research journal articles about covid 19

Public Health Modeling : Research involving modeling to determine population or public health outcomes. Biological Modeling/Simulation : Research involving any computer-simulated or generated modeling regarding molecular biology or biochemistry (does not apply to statistical analysis using software). Clinical Trials : Experimental evaluation of a medical therapeutic or device with human volunteers. Cross-Sectional : Group of human research subjects examined at a particular point in time, including formal surveys. Cohort : Observational study involving human subjects followed over time (prospective) or historical exposures, behaviors, etc. (retrospective). Case-Control : Observation of two groups of patients regarding an exposure or disease outcome with a designated control group using either retrospective or prospective design Case Report : Examination of a medical case involving a single patient. Case Series : Examination of multiple medical cases. Expert Opinion : Articles presenting no original research and providing commentary/opinion of previously published research, current events in science, medicine, or public health, including letters-to-editor, editorial, opinion, viewpoint, commentary articles, and guidelines for medical or scientific practice. Review : Review, summary, or statistical analysis of previously published studies on a particular topic, including meta-analysis and systemic and literature reviews. Theoretical : A topic outlining a new theory or providing a mathematical or logical proof defending or rebutting a theory.

Reasons for retraction were classified according to the following categories:

Plagiarism : Duplication of a part or whole of published research, including inappropriate use of data sets gathered and published by other authors. Duplicated : Duplicate or highly similar article published in another journal by the same authors. IRB/Privacy : Breaches or lack of IRB protocol, as well as breaches of confidentiality and data privacy. Methodology : Errors in study design. Includes instances where authors withdrew publication to revise methods. Data Integrity : Fabricated, inaccurate, or unverified data sets or patients, including survey or public health data that do not reflect current conditions. Reporting/Analysis : Inappropriately performed analysis or inappropriately drawn conclusions, including papers that have insufficient data or reasoning to support conclusions. Author Consent : Decisions made without the approval of all authors, including changes to study design or submission of the manuscript. Other : Reasoning that does not qualify for the above-mentioned categories. Unknown : Reasons not provided by authors or publishers.

The full text of the article was examined when possible, either from the publishing website or from the hosting pre-print server. However, since many of these articles have been removed from circulation, it was often necessary to obtain a copy of the article through other independent repositories, such as ResearchGate. In the absence of a full text, relevant information regarding study type was determined from the abstract or designated “N/A”.

Sixty-eight papers were identified as having been retracted, withdrawn, or temporarily withdrawn by January 1, 2021. Thirty-seven articles were explicitly based on either public health or clinical data. Of these, cohort studies (n = 13, 35.1%) were the most frequent, followed by case-control studies (n = 5, 13.5%), cross-sectional studies (n = 5, 13.5%), case series (n = 4, 10.8%), case reports (n = 3, 8.1%), and clinical trials (n = 2, 5.4%). Of the 20 papers not explicitly based on public health or clinical data, expert opinion (n = 10, 50%) was the most frequent, followed by biological modeling/simulation studies (n = 6, 30%), reviews (n = 2, 10%), and theoretical analyses (n = 2, 10%) ( Table 1 ). Eleven papers could not be categorized due to unavailability.

Summary of Study Types.

Twenty-three papers did not have a reason for retraction listed by the authors or publisher. The most frequent reported reason was duplication. Reasons for retraction categorized as “Other” could not be reasonably grouped into a more specific category ( Table 2 ). These reasons included “substantial manipulation of the peer review process,” 17 “language issues,” 18 “serious scientific fraud,” 19 and “to prevent any possible dispute on some expressions.” 20 A contingency table of retractions and study type is presented in Table 3 .

Summary of Reasons for Retraction.

Contingency Table of Reason for Retraction based on Study Type.

Thirty-eight papers were published in journals with an impact factor listed by Clarivate ™ with a mean impact factor of 10.5 ± 19.1 (median: 3.3). Twenty-two articles were published in 20 first quartile journals (list available from corresponding author). Nineteen papers were published in pre-print servers (9 in medRxiv, 6 in SSRN, 3 in bioRxiv) and 11 in journals without an impact factor indexed by Calvairate. Three journals published more than one retracted article; these included The Lancet (n = 3), Journal of the American Pharmacists Association (n = 2), and Asian Journal of Psychiatry (n = 2).

In several retractions, the exact date of publication and removal could not be determined. For those with both available dates, the average time from publication (or availability on a server) to removal was 42.7 ± 52.2 days. The most frequent geographic origin for study authors was the United States with 23 papers, followed by China (n = 19), India (n = 5), Italy (n = 4), and France and Greece (n = 3). Several countries had 2 publications (Iran, South Korea, and the UK) and one publication (Australia, Belgium, Jordan, Nigeria, Philippines, Russia, Singapore, South Africa, and Turkey) ( Table 4 ). Seven articles had authors from multiple countries. Articles had an average of 6.7 ± 5.5 authors.

Retracted Publications by Country.

The following countries had one publication: Australia, Belgium, Jordan, Nigeria, Philippines, Russia, Singapore, South Africa, Turkey.

With a rapid influx of COVID-19 publications and removals, the characteristics of the removed papers can provide important insights into the nature of the removals and the review process. For example, the impact factor of the publishing journals can indicate the quality of the journal and, by implication, the papers it publishes. It might be assumed that removed papers are more likely to be published in lower quartile or unranked journals. However, we found 22 articles published in 20 first quartile journals, including prominent journals such as The Lancet and The New England Journal of Medicine . While these journals are in the minority regarding COVID-19 removals, their influence potentially makes removals from these journals a greater concern for the scientific community.

The country of origin was of interest given the tremendous global response to the COVID-19 pandemic. The countries with the most retractions were the USA (n = 23), followed by China (n = 19), which coincides with studies showing the USA and China as the top producers of COVID-19 research. 16 , 21 This suggests that the number of retractions may be correlated to the volume of research produced by a country, although scientific standards and journals within countries may also affect this.

