, hypertension, or obesity. Those above the age of 60 have displayed the highest mortality rate in China, a finding that is mirrored in other nations as well ( Figure 3 ) ( 55 ). If we cross-verify these findings with the population share that is above the age of 70, we find that Italy, the United Kingdom, Canada, and the USA have one of the highest elderly populations as compared to countries such as India and China ( Figure 4 ), and this also reflects the case fatality rates accordingly ( Figure 5 ) ( 33 ). This is a clear indicator that aside from comorbidities, age is also an independent risk factor for death in those infected by COVID-19. Also, in the US, it was seen that the rates of African American deaths were higher. This is probably due to the fact that the prevalence of hypertension and obesity in this community is higher than in Caucasians ( 56 , 57 ). In late April 2020, there are also claims in the US media that young patients in the US with COVID-19 may be at increased risk of stroke; however, this is yet to be proven. We know that coagulopathy is a feature of COVID-19, and thus stroke is likely in this condition ( 58 , 59 ). The main cause of death in COVID-19 patients was acute respiratory distress due to the inflammation in the linings of the lungs caused by the cytokine storm, which is seen in all non-survival cases and in respiratory failure. The resultant inflammation in the lungs, served as an entry point of further infection, associated with coagulopathy end-organ failure, septic shock, and secondary infections leading to death ( 60 – 63 ).

Figure 3 . Case fatality rate by age in selected countries as of April 2020 ( 33 ).

Figure 4 . Case fatality rate in selected countries ( 33 ).

Figure 5 . Population share above 70 years of age ( 33 ).

For COVID-19, there is no specific treatment available. The WHO announced the organization of a trial dubbed the “Solidarity” clinical trial for COVID-19 treatments ( 64 ). This is an international collaborative study that investigates the use of a few prime candidate drugs for use against COVID-19, which are discussed below. The study is designed to reduce the time taken for an RCT by over 80%. There are over 1087 studies ( Supplementary Data 1 ) for COVID-19 registered at clinicaltrials.gov , of which 657 are interventional studies ( Supplementary Data 2 ) ( 65 ). The primary focus of the interventional studies for COVID-19 has been on antimalarial drugs and antiviral agents ( Table 1 ), while over 200 studies deal with the use of different forms of oxygen therapy. Most trials focus on improvement of clinical status, reduction of viral load, time to improvement, and reduction of mortality rates. These studies cover both severe and mild cases.

Table 1 . List of therapeutic drugs under study for COVID-19 as per clinical trials registered under clinicaltrials.gov .

Use of Antimalarial Drugs Against SARS-CoV-2

The use of chloroquine for the treatment of corona virus-based infection has shown some benefit in the prevention of viral replication in the cases of SARS and MERS. However, it was not validated on a large scale in the form of a randomized control trial ( 50 , 66 – 68 ). The drugs of choice among antimalarials are Chloroquine (CQ) and Hydroxychloroquine (HCQ). The use of CQ for COVID-19 was brought to light by the Chinese, especially by the publication of a letter to the editor of Bioscience Trends by Gao et al. ( 69 ). The letter claimed that several studies found CQ to be effective against COVID-19; however, the letter did not provide many details. Immediately, over a short span of time, interest in these two agents grew globally. Early in vitro data have revealed that chloroquine can inhibit the viral replication ( 70 , 71 ).

HCQ and CQ work by raising the pH of the lysosome, the cellular organelle that is responsible for phagocytic degradation. Its function is to combine with cell contents that have been phagocytosed and break them down eventually, in some immune cells, as a downstream process to display some of the broken proteins as antigens, thus further enhancing the immune recruitment against an antigen/pathogen. The drug was to be administered alone or with azithromycin. The use of azithromycin may be advocated by the fact that it has been seen previously to have some immunomodulatory role in airway-related disease. It appears to reduce the release of pro-inflammatory cytokines in respiratory illnesses ( 72 ). However, HCQ and azithromycin are known to have a major drug interaction when co-administered, which increases the risk of QT interval prolongation ( 73 ). Quinine-based drugs are known to have adverse effects such as QT prolongation, retinal damage, hypoglycemia, and hemolysis of blood in patients with G-6-PD deficiency ( 66 ). Several preprints, including, a metanalysis now indicate that HCQ may have no benefit for severe or critically ill patients who have COVID-19 where the outcome is need for ventilation or death ( 74 , 75 ). As of April 21, 2020, after having pre-emptively recommended their use for SARS-CoV-2 infection, the US now advocates against the use of these two drugs based on the new data that has become available.

Use of Antiviral Drugs Against SARS-CoV-2

The antiviral agents are mainly those used in the case of HIV/AIDS, these being Lopinavir and Ritonavir. Other agents such as nucleoside analogs like Favipiravir, Ribavirin, Remdesivir, and Galidesivir have been tested for possible activity in the prevention of viral RNA synthesis ( 76 ). Among these drugs, Lopinavir, Ritonavir, and Remdesivir are listed in the Solidarity trial by the WHO.

Remdesivir is a nucleotide analog for adenosine that gets incorporated into the viral RNA, hindering its replication and causing chain termination. This agent was originally developed for Ebola Virus Disease ( 77 ). A study was conducted with rhesus macaques infected with SARS-CoV-2 ( 78 ). In that study, after 12 h of infection, the monkeys were treated with either Remdesivir or vehicle. The drug showed good distribution in the lungs, and the animals treated with the drug showed a better clinical score than the vehicle group. The radiological findings of the study also indicated that the animals treated with Remdesivir have less lung damage. There was a reduction in viral replication but not in virus shedding. Furthermore, there were no mutations found in the RNA polymerase sequences. A randomized clinical control study that became available in late April 2020 ( 79 ), having 158 on the Remdesivir arm and 79 on the placebo arm, found that Remdesivir reduced the time to recovery in the Remdesivir-treated arm to 11 days, while the placebo-arm recovery time was 15 days. Though this was not found to be statistically significant, the agent provided a basis for further studies. The 28-days mortality was found to be similar for both groups. This has now provided us with a basis on which to develop future molecules. The study has been supported by the National Institute of Health, USA. The authors of the study advocated for more clinical trials with Remdesivir with a larger population. Such larger studies are already in progress, and their results are awaited. Remdesivir is currently one of the drugs that hold most promise against COVID-19.

An early trial in China with Lopinavir and Ritonavir showed no benefit compared with standard clinical care ( 80 ). More studies with this drug are currently underway, including one in India ( 81 , 82 ).

Use of Convalescent Patient Plasma

Another possible option would be the use of serum from convalescent individuals, as this is known to contain antibodies that can neutralize the virus and aid in its elimination. This has been tried previously for other coronavirus infections ( 83 ). Early emerging case reports in this aspect look promising compared to other therapies that have been tried ( 84 – 87 ). A report from China indicates that five patients treated with plasma recovered and were eventually weaned off ventilators ( 84 ). They exhibited reductions in fever and viral load and improved oxygenation. The virus was not detected in the patients after 12 days of plasma transfusion. The US FDA has provided detailed recommendations for investigational COVID-19 Convalescent Plasma use ( 88 ). One of the benefits of this approach is that it can also be used for post-exposure prophylaxis. This approach is now beginning to be increasingly adopted in other countries, with over 95 trials registered on clinicaltrials.gov alone, of which at least 75 are interventional ( 89 ). The use of convalescent patient plasma, though mostly for research purposes, appears to be the best and, so far, the only successful option for treatment available.

From a future perspective, the use of monoclonal antibodies for the inhibition of the attachment of the virus to the ACE-2 receptor may be the best bet. Aside from this, ACE-2-like molecules could also be utilized to attach and inactivate the viral proteins, since inhibition of the ACE-2 receptor would not be advisable due to its negative repercussions physiologically. In the absence of drug regimens and a vaccine, the treatment is symptomatic and involves the use of non-invasive ventilation or intubation where necessary for respiratory failure patients. Patients that may go into septic shock should be managed as per existing guidelines with hemodynamic support as well as antibiotics where necessary.

The WHO has recommended that simple personal hygiene practices can be sufficient for the prevention of spread and containment of the disease ( 90 ). Practices such as frequent washing of soiled hands or the use of sanitizer for unsoiled hands help reduce transmission. Covering of mouth while sneezing and coughing, and disinfection of surfaces that are frequently touched, such as tabletops, doorknobs, and switches with 70% isopropyl alcohol or other disinfectants are broadly recommended. It is recommended that all individuals afflicted by the disease, as well as those caring for the infected, wear a mask to avoid transmission. Healthcare works are advised to wear a complete set of personal protective equipment as per WHO-provided guidelines. Fumigation of dormitories, quarantine rooms, and washing of clothes and other fomites with detergent and warm water can help get rid of the virus. Parcels and goods are not known to transmit the virus, as per information provided by the WHO, since the virus is not able to survive sufficiently in an open, exposed environment. Quarantine of infected individuals and those who have come into contact with an infected individual is necessary to further prevent transmission of the virus ( 91 ). Quarantine is an age-old archaic practice that continues to hold relevance even today for disease containment. With the quarantine being implemented on such a large scale in some countries, taking the form of a national lockdown, the question arises of its impact on the mental health of all individuals. This topic needs to be addressed, especially in countries such as India and China, where it is still a matter of partial taboo to talk about it openly within the society.

In India, the Ministry of Ayurveda, Yoga, and Naturopathy, Unani, Siddha and Homeopathy (AYUSH), which deals with the alternative forms of medicine, issued a press release that the homeopathic, drug Arsenicum album 30, can be taken on an empty stomach for 3 days to provide protection against the infection ( 92 ). It also provided a list of herbal drugs in the same press release as per Ayurvedic and Unani systems of medicine that can boost the immune system to deal with the virus. However, there is currently no evidence to support the use of these systems of medicine against COVID-19, and they need to be tested.

The prevention of the disease with the use of a vaccine would provide a more viable solution. There are no vaccines available for any of the coronaviruses, which includes SARS and MERS. The development of a vaccine, however, is in progress at a rapid pace, though it could take about a year or two. As of April 2020, no vaccine has completed the development and testing process. A popular approach has been with the use of mRNA-based vaccine ( 93 – 96 ). mRNA vaccines have the advantage over conventional vaccines in terms of production, since they can be manufactured easily and do not have to be cultured, as a virus would need to be. Alternative conventional approaches to making a vaccine against SARS-CoV-2 would include the use of live attenuated virus as well as using the isolated spike proteins of the virus. Both of these approaches are in progress for vaccine development ( 97 ). Governments across the world have poured in resources and made changes in their legislation to ensure rapid development, testing, and deployment of a vaccine.

Barriers to Treatment

Lack of transparency and poor media relations.

The lack of government transparency and poor reporting by the media have hampered the measures that could have been taken by healthcare systems globally to deal with the COVID-19 threat. The CDC, as well as the US administration, downplayed the threat and thus failed to stock up on essential supplies, ventilators, and test kits. An early warning system, if implemented, would have caused borders to be shut and early lockdowns. The WHO also delayed its response in sounding the alarm regarding the severity of the outbreak to allow nations globally to prepare for a pandemic. Singapore is a prime example where, despite the WHO not raising concerns and banning travel to and from China, a country banned travelers and took early measures, thus managing the outbreak quite well. South Korea is another example of how things may have played out had those measures by agencies been taken with transparency. Increased transparency would have allowed the healthcare sector to better prepare and reduced the load of patients they had to deal with, helping flatten the curve. The increased patient load and confusion among citizens arising from not following these practices has proved to be a barrier to providing effective treatments to patients with the disease elsewhere in the world.

Lack of Preparedness and Protocols

Despite the previous SARS outbreak teaching us important lessons and providing us with data on a potential outbreak, many nations did not take the important measures needed for a future outbreak. There was no allocation of sufficient funds for such an event. Many countries experienced severe lack of PPE, and the lockdown precautions hampered the logistics of supply and manufacturing of such essential equipment. Singapore and South Korea had protocols in place and were able to implement them at a moment's notice. The spurt of cases that Korea experienced was managed well, providing evidence to this effect. The lack of preparedness and lack of protocol in other nations has resulted in confusion as to how the treatment may be administered safely to the large volume of patients while dealing with diagnostics. Both of these factors have limited the accessibility to healthcare services due to sheer volume.

Socio-Economic Impact

During the SARS epidemic, China faced an economic setback, and experts were unsure if any recovery would be made. However, the global and domestic situation was then in China's favor, as it had a lower debt, allowing it to make a speedy recovery. This is not the case now. Global experts have a pessimistic outlook on the outcome of this outbreak ( 98 ). The fear of COVID-19 disease, lack of proper understanding of the dangers of the virus, and the misinformation spread on the social media ( 99 ) have caused a breakdown of the economic flow globally ( 100 ). An example of this is Indonesia, where a great amount of fear was expressed in responses to a survey when the nation was still free of COVID-19 ( 101 ). The pandemic has resulted in over 2.6 billion people being put under lockdown. This lockdown and the cancellation of the lunar year celebration has affected business at the local level. Hundreds of flights have been canceled, and tourism globally has been affected. Japan and Indonesia are estimated to lose over 2.44 billion dollars due to this ( 102 , 103 ). Workers are not able to work in factories, transportation in all forms is restricted, and goods are not produced or moved. The transport of finished products and raw materials out of China is low. The Economist has published US stock market details indicating that companies in the US that have Chinese roots fell, on average, 5 points on the stock market as compared to the S&P 500 index ( 104 ). Companies such as Starbucks have had to close over 4,000 outlets due to the outbreak as a precaution. Tech and pharma companies are at higher risk since they rely on China for the supply of raw materials and active pharmaceutical ingredients. Paracetamol, for one, has reported a price increase of over 40% in India ( 104 – 106 ). Mass hysteria in the market has caused selling of shares of these companies, causing a tumble in the Indian stock market. Though long-term investors will not be significantly affected, short-term traders will find themselves in soup. Politically, however, this has further bolstered support for world leaders in countries such as India, Germany, and the UK, who are achieving good approval ratings, with citizens being satisfied with the government's approach. In contrast, the ratings of US President Donald Trump have dropped due to the manner in which the COVID-19 pandemic was handled. These minor impacts may be of temporary significance, and the worst and direct impact will be on China itself ( 107 – 109 ), as the looming trade war with the USA had a negative impact on the Chinese and Asian markets. The longer production of goods continues to remain suspended, the more adversely it will affect the Chinese economy and the global markets dependent on it ( 110 ). If this disease is not contained, more and more lockdowns by multiple nations will severely affect the economy and lead to many social complications.

The appearance of the 2019 Novel Coronavirus has added and will continue to add to our understanding of viruses. The pandemic has once again tested the world's preparedness for dealing with such outbreaks. It has provided an outlook on how a massive-scale biological event can cause a socio-economic disturbance through misinformation and social media. In the coming months and years, we can expect to gain further insights into SARS-CoV-2 and COVID-19.

Author Contributions

KN: conceptualization. RK, AA, JM, and KN: investigation. RK and AA: writing—original draft preparation. KN, PN, and JM: writing—review and editing. KN: supervision.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The authors would like to acknowledge the contributions made by Dr. Piya Paul Mudgal, Assistant Professor, Manipal Institute of Virology, Manipal Academy of Higher Education towards inputs provided by her during the drafting of the manuscript.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpubh.2020.00216/full#supplementary-material

Supplementary Data 1, 2. List of all studies registered for COVID-19 on clinicaltrials.gov .

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Keywords: 2019-nCoV, COVID-19, SARS-CoV-2, coronavirus, pandemic, SARS

Citation: Keni R, Alexander A, Nayak PG, Mudgal J and Nandakumar K (2020) COVID-19: Emergence, Spread, Possible Treatments, and Global Burden. Front. Public Health 8:216. doi: 10.3389/fpubh.2020.00216

Received: 21 February 2020; Accepted: 11 May 2020; Published: 28 May 2020.

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*Correspondence: Krishnadas Nandakumar, mailnandakumar77@gmail.com

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• Published: 15 February 2023

Coronavirus research: knowledge gaps and research priorities

• Stanley Perlman   ORCID: orcid.org/0000-0003-4213-2354 1 &
• Malik Peiris   ORCID: orcid.org/0000-0001-8217-5995 2 , 3  

Nature Reviews Microbiology volume  21 ,  pages 125–126 ( 2023 ) Cite this article

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Decades of coronavirus research and intense studies of SARS-CoV-2 since the beginning of the COVID-19 pandemic have led to an unprecedented level of knowledge of coronavirus biology and pathogenesis, yet many outstanding questions remain. Here, we discuss knowledge gaps and research priorities in the field.

