sample research paper about covid 19

• Research article
• Open access
• 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

School of Nursing, Psychotherapy and Community Health, Dublin City University, Dublin, Ireland

Department of Anesthesiology, Intensive Care and Pain Medicine, University of Münster, Münster, Germany

Thilo Caspar von Groote

Department of Sport and Health Science, Technische Universität München, Munich, Germany

Hebatullah Mohamed Abdulazeem

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Ishanka Weerasekara

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Livia Puljak

Cochrane Brazil, Evidence-Based Health Program, Universidade Federal de São Paulo, São Paulo, Brazil

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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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Coronavirus disease 2019 (COVID-19): A literature review

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

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Peer-reviewed

Research Article

The impact of COVID-19 pandemic on physical and mental health of Asians: A study of seven middle-income countries in Asia

Roles Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Institute of Cognitive Neuroscience, Faculty of Education, Huaibei Normal University, Huaibei, China

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation College of Medicine, University of the Philippines, Manila, Philippines

Roles Conceptualization, Supervision, Visualization

Affiliation University Malaysia Sarawak (UNIMAS), Sarawak, Malaysia

Roles Conceptualization, Methodology, Supervision, Visualization, Writing – original draft, Writing – review & editing

Affiliation Department of Psychology, Zahedan Branch, Islamic Azad University, Zahedan, Iran

Roles Conceptualization, Investigation, Methodology, Supervision, Visualization

Affiliation College of Public Health Sciences, Chulalongkorn University, a member of Thailand One Health University Network (THOHUN), Bangkok, Thailand

Roles Conceptualization, Investigation, Methodology, Supervision, Visualization, Writing – original draft, Writing – review & editing

Affiliation Institute of Clinical Psychology, University of Karachi, Karachi, Pakistan

Affiliations Institute for Preventive Medicine and Public Health, Hanoi Medical University, Hanoi, Vietnam, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States of America

Roles Formal analysis, Investigation, Methodology, Supervision, Validation

Affiliation DHQ Hospital Jhelum, Jhelum, Pakistan

Roles Formal analysis, Investigation, Methodology, Supervision

Affiliation Institute for Global Health Innovations, Duy Tan University, Da Nang, Vietnam

Roles Investigation, Methodology, Project administration, Supervision, Validation

Affiliation Institute for Preventive Medicine and Public Health, Hanoi Medical University, Hanoi, Vietnam

Roles Data curation, Investigation, Methodology, Project administration, Supervision, Validation

Roles Investigation, Methodology, Supervision, Validation

Affiliation Faculty of Medicine, Duy Tan University, Da Nang, Vietnam

Roles Data curation, Investigation, Methodology, Supervision, Validation

Affiliation Department of Psychology, University of Sistan and Baluchestan, Zahedan, Iran

Affiliation Center of Excellence in Evidence-based Medicine, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam

Roles Data curation, Project administration, Validation

Affiliation Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

Roles Formal analysis, Writing – original draft, Writing – review & editing

Affiliation Mood Disorders Psychopharmacology Unit, University Health Network, University of Toronto, Toronto, Canada

Roles Formal analysis, Validation, Writing – original draft, Writing – review & editing

Affiliation Department of Psychological Medicine, National University Health System, Singapore, Singapore

Roles Conceptualization, Formal analysis, Funding acquisition, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Institute for Health Innovation and Technology (iHealthtech), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

•  [ ... ],

Roles Conceptualization, Investigation, Methodology, Supervision, Validation, Writing – original draft, Writing – review & editing

Affiliation Southeast Asia One Health University Network (SEAOHUN), Chiang Mai, Thailand

• [ view all ]
• [ view less ]
• Cuiyan Wang, 
• Michael Tee, 
• Ashley Edward Roy, 
• Mohammad A. Fardin, 
• Wandee Srichokchatchawan, 
• Hina A. Habib, 
• Bach X. Tran, 
• Shahzad Hussain, 
• Men T. Hoang, 

• Published: February 11, 2021
• https://doi.org/10.1371/journal.pone.0246824
• Reader Comments

The coronavirus disease (COVID-19) pandemic has impacted the economy, livelihood, and physical and mental well-being of people worldwide. This study aimed to compare the mental health status during the pandemic in the general population of seven middle income countries (MICs) in Asia (China, Iran, Malaysia, Pakistan, Philippines, Thailand, and Vietnam). All the countries used the Impact of Event Scale–Revised (IES-R) and Depression, Anxiety and Stress Scale (DASS-21) to measure mental health. There were 4479 Asians completed the questionnaire with demographic characteristics, physical symptoms and health service utilization, contact history, knowledge and concern, precautionary measure, and rated their mental health with the IES-R and DASS-21. Descriptive statistics, One-Way analysis of variance (ANOVA), and linear regression were used to identify protective and risk factors associated with mental health parameters. There were significant differences in IES-R and DASS-21 scores between 7 MICs (p<0.05). Thailand had all the highest scores of IES-R, DASS-21 stress, anxiety, and depression scores whereas Vietnam had all the lowest scores. The risk factors for adverse mental health during the COVID-19 pandemic include age <30 years, high education background, single and separated status, discrimination by other countries and contact with people with COVID-19 (p<0.05). The protective factors for mental health include male gender, staying with children or more than 6 people in the same household, employment, confidence in doctors, high perceived likelihood of survival, and spending less time on health information (p<0.05). This comparative study among 7 MICs enhanced the understanding of metal health in the general population during the COVID-19 pandemic.