The type of research and articles published during the pandemic has also been interesting. A surprising number of expert opinion articles were removed, given that these articles were not presenting original research. In most cases, this was either due to duplication (n = 5) or for unknown reasons (n = 4). The frequency of secondary COVID-19 publications may also contribute to the number of secondary article retractions. 16 , 21 , 22

Reasons for removal varied drastically across studies. Most studies (other than those whose reasons were unspecified) were removed for being duplications. In one instance, this was apparently due to authors violating the publisher’s protocol regarding submission to multiple journals, 23 but most duplications were described as “accidental.” 24 , 25 Expedited review and publishing processes may have led to duplicate articles being published. More serious removals (ie, those involving errors that significantly affected data or outcomes) involved issues of reporting/analysis (n = 9), data integrity (n = 7), plagiarism (n = 3), and IRB or privacy issues (n = 5). These retractions involved issues such as falsely reported first-hand accounts, 26 failure to obtain IRB approval, 27 and inability to complete an independent data review. 28 In one instance, the authors claimed that IRB approval was unavailable due to university closure, although the study did involve human subjects. 29

Many reported reasons for removal were vague and provided little information regarding the nature of retraction. For example, 1 article was reportedly retracted for “language issues” 18 (it was subsequently republished). 30 Another paper was reportedly removed for “serious scientific fraud” by the publisher but was later revealed to be an attempt by the authors to expose what they considered a predatory journal. 19 One paper was withdrawn by the authors because their paper referenced another retracted study. 31 There were also 6 republications, suggesting that the error for the removal was not so significant as to invalidate the entire study or compromise the integrity of the author’s research. It is also possible that some removals could have been avoided if a more rigorous review process was used and/or a global urgency for COVID-19 information was not present, particularly those with errors involving duplications or study design. Therefore, removed COVID-19 papers should not be treated equally; the severity of the error can range widely and, in some cases, may be due to “flaws” and not necessarily “fraud”. 26

In many cases, it was not possible to determine the reason for a paper’s removal, and thus the reasons for and implications of these removals remain unknown. In these instances, publishers often released a statement noting that the article had been removed and indicating where the journal’s policy on removals could be found, without any mention of the reasons for the removals. Authors and publishers have a right to privacy on these decisions and may understandably want to avoid acknowledging specific errors. However, the current environment involving a massive influx of COVID-19 publications, expedited editorial review processes, a noticeable volume of retracted COVID-19 articles, and expressions of concern from the scientific community concerning the quality of the publishing process and the research itself, transparency regarding retractions is needed. Understanding the reasons for the removal allows the scientific community to assess the effectiveness of expedited publishing processes more accurately. It also prevents authors whose work was removed for minor reasons from being equated with those removed for more egregious ones. And while the number and severity of removals do not determine the quality of other, non-retracted studies, it has been shown that these retractions can nonetheless alter the perception of this larger body of COVID-19 research. This may prove especially important during a pandemic in which scientific and medical professionals and the public have an interest in rapid and reliable research.

The major limitation of this review was the availability of reasons for removal provided by the publisher or study authors. Furthermore, some articles and abstracts were no longer available after removal. While this limits information for this study, removing problematic articles from circulation helps prevent the spread of disinformation (although some articles remain available despite removal status).

In summary, we suggest that more transparency regarding the removal process and its rationale will allow the scientific community and public to better assess the integrity of COVID-19 research and expedited reviews. Since some articles may be removed for less severe or minor reasons, they need to be differentiated from those involving more serious errors.

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Scientific papers and resources on COVID-19

Readers will find below recently published articles on COVID-19, including links to the full-texts.

The Pan American Health Organization has put together a set of technical guidelines, recommendations, scientific publications, and ongoing research protocols from the Americas and affected countries worldwide regarding the coronavirus disease (COVID-19) pandemic. These platforms of trusted information may be useful for decision and policy-making authorities, researchers, health professionals, and individuals.

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Impact of Covid-19 on health-related quality of life of patients: A structured review

Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Health Sciences, University of Leicester, Leicester, England, United Kingdom

Roles Data curation, Methodology, Writing – review & editing

Affiliation Primary Care and Population Sciences, University of Southampton, Southampton, England, United Kingdom

Roles Supervision, Writing – review & editing

Roles Writing – review & editing

Roles Conceptualization, Supervision, Writing – review & editing

Introduction

Coronavirus disease (Covid-19) has led to a global pandemic since its emergence in December 2019. The majority of research into Covid-19 has focused on transmission, and mortality and morbidity associated with the virus. However, less attention has been given to its impact on health-related quality of life (HRQoL) of patients with Covid-19.

We searched for original studies published between December 2019 and Jan 2021 in PubMed, Scopus and Medline databases using a specific search strategy. We also explored literature on websites of distinguished public health organisations and hand-searched reference lists of eligible studies. The studies were screened by two reviewers according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) flowchart using pre-determined eligibility criteria. Data were synthesised, analysed descriptively and reported in line with PRISMA guidelines.

In total, 1276 studies were identified through the search strategy. Of these, 77 studies were selected for full-text reading after screening the studies. After reading full-text, 12 eligible studies were included in this review. The majority of the studies used a generic HRQoL assessment tool; five studies used SF-36, five studies used EQ-5D-5L, and three used pulmonary disease-specific HRQoL tools (two studies used two tools each). The impact of Covid-19 on HRQoL was found to be considerable in both Acute Covid and Long Covid patients. Higher impact on HRQoL was reported in Acute Covid, females, older ages, patients with more severe disease and patients from low-income countries.

The impact of Covid-19 on HRQoL of Acute and Long Covid patients is substantial. There was disproportional impact on patients by gender, age, severity of illness and study country. The long-term impact of Covid-19 is still in its initial stage. The findings of the review may be useful to researchers, policymakers, and clinicians caring for people following Covid-19 infection.