Introduction

The COVID-19 pandemic showed that, based on previous research efforts, we understood many aspects of coronavirus biology and pathogenesis, but also that there was much we did not know. In 2019, the worldwide number of coronavirus investigators was small, having increased after the severe acute respiratory syndrome coronavirus (SARS-CoV) outbreak in 2003 but decreasing thereafter. The influx of scientists with diverse expertise into the field after the pandemic onset contributed to an increased understanding of coronavirus replication, epidemiology, SARS-CoV-2 pathogenesis and immune responses in humans, to the development and characterization of experimentally infected animal models for COVID-19, and to SARS-CoV-2 vaccine and antiviral drug development. Here, as investigators who have studied coronaviruses for decades, we outline some of the outstanding research questions that we think need to be addressed.

SARS-CoV-2 emergence

Where did SARS-CoV-2 originate and how did it evolve to infect humans? The emergence of SARS-CoV-2 continues to be an area of controversy and has been, and is being, investigated by many national and international organizations, including the WHO (World Health Organization). It is almost certain that the virus originated in bats and crossed species to humans either directly or indirectly via intermediary hosts. There remains debate on whether the virus first infected humans from a zoonotic source or from a research laboratory, but, no matter what the answer to this question is, it is clear to us that in order to be prepared for the next pandemic, we need to further delineate the panoply of coronaviruses present in bats and possible intermediary hosts 1 . We need to better understand coronavirus circulation in hotspots, such as parts of China and Southeast Asia, where humans, wildlife gathered for food or medicinal purposes and bats are in close proximity. These investigations should include surveillance (virological and serological) of humans in close contact with bats and the game animal trade, with or without respiratory disease, for evidence of coronavirus infection. A related question, discussed below, is why coronaviruses are especially good at jumping species, to humans and other animals.

Zoonotic risk

Once coronaviruses in animal reservoirs are identified, can they be better risk assessed for threats for human spillover? Surveillance of bat reservoirs of sarbecoviruses (Sarbecovirus is the subgenus to which SARS-CoV-2 belongs) had previously found evidence of viruses with a capacity for infecting human cells using the angiotensin converting enzyme 2 (ACE2) receptor (reminiscent of SARS-CoV) 2 . Serological evidence of viral spillover to humans was demonstrated before the emergence of SARS-CoV-2 (ref. 3 ). Arguably, these signals together should have been triggers for action to develop countermeasures with greater urgency. The availability of human organoid cultures and ex vivo cultures of human respiratory tissue may enable the use of physiologically relevant systems for a more systematic risk assessment of animal coronaviruses in the future, analogous to ongoing risk assessments being carried out for animal influenza viruses 4 .

SARS-CoV-2 transmissibility

What explains the high transmissibility of SARS-CoV-2 compared with SARS-CoV or Middle East respiratory syndrome coronavirus (MERS-CoV)? A critical factor leading to the COVID-19 pandemic was the ability of SARS-CoV-2 to grow to high levels in the upper respiratory tract and therefore to readily transmit to other humans. Titres of SARS-CoV and MERS-CoV in the upper respiratory tract peak at later times after infection 5 , consistent with the ability to interrupt transmission with relevant public health infection-prevention methods. A second, related question is why SARS-CoV and a common cold coronavirus, HCoV-NL63, which both use the same receptor as SARS-CoV-2 (ACE2) 6 , have such different patterns of infection within the human respiratory tract. HCoV-NL63 rarely infects the lower respiratory tract, whereas SARS-CoV preferentially causes pneumonia. These different patterns of infection most likely relate to differences in cell entry, including differences in co-receptor usage, host protease usage or fusogenicity of the spike protein, but there are other possibilities. Understanding these differences will provide information on which coronavirus might be expected to be transmissible and to identify additional targets for therapeutic interventions. Further elucidation of the factors that contribute to virus spread will require additional experimental animal models of coronavirus transmission.

The SARS-CoV-2 outbreak also highlighted the lack of evidence-based data on the transmission of coronaviruses, or indeed respiratory viruses in in general, and on which non-pharmaceutical countermeasures (for example, social distancing and masks (surgical versus N99/FFP3 masks)) are effective or not. The SARS-CoV-2 outbreak demonstrated that the only effective control options available in the first months of the pandemic were non-pharmaceutical, but our understanding of the efficacy of specific measures is limited.

Coronavirus genome complexity

Why do coronavirus genomes encode so many more proteins than other RNA viruses? Coronavirus genomes are bigger than those of any other RNA virus, apart from those of related members of the Nidovirales order. The genomes are so large that they require genomic proofreading activity to avoid error catastrophe 7 . A large genome size may contribute to enhanced cross-species transmission, but, at present, this notion is speculative. In any case, an important question is to understand the function of the many non-structural proteins involved in virus replication. Development of a cell-free or entirely in vitro replication system would facilitate detailed probing of the role of individual proteins in replication and transmission. Efforts to develop such cell-free systems were initiated 40 years ago, but it is only in the past few years with the advent of cryo-electron microscopy and new biochemical approaches that progress has been made. These efforts are expected to complement studies in intact cells, which use high-resolution microscopy and related techniques to analyse macromolecular interactions and function at the subcellular level.

Related to the previous question, why do coronaviruses encode so many proteins with apparent immunoevasive function? Coronaviruses encode a variable number of accessory proteins, the genes of which are intermingled within the structural protein genes located at the 3′ end of the genome. For example, SARS-CoV-2 encodes at least six such proteins, with several other putative open reading frames in the genome hypothesized to be expressed and have immunoevasive properties 8 . Confusingly, these genes are often deleted in viruses isolated from infected animals, without apparent loss of virulence. This was shown most clearly in the case of MERS-CoV, in which diverse deletions and insertions in accessory genes were detected in some isolates obtained in Africa from camels, the primary host of the virus 9 . These genetic changes may have unpredictable consequences for virus transmissibility or pathogenesis. Deletion of these genes occasionally leads to increased virulence 10 . The variable and sometimes unexpectedly high numbers of these proteins suggest that they have redundant and, perhaps, additional functions. Such redundancy could contribute to cross-species transmission. The genetic instability of MERS-CoV camels in Africa therefore needs to be monitored and evidence for human spillover needs to be continually assessed.

Predictive evolution

Can coronavirus evolution in infected human or other animal hosts be predicted? Coronaviruses readily mutate and recombine as they adapt to a new host. This is well illustrated by the COVID-19 pandemic, in which ancestral strains of SARS-CoV-2 initially mutated to better infect humans, and later evolved to evade the human immune response, generating a series of variants of concern. Several studies have modelled SARS-CoV-2 evolution but so far it has not been possible to predict how the virus will evolve in the future. Such predictive modelling is recognized to be difficult, but would be very useful in the present pandemic as well as in future coronavirus outbreaks or pandemics for vaccine development, for anticipating clinical disease and pathogenesis, and for risk assessment of animal viruses with zoonotic potential.

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Stanley Perlman

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Perlman, S., Peiris, M. Coronavirus research: knowledge gaps and research priorities. Nat Rev Microbiol 21 , 125–126 (2023). https://doi.org/10.1038/s41579-022-00837-3

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Affiliations.

• 1 Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Tropical Disease Centre, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Department of Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
• 2 Division of Infectious Diseases, AichiCancer Center Hospital, Chikusa-ku Nagoya, Japan. Electronic address: [email protected].
• 3 Department of Family Medicine, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
• 4 Department of Pulmonology and Respiratory Medicine, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
• 5 School of Medicine, The University of Western Australia, Perth, Australia. Electronic address: [email protected].
• 6 Siem Reap Provincial Health Department, Ministry of Health, Siem Reap, Cambodia. Electronic address: [email protected].
• 7 Department of Microbiology and Parasitology, Faculty of Medicine and Health Sciences, Warmadewa University, Denpasar, Indonesia; Department of Medical Microbiology and Immunology, University of California, Davis, CA, USA. Electronic address: [email protected].
• 8 Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Tropical Disease Centre, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Department of Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Department of Clinical Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
• 9 Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, MI 48109, USA. Electronic address: [email protected].
• 10 Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Tropical Disease Centre, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Department of Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
• PMID: 32340833
• PMCID: PMC7142680
• DOI: 10.1016/j.jiph.2020.03.019

In early December 2019, an outbreak of coronavirus disease 2019 (COVID-19), caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), occurred in Wuhan City, Hubei Province, China. On January 30, 2020 the World Health Organization declared the outbreak as a Public Health Emergency of International Concern. As of February 14, 2020, 49,053 laboratory-confirmed and 1,381 deaths have been reported globally. Perceived risk of acquiring disease has led many governments to institute a variety of control measures. We conducted a literature review of publicly available information to summarize knowledge about the pathogen and the current epidemic. In this literature review, the causative agent, pathogenesis and immune responses, epidemiology, diagnosis, treatment and management of the disease, control and preventions strategies are all reviewed.

Keywords: 2019-nCoV; COVID-19; Novel coronavirus; Outbreak; SARS-CoV-2.

Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.

Publication types

• Betacoronavirus
• Clinical Trials as Topic
• Coronavirus Infections* / epidemiology
• Coronavirus Infections* / immunology
• Coronavirus Infections* / therapy
• Coronavirus Infections* / virology
• Disease Outbreaks* / prevention & control
• Pneumonia, Viral* / epidemiology
• Pneumonia, Viral* / immunology
• Pneumonia, Viral* / therapy
• Pneumonia, Viral* / virology

The Centre for Evidence-Based Medicine

Evidence Service to support the COVID-19 response

Coronaviruses – a general introduction

March 25, 2020

Who first described them; why they are called coronaviruses; what they are; how they invade cells; how we detect them

Jeffrey K Aronson Centre for Evidence-Based Medicine, Nuffield Department of Primary Care Health Sciences University of Oxford

Until recently, most people will never have heard of coronaviruses. But they, and the diseases they cause in humans and animals, have been recognized for over 50 years.

Who first discovered coronaviruses?

Avian infectious bronchitis was first described in newborn chicks in 1931 by Schalk & Hawn (J Am Vet Med Ass 1931; 78: 413–23) and by Bushnell & Brandly in 1933 (Poultry Science 1933; 12: 55-60). These papers were both cited by Beach & Schalm , 1936, who confirmed that the infection was due to a filterable virus and identified two strains, with cross-immunity. The virus was cultivated in 1937 by Fred Beaudette and Charles Hudson, from the New Jersey Agricultural Experiment Station (J Am Vet Med Ass 1937; 90: 51–8 cited by Marks ) and later by Cunningham & Stuart in 1947 .

In 1951 Gledhill & Andrewes isolated a hepatitis virus from mice, now also known to be a coronavirus.

In 1965, the virologist David Tyrrell, Director of the Medical Research Council’s Common Cold Research Unit at Harnham Down near Salisbury in Wiltshire, and his colleague Mark Bynoe published a paper in the British Medical Journal , in which they described a virus, which they called B814, and identified it as a cause of the common cold. They tried to characterize other viruses, but without much success, and thought that viruses of which they found evidence were rhinoviruses.

On 1 April 1967 Tyrell, this time with his colleague June Almeida, from the Department of Medical Microbiology in London’s St Thomas’s Hospital Medical School, identified three uncharacterized respiratory viruses, of which two had not previously been associated with human diseases. They reported that two of the viruses, 229E and B814, of which they published electron micrographs, were indistinguishable from the particles of avian infectious bronchitis.

Then Almeida and Tyrell, with six other colleagues, reported in Nature in 1968 that there was a group of viruses that caused not only avian bronchitis but also murine hepatitis and upper respiratory tract diseases in humans, as shown in Figure 1, taken from their brief annotation, which was published under the general heading “News and Views” (Almeida JD, Berry DM, Cunningham CH, Hamre D, Hofstad MS, Mallucci L, McIntosh K, Tyrrell DAJ. Virology: Coronaviruses. Nature 1968; 220(5168): 650). This is the first recorded instance of the term “coronaviruses”.

The virus of avian infectious bronchitis is classified as a gammacoronavirus, while most of the coronaviruses that infect humans are betacoronoviruses. The human coronavirus HCoV-229E described by Almeida and Tyrrell is an alphacoronavirus.

Figure 1 . Details of the properties of coronaviruses, first published in Nature (1968; 220(5168): 650); David Tyrrell, at the Common Cold Research Unit, Salisbury, Wiltshire, offered to provide a short bibliography to anyone interested in the data on which the table was based

Why are they called coronaviruses?

As the journal Nature reported in 1968, “these viruses are members of a previously unrecognized group which [the virologists] suggest should be called the coronaviruses, to recall the characteristic appearance by which these viruses are identified in the electron microscope.”

The word “corona” has many different meanings (see Appendix 2). But it was the sun that the virologists had in mind when they chose the name coronaviruses. As they wrote, they compared “the characteristic ‘fringe’ of projections” on the outside of the virus with the solar corona (not, as some have suggested, the points on a crown). Figure 2 illustrates this.

Figure 2 . Left: The virions of coronaviruses; Right: The corona of the sun seen during an eclipse

What are coronaviruses and how do they invade cells?

Coronaviruses are single-stranded RNA viruses, about 120 nanometers in diameter. They are susceptible to mutation and recombination and are therefore highly diverse. There are about 40 different varieties (see Appendix 1) and they mainly infect human and non-human mammals and birds. They reside in bats and wild birds, and can spread to other animals and hence to humans. The virus that causes COVID-19 is thought to have originated in bats and then spread to snakes and pangolins and hence to humans, perhaps by contamination of meat from wild animals, as sold in China’s meat markets.

The corona-like appearance of coronaviruses is caused by so-called spike glycoproteins, or peplomers, which are necessary for the viruses to enter host cells. The spike has two subunits; one subunit, S1, binds to a receptor on the surface of the host’s cell; the other subunit, S2, fuses with the cell membrane. The cell membrane receptor for both SARS-CoV-1 and SARS-CoV-2 is a form of angiotensin converting enzyme, ACE-2, different from the enzyme that is inhibited by conventional ACE-1 inhibitors, such as enalapril and ramipril.

Briefly, the S1 subunit of the spike binds to the ACE-2 enzyme on the cell membrane surface. A host transmembrane serine protease, TMPRSS2 , then activates the spike and cleaves ACE-2. TMPRSS2 also acts on the S2 subunit, facilitating fusion of the virus to the cell membrane. The virus then enters the cell. Inside the cell the virus is released from endosomes by acidification or the action of an intracellular cysteine protease, cathepsin.

A model and a more detailed description of these events is shown in Figure 3.

Figure 3 . A proposed model of the mechanisms whereby coronavirus SRA-CoV-2 enters cells

• The coronavirus approaches the cell membrane
• An S1 subunit (red) at the distal end of a glycoprotein spike of the virus binds to a membrane-bound molecule of ACE-2 (blue)
• As more S1 subunits of the glycoprotein spikes bind to membrane-bound molecules of ACE-2, the membrane starts to form an envelope around the virus (an endosome)
• The process continues …
• … until the endosome is complete
• The virus can enter the cell in two ways:

(a)    A cell membrane-bound serine protease (brown), TMPRSS2, cleaves the virus’s S1 subunits (red) from its S2 subunits (black) and also cleaves the ACE-2 enzymes; the endosome enters the cell ( endocytosis ), where the virus is released by acidification or the action of another protease, cathepsin

(b)    The same serine protease, TMPRSS2, causes irreversible conformational changes in the virus’s S2 subunits, activating them, after which the virus fuses to the cell membrane and can be internalized by the cell

A serine protease inhibitor, camostat mesylate, used in Japan to treat chronic pancreatitis , inhibits the TMPRSS2 and partially blocks the entry of SARS-CoV-2 into bronchial epithelial cells in vitro.

Research interest in coronaviruses

The first coronaviruses found to infect humans were called 229E and OC43, but they caused very mild infections, similar to the common cold. It was not until the outbreaks of SARS (severe acute respiratory syndrome) and then MERS (the Middle Eastern respiratory syndrome or camel flu) that it was appreciated that they could cause serious human infections. Those two infections are thought to have come from bats via civet cats and camels.

This awakening of interest in coronaviruses at different times is reflected in the pattern of publications about them. After the initial description of coronaviruses in 1968 there was a slow increase in the numbers of publications dealing with them, followed by two peaks, after two epidemics: the SARS coronavirus epidemic in 2003–4 and an outbreak of porcine epidemic diarrhoea in North America in 2013 (Figure 4). Identification of the first cases of MERS in Saudi Arabia in 2012, and then elsewhere (e.g. in South Korea in 2015), also caused by a coronavirus, may also have contributed.