Citation: Wang C, Tee M, Roy AE, Fardin MA, Srichokchatchawan W, Habib HA, et al. (2021) The impact of COVID-19 pandemic on physical and mental health of Asians: A study of seven middle-income countries in Asia. PLoS ONE 16(2): e0246824. https://doi.org/10.1371/journal.pone.0246824

Editor: Tauqeer Hussain Mallhi, Jouf University, Kingdom of Saudi Arabia, SAUDI ARABIA

Received: October 17, 2020; Accepted: January 27, 2021; Published: February 11, 2021

Copyright: © 2021 Wang 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: This study has the following funding sources: 1. Author C.W, 1 grant, Huaibei Normal University, China. 2. Author R.H, 1 grant, National University of Singapore iHealthtech Other Operating Expenses (R-722-000-004-731) 3. Author B.X.T, 1 grant, Vingroup Innovation Foundation (VINIF) COVID research grant (VINIF.2020.Covid19.DA07) in Vietnam

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

Introduction

Emerging psychiatric conditions and mental well-being were identified as the tenth most frequent research topic during the COVID-19 pandemic [ 1 ]. A recent systematic review found that relatively high rates of symptoms of anxiety, depression, post-traumatic stress disorder and stress were reported in the general population and health care professionals during the COVID-19 pandemic globally [ 2 , 3 ]. Asia has a number of middle income countries (MICs) that face tremendous economic challenges and limited medical resources to maintain physical and mental well-being during the pandemic [ 4 ]. This extended to North America as well, with the sudden change in economic security during COVID-19 projected to increase suicide rates [ 5 ]. During the pandemic, the Asia Pacific Disaster Mental Health Network recommended to establish a mental health agenda for Asia [ 6 ]. It is therefore important to conduct research to assess psychiatric status of Asians living in MICs to develop capacity of various health systems to respond to COVID-19. Previous studies mainly focused on mental health of individual Asian countries during the pandemic without cross comparison [ 7 – 9 ].

With no prior comparative study found on physical and mental health of Asians living in MICs during the COVID-19 pandemic, this study aimed to investigate the impact of the pandemic on physical and mental health in 7 Asian MICs (China, Iran, Malaysia, Pakistan, Philippines, Thailand and Vietnam), identify differences among countries, understand their concerns and precautions toward COVID-19, as well as to identify protective and risk factors associated with mental health outcomes.

Methodology

Study design and study population.

This was a cross-sectional study that involved seven countries. The recruitment was conducted after COVID-19 became an epidemic in each country. To minimize risks of COVID-19 infection, a respondent-driven sampling strategy on recruiting the general public was utilized where new participants were electronically invited by existing study respondents rather than face-to-face interaction. The respondents completed the questionnaires through an online survey platform (‘SurveyStar’, Changsha Ranxing Science and Technology in China, SurveyMonkey in Philippines, and Google Forms in other countries).

Ethics approval

The study was approved by the Institutional Review Boards from each MIC, China (Huaibei Normal University of China, HBU-IRB-2020-001/002), Iran (Islamic Azad University, Protocol Number: IRB-2020-001), Malaysia (Universiti Malaysia Sarawak, UNIMAS/NC-21.02/03-02 Jld.4 (85)), Pakistan (University of Karachi Protocol Number: ICP-1 (101) 2698), Philippines (University of Philippines Manila Research Ethics Board, UPMREB 2020-198-01), Thailand (Chulalongkorn University, COA No. 147/2563), and Vietnam (Hanoi Medical University, QD 75/QD-YHDP&YHDP). All IRBs allowed participants aged 12 years to 17 years to participate in this study and provide their own consent because the online survey did not pose any risk to research participants. All respondents provided informed consent. Confidentiality was maintained because no personally identifiable information was collected.

Measures and instruments

The COVID-19 online questionnaire designed by the National University of Singapore [ 10 ] had five sections: demographic, physical symptoms related to COVID-19 in the past 14 days, knowledge and concerns about COVID-19, precautionary measures against COVID, and views of health information required. Psychometric properties of the questionnaire were established in the initial phase and peak of the COVID-19 epidemic [ 8 , 9 ].