Citation: Poudel AN, Zhu S, Cooper N, Roderick P, Alwan N, Tarrant C, et al. (2021) Impact of Covid-19 on health-related quality of life of patients: A structured review. PLoS ONE 16(10): e0259164. https://doi.org/10.1371/journal.pone.0259164

Editor: Prasenjit Mitra, Post Graduate Institute of Medical Education and Research, INDIA

Received: March 31, 2021; Accepted: October 13, 2021; Published: October 28, 2021

Copyright: © 2021 Poudel et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Coronavirus disease (Covid-19) is a contagious disease caused by a newly-discovered virus known as SAR-CoV-2 [ 1 ]. The World Health Organisation (WHO) declared Covid-19 a pandemic on 11 March 2020 [ 2 ]. Leading health organisations including WHO are working with medical experts, government bodies and public health scientists to expand scientific knowledge for tracking the spread and consequences of the virus with an aim of providing timely advice in controlling and minimising the transmission and impact of the virus [ 3 ]. The WHO has published a number of guidelines, strategies and action plans. According to the United Nations (UN) [ 4 ], the coronavirus pandemic has revealed unambiguous global inequities, fragilities, and unsustainable practices, and has exerted its impact all over the world [ 4 ].

It is well-established that Covid-19 causes a wide variety of symptoms [ 5 ]. It may cause prolonged illness and persistent symptoms not only in the elderly and individuals with underlying conditions, but also in young adults and people with no or few chronic underlying medical conditions [ 6 ]. Coronavirus causes interstitial pneumonia and respiratory distress syndrome, which may lead to multiple organ failure [ 7 ]. The virus may affect different organs and body systems such as heart (damage to heart muscle, heart failure), lungs (damage to lung tissue and restrictive lung failure), brain and nervous system (anosmia, consequences of thrombo-embolic events, such as stroke, cognitive impairment), mental health (anxiety, depression, sleep disturbance) and musculoskeletal problems and fatigue [ 8 ]. Patients who recover may continue to be affected with hypoxia, shortness of breath and reduced ability to work [ 9 , 10 ]. Recent reports suggest that some patients may develop medical complications and 11%-24% of Covid-19 patients may experience long-term symptoms even after three months from the onset of Covid-19 illness [ 8 , 11 , 12 ]. Because of the above reasons, Covid-19 may lead to poorer health-related quality of life (HRQoL) of the patients infected both in short and long term.

Impacts of an illness usually go beyond its clinical outcome such as mortality and morbidity, and encompass subjective measures in terms of HRQoL [ 13 ]. HRQoL is a multi-dimensional concept that includes domains related to physical, mental, social and emotional functioning [ 14 ]. There are a number of HRQoL measurement tools, some of which are generic and some disease specific. Generic HRQoL tools (e.g. SF-36 (36-item Short-Form Health Survey), SF-6D (Short-Form 6 Dimension) derived from the SF-36, and EQ-5D (EuroQol- 5 Dimension)) are widely used to assess multi-dimensional domains of the health and well-being of different populations [ 15 ]. Disease specific quality of life assessment instruments related to pulmonary disease include St. George Respiratory Questionnaire (SGRQ) and Clinical COPD Questionnaire (CCQ) [ 16 , 17 ], which have been used in HRQoL assessment of Covid-19 patients [ 10 , 18 ].

Various measures have been taken by different countries in controlling the spread of the virus ranging from city-level quarantine, local lockdown, closing borders to patient-level isolation. Research shows that social distancing measures (e.g. ‘stay-at-home order’), use of masks and closures of restaurants, bars, and entertainment-related businesses considerably reduce the spread of Covid-19 [ 19 , 20 ]. However, such measures not only affect economy and education, but also affect the physical and mental health, and quality of life of restricted patients [ 21 – 24 ]. Studies from the USA and Bangladesh evidenced that social distancing measures, such as ‘a stay-at-home order’, is associated with greater health risks, financial worry, and loneliness [ 25 , 26 ].

To our knowledge, no review has been published to date assessing the impact of Covid-19 on the HRQoL of patients with Covid-19 (confirmed or suspected). Moreover, very little is known about the impact of Covid-19 on HRQoL of Acute Covid (≤4 weeks from onset of symptoms) and Long Covid (>4 weeks from onset of symptoms) patients. Therefore, the aims of this review are to fill the knowledge gap by identifying and assessing the studies reporting on the impacts of COVID-19 on HRQoL of patients with Covid-19 (confirmed or suspected) and exploring the risk factors for reduced HRQoL of Covid-19 patients.

This is a rapid review and it has been reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 27 ]. This review addresses the following research questions:

Literature coverage and search strategies

We searched PubMed, Scopus and Medline using a combination of the following search terms (in Title/Abstract): Corona, Covid, SARS-CoV-2, "quality of life". An example of search strategy is presented below (for PubMed).

("Corona"[Title/Abstract] OR "Covid"[Title/Abstract] OR "SARS-CoV-2"[Title/Abstract]) AND ("quality of life"[Title/Abstract])

Additional filters used in the search strategies were English language, and original articles published between December 2019 and 25 th Jan 2021. We excluded letters, correspondences, notes, case reports, case series, communications, conference reports, reviews and editorials.

In addition to searching databases, reference lists of eligible studies were reviewed to identify additional papers. Grey literature was identified by searching the following websites: Public Health England (PHE), Public Health Wales (PHW), Health Protection Scotland (HPS), Public Health Scotland (PHS), Department of Health and Social Care (DHSC) (UK), Health Protection Agency (HPA), National Institute for Health and Care Excellence (NICE), Centre for Disease Control and Prevention (CDC), World Health Organisation (WHO), Public Health Europe (*PHE).