I have previously highlighted the fact that the major peaks of interest in the coronaviruses have followed major infections in humans and animals. In my BMJ opinion column on 31 January this year, where some of this article has previously appeared. I wrote that I expected to see another peak in the numbers of publications following the current epidemic. My original graph ended with the 2019 figures. I have now added the latest numbers, from 2020, to the graph, which shows that my prophecy has already been fulfilled. More publications on coronaviruses have been logged in Pubmed in the first 12 weeks of 2020 than in any previous complete year. The difficulty in preventing and treating the infection is matched by the difficulty in keeping up with the published literature.

Figure 4 . Numbers of publications with “coronavirus/es” as text words (blue) or in titles (orange) (source PubMed Legacy); each point represents one year, but the rightmost points cover only the first 12 weeks of 2020

Testing for coronavirus, SARS-CoV-2

Viral RNA can be detected by polymerase chain reaction (PCR, or quantitative PCR, qPCR, sometimes referred to as “real-time PCR” or RT-PCR, causing confusion with another term, “reverse transcriptase PCR”) (Figure 5). In this test, the virus’s single-stranded RNA is converted to its complementary DNA by reverse transcriptase; specific regions of the DNA, marked by so-called primers , are then amplified. This is done by synthesizing new DNA strands from deoxynucleoside triphosphates using DNA polymerase. Occasional false negatives have been reported .

Figure 5 . Reverse Transcriptase Polymerase Chain Reaction (RT-PCR)

• A primer is attached to the 3 prime end of a single strand of viral RNA
• Deoxynucleoside triphosphates are added stepwise …
•  … creating a DNA copy of the viral RNA
• The single strand of DNA is separated …
• … and double-stranded complementary DNA (cDNA) is prepared …
• … copies of which are synthesized using primers and DNA polymerase

Step 6 can be repeated many times, doubling the numbers of DNA molecules created each time; 30 steps, for example, will yield 2 30  (i.e. 1,073,741,824) or about 10 9  molecules

An immunoassay has also been described , but it has a high false omission (or exclusion) rate (Table 1).

Table 1 . Diagnostic features of an immunoassay for SARS-CoV-2

Efforts are currently being made to develop and implement an immunoassay for antiviral antibodies to determine whether infection has previously occurred.

Appendix 1: Varieties of coronaviruses

Coronaviridae is the name given to a family of viruses with two subfamilies, Letovirinae and Coronavirinae. The latter has four genera, Alphacoronavirus, Betacoronavirus, Gammacoronavirus, and Deltacoronavirus, These include seven coronaviruses that can infect humans (Table 2). Coronaviruses can also infect non-human mammals (Table 3), they can be carried by birds or infect them (Table 4), and they can be carried by bats (Table 5).

Table 2 . Taxonomy of coronaviruses that can cause disease in humans

Table 3 . Some non-human mammals that can be infected by coronaviruses

Table 4 . Some birds that can carry or be infected by coronaviruses (gammacoronaviruses and deltacoronaviruses)

Table 5 . Some coronaviruses carried by bats

Appendix 2: Meanings of the word “corona”

I have listed the many different meanings of “corona” and some of its derivatives in Table 6 below.

Table 6 . Different meanings of “corona” and some derivatives (based on definitions in the Oxford English Dictionary )

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• Volume 14, Issue 3
• Evolution of the data and methods in real-world COVID-19 vaccine effectiveness studies on mortality: a scoping review protocol
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• http://orcid.org/0000-0002-5397-228X Paulina Stehlik 1 , 2 ,
• http://orcid.org/0000-0001-7734-9436 Caroline Dowsett 1 ,
• Ximena Camacho 3 ,
• http://orcid.org/0000-0001-6444-7272 Michael O Falster 3 ,
• http://orcid.org/0000-0003-4135-2523 Renly Lim 4 ,
• http://orcid.org/0000-0002-9793-113X Sharifa Nasreen 5 ,
• Nicole L Pratt 6 ,
• Sallie-Anne Pearson 3 ,
• http://orcid.org/0000-0003-2934-2242 David Henry 2 , 3
• 1 School of Pharmacy and Medical Sciences , Griffith University Faculty of Health , Gold Coast , Queensland , Australia
• 2 Institute for Evidence-Based Healthcare , Bond University Faculty of Health Sciences and Medicine , Gold Coast , Queensland , Australia
• 3 School of Population Health , University of New South Wales Medicine & Health , Sydney , New South Wales , Australia
• 4 Quality Use of Medicines and Pharmacy Research Centre , University of South Australia Division of Health Sciences , Adelaide , South Australia , Australia
• 5 SUNY Downstate Health Sciences, University School of Public Health , New York , New York , USA
• 6 Quality Use of Medicines and Pharmacy Research Centre , University of South Australia Clinical & Health Sciences Academic Unit , Adelaide , South Australia , Australia
• Correspondence to Paulina Stehlik; p.stehlik{at}griffith.edu.au

Background Early evidence on COVID-19 vaccine efficacy came from randomised trials. Many important questions subsequently about vaccine effectiveness (VE) have been addressed using real-world studies (RWS) and have informed most vaccination policies globally. As the questions about VE have evolved during the pandemic so have data, study design, and analytical choices. This scoping review aims to characterise this evolution and provide insights for future pandemic planning—specifically, what kinds of questions are asked at different stages of a pandemic, and what data infrastructure and methods are used?

Methods and analysis We will identify relevant studies in the Johns Hopkins Bloomberg School of Public Health VIEW-hub database, which curates both published and preprint VE RWS identified from PubMed, Embase, Scopus, Web of Science, the WHO COVID Database, MMWR, Eurosurveillance, medRxiv, bioRxiv, SSRN, Europe PMC, Research Square, Knowledge Hub, and Google. We will include RWS of COVID-19 VE that reported COVID-19-specific or all-cause mortality (coded as ‘death’ in the ‘effectiveness studies’ data set).

Information on study characteristics; study context; data sources; design and analytic methods that address confounding will be extracted by single reviewer and checked for accuracy and discussed in a small group setting by methodological and analytic experts. A timeline mapping approach will be used to capture the evolution of this body of literature.

By describing the evolution of RWS of VE through the COVID-19 pandemic, we will help identify options for VE studies and inform policy makers on the minimal data and analytic infrastructure needed to support rapid RWS of VE in future pandemics and of healthcare strategies more broadly.

Ethics and dissemination As data is in the public domain, ethical approval is not required. Findings of this study will be disseminated through peer-reviewed publications, conference presentations, and working-papers to policy makers.

Registration https://doi.org/10.17605/OSF.IO/ZHDKR

• STATISTICS & RESEARCH METHODS
• Protocols & guidelines
• INFECTIOUS DISEASES
• PUBLIC HEALTH

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/bmjopen-2023-079071

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Strengths and limitations of this study

We will use a comprehensive curated database (Johns Hopkins Bloomberg School of Public Health VIEW-hub) that compiles relevant studies on a weekly basis from multiple databases, preprint servers, and the grey literature.

While use of a curated database may lead to some studies being missed, this is unlikely to change the overall findings of this scoping review.

All extraction will be conducted by a single author to ensure consistency in extraction and checked by a second author to ensure accuracy.

Weekly group discussions about the individual studies and coding of data will strengthen data integrity.

End users have been involved in the design of this study and will continue to be consulted throughout its conduct.

Introduction

The COVID-19 pandemic has been unprecedented in terms of its direct health impacts and disruption of many aspects of modern society. It has also been remarkable in the speed with which scientists and industry collaborated in the production and testing of a range of vaccines.

It became apparent quickly that the COVID-19 vaccines did not stimulate sterilising immunity but provided protection against severe illness and death, most importantly in those with underlying risk factors. 1 2 The randomised trials that formed the evidence base for the initial deployment of vaccines included few subjects who were elderly, very young, pregnant, had immunodeficiency or severe comorbidity states. 3 Although quite large, the randomised trials documented few deaths and could not provide precise estimates of the effectiveness of the vaccines in reducing COVID-related and all-cause mortality.

The subsequent evaluation of vaccine effectiveness (VE) using controlled observational studies has been complicated by changes in the infectiousness and virulence of the SARS-CoV-2 virus, and rising background levels of vaccine-induced or naturally acquired immunity. Case fatality rates have fallen substantially, particularly in highly vaccinated countries. 4 Deaths are now concentrated in a group of older patients, those with obesity and those who have serious comorbidities or are immunocompromised. 5 This rapidly changing landscape created a need for continuous ‘real-world’ studies (RWS) of VE in susceptible groups, against emerging viral variants and after repeated vaccine doses. 6 These studies use data collected outside of clinical trial settings to define exposures, endpoints, and relevant covariates. This is achieved by analysing data from electronic medical records, administrative records, death registries, and registries established specifically to record infection status and vaccine receipt. 6

Most VE studies of COVID-19 vaccines have employed large population-scale linked routinely collected data sets. However, countries have varied in the timeliness of their response to this major challenge. In some countries, for instance Israel and UK, collaborations between researchers, health service providers, and government agencies enabled rapid analyses of large data sets using sophisticated techniques to adjust for confounding and other sources of bias. In contrast, other countries, for instance Australia and Aotearoa/New Zealand, were slow to conduct effectiveness studies, in part because of low infection rates early in the pandemic, and in Australia because of difficulties in accessing the necessary linked data sets. 7 8

Systematic reviews of VE studies have concentrated, appropriately, on the vaccines’ ability to prevent serious illness and death. 9–12 They have been consistent in confirming that multiple doses of the available vaccines have been associated with large reductions in mortality, with quite rapid waning (over months) in protection, mandating a need for repeated booster doses. As the impacts of vaccines on infection and transmission have been limited and transient, 13 it diminishes the value of infection as the principal study endpoint. The decline in PCR testing and registration of antigen test results have reduced the value of test results as the basis for test negative designs. 14 15 The nature of COVID-19-related hospitalisations has changed during the pandemic with an increase in incidental findings of infection through routine testing of patients admitted for other reasons. 15 On the other hand, there has been an increasing focus on excess all-cause mortality as a measure of the success of countries in controlling the spread of the virus and mitigating its negative impacts on healthcare systems. 16 17

The COVID-19 pandemic has been a historic event that we must learn from. The rapid deployment of vaccines, followed by studies of their effectiveness, represents the largest and most important healthcare intervention in recent history and one that was evaluated largely using non-randomised studies. The sense of pandemic urgency led to rapid development of strategies to establish data sets, designs, and analytic approaches. This evolution of study questions, data designs, and methods through the course of the pandemic provides a unique learning opportunity for policy makers and researchers alike.

We plan to conduct a scoping review of the evidence base on real-world COVID-19 VE, focusing on studies that report on death as an outcome, to document this evolution. Specifically we will explore: how policy-relevant questions changed over the course of the pandemic, and how these affected the choices of data sources, designs, and analytical methods. By analysing these, we hope to provide information that is useful to the following stakeholders:

Policy makers and health system managers: by indicating what data sets will have to be created de novo and the need for linkage to existing routinely collected data in responding to future pandemics.

Clinicians and laboratory scientists: by identifying the disease manifestations and clinical and demographic vulnerability factors that will be required to inform the designs and analyses needed to evaluate the effectiveness of vaccines and other interventions, how these may change over the course of a future pandemic, and how the clinical community can advocate for the appropriate data elements to be linked and made available to researchers.

Data scientists and methodologists: to provide guidance as to study designs, analytical and adjustment techniques that are most often used in providing rapid estimates of VE early in a future pandemic; to advocate for the data elements required to deal with confounding to be collected and available in a linked analysable form.

Vaccine manufacturers: to understand better the postlicensing requirements for vaccines and pharmaceutical products under pandemic conditions and contribute appropriately to the necessary evaluations.

The pharmacoepidemiology community generally: the rapid evaluation of VE during the COVID-19 pandemic provides lessons for the timely investigation of a range of pharmaceutical treatments for emerging health threats.

We will conduct a scoping review, following the methods published by the Joanna Briggs Institute 18 and report the results according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement for scoping review (PRISMA-ScR). 19 This scoping review is registered with the Open Science Framework (OSF; https://doi.org/10.17605/OSF.IO/ZHDKR ). Data extraction has begun (25 September 2023, after protocol registration), and will continue for approximately 12 months.

Information sources and data selection

We will retrieve relevant studies from the VIEW-hub database, 20 maintained by Johns Hopkins Bloomberg School of Public Health. This database includes a wide range of study types including vaccine efficacy trials, VE studies, impact studies, and safety studies. As our principal aim is to describe the evolution of observational VE studies using real-world data, we used the VIEW-hub ‘effectiveness studies’ data set.

The VIEW-hub search strategy and inclusion criteria for this data set have been described in detail elsewhere (see online supplemental file ). 21 Briefly, the ‘effectiveness studies’ data set includes both published and preprint studies of VE identified from PubMed, Embase, Scopus, Web of Science, the WHO COVID Database, MMWR, Eurosurveillance, medRxiv, bioRxiv, SSRN, Europe PMC, Research Square, and Knowledge Hub, as well as Google alerts for COVID-19 VE studies. Studies are screened weekly by the same two epidemiologists at Johns Hopkins Bloomberg School of Public Health, and the following data elements are extracted for studies included in the data set: study author, title, date published, link to paper, country of origin, vaccine studied, variant studied, population, study start and end date, and outcomes of interest. Studies in the data set can be filtered by the vaccine, variant, outcomes, study population, and region variables through drop-down menus.

Supplemental material

Studies must also meet minimum criteria for causal inference studies using real-world data. The studies must include both vaccinated and unvaccinated (or other control) subjects, drawn from a comparable time period, capturing the relevant endpoints in both groups, having a secure record of vaccination (not relying on recall) and be free of obvious major methodological flaws. The latter judgement was not based on a strict risk of bias assessment.

To identify studies in the VIEW-hub’s ‘effectiveness studies’ data set that examine mortality (either all-cause or cause-specific), we will use the drop-down menu feature to select study outcomes coded as ‘death’. No additional eligibility criteria will be applied.

At the time of writing this protocol (1 August 2023), the VIEW-hub database lists 495 observational studies of VE from 50 countries, and 92 (~19%) list ‘death’ as an endpoint.

Data extraction

We will extract data on:

Study characteristics : country, study design, publication status, protocol available, funding sources (including whether the study was funded by an independent source or manufacturer), study ethics approval (or waiver), consent requirements (or waiver).

Study context : reported vaccine policies in place, reported dominant viral variant at time of study.

PICO-T : inclusion and exclusion criteria, exposure (ie, vaccine(s)) and definition of exposure, control group, outcome definitions, outcomes collection period duration of follow-up and number of deaths.

Data sources and additional variables : the types of data sources used (eg, survey, electronic medical records, and administrative data), which were linked at an individual level and which were not, baseline confounders collected, and for adjusted outcomes which variables they were adjusted for.

Analytical strategies to minimise bias : methods for minimising baseline confounding (eg, propensity score analysis, instrumental variable analysis, covariate adjustment, self-controlled designs, etc) and further details of how the methods were implemented as appropriate, such as how the propensity score was implemented (matching, stratification, or inverse probability of treatment weights) and which variables were included in the propensity score model. Additionally, we will extract details on whether a sensitivity analyses was conducted, subgroups analysed, methods used for dealing with missing data, and methods used for dealing with time varying environmental risk.

We anticipate that there will be a few data points where it will be difficult to provide an exhaustive list of potential categories for some of the variables of interest a priori. We will therefore take an inductive approach to categorising variables such as ‘data sources’, ‘inclusion criteria’, and ‘adjustment techniques’ by entering them in free text and then developing categories through group discussion.

The lead author (PS) will develop a purpose-built data-extraction form in SharePoint Lists and a blank copy of the form and data dictionary will be provided on our OSF site. PS will also develop a validation set using a random sample of seven papers and verified by experts in pharmacoepidemiology (DH) and analysis (XC). A single author (CD) will independently extract data on the validation set until 80% agreement is achieved, at which stage they will continue with data extraction. A second reviewer (PS) will check the accuracy of all data extractions, and a core team (DH, CD, PS, and XC) will meet regularly to discuss each study, ensure it meets the inclusion criteria, and the main messages that it provides. The broader study team will meet less frequently to address issues arising and ensure data are categorised in a meaningful way that helps to inform decision making.

All data will be made publicly available via our study’s OSF page ( https://osf.io/m4cbf/ ).

Assessment of risk of bias

We aim to describe the evolution of the literature and will therefore not conduct a formal assessment of the risk of bias in the included studies. However, all included studies in the VIEW-hub database must meet a minimal set of quality criteria, and while this does not mean that they are free of bias, the process aims to ensure a baseline level of quality.

Data synthesis

To describe the evolution of RWS of COVID-19 VE over the course of the pandemic, we will use descriptive statistics to quantify study characteristics—including evolution of study designs (eg, test-negative designs, cohorts, and regression discontinuity), research questions asked (eg, comparisons of two doses vs boosters, effectiveness, and waning effect), data sources (eg, regularly collected population data and registry data), analytic approaches (eg, by design or form of adjustment), populations included, countries studied, outcome definitions, and event rates.

We will provide a temporal sequence of these characteristics overall, and where there are sufficient data within countries, present them visually (eg, as annotated stacked area graphs) to establish a template that enables anticipation of study questions and therefore supports planning for data availability in future pandemics.

We plan to develop interactive visuals as outputs so that stakeholders can interrogate the data further. All data manipulation, analysis, and visualisation will occur using Python and R and we will share all code via OSF.

Review team and consultation

Our review team and reference group consist of content experts in review methodology, vaccine and drug effectiveness studies, biostatistics, and data science. Several have been involved directly in the conduct of VE studies during the COVID-19 pandemic and have a good working knowledge of the relevant literature. Most of the team members are actively involved in the National Health and Medical Research Council (NHMRC)-funded Centre for Research Excellence in Medicines Intelligence, which aims to accelerate real-world evidence development to inform medicines policy decision making. 22 Our reference group also comprises end users in infectious diseases and pandemic management, vaccine epidemiology, and medicines and vaccine policy.

All authors and advisory group members have provided comment on this protocol, and the appropriateness of the research questions and data elements. The advisory group will be consulted on how best to present the data so that it is usable and helps with decision making in each member’s respective area.

In addition, we anticipate that the data we collect can be used for future review automation work and improve the efficiency of research. Our advisory group also includes an expert in review methodology and automation who will provide advice on future-proofing our dataset.

Ethics and dissemination

As this scoping review will only include data in the public domain, ethics review is not required.

Findings of this review will be relevant to several stakeholders, including those involved in pandemic response, data infrastructure, and health technology evaluation. As such, we will disseminate our findings in five ways: (1) working papers for policy makers in Australia; (2) open access publication of findings in peer-reviewed journals; (3) presentation of findings at local and international infectious disease, vaccine, health systems, and health management conferences; (4) online interactive visual to allow interrogation of the extracted data; and (5) open access to our data, code, and preprints via OSF.

Ethics statements

Patient consent for publication.

Not applicable.

Acknowledgments

We would like to acknowledge the advisory group and Oyungerel Byambasuren to their feedback and comments on draft versions of this document, particularly on the methodology and which variables to collect to provide meaningful information to decision makers.

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Contributors PS and DH conceptualised the project, acquired the funding, and are acting as project supervisors. PS, CD, XC, MOF, RL, SN, NLP, S-AP, and DH contributed to the methodology. PS developed the resources and database and will oversee database and project management. PS, DH, and XC piloted the database and extraction tool and developed the validation set. CD is conducting the data extraction which will be checked by PS. PS, XC, and MOF developed the data synthesis plan. PS and DH wrote the original draft of this manuscript, and PS, CD, XC, MOF, RL, SN, NLP, S-AP, and DH all edited and reviewed the draft and final revisions.

Funding Medicines Intelligence Centre for Research Excellence (MI-CRE) 2022 Project Incubator Grant; The MI-CRE is supported by the National Health and Medical Research Council’s Centres of Research Excellence (CRE) scheme (ID 1196900). RL is supported by a National Health and Medical Research Council (NHMRC) Early Career Fellowship (APP1156368). MOF is supported by a Future Leader Fellowship from the National Heart Foundation of Australia (ID: 105609). XC is supported by a NHMRC Postgraduate Scholarship (ID: 2005259).

Competing interests None declared.

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A Review of Coronavirus Disease-2019 (COVID-19)

Tanu singhal.

Department of Pediatrics and Infectious Disease, Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute, Mumbai, India

There is a new public health crises threatening the world with the emergence and spread of 2019 novel coronavirus (2019-nCoV) or the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus originated in bats and was transmitted to humans through yet unknown intermediary animals in Wuhan, Hubei province, China in December 2019. There have been around 96,000 reported cases of coronavirus disease 2019 (COVID-2019) and 3300 reported deaths to date (05/03/2020). The disease is transmitted by inhalation or contact with infected droplets and the incubation period ranges from 2 to 14 d. The symptoms are usually fever, cough, sore throat, breathlessness, fatigue, malaise among others. The disease is mild in most people; in some (usually the elderly and those with comorbidities), it may progress to pneumonia, acute respiratory distress syndrome (ARDS) and multi organ dysfunction. Many people are asymptomatic. The case fatality rate is estimated to range from 2 to 3%. Diagnosis is by demonstration of the virus in respiratory secretions by special molecular tests. Common laboratory findings include normal/ low white cell counts with elevated C-reactive protein (CRP). The computerized tomographic chest scan is usually abnormal even in those with no symptoms or mild disease. Treatment is essentially supportive; role of antiviral agents is yet to be established. Prevention entails home isolation of suspected cases and those with mild illnesses and strict infection control measures at hospitals that include contact and droplet precautions. The virus spreads faster than its two ancestors the SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV), but has lower fatality. The global impact of this new epidemic is yet uncertain.

Introduction

The 2019 novel coronavirus (2019-nCoV) or the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) as it is now called, is rapidly spreading from its origin in Wuhan City of Hubei Province of China to the rest of the world [ 1 ]. Till 05/03/2020 around 96,000 cases of coronavirus disease 2019 (COVID-19) and 3300 deaths have been reported [ 2 ]. India has reported 29 cases till date. Fortunately so far, children have been infrequently affected with no deaths. But the future course of this virus is unknown. This article gives a bird’s eye view about this new virus. Since knowledge about this virus is rapidly evolving, readers are urged to update themselves regularly.

Coronaviruses are enveloped positive sense RNA viruses ranging from 60 nm to 140 nm in diameter with spike like projections on its surface giving it a crown like appearance under the electron microscope; hence the name coronavirus [ 3 ]. Four corona viruses namely HKU1, NL63, 229E and OC43 have been in circulation in humans, and generally cause mild respiratory disease.

There have been two events in the past two decades wherein crossover of animal betacorona viruses to humans has resulted in severe disease. The first such instance was in 2002–2003 when a new coronavirus of the β genera and with origin in bats crossed over to humans via the intermediary host of palm civet cats in the Guangdong province of China. This virus, designated as severe acute respiratory syndrome coronavirus affected 8422 people mostly in China and Hong Kong and caused 916 deaths (mortality rate 11%) before being contained [ 4 ]. Almost a decade later in 2012, the Middle East respiratory syndrome coronavirus (MERS-CoV), also of bat origin, emerged in Saudi Arabia with dromedary camels as the intermediate host and affected 2494 people and caused 858 deaths (fatality rate 34%) [ 5 ].

Origin and Spread of COVID-19 [ 1 , 2 , 6 ]

In December 2019, adults in Wuhan, capital city of Hubei province and a major transportation hub of China started presenting to local hospitals with severe pneumonia of unknown cause. Many of the initial cases had a common exposure to the Huanan wholesale seafood market that also traded live animals. The surveillance system (put into place after the SARS outbreak) was activated and respiratory samples of patients were sent to reference labs for etiologic investigations. On December 31st 2019, China notified the outbreak to the World Health Organization and on 1st January the Huanan sea food market was closed. On 7th January the virus was identified as a coronavirus that had >95% homology with the bat coronavirus and > 70% similarity with the SARS- CoV. Environmental samples from the Huanan sea food market also tested positive, signifying that the virus originated from there [ 7 ]. The number of cases started increasing exponentially, some of which did not have exposure to the live animal market, suggestive of the fact that human-to-human transmission was occurring [ 8 ]. The first fatal case was reported on 11th Jan 2020. The massive migration of Chinese during the Chinese New Year fuelled the epidemic. Cases in other provinces of China, other countries (Thailand, Japan and South Korea in quick succession) were reported in people who were returning from Wuhan. Transmission to healthcare workers caring for patients was described on 20th Jan, 2020. By 23rd January, the 11 million population of Wuhan was placed under lock down with restrictions of entry and exit from the region. Soon this lock down was extended to other cities of Hubei province. Cases of COVID-19 in countries outside China were reported in those with no history of travel to China suggesting that local human-to-human transmission was occurring in these countries [ 9 ]. Airports in different countries including India put in screening mechanisms to detect symptomatic people returning from China and placed them in isolation and testing them for COVID-19. Soon it was apparent that the infection could be transmitted from asymptomatic people and also before onset of symptoms. Therefore, countries including India who evacuated their citizens from Wuhan through special flights or had travellers returning from China, placed all people symptomatic or otherwise in isolation for 14 d and tested them for the virus.

Cases continued to increase exponentially and modelling studies reported an epidemic doubling time of 1.8 d [ 10 ]. In fact on the 12th of February, China changed its definition of confirmed cases to include patients with negative/ pending molecular tests but with clinical, radiologic and epidemiologic features of COVID-19 leading to an increase in cases by 15,000 in a single day [ 6 ]. As of 05/03/2020 96,000 cases worldwide (80,000 in China) and 87 other countries and 1 international conveyance (696, in the cruise ship Diamond Princess parked off the coast of Japan) have been reported [ 2 ]. It is important to note that while the number of new cases has reduced in China lately, they have increased exponentially in other countries including South Korea, Italy and Iran. Of those infected, 20% are in critical condition, 25% have recovered, and 3310 (3013 in China and 297 in other countries) have died [ 2 ]. India, which had reported only 3 cases till 2/3/2020, has also seen a sudden spurt in cases. By 5/3/2020, 29 cases had been reported; mostly in Delhi, Jaipur and Agra in Italian tourists and their contacts. One case was reported in an Indian who traveled back from Vienna and exposed a large number of school children in a birthday party at a city hotel. Many of the contacts of these cases have been quarantined.

These numbers are possibly an underestimate of the infected and dead due to limitations of surveillance and testing. Though the SARS-CoV-2 originated from bats, the intermediary animal through which it crossed over to humans is uncertain. Pangolins and snakes are the current suspects.

Epidemiology and Pathogenesis [ 10 , 11 ]

All ages are susceptible. Infection is transmitted through large droplets generated during coughing and sneezing by symptomatic patients but can also occur from asymptomatic people and before onset of symptoms [ 9 ]. Studies have shown higher viral loads in the nasal cavity as compared to the throat with no difference in viral burden between symptomatic and asymptomatic people [ 12 ]. Patients can be infectious for as long as the symptoms last and even on clinical recovery. Some people may act as super spreaders; a UK citizen who attended a conference in Singapore infected 11 other people while staying in a resort in the French Alps and upon return to the UK [ 6 ]. These infected droplets can spread 1–2 m and deposit on surfaces. The virus can remain viable on surfaces for days in favourable atmospheric conditions but are destroyed in less than a minute by common disinfectants like sodium hypochlorite, hydrogen peroxide etc. [ 13 ]. Infection is acquired either by inhalation of these droplets or touching surfaces contaminated by them and then touching the nose, mouth and eyes. The virus is also present in the stool and contamination of the water supply and subsequent transmission via aerosolization/feco oral route is also hypothesized [ 6 ]. As per current information, transplacental transmission from pregnant women to their fetus has not been described [ 14 ]. However, neonatal disease due to post natal transmission is described [ 14 ]. The incubation period varies from 2 to 14 d [median 5 d]. Studies have identified angiotensin receptor 2 (ACE 2 ) as the receptor through which the virus enters the respiratory mucosa [ 11 ].

The basic case reproduction rate (BCR) is estimated to range from 2 to 6.47 in various modelling studies [ 11 ]. In comparison, the BCR of SARS was 2 and 1.3 for pandemic flu H1N1 2009 [ 2 ].

Clinical Features [ 8 , 15 – 18 ]

The clinical features of COVID-19 are varied, ranging from asymptomatic state to acute respiratory distress syndrome and multi organ dysfunction. The common clinical features include fever (not in all), cough, sore throat, headache, fatigue, headache, myalgia and breathlessness. Conjunctivitis has also been described. Thus, they are indistinguishable from other respiratory infections. In a subset of patients, by the end of the first week the disease can progress to pneumonia, respiratory failure and death. This progression is associated with extreme rise in inflammatory cytokines including IL2, IL7, IL10, GCSF, IP10, MCP1, MIP1A, and TNFα [ 15 ]. The median time from onset of symptoms to dyspnea was 5 d, hospitalization 7 d and acute respiratory distress syndrome (ARDS) 8 d. The need for intensive care admission was in 25–30% of affected patients in published series. Complications witnessed included acute lung injury, ARDS, shock and acute kidney injury. Recovery started in the 2nd or 3rd wk. The median duration of hospital stay in those who recovered was 10 d. Adverse outcomes and death are more common in the elderly and those with underlying co-morbidities (50–75% of fatal cases). Fatality rate in hospitalized adult patients ranged from 4 to 11%. The overall case fatality rate is estimated to range between 2 and 3% [ 2 ].

Interestingly, disease in patients outside Hubei province has been reported to be milder than those from Wuhan [ 17 ]. Similarly, the severity and case fatality rate in patients outside China has been reported to be milder [ 6 ]. This may either be due to selection bias wherein the cases reporting from Wuhan included only the severe cases or due to predisposition of the Asian population to the virus due to higher expression of ACE 2 receptors on the respiratory mucosa [ 11 ].

Disease in neonates, infants and children has been also reported to be significantly milder than their adult counterparts. In a series of 34 children admitted to a hospital in Shenzhen, China between January 19th and February 7th, there were 14 males and 20 females. The median age was 8 y 11 mo and in 28 children the infection was linked to a family member and 26 children had history of travel/residence to Hubei province in China. All the patients were either asymptomatic (9%) or had mild disease. No severe or critical cases were seen. The most common symptoms were fever (50%) and cough (38%). All patients recovered with symptomatic therapy and there were no deaths. One case of severe pneumonia and multiorgan dysfunction in a child has also been reported [ 19 ]. Similarly the neonatal cases that have been reported have been mild [ 20 ].

Diagnosis [ 21 ]

A suspect case is defined as one with fever, sore throat and cough who has history of travel to China or other areas of persistent local transmission or contact with patients with similar travel history or those with confirmed COVID-19 infection. However cases may be asymptomatic or even without fever. A confirmed case is a suspect case with a positive molecular test.

Specific diagnosis is by specific molecular tests on respiratory samples (throat swab/ nasopharyngeal swab/ sputum/ endotracheal aspirates and bronchoalveolar lavage). Virus may also be detected in the stool and in severe cases, the blood. It must be remembered that the multiplex PCR panels currently available do not include the COVID-19. Commercial tests are also not available at present. In a suspect case in India, the appropriate sample has to be sent to designated reference labs in India or the National Institute of Virology in Pune. As the epidemic progresses, commercial tests will become available.

Other laboratory investigations are usually non specific. The white cell count is usually normal or low. There may be lymphopenia; a lymphocyte count <1000 has been associated with severe disease. The platelet count is usually normal or mildly low. The CRP and ESR are generally elevated but procalcitonin levels are usually normal. A high procalcitonin level may indicate a bacterial co-infection. The ALT/AST, prothrombin time, creatinine, D-dimer, CPK and LDH may be elevated and high levels are associated with severe disease.

The chest X-ray (CXR) usually shows bilateral infiltrates but may be normal in early disease. The CT is more sensitive and specific. CT imaging generally shows infiltrates, ground glass opacities and sub segmental consolidation. It is also abnormal in asymptomatic patients/ patients with no clinical evidence of lower respiratory tract involvement. In fact, abnormal CT scans have been used to diagnose COVID-19 in suspect cases with negative molecular diagnosis; many of these patients had positive molecular tests on repeat testing [ 22 ].

Differential Diagnosis [ 21 ]

The differential diagnosis includes all types of respiratory viral infections [influenza, parainfluenza, respiratory syncytial virus (RSV), adenovirus, human metapneumovirus, non COVID-19 coronavirus], atypical organisms (mycoplasma, chlamydia) and bacterial infections. It is not possible to differentiate COVID-19 from these infections clinically or through routine lab tests. Therefore travel history becomes important. However, as the epidemic spreads, the travel history will become irrelevant.

Treatment [ 21 , 23 ]

Treatment is essentially supportive and symptomatic.