Eligibility criteria

We selected original studies using the eligibility criteria given in Table 1 . We also used the PICO (Population, Intervention, Comparison and Outcome) framework. In this review, population (P) will be humans with all ages and sexes, and Covid-19 confirmed or suspected patients who were isolated, intervention (I) is not applicable in this review, comparators (C) will be Acute Covid (≤4 weeks from onset of symptoms) and Long Covid (>4 weeks from onset of symptoms), and outcomes (O) will be HRQoL of Covid-19 on health-related quality of life of patients (measured in physical, psychological, emotional and social dimensions), which were measured by different generic and specific tools, such as EQ-5D, SF-36, SF-6D (derived from SF-36), HUI (Health Utility Index), SGRQ. In this review, Covid-19 ‘confirmed patients’ are defined as those patients who are diagnosed with Covid-19 infection and confirmed by laboratory test (antigen or antibody). ‘Suspected patients’ are those patients with symptoms of Covid-19 who could not get confirmation because of a variety of reasons (e.g. unavailability of testing facilities, or unable to carry out the test), and who were self-isolated.

https://doi.org/10.1371/journal.pone.0259164.t001

Study selection, data extraction, analysis and reporting

Studies in this review was selected by two reviewers (ANP and SZ) independently using eligibility criteria. Disagreement were discussed by third author (GLY) and resolved. Detailed study selection processes are presented in Fig 1 . Data extraction was also done by two reviewers (ANP and SZ) using an Excel spreadsheet. The third author (GLY) checked the completeness of the data extraction and suggested additions where necessary. The form was piloted using three eligible papers and revised before use. The following information were extracted from the selected studies: first author and publication year, study title, study type (e.g. survey, observational or experimental studies), study country, sample size (male/female), age of patients (e.g. mean, median, range), Covid-19 confirmed or suspected cases, how data were collected, severity of the patients, hospitalised or non-hospitalised patients, tools used to assess the quality of life (e.g. SF-36, SF-6D, EQ-5D-5L, HUI, SGRQ), and the time point at which HRQoL data were collected (assessment time from the onset of symptoms). In addition, we extracted data on health-related HRQoL (mean, median, IQR, SD, percentage, frequencies, p values, etc.), and also statistically significant factors identified in the study as affecting HRQoL of patients due to Covid-19.

https://doi.org/10.1371/journal.pone.0259164.g001

Based on literature, we categorised Covid-19 into ‘Acute Covid’ (AC) and ‘Long Covid’ (LC). Covid-19 is defined as ‘Acute’ when the symptoms last ‘up to 4 weeks’ from its onset [ 28 ], and it is defined as ‘Long’ if the symptoms last ‘more than 4 weeks’ [ 29 , 30 ]. For those studies which did not clearly report their assessment time from the onset of symptoms (e.g. one month after discharge), we estimated the assessment time considering average length of stay reported in that study. Factors affecting Covid-19 on HRQoL on both groups of patients (i.e. Acute and Long Covid) are also assessed.

We conducted descriptive synthesis and analysis of the data in this review but did not perform meta-analysis because of the limited number of studies and heterogeneous nature of the data. The study outcomes of interest were the impact of Covid-19 on HRQoL of Acute Covid patients and Long Covid patients and factors affecting these outcomes. Data were extracted on mean or median values of all HRQoL variables (such as ‘pain/discomfort’, ‘self-care’) including respective standard deviation or 95% confidence interval, or interquartile range were reported, as it is important to know spectrum of HRQoL impacts. We estimated confidence intervals for studies in cases where this information was missing (e.g. Halpin et al. 2020), based on the included studies [ 31 ]. Where combined HRQoL scores of all patients were not given, separate index values of each group (e.g. male and female patients, ward and ICU patients) were calculated as the weighted mean (e.g. for study by Halpin et al. 2020) [ 32 ]. References were managed in EndNote and the report was prepared in line with PRISMA guidelines.

Fig 1 shows a flow diagram showing a total of 1227 studies were identified from database searches (PubMed, Medline and Scopus) and 49 studies were obtained from the website search. After removing duplicates, we retained 1023 studies. After screening by title and abstract, we retrieved 77 studies for full-text reading. After assessing the full-text, only 12 studies met our inclusion criteria and were therefore included in this review (no eligible studies were obtained from reference lists). Summary of these studies are provided in Table 2 . Out of these 12 studies, the majority (n = 11) were observational (e.g. cross-sectional surveys) and one was an experimental study. The majority of the studies (n = 10) used generic HRQoL assessment tool (five used SF-36, five EQ-5D-5L), and the rest used a pulmonary disease-specific HRQoL tool, i.e. SGRQ (St George’s Respiratory Questionnaire) tool (2/12),Clinical COPD Questionnaire (CCQ) (1/12), and PROMIS tool (1/12) (2 out of the 12 studies used two HRQoL assessment tools i.e. SGRQ and EQ-5D-5L, and CCQ and EQ-5D-5L). Among 12 studies, nine studies included all confirmed Covid-19 cases, two studies included a mix of both confirmed and suspected cases and one study included all suspected cases. Likewise, nine out of 12 studies included hospitalised or previously hospitalised patients, two studies included non-hospitalised patients and one study included a mix of hospitalised and non-hospitalised patients. Three studies were conducted on Acute Covid patients (≤4 weeks from onset of symptoms) and 11 studies covered Long Covid patients (10 studies 4–12 weeks; 1 study >12 weeks) (HRQoL was assessed in both Acute and Long Covid patients in two studies, therefore total is >12).

https://doi.org/10.1371/journal.pone.0259164.t002

Health-related quality of life measured by SF-36

Five out of twelve studies used SF-36 tool to assess the HRQoL of patients affected by Covid-19 [ 13 , 23 , 33 , 34 ]. A 36-item Short-Form (SF-36) health survey is a generic instrument (which does not use a preference based approach) to assess the HRQoL, which is used in clinical practice and research, health policy and evaluations and general population surveys [ 39 ]. It assesses eight health concepts (score range from zero to 100, a score of zero is equivalent to maximum disability and a score of 100 is equivalent to no disability): physical functioning (PF), role physical (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role emotional (RE) and mental health (MH) [ 39 , 40 ]. The majority of the included studies were conducted in China (3/5) and studies were mainly observational (4/5). Only three studies provided HRQoL scores of Covid-19 patients (using SF-36) [ 13 , 33 , 34 ]; one study provided combined (i.e. average total of all dimensions) HRQoL score (62.1±18.8) [ 23 ] and another study provided proportion of patients with functional and emotional impairment [ 35 ]. Amongst the three studies that reported HRQoL scores, only one study assessed HRQoL during Acute stage (<4 weeks) and after Acute stage, i.e. Long Covid (>4 weeks) [ 34 ]. The overall mean HRQoL scores of Acute Covid patients was 60.3 [ 34 ] and Long Covid patients ranged from 60.4 [ 34 ] to 86.4 [ 13 ], with higher SF-36 score representing better health ( Table 3 ). The lowest HRQoL score (60.4) was among the elderly patients (aged over 65 years) and highest HRQoL score (86.4) was with the majority of younger patients (54%, 18–46 years) and all patients were without comorbidities.