The first step is to ensure adequate isolation (discussed later) to prevent transmission to other contacts, patients and healthcare workers. Mild illness should be managed at home with counseling about danger signs. The usual principles are maintaining hydration and nutrition and controlling fever and cough. Routine use of antibiotics and antivirals such as oseltamivir should be avoided in confirmed cases. In hypoxic patients, provision of oxygen through nasal prongs, face mask, high flow nasal cannula (HFNC) or non-invasive ventilation is indicated. Mechanical ventilation and even extra corporeal membrane oxygen support may be needed. Renal replacement therapy may be needed in some. Antibiotics and antifungals are required if co-infections are suspected or proven. The role of corticosteroids is unproven; while current international consensus and WHO advocate against their use, Chinese guidelines do recommend short term therapy with low-to-moderate dose corticosteroids in COVID-19 ARDS [ 24 , 25 ]. Detailed guidelines for critical care management for COVID-19 have been published by the WHO [ 26 ]. There is, as of now, no approved treatment for COVID-19. Antiviral drugs such as ribavirin, lopinavir-ritonavir have been used based on the experience with SARS and MERS. In a historical control study in patients with SARS, patients treated with lopinavir-ritonavir with ribavirin had better outcomes as compared to those given ribavirin alone [ 15 ].

In the case series of 99 hospitalized patients with COVID-19 infection from Wuhan, oxygen was given to 76%, non-invasive ventilation in 13%, mechanical ventilation in 4%, extracorporeal membrane oxygenation (ECMO) in 3%, continuous renal replacement therapy (CRRT) in 9%, antibiotics in 71%, antifungals in 15%, glucocorticoids in 19% and intravenous immunoglobulin therapy in 27% [ 15 ]. Antiviral therapy consisting of oseltamivir, ganciclovir and lopinavir-ritonavir was given to 75% of the patients. The duration of non-invasive ventilation was 4–22 d [median 9 d] and mechanical ventilation for 3–20 d [median 17 d]. In the case series of children discussed earlier, all children recovered with basic treatment and did not need intensive care [ 17 ].

There is anecdotal experience with use of remdeswir, a broad spectrum anti RNA drug developed for Ebola in management of COVID-19 [ 27 ]. More evidence is needed before these drugs are recommended. Other drugs proposed for therapy are arbidol (an antiviral drug available in Russia and China), intravenous immunoglobulin, interferons, chloroquine and plasma of patients recovered from COVID-19 [ 21 , 28 , 29 ]. Additionally, recommendations about using traditional Chinese herbs find place in the Chinese guidelines [ 21 ].

Prevention [ 21 , 30 ]

Since at this time there are no approved treatments for this infection, prevention is crucial. Several properties of this virus make prevention difficult namely, non-specific features of the disease, the infectivity even before onset of symptoms in the incubation period, transmission from asymptomatic people, long incubation period, tropism for mucosal surfaces such as the conjunctiva, prolonged duration of the illness and transmission even after clinical recovery.

Isolation of confirmed or suspected cases with mild illness at home is recommended. The ventilation at home should be good with sunlight to allow for destruction of virus. Patients should be asked to wear a simple surgical mask and practice cough hygiene. Caregivers should be asked to wear a surgical mask when in the same room as patient and use hand hygiene every 15–20 min.

The greatest risk in COVID-19 is transmission to healthcare workers. In the SARS outbreak of 2002, 21% of those affected were healthcare workers [ 31 ]. Till date, almost 1500 healthcare workers in China have been infected with 6 deaths. The doctor who first warned about the virus has died too. It is important to protect healthcare workers to ensure continuity of care and to prevent transmission of infection to other patients. While COVID-19 transmits as a droplet pathogen and is placed in Category B of infectious agents (highly pathogenic H5N1 and SARS), by the China National Health Commission, infection control measures recommended are those for category A agents (cholera, plague). Patients should be placed in separate rooms or cohorted together. Negative pressure rooms are not generally needed. The rooms and surfaces and equipment should undergo regular decontamination preferably with sodium hypochlorite. Healthcare workers should be provided with fit tested N95 respirators and protective suits and goggles. Airborne transmission precautions should be taken during aerosol generating procedures such as intubation, suction and tracheostomies. All contacts including healthcare workers should be monitored for development of symptoms of COVID-19. Patients can be discharged from isolation once they are afebrile for atleast 3 d and have two consecutive negative molecular tests at 1 d sampling interval. This recommendation is different from pandemic flu where patients were asked to resume work/school once afebrile for 24 h or by day 7 of illness. Negative molecular tests were not a prerequisite for discharge.

At the community level, people should be asked to avoid crowded areas and postpone non-essential travel to places with ongoing transmission. They should be asked to practice cough hygiene by coughing in sleeve/ tissue rather than hands and practice hand hygiene frequently every 15–20 min. Patients with respiratory symptoms should be asked to use surgical masks. The use of mask by healthy people in public places has not shown to protect against respiratory viral infections and is currently not recommended by WHO. However, in China, the public has been asked to wear masks in public and especially in crowded places and large scale gatherings are prohibited (entertainment parks etc). China is also considering introducing legislation to prohibit selling and trading of wild animals [ 32 ].

The international response has been dramatic. Initially, there were massive travel restrictions to China and people returning from China/ evacuated from China are being evaluated for clinical symptoms, isolated and tested for COVID-19 for 2 wks even if asymptomatic. However, now with rapid world wide spread of the virus these travel restrictions have extended to other countries. Whether these efforts will lead to slowing of viral spread is not known.

A candidate vaccine is under development.

Practice Points from an Indian Perspective

At the time of writing this article, the risk of coronavirus in India is extremely low. But that may change in the next few weeks. Hence the following is recommended:

• Healthcare providers should take travel history of all patients with respiratory symptoms, and any international travel in the past 2 wks as well as contact with sick people who have travelled internationally.
• They should set up a system of triage of patients with respiratory illness in the outpatient department and give them a simple surgical mask to wear. They should use surgical masks themselves while examining such patients and practice hand hygiene frequently.
• Suspected cases should be referred to government designated centres for isolation and testing (in Mumbai, at this time, it is Kasturba hospital). Commercial kits for testing are not yet available in India.
• Patients admitted with severe pneumonia and acute respiratory distress syndrome should be evaluated for travel history and placed under contact and droplet isolation. Regular decontamination of surfaces should be done. They should be tested for etiology using multiplex PCR panels if logistics permit and if no pathogen is identified, refer the samples for testing for SARS-CoV-2.
• All clinicians should keep themselves updated about recent developments including global spread of the disease.
• Non-essential international travel should be avoided at this time.
• People should stop spreading myths and false information about the disease and try to allay panic and anxiety of the public.

Conclusions

This new virus outbreak has challenged the economic, medical and public health infrastructure of China and to some extent, of other countries especially, its neighbours. Time alone will tell how the virus will impact our lives here in India. More so, future outbreaks of viruses and pathogens of zoonotic origin are likely to continue. Therefore, apart from curbing this outbreak, efforts should be made to devise comprehensive measures to prevent future outbreaks of zoonotic origin.

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‘Getting control of Corona takes many angles’: COVID-19 vaccine knowledge, attitudes and beliefs among refugee/immigrant/migrant communities in four US cities

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A Owen-Smith, J Porter, C m Thomas, S Clarke, M m Ogrodnick, L J Hand, E Dawson-Hahn, M h O’Connor, I Feinberg, S Adde, R Desta, Z Yubo, A Chin, M Safi, ‘Getting control of Corona takes many angles’: COVID-19 vaccine knowledge, attitudes and beliefs among refugee/immigrant/migrant communities in four US cities, Health Education Research , Volume 39, Issue 2, April 2024, Pages 182–196, https://doi.org/10.1093/her/cyae003

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The objectives of the study were to (i) document refugee, immigrant and migrant (RIM) communities’ knowledge, attitudes and beliefs (KABs) related to the Coronavirus disease (COVID-19) vaccine and (ii) identify best practices for developing and disseminating culturally and linguistically responsive health messaging addressing those KABs. Thirteen online focus groups (OFGs) in 10 languages were conducted. Each OFG was conducted in the participants’ native language. OFGs were recorded, transcribed, translated and uploaded to qualitative software for coding. A thematic analysis was conducted. Results suggest that while there was some variation between different language groups (e.g. whether religious leaders were seen as trusted sources of information about COVID), there were also important commonalities. Most language groups (i) alluded to hearing about or having gaps in knowledge about COVID-19/the COVID-19 vaccine, (ii) reported hearing negative or conflicting stories about the vaccine and (iii) shared concerns about the negative side effects of the vaccine. There continues to be a need for health messaging in RIM communities that is culturally and linguistically concordant and follows health literacy guidelines. Message content about the COVID-19 vaccine should focus on vaccine importance, effectiveness and safety, should be multimodal and should be primarily delivered by healthcare professionals and community members who have already been vaccinated.

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About COVID-19

What is covid-19.

COVID-19 (coronavirus disease 2019) is a disease caused by a virus named SARS-CoV-2. It can be very contagious and spreads quickly. Over one million people have died from COVID-19 in the United States.

COVID-19 most often causes respiratory symptoms that can feel much like a cold, the flu, or pneumonia. COVID-19 may attack more than your lungs and respiratory system. Other parts of your body may also be affected by the disease. Most people with COVID-19 have mild symptoms, but some people become severely ill.

Some people including those with minor or no symptoms will develop Post-COVID Conditions – also called “Long COVID.”

How does COVID-19 spread?

COVID-19 spreads when an infected person breathes out droplets and very small particles that contain the virus. Other people can breathe in these droplets and particles, or these droplets and particles can land on their eyes, nose, or mouth. In some circumstances, these droplets may contaminate surfaces they touch.

Anyone infected with COVID-19 can spread it, even if they do NOT have symptoms.

The risk of animals spreading the virus that causes COVID-19 to people is low. The virus can spread from people to animals during close contact. People with suspected or confirmed COVID-19 should avoid contact with animals.

What are antibodies and how do they help protect me?

Antibodies are proteins your immune system makes to help fight infection and protect you from getting sick in the future. A positive antibody test  result can help identify someone who has had COVID-19 in the past or has been vaccinated against COVID-19. Studies show that people who have antibodies from an infection with the virus that causes COVID-19 can improve their level of protection by getting vaccinated.

What are ways to prevent COVID-19?

There are many actions you can take to help protect you, your household, and your community from COVID-19. CDC’s COVID-19 hospital admission levels help individuals and communities decide when to take action to protect yourself and others based on the latest data and information from your area.

In addition to staying up to date with  COVID-19 vaccines and basic health and hygiene practices like handwashing , CDC recommends some prevention actions at all COVID-19 hospital admission levels.

Who is at risk of severe illness from COVID-19?

Some people are more likely than others to get very sick if they get COVID-19. This includes people who are older, are immunocompromised, have certain disabilities , or have underlying health conditions . Understanding your COVID-19 risk and the risks that might affect others can help you make decisions to protect yourself and others .

What are variants of COVID-19?

Viruses are constantly changing, including the virus that causes COVID-19. These changes occur over time and can lead to new strains of the virus or variants of COVID-19 . Slowing the spread of the virus, by protecting yourself and others , can help slow new variants from developing. CDC is working with state and local public health officials to monitor the spread of all variants, including Omicron.

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Research Roundup: How the Pandemic Changed Management

• Mark C. Bolino,
• Jacob M. Whitney,
• Sarah E. Henry

Lessons from 69 articles published in top management and applied psychology journals.

Researchers recently reviewed 69 articles focused on the management implications of the Covid-19 pandemic that were published between March 2020 and July 2023 in top journals in management and applied psychology. The review highlights the numerous ways in which employees, teams, leaders, organizations, and societies were impacted and offers lessons for managing through future pandemics or other events of mass disruption.

The recent pandemic disrupted life as we know it, including for employees and organizations around the world. To understand such changes, we recently reviewed 69 articles focused on the management implications of the Covid-19 pandemic. These papers were published between March 2020 and July 2023 in top journals in management and applied psychology.

• Mark C. Bolino is the David L. Boren Professor and the Michael F. Price Chair in International Business at the University of Oklahoma’s Price College of Business. His research focuses on understanding how an organization can inspire its employees to go the extra mile without compromising their personal well-being.
• JW Jacob M. Whitney is a doctoral candidate in management at the University of Oklahoma’s Price College of Business and an incoming assistant professor at Kennesaw State University. His research interests include leadership, teams, and organizational citizenship behavior.
• SH Sarah E. Henry is a doctoral candidate in management at the University of Oklahoma’s Price College of Business and an incoming assistant professor at the University of South Florida. Her research interests include organizational citizenship behaviors, workplace interpersonal dynamics, and international management.

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How americans view the coronavirus, covid-19 vaccines amid declining levels of concern, continued decline in share of u.s. adults with up-to-date vaccination.

Pew Research Center conducted this study to understand Americans’ views of the coronavirus and COVID-19 vaccines. For this analysis, we surveyed 10,133 U.S. adults from Feb. 7 to 11, 2024.

Everyone who took part in the survey is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way, nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for this report , along with responses, and its methodology .

A new Pew Research Center survey finds that just 20% of Americans view the coronavirus as a major threat to the health of the U.S. population today and only 10% are very concerned they will get it and require hospitalization. This data represents a low ebb of public concern about the virus that reached its height in the summer and fall of 2020, when as many as two-thirds of Americans viewed COVID-19 as a major threat to public health.

Just 28% of U.S. adults say they have received the updated COVID-19 vaccine, which the Centers for Disease Control and Prevention (CDC) recommended last fall to protect against serious illness. This stands in stark contrast to the spring and summer of 2021, when long lines and limited availability characterized the initial rollout of the first COVID-19 vaccines. A majority of U.S. adults (69%) had been fully vaccinated by August 2021.

Underscoring the limited demand for the updated COVID-19 vaccines, a larger share of U.S. adults say they’ve gotten a flu shot in the last six months than the updated coronavirus vaccine (44% vs. 28%). And despite a public health push encouraging adults to get both vaccines at the same time, almost half of those who received a flu shot from a health care provider chose not to get the updated COVID-19 vaccine.

The vast majority of Americans have some level of protection from the coronavirus because of vaccination, prior infection or a combination of the two. This has led to a decline in severe illness from the disease.

Still, the virus continues to circulate widely in the United States , with wastewater data suggesting that cases in the early part of 2024 were among the highest they have been since the first omicron wave in 2022.  

Long COVID ranks among the concerns of public health experts. Long COVID refers to a variety of symptoms such as fatigue and brain fog that last longer than a month after a COVID-19 infection.

The survey – conducted among 10,133 U.S. adults from Feb. 7 to 11, 2024 – finds that 50% of Americans say it is extremely or very important for medical researchers and health care providers to understand and treat long COVID; 27% see this as a less important issue and 22% of Americans say they haven’t heard of long COVID.

Continuity and change: Partisan views of COVID-19

Partisanship remains one of the most powerful factors shaping views about COVID-19 vaccines and the virus. But the size and nature of differences between Republicans and Democrats have evolved since earlier stages of the outbreak.

For instance, the gap between the shares of Democrats and Republicans who view the coronavirus as a major threat to public health has fallen from 37 percentage points in May 2022 to 16 points today. In the pandemic’s first year, Democrats were routinely about 40 points more likely than Republicans to view the coronavirus as a major threat to the health of the U.S. population. This gap has waned as overall levels of concern have fallen.

When it comes to vaccination, Democrats and Democratic-leaning independents remain more likely than Republicans and GOP leaners to say they’ve received an updated COVID-19 vaccine (42% vs. 15%). This 27-point gap in recent vaccination is about the same as in January 2022 when 62% of Democrats and 33% of Republicans said they were up to date (i.e., fully vaccinated and recently boosted).

In addition to partisanship, age continues to matter a great deal in attitudes and behaviors tied to the coronavirus. And the intersection of partisanship and age reveals one of the biggest recent changes in the public’s response to the outbreak: a growing divergence between the oldest Republicans and oldest Democrats in vaccine uptake, which is explored below.

COVID-19 vaccination among adults ages 65 and older, by party

Older adults continue to be one of the most at-risk groups for severe illness and death from COVID-19.

When vaccines first became available in 2021, large majorities of both Republicans and Democrats ages 65 and older said they had received the vaccine. But as additional doses have become available, uptake among older Republicans has declined at a faster rate than among older Democrats.

In the current survey, 66% of Democrats ages 65 and older say they have received the updated COVID-19 vaccine, compared with 24% of Republicans ages 65 and older.

This 42-point partisan gap is much wider now than at other points since the start of the outbreak. For instance, in August 2021, 93% of older Democrats and 78% of older Republicans said they had received all the shots needed to be fully vaccinated (a 15-point gap). Go to the Appendix for more details .

How COVID-19 vaccination varies by age within parties

The impact of age is also striking when looking within political parties.

Among Democrats, about three-in-ten adults under 50 have received an updated COVID-19 vaccine, compared with 48% of those ages 50 to 64 and 66% of Democrats ages 65 and older.

Age differences within the GOP run in the same direction, but are much more modest, reflecting, in part, low overall levels of vaccine uptake.