https://doi.org/10.1371/journal.pone.0259164.t003

In the Acute Covid, highest score was reported in bodily pain (63.5) and lowest score was reported in physical functioning (53.2). However, in Long Covid highest score was reported in different dimensions in different studies. For example, Chen et al. (2020) reported highest score on physical functioning (94.2) [ 33 ]and Guo et al. (2020) reported the highest score on role emotional (100%) [ 13 ]. Likewise, similar variations were found in the lowest score on different dimensions, meaning there were no pattern on the highest or lowest scores based on HRQoL dimensions ( Table 3 ). In Long Covid, mean physical components scores (PCS) were slightly higher than mental components scores in general ( Fig 2 ). It is not possible to compare SF-36 HRQoL scores by country because of heterogeneity in presenting results and all three studies were from one country (i.e. China) (other two studies reported outcomes differently, not suitable for comparison). Likewise, impact of Covid-19 on HRQoL using SF-36 was not reported by illness severity to compare with. Only two study provided HRQoL scores by gender [ 13 , 33 ] and overall mean scores were higher in male patients (81.2 to 87.9) than female patients (78.7 to 83.9) in both studies [ 13 , 33 ] ( Table 3 ).

a. SF-36 physical and mental health components scores of Acute Covid. b. SF-36 physical and mental health components scores of Long Covid.

https://doi.org/10.1371/journal.pone.0259164.g002

According to a study on Acute Covid (≤4 weeks) [ 23 ], HRQoL score was significantly lower in the people aged 60 years or older (regression coefficient (B), -3.60; 95%CI, -5.13, -2.08, p < 0.001), and with comorbidity (B, -2.81; 95%CI, -4.18, -1.45, p < 0.001). HRQoL score was significantly higher in men (B, 1.89; 95% CI, 0.82, 2.95, p = 0.001), in people with higher education attainment (B, 6.82; 95% CI, 4.85, 8.78, p < 0.001, in people with their own business (B, 2.25; 95% CI, 0.73, 3.77, p = 0.004), in people with middle or high social status (B, 4.62; 95% CI, 3.09, 6.15, p < 0.001), in people who did not drink (B, 1.74; 95% CI, 0.61, 2.87, p = 0.003), and in those who did more physical activity (B, 2.72; 95% CI, 1.52, 3.92, p < 0.001) [ 23 ].

A study about Long Covid (> 4 weeks) reported that factor affecting HRQoL score was positive nucleic acid duration (longer duration had lower RE) was a factor affecting RE negatively (p = 0.01) [ 13 ]. Likewise, VT and MH scores were significantly affected by positive nucleic acid duration (longer than 14 days, p = 0.0311) and age group (age 46–69 years, p = 0.0472) [ 13 ]. Another study [ 33 ] showed that age was negatively associated with PF, RP (p<0.05), as reported above. PF, BP, and RE were negatively associated with the female sex (p< 0.05). Length of stay (LOS) was negatively associated with RE and RP. Likewise, there were significant negative relation between lung function (Forced vital capacity, FVC) and mental health dimension (MH) (P<0.05). Logistic regression analysis demonstrated that being overweight (OR 3.71, 95% CI 1.42–9.70) or obese (OR 3.94, 95% CI 1.47–10.52) were significant factors linked with a poor physical component summary (PCS) score. Female gender (OR 2.22, 95% CI 1.30–3.81) was a significant determinant associated with a mental component summary (MCS) (< 50) in COVID-19 patients.

Health-related quality of life measured by EQ-5D-5L

Five out of twelve studies used EQ-5D-5L tool to assess the HRQoL of patients with Covid-19 in this review [ 17 , 18 , 32 , 36 , 37 ]. EQ-5D-5L is a generic and preference based HRQoL instrument for describing and valuing health and higher index value represents a better health. It is based on a descriptive system that defines health in terms of five dimensions: Mobility, Self-Care, Usual Activities, Pain/Discomfort, and Anxiety/Depression [ 41 ]. A single utility score can be generated from the five dimensions questionnaire based on published tariffs with value 0 for death and 1 for perfect health. Negative value indicates life worse than death [ 41 , 42 ].

All five reviewed studies were observational, focused on Long Covid (>4 weeks) and conducted in Belgium, Germany, Iran, Norway and the United Kingdom. Mean HRQoL values in four studies (from Belgium, Iran, Norway, and the UK) were reported in a similar way, but the fifth study presented results in a different style [ 18 ]. The highest EQ-5D-5L index mean value was reported in the UK (0.714) [ 32 ], followed by Norway (0.690) [ 37 ], Belgium (0.620) [ 17 ] and lowest in Iran (0.612) [ 36 ] ( Fig 3 ). The study in Iran covered all patients same as in the UK, but time of HRQoL assessment was roughly two to four weeks earlier in Iran (4-6weeks from onset of symptoms) than in the UK (6–10 weeks from onset of symptoms). It can be confirmed that time of HRQoL assessment is not the sole factor affecting HRQoL score because the study in Belgium [ 17 ] reported lower score than in the UK and Norway although it was assessed two to four weeks later (10–12 weeks after the onset of symptoms) than those studies covering similar patients in the UK and Norway ( Fig 3 ).