How COVID-19 vaccination varies by race and ethnicity

Similar shares of White (28%), Black (29%) and Hispanic (27%) adults say they have gotten the updated vaccine. English-speaking Asian adults (35%) are slightly more likely to report receiving the updated vaccine.

As in past Center surveys, there are racial and ethnic differences in vaccine uptake among Democrats.

For instance, 50% of White Democrats and 42% of English-speaking Asian Democrats report having received the updated vaccine, compared with somewhat smaller shares of Black and Hispanic Democrats (32% each).

Views of long COVID

Half of Americans say it is extremely or very important for medical researchers and health care providers to understand and treat long COVID, considering all the different priorities they face.

About two-in-ten (21%) say it’s somewhat important for those in medicine to address long COVID, while 6% say it is not too or not at all important. Another 22% say they haven’t heard of long COVID.

More Democrats (61%) than Republicans (37%) say it is extremely or very important for medical researchers and health care providers to understand and treat long COVID.

A majority of women (56%) consider this extremely or very important; a smaller share of men (44%) say the same. The CDC has reported that women are more likely than men to develop long COVID symptoms.

Awareness of long COVID also shapes views on its importance: Those who have heard a lot about long COVID are more likely than those who have heard a little about it to say it’s extremely or very important for medical professional to address it (76% vs. 60%).

Views of the threat posed by the coronavirus

One-in-five Americans now say the coronavirus is a major threat to the health of the U.S. population, down from a high of 67% in July 2020.

Concern about the coronavirus as a major threat to the U.S. economy has also declined dramatically. Today, 23% of Americans say it’s a major threat to the economy, compared with 88% in May 2020. The pandemic spurred an economic recession in 2020 and a spike in unemployment that reached the highest levels since the Great Recession.

Federal policy on the coronavirus has changed as public concern – and the incidence of severe illness – has fallen. The Biden administration ended the public health emergency for the coronavirus pandemic in May 2023. And the CDC recently released updated guidelines with shorter isolation periods for adults testing positive for the disease.

While large partisan gaps characterized views of the coronavirus as a major threat to public health for much of the pandemic, those gaps were far smaller on views of the virus as a major threat to the economy. In the current survey, just a 6-point gap separates Republicans and Democrats with this view (20% vs. 26%, respectively) – similar to the 9-point party gap seen in May 2022.

Personal concern about getting or spreading COVID-19

About a quarter of Americans (27%) are very or somewhat concerned about getting a serious case of COVID-19 that would require hospitalization. A somewhat higher share (40%) say they are very or somewhat concerned they might spread the coronavirus to other people without knowing it.

Levels of concern for getting or spreading the coronavirus are about the same as they were in March 2023 and remain down dramatically from early in the pandemic.

The share of Americans who are very or somewhat concerned about getting a serious case is 26 points lower than in November 2020, before a COVID-19 vaccine was available to the public. And the share of Americans who are at least somewhat concerned about spreading COVID-19 without knowing it is down 24 points since November 2020.

Still, the current data shows how the virus remains a concern in daily life for many Americans, more than four years after the first confirmed coronavirus cases appeared in the U.S.

Consistent with past Center surveys, there are demographic and political differences in personal concern about getting a serious case of COVID-19 and unknowingly spreading the virus:

• Income: Lower-income Americans continue to be particularly concerned (38%) about getting a serious case of COVID-19. They’re also more likely than middle- and upper-income Americans to worry about unknowingly spreading COVID-19, but the differences are more modest.
• Party: Democrats (54%) are more than twice as likely as Republicans (24%) to be very or somewhat concerned about unknowingly spreading COVID-19. And they’re 16 points more likely to express concern about getting a serious case of the disease.
• Race and ethnicity: White Americans (20%) are less likely to be concerned about getting a serious case of COVID-19 than Black (43%), Hispanic (39%) and English-speaking Asian Americans (36%).

Some of the groups most personally concerned about getting a severe case of COVID-19 are also among the groups most concerned about the public health threat from the coronavirus. For example, Black adults and adults with lower incomes express more concern about the personal health and public health impact of the coronavirus than White adults and those with upper incomes.

Uptake of the flu shot

The survey finds 44% of U.S. adults say they have gotten a flu shot since August. This share is down slightly from last March, when 49% of Americans said they had recently gotten a flu shot.

Uptake varies by the following factors:

• Age: Older Americans continue to be more likely to report getting the flu shot. Two-thirds of Americans ages 65 and older say they have gotten the flu shot since August. By comparison, only about a third of those under age 50 say the same. These large age differences are seen among both Democrats and Republicans.
• Race and ethnicity: English-speaking Asian Americans (52%) and White Americans (48%) are more likely than Black Americans (38%) and Hispanic Americans (33%) to say they have gotten a flu shot since August. These racial and ethnic differences are consistent with past Center surveys.
• Partisan affiliation: Democrats are more likely than Republicans to say they got a flu shot this year (53% vs. 37%). This 16-point gap is twice as big now as it was in November 2020, during the pandemic’s first year. The current partisan difference in flu shot uptake is similar to the one recorded in March 2023.

The flu shot and updated COVID-19 vaccines are both recommended to protect against severe illness, but Americans approach these vaccines differently.

Americans are more likely to report that they received a flu shot than the updated COVID-19 vaccine this year (44% vs. 28%).

This gap in uptake between the flu shot and updated COVID-19 vaccine is more pronounced among Republicans than Democrats.

Republicans are more than twice as likely to say they’ve gotten a flu shot since August as to say they’ve received an updated COVID-19 vaccine (37% vs. 15%). Among Democrats, this difference is more modest (53% vs. 42%).

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About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .

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• The role of COVID-19 vaccines in preventing post-COVID-19 thromboembolic and cardiovascular complications
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• Núria Mercadé-Besora 1 , 2 , 3 ,
• Xintong Li 1 ,
• Raivo Kolde 4 ,
• Nhung TH Trinh 5 ,
• Maria T Sanchez-Santos 1 ,
• Wai Yi Man 1 ,
• Elena Roel 3 ,
• Carlen Reyes 3 ,
• http://orcid.org/0000-0003-0388-3403 Antonella Delmestri 1 ,
• Hedvig M E Nordeng 6 , 7 ,
• http://orcid.org/0000-0002-4036-3856 Anneli Uusküla 8 ,
• http://orcid.org/0000-0002-8274-0357 Talita Duarte-Salles 3 , 9 ,
• Clara Prats 2 ,
• http://orcid.org/0000-0002-3950-6346 Daniel Prieto-Alhambra 1 , 9 ,
• http://orcid.org/0000-0002-0000-0110 Annika M Jödicke 1 ,
• Martí Català 1
• 1 Pharmaco- and Device Epidemiology Group, Health Data Sciences, Botnar Research Centre, NDORMS , University of Oxford , Oxford , UK
• 2 Department of Physics , Universitat Politècnica de Catalunya , Barcelona , Spain
• 3 Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol) , IDIAP Jordi Gol , Barcelona , Catalunya , Spain
• 4 Institute of Computer Science , University of Tartu , Tartu , Estonia
• 5 Pharmacoepidemiology and Drug Safety Research Group, Department of Pharmacy, Faculty of Mathematics and Natural Sciences , University of Oslo , Oslo , Norway
• 6 School of Pharmacy , University of Oslo , Oslo , Norway
• 7 Division of Mental Health , Norwegian Institute of Public Health , Oslo , Norway
• 8 Department of Family Medicine and Public Health , University of Tartu , Tartu , Estonia
• 9 Department of Medical Informatics, Erasmus University Medical Center , Erasmus University Rotterdam , Rotterdam , Zuid-Holland , Netherlands
• Correspondence to Prof Daniel Prieto-Alhambra, Pharmaco- and Device Epidemiology Group, Health Data Sciences, Botnar Research Centre, NDORMS, University of Oxford, Oxford, UK; daniel.prietoalhambra{at}ndorms.ox.ac.uk

Objective To study the association between COVID-19 vaccination and the risk of post-COVID-19 cardiac and thromboembolic complications.

Methods We conducted a staggered cohort study based on national vaccination campaigns using electronic health records from the UK, Spain and Estonia. Vaccine rollout was grouped into four stages with predefined enrolment periods. Each stage included all individuals eligible for vaccination, with no previous SARS-CoV-2 infection or COVID-19 vaccine at the start date. Vaccination status was used as a time-varying exposure. Outcomes included heart failure (HF), venous thromboembolism (VTE) and arterial thrombosis/thromboembolism (ATE) recorded in four time windows after SARS-CoV-2 infection: 0–30, 31–90, 91–180 and 181–365 days. Propensity score overlap weighting and empirical calibration were used to minimise observed and unobserved confounding, respectively.

Fine-Gray models estimated subdistribution hazard ratios (sHR). Random effect meta-analyses were conducted across staggered cohorts and databases.

Results The study included 10.17 million vaccinated and 10.39 million unvaccinated people. Vaccination was associated with reduced risks of acute (30-day) and post-acute COVID-19 VTE, ATE and HF: for example, meta-analytic sHR of 0.22 (95% CI 0.17 to 0.29), 0.53 (0.44 to 0.63) and 0.45 (0.38 to 0.53), respectively, for 0–30 days after SARS-CoV-2 infection, while in the 91–180 days sHR were 0.53 (0.40 to 0.70), 0.72 (0.58 to 0.88) and 0.61 (0.51 to 0.73), respectively.

Conclusions COVID-19 vaccination reduced the risk of post-COVID-19 cardiac and thromboembolic outcomes. These effects were more pronounced for acute COVID-19 outcomes, consistent with known reductions in disease severity following breakthrough versus unvaccinated SARS-CoV-2 infection.

• Epidemiology
• PUBLIC HEALTH
• Electronic Health Records

Data availability statement

Data may be obtained from a third party and are not publicly available. CPRD: CPRD data were obtained under the CPRD multi-study license held by the University of Oxford after Research Data Governance (RDG) approval. Direct data sharing is not allowed. SIDIAP: In accordance with current European and national law, the data used in this study is only available for the researchers participating in this study. Thus, we are not allowed to distribute or make publicly available the data to other parties. However, researchers from public institutions can request data from SIDIAP if they comply with certain requirements. Further information is available online ( https://www.sidiap.org/index.php/menu-solicitudesen/application-proccedure ) or by contacting SIDIAP ([email protected]). CORIVA: CORIVA data were obtained under the approval of Research Ethics Committee of the University of Tartu and the patient level data sharing is not allowed. All analyses in this study were conducted in a federated manner, where analytical code and aggregated (anonymised) results were shared, but no patient-level data was transferred across the collaborating institutions.

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/heartjnl-2023-323483

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WHAT IS ALREADY KNOWN ON THIS TOPIC

COVID-19 vaccines proved to be highly effective in reducing the severity of acute SARS-CoV-2 infection.

While COVID-19 vaccines were associated with increased risk for cardiac and thromboembolic events, such as myocarditis and thrombosis, the risk of complications was substantially higher due to SARS-CoV-2 infection.

WHAT THIS STUDY ADDS

COVID-19 vaccination reduced the risk of heart failure, venous thromboembolism and arterial thrombosis/thromboembolism in the acute (30 days) and post-acute (31 to 365 days) phase following SARS-CoV-2 infection. This effect was stronger in the acute phase.

The overall additive effect of vaccination on the risk of post-vaccine and/or post-COVID thromboembolic and cardiac events needs further research.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

COVID-19 vaccines proved to be highly effective in reducing the risk of post-COVID cardiovascular and thromboembolic complications.

Introduction

COVID-19 vaccines were approved under emergency authorisation in December 2020 and showed high effectiveness against SARS-CoV-2 infection, COVID-19-related hospitalisation and death. 1 2 However, concerns were raised after spontaneous reports of unusual thromboembolic events following adenovirus-based COVID-19 vaccines, an association that was further assessed in observational studies. 3 4 More recently, mRNA-based vaccines were found to be associated with a risk of rare myocarditis events. 5 6

On the other hand, SARS-CoV-2 infection can trigger cardiac and thromboembolic complications. 7 8 Previous studies showed that, while slowly decreasing over time, the risk for serious complications remain high for up to a year after infection. 9 10 Although acute and post-acute cardiac and thromboembolic complications following COVID-19 are rare, they present a substantial burden to the affected patients, and the absolute number of cases globally could become substantial.

Recent studies suggest that COVID-19 vaccination could protect against cardiac and thromboembolic complications attributable to COVID-19. 11 12 However, most studies did not include long-term complications and were conducted among specific populations.

Evidence is still scarce as to whether the combined effects of COVID-19 vaccines protecting against SARS-CoV-2 infection and reducing post-COVID-19 cardiac and thromboembolic outcomes, outweigh any risks of these complications potentially associated with vaccination.

We therefore used large, representative data sources from three European countries to assess the overall effect of COVID-19 vaccines on the risk of acute and post-acute COVID-19 complications including venous thromboembolism (VTE), arterial thrombosis/thromboembolism (ATE) and other cardiac events. Additionally, we studied the comparative effects of ChAdOx1 versus BNT162b2 on the risk of these same outcomes.

Data sources

We used four routinely collected population-based healthcare datasets from three European countries: the UK, Spain and Estonia.

For the UK, we used data from two primary care databases—namely, Clinical Practice Research Datalink, CPRD Aurum 13 and CPRD Gold. 14 CPRD Aurum currently covers 13 million people from predominantly English practices, while CPRD Gold comprises 3.1 million active participants mostly from GP practices in Wales and Scotland. Spanish data were provided by the Information System for the Development of Research in Primary Care (SIDIAP), 15 which encompasses primary care records from 6 million active patients (around 75% of the population in the region of Catalonia) linked to hospital admissions data (Conjunt Mínim Bàsic de Dades d’Alta Hospitalària). Finally, the CORIVA dataset based on national health claims data from Estonia was used. It contains all COVID-19 cases from the first year of the pandemic and ~440 000 randomly selected controls. CORIVA was linked to the death registry and all COVID-19 testing from the national health information system.

Databases included sociodemographic information, diagnoses, measurements, prescriptions and secondary care referrals and were linked to vaccine registries, including records of all administered vaccines from all healthcare settings. Data availability for CPRD Gold ended in December 2021, CPRD Aurum in January 2022, SIDIAP in June 2022 and CORIVA in December 2022.

All databases were mapped to the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) 16 to facilitate federated analytics.

Multinational network staggered cohort study: study design and participants

The study design has been published in detail elsewhere. 17 Briefly, we used a staggered cohort design considering vaccination as a time-varying exposure. Four staggered cohorts were designed with each cohort representing a country-specific vaccination rollout phase (eg, dates when people became eligible for vaccination, and eligibility criteria).

The source population comprised all adults registered in the respective database for at least 180 days at the start of the study (4 January 2021 for CPRD Gold and Aurum, 20 February 2021 for SIDIAP and 28 January 2021 for CORIVA). Subsequently, each staggered cohort corresponded to an enrolment period: all people eligible for vaccination during this time were included in the cohort and people with a history of SARS-CoV-2 infection or COVID-19 vaccination before the start of the enrolment period were excluded. Across countries, cohort 1 comprised older age groups, whereas cohort 2 comprised individuals at risk for severe COVID-19. Cohort 3 included people aged ≥40 and cohort 4 enrolled people aged ≥18.

In each cohort, people receiving a first vaccine dose during the enrolment period were allocated to the vaccinated group, with their index date being the date of vaccination. Individuals who did not receive a vaccine dose comprised the unvaccinated group and their index date was assigned within the enrolment period, based on the distribution of index dates in the vaccinated group. People with COVID-19 before the index date were excluded.

Follow-up started from the index date until the earliest of end of available data, death, change in exposure status (first vaccine dose for those unvaccinated) or outcome of interest.

COVID-19 vaccination

All vaccines approved within the study period from January 2021 to July 2021—namely, ChAdOx1 (Oxford/AstraZeneca), BNT162b2 (BioNTech/Pfizer]) Ad26.COV2.S (Janssen) and mRNA-1273 (Moderna), were included for this study.

Post-COVID-19 outcomes of interest

Outcomes of interest were defined as SARS-CoV-2 infection followed by a predefined thromboembolic or cardiac event of interest within a year after infection, and with no record of the same clinical event in the 6 months before COVID-19. Outcome date was set as the corresponding SARS-CoV-2 infection date.

COVID-19 was identified from either a positive SARS-CoV-2 test (polymerase chain reaction (PCR) or antigen), or a clinical COVID-19 diagnosis, with no record of COVID-19 in the previous 6 weeks. This wash-out period was imposed to exclude re-recordings of the same COVID-19 episode.