[Note: Only those studies that reported mean EQ-5D-5L scores were presented in the Fig 3].

https://doi.org/10.1371/journal.pone.0259164.g003

EQ-5D-5L scores for various dimensions were reported differently, making it difficult to present the pooled estimates for these dimensions. However, three out of five studies ( Table 4 ) provided percentage of Covid-19 patients reporting difficulties for different dimensions of EQ-5D-5L [ 17 , 32 , 36 ]. Table 4 shows that overall difficulties (average %) the patients are facing, are comparable across three studies (25.9% to 45.2%). However, highest mobility problem was reported by the study in Iran (46.7%), self-care in the UK (16.0%), usual activities and pain/discomfort in Belgium (67.0% and 69.6% respectively), and anxiety/depression in Iran (58.7%) (See Table 4 for detail). Two studies [ 17 , 18 ] reported EuroQoL Visual Analogue Scale (EQ VAS) scores 63 reported by Daher et al. (2020) in Germany [ 18 ] and 50.7 reported by Meys et al. (2020) in Belgium [ 17 ] ( Table 2 ). The review found the higher HRQoL score for: non- ICU patients compared to ICU patients ( Fig 4 ), male patients (0.63±20) compared to female patients (0.58±20), and younger patients (age ≤40 yrs) (0.62±0.32) compared to older patients (age ≥40) (0.55±0.15) ( Table 2 , study by Arab-Zozani et al. 2020) [ 36 ].

https://doi.org/10.1371/journal.pone.0259164.g004

https://doi.org/10.1371/journal.pone.0259164.t004

A study about Long Covid (> 4weeks) in Iran [ 36 ] reported that the EQ-5D-5L index score was significantly different (in univariate analysis) by gender (p = 0.002) (males had higher score), age (p = 0.005) (higher in age ≤ 40 years), educational status (p<0.001) (higher in patients with higher educational status), employment status (p < 0.001) (higher in patients with employment), and workplace status (p = 0.002) (higher in uncrowded workplace). Among the clinical factors (from univariate analysis), the mean EQ-5D-5L index score was significantly lower if the patient had diabetes (p < 0.001), or heart failure (p = 0.002) or was admitted to hospital (p < 0.001) [ 36 ].

Health-related quality of life measured by SGRQ

There were two studies which assessed HRQoL of patients using St George’s Respiratory Questionnaire (SGRQ) [ 10 , 18 ], which is pulmonary disease specific quality of life assessment tool. The score for each domain and the total score are ranged from 0 (no impairment/ no effect on quality of life) to 100 (maximum impairment/ maximum perceived distress). Thus, a higher score represents greater impairment or a poorer HRQoL. Both were observational studies and conducted in Italy and Germany. One of the studies compared HRQoL scores at two points of time: at the time of discharge from hospital and at 15 days of discharge [ 10 ].

Table 5 reports the SGRQ score on different dimensions among Acute Covid and Long Covid patients. The study in Italy by Santus et al. (2020) [ 10 ] reported that the SGRQ scores are significantly decreased (i.e. improved health) (p<0.01) in each dimension by time (comparing the assessment between around 2–3 weeks and 4–5 weeks, i.e. Acute Covid and Long Covid). The study also reported that 65% of patients achieved a clinically significant improvement in the SGRQ total score between hospital discharge and Day 15 [ 10 ]. However, while looking at the study conducted by Daher et al. (2020) in Germany [ 18 ] ( Table 5 ), the patients with Long Covid (8 weeks from symptoms onset), SGRQ scores are comparable to the Acute Covid reported by Santus et al. (2020). As we found in the study, all respondents included in Daher et al. (2020) study had severe illness due to Covid-19, unlike reported in the study by Santus et al. (2020).

https://doi.org/10.1371/journal.pone.0259164.t005

Health-related quality of life measured by CCQ

The Clinical COPD Questionnaire (CCQ) is a 10-item respiratory-specific quality of life assessment tool, which is divided into three domains: symptoms, mental state and functional state. The main outcomes are the CCQ total score (total scores of all domains divided by 10) and mean scores of the three separate domains. The scores are ranged from 0 to 6 points, with a higher value indicating lower quality of life [ 43 ]. The Clinical COPD Questionnaire (CCQ) tool was used by a study conducted in Belgium [ 17 ] for the Long Covid patients and reported the mean CCQ score as 2.01 points (± 0.98). According to the study, the symptoms and functional state domains were equally affected (2.13 ± 1.12 and 2.12 ± 1.22 points, respectively). The mental state domain was less affected compared to symptoms and functional state (1.56 ± 1.31) [ 17 ]. CCQ items 2 (Shortness of breath doing physical activities: 3.24±1.80) and 7 (Strenuous physical activities: 3.41±1.74) had the greatest impact on total scores, with 64% of the patients having shortness of breath during physical activities and 70% had problems during strenuous physical activities, respectively [ 17 ].

Health-related quality of life measured by PROMIS scale

PROMIS tool is used to identify symptoms and assesses the quality of life parameters [ 38 ]. This tool particularly assesses the general health, quality of life, physical health, mental health and social active role including fatigue, dyspnoea and muscular pain. A study in the USA [ 38 ] reported that 72.7% Covid-19 patients had persistent symptoms at 35 days after discharge, 55.0% reported fatigue, 50.6% muscular pain, 45.3% shortness of breath and 41.82% cough. Older patients aged 65 to 75 years [OR 8.666 (2.216–33.884), p = 0.0019] and women (male vs female: OR 0.462 (0.225–0.949), p = 0.0356), had significantly higher odds of experiencing persistent Covid-19 symptoms [ 38 ]. Covid-19 patients’ self-rated quality of life and activities of daily living scores at 35 day after discharge were: a lower odds rating general health (poor/fair 20.2%, OR 0.093 [95% CI: 0.026, 0.329], p = 0.0002), quality of life (poor/fair 23.2%; OR 0.116 [95% CI: 0.038, 0.364], p = 0.0002), physical health (poor/fair 27.1%, OR 0.055 [95% CI: 0.016, 0.193], p <0.0001), mental health (poor/fair 16.9%, OR 0.093 [95% CI: 0.021, 0.418], p = 0.0019) and social relationship (poor/fair 60.4%, OR 0.095 [95% CI: 0.031, 0.291], p<0.0001) [ 38 ]. Thus, even at 35 days after discharge, a considerable proportion of Covid-19 patients experienced persistence symptoms and poor quality of life.

Main findings of the review are- the HRQoL score (i.e. SF-36 score) of patients with Acute Covid found to be lower compared to the patients with Long Covid. In Acute Covid, mental components score was slightly higher than physical components score (PCS) [ 34 ], but opposite was found in Long Covid [ 13 , 33 ]. The HRQoL scores of elderly patients were not considerably improved even after six weeks of discharge from hospitals [ 34 ]. The long-term impacts of Covid-19 is still in its initial stage and it has not been fully developed yet. Most of the available studies on impact of Covid-19 on HRQoL were conducted between 4 and 12 weeks from the onset of symptoms. There were some symptoms which were reported by patients with Long Covid found in our review include fatigue, muscular pain, shortness of breath and cough [ 35 , 38 ]. There were differences in the impact of Covid-19 on HRQoL of patients by study country, i.e. better HRQoL of the patients with Covid-19 from HICs compared to LMICs [ 32 , 36 , 37 ]. The common factors causing impact on both Acute and Long Covid were age, gender, severity of illness, comorbidity, income and educational level of the patients.

As reported in the main findings above, overall HRQoL score of Acute Covid patients was lower (mean SF-36 score 60.3) compared to patients with Long Covid. However, HRQoL scores (using SF-36 tool) of Long Covid patients are still low and vary from 60.4 (lowest) to 86.4 (highest) [ 13 ]. The lowest HRQoL score in Long Covid patients in this review was mainly due to recruitment of only elderly Covid-19 patients group (aged >65 years) [ 34 ] unlike in other studies [ 13 , 33 ]. In addition, the HRQoL scores were not considerably improved among certain patient groups (e.g. elderly, ICU admitted patients) even after six weeks of discharge and lower in some domains even after three months of recovery (fatigue 69%, functional impairments in daily life 64%, and general quality of life 72%) [ 35 ]. In line with our findings, a study in Brazil among general population (age ≥7 years) reported that all dimensions of quality of life (using SF-36) significantly reduced during Covid-19 isolation than before isolation (p<0.05) [ 21 ].

All reviewed studies using EQ-5D-5L were on Long Covid (4 to 13 weeks from the onset of symptoms) and the mean EQ-5D-5L index values ranging from 0.61 to 0.71, which are considerably lower than outcomes of a similar study conducted with general population in China during the pandemic (0.949, SD 0.102) [ 44 ] and in Morocco (0.86) [ 45 ]. Lower magnitude of difficulties were reported among general population during Covid-19 pandemic in Vietnam [ 46 ] than found in our review [ 18 ]. Using SGRQ tool, studies found that there were considerable negative effects on patients’ HRQoL mean score, ranging from 17.3 (SD: 15.9) to 35.7 (SD: 24.2) in Acute Covid and 10.6 (SD: 10.7) to 54 (IQR 19–78) in Long Covid for different dimensions of SGRQ. Higher SGRQ score (means lower HRQoL) in Long Covid in this review was mainly found in the study in Germany [ 18 ] because they included only severe patients in their study. Unlike shown by SF-36 and EQ-5D-5L, a study using SGRQ by Santus et al. (2020) showed significant improvement in HRQoL of patients even after two weeks of discharge (i.e. Acute Covid vs Long Covid) [ 10 ]. This may be because they included only those patients who were clinically stable and able to fill the questionnaire [ 10 ].

A study on Long Covid included in our review (Jacobs et al., 2020, USA) reported that 72.7% patients (95% CI: 65.6, 78.9) had persistent symptoms at day 35 after discharge and majority experienced fatigue (55%), muscular pain (50.6%), shortness of breath (45.3%) and cough (41.8%) [ 38 ]. These are similar to the findings reported in other studies [ 17 , 32 ]. Although there were studies conducted on the impact of Long Covid on HRQoL (conducted between 4 and 13 weeks from onset of symptoms), longer-term effects of Covid-19 (beyond 13 weeks) has not been fully developed yet [ 9 ]. A report published by WHO discussed about possible long-term impact of corona virus [ 8 ]. They reported that people recover from the illness after two to six weeks. However, some symptoms may linger or recur for weeks or months. Some patients may develop medical complications that may have lasting health effects. There may be prolonged illness due to the virus in young adults and children without underlying chronic medical conditions. More research needed to understand the long-term effects of coronavirus, why symptoms persist or recur, how these health problems affect patients and the clinical course and likelihood of full recovery.

While comparing the HRQoL by study countries, the highest EQ-5D-5L index value was reported in the high income countries (HICs), like UK (0.714) [ 32 ] and Norway (0.690) [ 37 ], and lowest in the low-and middle-income country (LMIC), Iran (0.612) [ 36 ]. The higher HRQoL of Covid-19 patients in high income countries like in the United Kingdom and Norway may be due to better health services of the countries rather than other factors [ 47 , 48 ] compared to LMIC, such as Iran. We confirmed from the study level investigation that patients’ characteristics were not the causal factors for better health of the patients from the UK and Norway and worse HRQoL from the patients of Iran. For example, mean age of patients in the study of Iran was 58.4 (SD 18.2) and 18% of these patients were admitted in ICU. In the study in the UK, median age of the patients were 70.5 (range 18–93) and 32% of the patients were admitted in ICU. This means, the lower HRQoL of patients in Iran was not due to patients’ characteristics, such as elderly patients or severity of illness.

The review also explored the factors affecting Acute Covid (≤4 weeks from onset of symptoms) from different studies. HRQoL score (using SF-36) was significantly different by age of patients (lower in the patients aged 60 years or older, p< 0.001) and comorbidity (patients with comorbidity, p< 0.001) [ 23 ]. This is similar to the finding reported in a study from Canada [ 49 ]. In addition, HRQoL score was significantly different by gender (higher in male patients, p = 0.001), educational status (higher in patients with higher education attainment, p<0.001), business status (in people with their own business, p = 0.004), ability to pay for medication (higher score with better ability to pay, p <0.001), social class (in people with middle or high social status, p<0.001), alcohol use (in people who did not drink, p = 0.003), and physical exercise (in those who did more physical activity, p<0.001) [ 23 ].