Post-COVID-19 outcome events were selected based on previous studies. 11–13 Events comprised ischaemic stroke (IS), haemorrhagic stroke (HS), transient ischaemic attack (TIA), ventricular arrhythmia/cardiac arrest (VACA), myocarditis/pericarditis (MP), myocardial infarction (MI), heart failure (HF), pulmonary embolism (PE) and deep vein thrombosis (DVT). We used two composite outcomes: (1) VTE, as an aggregate of PE and DVT and (2) ATE, as a composite of IS, TIA and MI. To avoid re-recording of the same complication we imposed a wash-out period of 90 days between records. Phenotypes for these complications were based on previously published studies. 3 4 8 18

All outcomes were ascertained in four different time periods following SARS-CoV-2 infection: the first period described the acute infection phase—that is, 0–30 days after COVID-19, whereas the later periods - which are 31–90 days, 91–180 days and 181–365 days, illustrate the post-acute phase ( figure 1 ).

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Study outcome design. Study outcomes of interest are defined as a COVID-19 infection followed by one of the complications in the figure, within a year after infection. Outcomes were ascertained in four different time windows after SARS-CoV-2 infection: 0–30 days (namely the acute phase), 31–90 days, 91–180 days and 181–365 days (these last three comprise the post-acute phase).

Negative control outcomes

Negative control outcomes (NCOs) were used to detect residual confounding. NCOs are outcomes which are not believed to be causally associated with the exposure, but share the same bias structure with the exposure and outcome of interest. Therefore, no significant association between exposure and NCO is to be expected. Our study used 43 different NCOs from previous work assessing vaccine effectiveness. 19

Statistical analysis

Federated network analyses.

A template for an analytical script was developed and subsequently tailored to include the country-specific aspects (eg, dates, priority groups) for the vaccination rollout. Analyses were conducted locally for each database. Only aggregated data were shared and person counts <5 were clouded.

Propensity score weighting

Large-scale propensity scores (PS) were calculated to estimate the likelihood of a person receiving the vaccine based on their demographic and health-related characteristics (eg, conditions, medications) prior to the index date. PS were then used to minimise observed confounding by creating a weighted population (overlap weighting 20 ), in which individuals contributed with a different weight based on their PS and vaccination status.

Prespecified key variables included in the PS comprised age, sex, location, index date, prior observation time in the database, number of previous outpatient visits and previous SARS-CoV-2 PCR/antigen tests. Regional vaccination, testing and COVID-19 incidence rates were also forced into the PS equation for the UK databases 21 and SIDIAP. 22 In addition, least absolute shrinkage and selection operator (LASSO) regression, a technique for variable selection, was used to identify additional variables from all recorded conditions and prescriptions within 0–30 days, 31–180 days and 181-any time (conditions only) before the index date that had a prevalence of >0.5% in the study population.

PS were then separately estimated for each staggered cohort and analysis. We considered covariate balance to be achieved if absolute standardised mean differences (ASMDs) were ≤0.1 after weighting. Baseline characteristics such as demographics and comorbidities were reported.

Effect estimation

To account for the competing risk of death associated with COVID-19, Fine-and-Grey models 23 were used to calculate subdistribution hazard ratios (sHRs). Subsequently, sHRs and confidence intervals were empirically calibrated from NCO estimates 24 to account for unmeasured confounding. To calibrate the estimates, the empirical null distribution was derived from NCO estimates and was used to compute calibrated confidence intervals. For each outcome, sHRs from the four staggered cohorts were pooled using random-effect meta-analysis, both separately for each database and across all four databases.

Sensitivity analysis

Sensitivity analyses comprised 1) censoring follow-up for vaccinated people at the time when they received their second vaccine dose and 2) considering only the first post-COVID-19 outcome within the year after infection ( online supplemental figure S1 ). In addition, comparative effectiveness analyses were conducted for BNT162b2 versus ChAdOx1.

Supplemental material

Data and code availability.

All analytic code for the study is available in GitHub ( https://github.com/oxford-pharmacoepi/vaccineEffectOnPostCovidCardiacThromboembolicEvents ), including code lists for vaccines, COVID-19 tests and diagnoses, cardiac and thromboembolic events, NCO and health conditions to prioritise patients for vaccination in each country. We used R version 4.2.3 and statistical packages survival (3.5–3), Empirical Calibration (3.1.1), glmnet (4.1-7), and Hmisc (5.0–1).

Patient and public involvement

Owing to the nature of the study and the limitations regarding data privacy, the study design, analysis, interpretation of data and revision of the manuscript did not involve any patients or members of the public.

All aggregated results are available in a web application ( https://dpa-pde-oxford.shinyapps.io/PostCovidComplications/ ).

We included over 10.17 million vaccinated individuals (1 618 395 from CPRD Gold; 5 729 800 from CPRD Aurum; 2 744 821 from SIDIAP and 77 603 from CORIVA) and 10.39 million unvaccinated individuals (1 640 371; 5 860 564; 2 588 518 and 302 267, respectively). Online supplemental figures S2-5 illustrate study inclusion for each database.

Adequate covariate balance was achieved after PS weighting in most studies: CORIVA (all cohorts) and SIDIAP (cohorts 1 and 4) did not contribute to ChAdOx1 subanalyses owing to sample size and covariate imbalance. ASMD results are accessible in the web application.

NCO analyses suggested residual bias after PS weighting, with a majority of NCOs associated positively with vaccination. Therefore, calibrated estimates are reported in this manuscript. Uncalibrated effect estimates and NCO analyses are available in the web interface.

Population characteristics

Table 1 presents baseline characteristics for the weighted populations in CPRD Aurum, for illustrative purposes. Online supplemental tables S1-25 summarise baseline characteristics for weighted and unweighted populations for each database and comparison. Across databases and cohorts, populations followed similar patterns: cohort 1 represented an older subpopulation (around 80 years old) with a high proportion of women (57%). Median age was lowest in cohort 4 ranging between 30 and 40 years.

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Characteristics of weighted populations in CPRD Aurum database, stratified by staggered cohort and exposure status. Exposure is any COVID-19 vaccine

COVID-19 vaccination and post-COVID-19 complications

Table 2 shows the incidence of post-COVID-19 VTE, ATE and HF, the three most common post-COVID-19 conditions among the studied outcomes. Outcome counts are presented separately for 0–30, 31–90, 91–180 and 181–365 days after SARS-CoV-2 infection. Online supplemental tables S26-36 include all studied complications, also for the sensitivity and subanalyses. Similar pattern for incidences were observed across all databases: higher outcome rates in the older populations (cohort 1) and decreasing frequency with increasing time after infection in all cohorts.

Number of records (and risk per 10 000 individuals) for acute and post-acute COVID-19 cardiac and thromboembolic complications, across cohorts and databases for any COVID-19 vaccination

Forest plots for the effect of COVID-19 vaccines on post-COVID-19 cardiac and thromboembolic complications; meta-analysis across cohorts and databases. Dashed line represents a level of heterogeneity I 2 >0.4. ATE, arterial thrombosis/thromboembolism; CD+HS, cardiac diseases and haemorrhagic stroke; VTE, venous thromboembolism.

Results from calibrated estimates pooled in meta-analysis across cohorts and databases are shown in figure 2 .

Reduced risk associated with vaccination is observed for acute and post-acute VTE, DVT, and PE: acute meta-analytic sHR are 0.22 (95% CI, 0.17–0.29); 0.36 (0.28–0.45); and 0.19 (0.15–0.25), respectively. For VTE in the post-acute phase, sHR estimates are 0.43 (0.34–0.53), 0.53 (0.40–0.70) and 0.50 (0.36–0.70) for 31–90, 91–180, and 181–365 days post COVID-19, respectively. Reduced risk of VTE outcomes was observed in vaccinated across databases and cohorts, see online supplemental figures S14–22 .

Similarly, the risk of ATE, IS and MI in the acute phase after infection was reduced for the vaccinated group, sHR of 0.53 (0.44–0.63), 0.55 (0.43–0.70) and 0.49 (0.38–0.62), respectively. Reduced risk associated with vaccination persisted for post-acute ATE, with sHR of 0.74 (0.60–0.92), 0.72 (0.58–0.88) and 0.62 (0.48–0.80) for 31–90, 91–180 and 181–365 days post-COVID-19, respectively. Risk of post-acute MI remained lower for vaccinated in the 31–90 and 91–180 days after COVID-19, with sHR of 0.64 (0.46–0.87) and 0.64 (0.45–0.90), respectively. Vaccination effect on post-COVID-19 TIA was seen only in the 181–365 days, with sHR of 0.51 (0.31–0.82). Online supplemental figures S23-31 show database-specific and cohort-specific estimates for ATE-related complications.

Risk of post-COVID-19 cardiac complications was reduced in vaccinated individuals. Meta-analytic estimates in the acute phase showed sHR of 0.45 (0.38–0.53) for HF, 0.41 (0.26–0.66) for MP and 0.41 (0.27–0.63) for VACA. Reduced risk persisted for post-acute COVID-19 HF: sHR 0.61 (0.51–0.73) for 31–90 days, 0.61 (0.51–0.73) for 91–180 days and 0.52 (0.43–0.63) for 181–365 days. For post-acute MP, risk was only lowered in the first post-acute window (31–90 days), with sHR of 0.43 (0.21–0.85). Vaccination showed no association with post-COVID-19 HS. Database-specific and cohort-specific results for these cardiac diseases are shown in online supplemental figures S32-40 .

Stratified analyses by vaccine showed similar associations, except for ChAdOx1 which was not associated with reduced VTE and ATE risk in the last post-acute window. Sensitivity analyses were consistent with main results ( online supplemental figures S6-13 ).

Figure 3 shows the results of comparative effects of BNT162b2 versus ChAdOx1, based on UK data. Meta-analytic estimates favoured BNT162b2 (sHR of 0.66 (0.46–0.93)) for VTE in the 0–30 days after infection, but no differences were seen for post-acute VTE or for any of the other outcomes. Results from sensitivity analyses, database-specific and cohort-specific estimates were in line with the main findings ( online supplemental figures S41-51 ).

Forest plots for comparative vaccine effect (BNT162b2 vs ChAdOx1); meta-analysis across cohorts and databases. ATE, arterial thrombosis/thromboembolism; CD+HS, cardiac diseases and haemorrhagic stroke; VTE, venous thromboembolism.

Key findings

Our analyses showed a substantial reduction of risk (45–81%) for thromboembolic and cardiac events in the acute phase of COVID-19 associated with vaccination. This finding was consistent across four databases and three different European countries. Risks for post-acute COVID-19 VTE, ATE and HF were reduced to a lesser extent (24–58%), whereas a reduced risk for post-COVID-19 MP and VACA in vaccinated people was seen only in the acute phase.

Results in context

The relationship between SARS-CoV-2 infection, COVID-19 vaccines and thromboembolic and/or cardiac complications is tangled. Some large studies report an increased risk of VTE and ATE following both ChAdOx1 and BNT162b2 vaccination, 7 whereas other studies have not identified such a risk. 25 Elevated risk of VTE has also been reported among patients with COVID-19 and its occurrence can lead to poor prognosis and mortality. 26 27 Similarly, several observational studies have found an association between COVID-19 mRNA vaccination and a short-term increased risk of myocarditis, particularly among younger male individuals. 5 6 For instance, a self-controlled case series study conducted in England revealed about 30% increased risk of hospital admission due to myocarditis within 28 days following both ChAdOx1 and BNT162b2 vaccines. However, this same study also found a ninefold higher risk for myocarditis following a positive SARS-CoV-2 test, clearly offsetting the observed post-vaccine risk.

COVID-19 vaccines have demonstrated high efficacy and effectiveness in preventing infection and reducing the severity of acute-phase infection. However, with the emergence of newer variants of the virus, such as omicron, and the waning protective effect of the vaccine over time, there is a growing interest in understanding whether the vaccine can also reduce the risk of complications after breakthrough infections. Recent studies suggested that COVID-19 vaccination could potentially protect against acute post-COVID-19 cardiac and thromboembolic events. 11 12 A large prospective cohort study 11 reports risk of VTE after SARS-CoV-2 infection to be substantially reduced in fully vaccinated ambulatory patients. Likewise, Al-Aly et al 12 suggest a reduced risk for post-acute COVID-19 conditions in breakthrough infection versus SARS-CoV-2 infection without prior vaccination. However, the populations were limited to SARS-CoV-2 infected individuals and estimates did not include the effect of the vaccine to prevent COVID-19 in the first place. Other studies on post-acute COVID-19 conditions and symptoms have been conducted, 28 29 but there has been limited reporting on the condition-specific risks associated with COVID-19, even though the prognosis for different complications can vary significantly.

In line with previous studies, our findings suggest a potential benefit of vaccination in reducing the risk of post-COVID-19 thromboembolic and cardiac complications. We included broader populations, estimated the risk in both acute and post-acute infection phases and replicated these using four large independent observational databases. By pooling results across different settings, we provided the most up-to-date and robust evidence on this topic.

Strengths and limitations

The study has several strengths. Our multinational study covering different healthcare systems and settings showed consistent results across all databases, which highlights the robustness and replicability of our findings. All databases had complete recordings of vaccination status (date and vaccine) and are representative of the respective general population. Algorithms to identify study outcomes were used in previous published network studies, including regulatory-funded research. 3 4 8 18 Other strengths are the staggered cohort design which minimises confounding by indication and immortal time bias. PS overlap weighting and NCO empirical calibration have been shown to adequately minimise bias in vaccine effectiveness studies. 19 Furthermore, our estimates include the vaccine effectiveness against COVID-19, which is crucial in the pathway to experience post-COVID-19 complications.

Our study has some limitations. The use of real-world data comes with inherent limitations including data quality concerns and risk of confounding. To deal with these limitations, we employed state-of-the-art methods, including large-scale propensity score weighting and calibration of effect estimates using NCO. 19 24 A recent study 30 has demonstrated that methodologically sound observational studies based on routinely collected data can produce results similar to those of clinical trials. We acknowledge that results from NCO were positively associated with vaccination, and estimates might still be influenced by residual bias despite using calibration. Another limitation is potential under-reporting of post-COVID-19 complications: some asymptomatic and mild COVID-19 infections might have not been recorded. Additionally, post-COVID-19 outcomes of interest might be under-recorded in primary care databases (CPRD Aurum and Gold) without hospital linkage, which represent a large proportion of the data in the study. However, results in SIDIAP and CORIVA, which include secondary care data, were similar. Also, our study included a small number of young men and male teenagers, who were the main population concerned with increased risks of myocarditis/pericarditis following vaccination.

Conclusions

Vaccination against SARS-CoV-2 substantially reduced the risk of acute post-COVID-19 thromboembolic and cardiac complications, probably through a reduction in the risk of SARS-CoV-2 infection and the severity of COVID-19 disease due to vaccine-induced immunity. Reduced risk in vaccinated people lasted for up to 1 year for post-COVID-19 VTE, ATE and HF, but not clearly for other complications. Findings from this study highlight yet another benefit of COVID-19 vaccination. However, further research is needed on the possible waning of the risk reduction over time and on the impact of booster vaccination.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

The study was approved by the CPRD’s Research Data Governance Process, Protocol No 21_000557 and the Clinical Research Ethics committee of Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol) (approval number 4R22/133) and the Research Ethics Committee of the University of Tartu (approval No. 330/T-10).

Acknowledgments

This study is based in part on data from the Clinical Practice Research Datalink (CPRD) obtained under licence from the UK Medicines and Healthcare products Regulatory Agency. We thank the patients who provided these data, and the NHS who collected the data as part of their care and support. All interpretations, conclusions and views expressed in this publication are those of the authors alone and not necessarily those of CPRD. We would also like to thank the healthcare professionals in the Catalan healthcare system involved in the management of COVID-19 during these challenging times, from primary care to intensive care units; the Institut de Català de la Salut and the Program d’Analítica de Dades per a la Recerca i la Innovació en Salut for providing access to the different data sources accessible through The System for the Development of Research in Primary Care (SIDIAP).

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1

AMJ and MC are joint senior authors.

Contributors DPA and AMJ led the conceptualisation of the study with contributions from MC and NM-B. AMJ, TD-S, ER, AU and NTHT adapted the study design with respect to the local vaccine rollouts. AD and WYM mapped and curated CPRD data. MC and NM-B developed code with methodological contributions advice from MTS-S and CP. DPA, MC, NTHT, TD-S, HMEN, XL, CR and AMJ clinically interpreted the results. NM-B, XL, AMJ and DPA wrote the first draft of the manuscript, and all authors read, revised and approved the final version. DPA and AMJ obtained the funding for this research. DPA is responsible for the overall content as guarantor: he accepts full responsibility for the work and the conduct of the study, had access to the data, and controlled the decision to publish.