This review found that HRQoL of Long Covid patients (>4 weeks of onset of symptoms) admitted in ICU (severely ill patients) were worse EQ-5D-5L scores ranging from 0.581 to 0.693) than patients admitted in normal ward (moderately ill patients) (scores ranging from 0.613 to 0.724) [ 32 , 36 , 37 ]. This finding is intuitive as severity of illness impact on physical health, mental health and well-being of people and thus reduces quality of life [ 50 ]. Moreover, this review found HRQoL scores in male patients (SF-36 scores from 81.2 to 87.9) were higher than female patients (scores from 78.7 to 83.9) [ 13 , 33 ] (while keeping other factors constant). These findings are also supported by other similar study [ 36 ]. The impact of Covid-19 was found worse in older patients (≥60 yrs: 0.554) than younger patients (≤40 yrs: 0.618). A study in the USA also supported above findings [ 38 ]. A study among general population during Covid-19 pandemic also reported that people with aging had lower HRQoL scores than younger population [ 44 ]. In addition, a study about Long Covid (> 4 weeks) (using SF-36) reported that factor affecting HRQoL score was positive nucleic acid duration (longer duration had lower RE) (p = 0.01) [ 13 ]. Length of stay (LOS) was negatively associated with RE and RP. Logistic regression analysis showed that being overweight (p<0.05) or obese (p<0.05) were significant factors linked with a poor physical component summary (PCS) [ 33 ]. These findings were also supported by a study in Morocco and Vietnam [ 45 , 46 ].

Majority of the included studies covered impact of Covid-19 on hospitalised or previously hospitalised patients. There were lack of studies covering non-hospitalised patients with Covid-19. Likewise, most of the studies (10 out of 12, 2 studies covered both- both Acute and Long Covid) assessed the impact of Covid-19 on HRQoL between four weeks and 12 weeks from the onset of symptoms. There were lack of HRQoL studies conducted on Acute Covid patients within 4 weeks from onset of symptoms and on Long Covid patients after 12 weeks from onset of symptoms. Similarly, there were no studies, which assessed impact of Covid-19 on patients under 18 years of age. As we discussed in the results section, impact of Covid-19 on HRQoL of patients were mainly measured using generic instruments, such as SF-36 and EQ-5D, and none of the studies have reported its preference-based counterpart SF-6D. Disease-specific HRQoL assessment tools were also used but less frequently than generic tools (SGRQ was used by two studies [ 10 , 18 ], CCQ and PROMIS were used by one each [ 17 , 38 ]). Likewise, they used different calculation methods and presentation styles even in the studies using similar tool. These issues not only make difficulties in comparison of impact of Covid-19 on HRQoL of patients with Covid-19 between studies, but also confuses policy makers about the use of research findings for policy interventions.

Strengths of the review include- it is a first review of its type to date, as there were no published review on this topic was found. Likewise, studies for this review were searched in multiple databases (PuBMed, Scopus and Medlines), websites of distinguished organisations and reference lists. We used robust selection criteria and the study was reported according PRISMA guidelines. Likewise, we included all eligible studies from all over the world without limiting geographical boundaries. Moreover, we compared the review findings by country, gender, age group, and severity of patients, using wide range of relevant literature published till date.

There are some limitations in this rapid review. First, we included the original articles published in English language only. Second, we included studies published online. There may be other unpublished studies about the impact of Covid-19 on HRQoL of confirmed or suspected patients. Third, we included only those articles which assessed HRQOL of patients with Covid-19 (confirmed or suspected) and excluded other HRQoL studies on general population or with other disease groups, because these were out of our study criteria. Fourth, we also included three papers with clinically suspected Covid-19 patients [ 23 ] and both confirmed and suspected patients [ 17 , 35 ] in this review, as during the start of the Covid-19 pandemic, testing facilities were not widely available and researchers had to include suspected Covid-19 patients as well in their research studies. Therefore, we included these studies in our review according to our inclusion criteria. However, these papers might be slightly impacted the outcomes of the review results. Fifth, we did not assess the quality of the included papers in this review; however, we ensured that the study had required information on important variables of interest (i.e. quality of life scores, types of patients included in the study).

Conclusions

We concluded that there were higher impact of Covid-19 on HRQoL of Acute Covid (confirmed or suspected) patients compared to Long Covid patients. However the impact was affected by many other factors, such as age, comorbidity, severity of illness of patients and the impact is not reduced considerably as time goes by (i.e. even after two months) [ 17 ]. In addition, HRQoL of patients with Covid-19 was considerably lower than the general population during the pandemic. This review also concluded that the impact of Covid-19 on HRQoL of patients from LMICs were considerably lower than the patients from high-income countries (HICs), such as the UK and Norway. Similarly, the HRQoL scores (both physical health and mental health components) were considerably lower among the severe patients who were admitted in ICU compared to moderate patients who were admitted in general wards; the HRQoL scores were found to be lower in female Covid-19 patients, and patients who were in old age (age >60 yrs). Although the long-term impact of Covid-19 is not fully developed, there is a consensus in the included studies that Covid-19 causes long-term problems such as fatigue, cough and shortness of breath, which reduce HRQoL of Covid-19 patients at a considerable level. In addition, most of the factors affecting HRQoL found to be similar for both Acute Covid and Long Covid patients.

There is a need for more studies on Acute Covid (within 4 weeks from the onset of symptoms) and Long Covid after 12 weeks from the onset of symptoms, covering non-hospitalised patients and children and adolescents below 18 years of ag., using standard HRQoL tools (e.g. tools using preference based approach (e.g. EQ-5D, SF-6D) and disease specific tools CCQ, SGRQ) with standard method of calculating HRQoL and presenting estimates (i.e. mean scores for each dimension with SD and 95% CI, median with range, or % of patients facing difficulties for each dimension).

The findings of the review may be useful to the researchers, policy makers, clinicians and those who are interested in the HRQoL of patients affected by Covid-19 pandemic.

Supporting information

S1 data. data file related to the paper..

https://doi.org/10.1371/journal.pone.0259164.s001

Acknowledgments

We would like to acknowledge the Newton Fund (UK Research and Innovation), all the members of the UK-China Partnership Hub and Department of Health Sciences at University of Leicester and Southampton University for their direct and indirect support in the preparation of this review paper.

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