Funding The research was supported by the National Institute for Health and Care Research (NIHR) Oxford Biomedical Research Centre (BRC). DPA is funded through a NIHR Senior Research Fellowship (Grant number SRF-2018–11-ST2-004). Funding to perform the study in the SIDIAP database was provided by the Real World Epidemiology (RWEpi) research group at IDIAPJGol. Costs of databases mapping to OMOP CDM were covered by the European Health Data and Evidence Network (EHDEN).

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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• Advancing Regulatory Science

A Rapid Query Model to Address Prioritized COVID-19 Questions Using EHR Data

CERSI Collaborators: University of California at San Francisco (UCSF): Atul Butte, MD, PhD; Rohit Vashisht, PhD

FDA Collaborators: Formerly of Office of the Commissioner: Amy Abernethy, MD, PhD; Tamar Lasky, PhD; Laura Roe; Joseph Franklin, PhD, JD; Aloka Chakravarty, PhD

CERSI Subcontractors: Flying Buttress Associates- Jeph Herrin, PhD

CERSI In-Kind Collaborators: OptumLabs - William Crown, PhD; University of San Francisco - Sanket Dhruva, MD

Non-Federal Entity Collaborators: Johnson and Johnson- Karla Childers, MSJ, Paul Coplan, ScD, MBA, Stephen Johnston, MSc

Project Start Date: September 2020 Project End Date: February 2022

Regulatory Science Framework

Charge I “Modernize development and evaluation of FDA-regulated project” and Focus Area “C. Analytical and computational Methods.”

Regulatory Science Challenge

Rapid collection, analyses, and reporting of COVID-19 data is needed to support COVID-19 pandemic response efforts. Public health professionals, healthcare providers, and others, use multiple data sources to improve our understanding of how the pandemic is impacting communities, and guide public health interventions and services. Example data include but are not limited to: COVID-19 case identification, hospitalization, death rates, and distribution/effectiveness of available treatments.

To help address this need, researchers developed a rapid query model in collaboration with University of California Health (UC Health) and U.S. FDA. The model enables FDA scientists to query, or ask questions of, UC Health data collected from over 7 million patients. Answers to these questions can be provided within days of receipt.

Project Description and Goals

UC Health, comprised of 19 health professional schools, 5 academic medical centers, and 12 hospitals, has built a secure central data warehouse of 7 million patient records. Patients documented within this central data warehouse receive care both within and outside the state of California. UC Health created a standardized Health Insurance Portability and Accountability Act (HIPAA) Limited Data Set called the UC COVID Research Data Set (UC CORDS) soon after the COVID-19 pandemic began. The UC CORDS database captures medical information related to patients infected with COVID-19 and various aspects of their medical care. UC Health uses UC CORDS to rapidly answer questions posed by the FDA. The rapid-query model is a multi-step framework comprised of a computational pipeline used to rapidly query UC CORDS and refine the quality of the questions being asked by conducting follow-up statistical analysis. UC Health proposes to deliver preliminary answers to COVID-19 questions within 2-4 days of the question transmittal, and more detailed answers within two weeks of the finally refined question. Answers are delivered in regular reports accompanied by tables of counts and data visualizations.

Research Outcomes/Results

Examples of research outcomes of this project are as follows:

• The UC Health team rapidly generated answers using real-world data to various questions posed by the team FDA on a daily or weekly basis. Example reports generated include but are not limited to: rates of COVID-19 treatment administration of Remdesivir, corticosteroids, interferons, cyclosporin A, tacrolimus, FK506, and Metformin. Daily medication counts were visualized using calendar plots that provided insights on the utilization of these medications throughout the pandemic.
• The team participated, in collaboration with five other healthcare systems, in assessing the real-world performance of SARS-CoV-2 antibody tests in the United States.
• A poster related to certain aspects of the rapid query model was presented in 2021 FDA science forum .

Research Impacts

Incorporating patient preference information into decisions that FDA makes about regulating devices is one of the major goals of FDA’s Center for Devices and Radiological Health (CDRH). Study findings show that patients prefer specific outcomes related to prostate ablation therapies like HIFU. The study results may help inform the design and regulation of current and future prostate tissue ablation devices by providing information about outcomes that patients most desire.

Publications

• PMID: 34677594; Citation: Wallach JD, Deng Y, McCoy RG, Dhruva SS, Herrin J, Berkowitz A, Polley EC, Quinto K, Gandotra C, Crown W, Noseworthy P, Yao X, Shah ND, Ross JS, Lyon TD. Real-world Cardiovascular Outcomes Associated With Degarelix vs Leuprolide for Prostate Cancer Treatment.  JAMA Netw Open. 2021;4(10):e2130587. doi:10.1001/jamanetworkopen.2021.30587 .
• PMID: 36191949; Citation: Deng Y, Polley EC, Wallach JD, Dhruva SS, Herrin J, Quinto K, Gandotra C, Crown W, Noseworthy P, Yao X, Lyon TD, Shah ND, Ross JS, McCoy RG. Emulating the GRADE trial using real world data: retrospective comparative effectiveness study. BMJ . 2022 Oct 3;379:e070717. doi: 10.1136/bmj-2022-070717 .

Four years after COVID, misinformation still endangers some Americans' health. Here's why.

Jesse Ehrenfeld, an anesthesiologist at a Wisconsin hospital , asked a patient about to have heart surgery if she would consent to a blood transfusion should it become necessary.

It's a standard question. But the patient refused.

It was 2021, and the COVID-19 vaccine had become publicly available only a few months earlier. This patient, though, made it clear she did not want it – or blood from anyone who already had it.

"It was at that moment I knew we were in for it," Ehrenfeld said.

More : Unsure how to tell medical fact from fiction? You're not alone. Experts offer some tips.

It was four years ago this week that the scope of the crisis facing the world began to crystallize: The World Health Organization classified COVID-19 as a pandemic , and then-President Donald Trump declared a nationwide emergency that would last three years .

Though the pandemic no longer dominates headlines as it once did, misinformation about nearly every aspect still spreads online. More than 1.1 million people in the U.S. have died of COVID-19 , including hundreds of thousands who, for reasons often rooted in misinformation , chose not to get vaccinated. About 30% of the population hasn't received the initial series of vaccines.

The spread of COVID-19 misinformation on social media has been a concern for public health experts since the start of the pandemic. Nearly 25% of all claims debunked by USA TODAY's fact-checking team from March 2020 to December 2021 were related to COVID-19. That fell to about 10% from January 2022 to December 2023.

The specific claims varied, but common themes included the existence and origin of the disease , purported alternative treatments and all manner of claims about the vaccine .

Fact check: No evidence COVID-19 vaccine 'shuts off' the heart, contrary to anti-Kelce post

Ehrenfeld said he and other doctors continue to have conversations with patients who believe misleading or outright false claims about COVID-19, sometimes to the detriment of their health. Thousands of people across the country are still hospitalized with the disease every week, and some never make it out .

"It's heartbreaking," said Ehrenfeld, who last year became president of the American Medical Association . "We work so hard to practice evidence-based medicine."

Experts told USA TODAY that misinformation about COVID-19 eroded trust in public health agencies, heightened already inflamed political divisions and created a near-constant challenge to discern fact from fiction. 

"We're more willing to believe that dark forces are working behind the scenes against us," said Paul Offit , director of the Vaccine Education Center at Children's Hospital of Philadelphia. "That's what these kinds of conspiracy theories provide."

Rebuilding trust, finding empathy for people swayed by misinformation

Medical providers said their focus now is finding ways to have respectful conversations with patients regardless of their perspective.

"(Frustration) doesn't get us anywhere," said Amanda Johnson , a New York City primary care doctor. "I think those conversations are more likely to go poorly if you take it as a personal affront."

She has talked about misinformation with patients, some of whom have even asked her to review social media posts they've seen. The most animated responses come from patients who believe they're losing control or having something forced on them, said Johnson, who also leads NYC Health + Hospitals' AfterCare program for New Yorkers recovering from COVID-19 or living with long COVID.

Many people are disparaging or dismissive when talking about people who believe misinformation, but it can happen to anyone, said Sedona Chinn , an assistant professor in the life sciences communication department at the University of Wisconsin-Madison.

"I never admit that I'm wrong when somebody backs me into a corner and yells at me. You're just going to get more defensive," Chinn said. "People have good intentions in trying to correct misinformation. But it's a challenging thing to do. It's a challenging thing to admit that you were deceived."

Ehrenfeld said he asks his patients questions to learn what they believe, why they believe it and where they heard it. It doesn't happen often, but he has "seen the lightbulb go off" for some patients, including some who have agreed to be vaccinated after talking with him. Most people, Ehrenfeld said, still have a level of trust in their doctor.

"While that trust has eroded a little bit, there is still tremendous value and opportunity in these personal one-on-one relationships," he said. 

Doctors have consistently been the most trusted source for health information during the pandemic, said Liz Hamel , director of public opinion and survey research at KFF , a healthy policy research firm.

The organization's polling shows more than 90% of people trust their doctor's health recommendations "at least a fair amount." Only about two-thirds had the same level of trust in federal agencies like the Centers for Disease Control and Prevention and the Food and Drug Administration.

The work of rebuilding trust in the medical community has only just begun.

"We have to continue to elevate credible messages," Ehrenfeld said. "We have to make it easy for people to obtain accurate, correct information."

The development of a safe and effective vaccine against COVID-19 was the "greatest scientific or medical achievement in my lifetime," said Offit, who lived through the development of the polio vaccine . 

But the spread of misinformation about the COVID-19 vaccine has lowered trust in other vaccines, risking outbreaks of diseases – measles, for instance – once thought all but eradicated. If that continues it could, in the long run, be the "horrific" legacy of this pandemic, he said.

"If we start to take down school vaccine mandates, you'll start to see these diseases come back," Offit said. "Maybe that's going to be the legacy of this pandemic. I hope not, but that's the scariest part."

Health misinformation, anti-vaccine sentiment predate the pandemic

The pandemic amplified mistrust in the medical establishment that existed long before COVID-19.

In 1982, a television documentary called "DPT: Vaccine Roulette" aired nationally featuring children with severe health problems purportedly caused by the vaccine for pertussis , or whooping cough .

Medical experts denounced it as "imbalanced" and "inaccurate." The American Academy of Pediatrics said the documentary's "distortion and total lack of balance of scientific fact" caused "extraordinary anguish and perhaps irreparable harm to the health and welfare of the nation's children."

The documentary – which Offit called the birth of the anti-vaccine movement – led to a wave of lawsuits against vaccine manufacturers that eventually prompted lawmakers to pass the National Childhood Vaccine Injury Act . That created a program to compensate people for injuries caused by vaccines and protects manufacturers from litigation.

Fact check: No, CDC data doesn't show 99% of reported COVID-19 deaths were from other causes

Peter Hotez , a vaccine researcher and dean of the National School of Tropical Medicine at Baylor College of Medicine, became familiar with health misinformation after his now-adult daughter was diagnosed with autism. Hotez took on those who blamed vaccines, publishing a book in 2018 titled, "Vaccines Did Not Cause Rachel's Autism: My Journey as a Vaccine Scientist, Pediatrician, and Autism Dad."

Hotez showed that, in his daughter's case, a rare genetic mutation caused repetitive behaviors and communication problems. The claim that vaccines are somehow linked to autism has been repeatedly debunked by multiple studies .

Vaccines weren't as political then as they became during the pandemic, Hotez said.

"It was mostly groups monetizing the internet, selling phony autism cures, nutritional supplements and anti-vaccine conspiracy books," he said.

That mirrors what Tara Kirk Sell , a senior researcher at the Johns Hopkins Center for Health Security, found studying health misinformation that spread during the Ebola outbreak in West Afri ca . The outbreak started in 2014 and, over about two years, killed 11,325 people.

Sell said she expected to find misinformation about the event itself – and did – but was surprised by the way it was also used as a "vehicle for all of these other goals."

"If you want to increase political division, if you want to promote a social policy, if you want some sort of financial advantage, the health event and health-related misinformation is what gets in front of people's eyes," she said.

The threat posed by health misinformation was a focus of Event 201 , a tabletop pandemic training exercise conducted by the Johns Hopkins Center for Health Security, the World Economic Forum and the Bill and Melinda Gates Foundation. The mock drill led to several recommendations , including that governments and the private sector find ways to fight misinformation before the next pandemic.

The training exercise took place in October 2019, less than two months before the first cases of COVID-19 were reported .

Even then, the stakes were clear: "It's really going to mess up the response," Sell recalled thinking about potential misinformation. "It's going to put responders in danger. It's going to make it so people don't trust the government."

COVID-19 misinformation left many in the 'muddled middle'

The pandemic created a perfect storm for misinformation.

The rapid pace of scientific research made it hard for some people to keep up, which created opportunities for misinformation to spread, Hamel said.

The isolation early on made people more reliant on social media and other online communities, Chinn said. More people were searching for reliable information because the situation was so uncertain.

"Those emotions, like anxiety and fear, lead us to want to try to find some more information," she said. The emotional intensity also led people to act and share info online "without critically evaluating the information."

A KFF survey released in August 2023 found most adults in the U.S. have encountered health misinformation – and many aren't certain what to believe.

Asked to evaluate several false claims about COVID-19 and vaccines, about a third of respondents thought the false claim that COVID-19 vaccines have caused thousands of sudden deaths in otherwise healthy people is either definitely or probably true.

"Black adults are more likely to believe this false statement than white adults, while Republicans and independents are more likely than Democrats to do so," the report says . "People with college degrees are less likely than those with a high-school education or less to say this is true."

Fewer respondents thought other false claims about COVID-19 were definitely or probably true, including that ivermectin is an effective treatment for the disease, that more people have died from the vaccines than from the virus, and that the vaccines cause infertility . 

Most people, however, are in what the report called the " muddled middle ."

"These are people who, when you ask them about a false claim, they say it's either probably true or probably false," Hamel said. "That's really the first indication of how confusing it can be for the public to decipher the information they're coming across."

Fact check: Post exaggerates global deaths, then blames them on the COVID vaccine

Adding to the confusion is the question of what sources of information to trust.

A 2023 study looking at the phrase "Do your own research" found the phrase, though technically a call to dig deeper, was instead often associated with "anti-expert attitudes and mistrust, leading to inaccurate beliefs," the study says .

"What we found was people who had positive views about 'doing your own research' were more likely to become more misinformed about COVID over time," said Chinn, one of the study's authors.

'Political allegiance' influenced willingness to believe misinformation

By the time the COVID-19 vaccines became available in late 2020, nearly 300,000 people in the U.S. had died of the disease. But it didn't affect all groups equally, illustrating the deadly toll misinformation can exact.

Offit, who called the vaccine a "ticket out of the pandemic," said he would have thought early on that such a vaccine, given the dire circumstances, might ultimately lead to the demise of anti-vaccine groups. 

Instead, the opposite has happened. Some prominent anti-vaccine groups have seen massive funding increases since the pandemic began.

"This was their chance to misinform the public about vaccines," Offit said.

Fact check: Recipients of FDA-approved COVID-19 vaccines can donate blood immediately

The vaccine has been perhaps the most frequent target of misinformation during the pandemic. It has been wrongly blamed for "sudden deaths" and "turbo cancer," among other things . There have also been false claims about its development , safety and effectiveness . 

But attitudes toward the vaccine – and the willingness to believe false claims about it – have been distinctly divided along political lines.

KFF polling shows Republicans were more likely than Democrats to say they believed false claims about the COVID-19 vaccine and other vaccines were true. KFF also reported that only about a quarter of Republicans planned to get the latest COVID-19 vaccine compared with nearly three-quarters of Democrats, "reflecting patterns seen throughout the COVID-19 pandemic."

In a study out of Cornell published in October 2020 , researchers analyzed millions of news articles published that year and found the "single largest driver" of COVID-19 misinformation at the time was one person: then-president Trump , a Republican. It notes the largest spike in misinformation coverage – at almost 18,000 articles – happened April 24, 2020, when Trump baselessly suggested bleach and other disinfectants might be a possible treatment for COVID-19.

And COVID-19 has accordingly taken a disproportionate toll.

A 2023 study by Yale researchers found excess deaths during the pandemic were more than 40% higher among Republicans than Democrats in the two states it examined, Ohio and Florida. A 2022 study published in Health Affairs found similar results.

Hotez said the hundreds of thousands of people in the U.S. who died after being convinced not to get vaccinated are victims of a "predatory movement."

"They went down that rabbit hole as a form of political allegiance and paid for it with their lives."