The psychological impact of COVID-19 was measured using the well-validated Impact of Event Scale-Revised (IES-R) in the Asians for determining the extent of psychological impact after exposure to a traumatic event (i.e., the COVID-19 pandemic) within one week of exposure [ 11 – 14 ]. In this study, the Cronbach’s alpha for different versions of IES-R is very high in all countries and ranges from 0.912–0.950. Cronbach’s alpha of 0.70 or higher in measuring the internal consistency is considered “acceptable” in most social science research [ 15 ].

The mental health status of respondents was measured using the Depression, Anxiety and Stress Scale (DASS-21) [ 16 ], which has been used to assess mental health in Asians [ 17 , 18 ]. Furthermore, DASS-21 assessed three domains (i.e. anxiety, depression and stress) and its psychometric properties was validated across clinical and non-clinical samples in different cultures and languages during the COVID-19 pandemic [ 19 ]. In this study, the Cronbach’s alpha (internal consistency) for different versions of DASS-21 is as follows: stress scale ranges from 0.839–0.934, anxiety scale ranges from 0.784–0.914, and depression scale ranges from 0.878–0.943. The IES-R and DASS-21 scales were previously used in research related to the COVID-19 epidemic [ 8 , 12 , 20 , 21 ]. The DASS and IES-R questionnaires are available in the public domain, and so permission is not required to use these two questionnaires [ 22 , 23 ].

Statistical analysis

Descriptive statistics were calculated to compare demographic characteristics, physical symptoms and health service utilization, contact history, knowledge and concern, precautionary measure and additional health information variables among 7 MICs. One-Way analysis of variance (ANOVA) was calculated to compare the mean IES-R and DASS-21 scores between 7 MICs in order to determine whether the associated population mean IES-R or DASS-21 scores were significantly different. If there were significant differences among 7 MICs, the Least Significant Difference (LSD) would calculate the smallest significant between mean scores of two countries with different combinations. Any difference larger than the LSD is considered a significant result. We used linear regressions to calculate the univariate associations between independent and dependent variables including the IES-S score and DASS-21 stress, anxiety and depression subscale scores for all respondents separately. All tests were two-tailed, with a significance level of p <0.05. Statistical analysis was performed on IBM SPSS Statistics version 21.0.

A total of 4479 participants from 7 MICs in Asia completed the survey. The distribution of the number of participants by country is listed as follows: China (27%), Philippines (19%), Malaysia (16.2%), Iran (12.3%), Thailand (11.6%), Pakistan (11.3%), and Vietnam (2.7%). Fig 1 compares the IES-R and DASS-21 scores amongst all 7 MICs in Asia.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0246824.g001

The top three countries with highest IES-R scores were Thailand (mean 42.35, SD 13.39), China (mean 32.98, SD 15.42), and Iran (mean 30.42, SD 15.82). The top three countries with highest DASS-21 stress scores were Thailand (mean 21.94, SD 7.74), Pakistan (mean 14.02, SD 11.53) and Philippines (mean 10.60, SD 8.01). The top three countries with highest DASS-21 anxiety scores were Thailand (mean 18.66, SD 5.98), Pakistan (mean 8.23, SD 9.69) and Malaysia (mean 7.80, SD 10.95). The top three countries with highest DASS-21 depression scores were Thailand (mean 19.74, SD 6.99), Pakistan (mean 11.33, SD 11.28) and Philippines (mean 9.72, SD 8.99).

Differences in IES-R scores and DASS-21 stress, anxiety, depression scores amongst the 7 MICs were all statistically significant (IES-R: F(6, 4472) = 144.47, p<0.001, η2 = 0.16; Stress: F(6,4472) = 167.49 p<0.001, η2 = 0.18; Anxiety: F (6,4471) = 172.03, p<0.001, η2 = 0.19; Depression: F(6, 4472) = 137.11, p<0.001, η2 = 0.16). Vietnam had the lowest scores of IES-R (mean 17.39, SD 13.72), stress (mean 3.80, SD 5.81), anxiety (mean 2.10, SD 4.91) and depression (mean 2.28, SD 5.43). The LSD analysis revealed that the scores of Vietnam were significantly lower than the other countries (p<0.05).

S1 Table compares the demographics of 7 MICs. More than half of participants were women in all countries (Range: 52.6% in Pakistan to 76.8% in Thailand). More than half of Chinese, Filipino, Iranian and Pakistani participants were below age of 31 years. Majority of Chinese, Vietnamese and Malaysian respondents were married while majority of Filipino and Thai respondents were single. Majority of Filipino, Iranian, Pakistani, Malaysian and Thai respondents did not have children. More than half of participants stayed in a household with more than 3–5 people across all countries except Pakistan (49%). Majority of respondents from Philippines, Pakistan, Vietnam and Malaysia were employed when the study was conducted.

Table 1 shows the association between demographic characteristics of all participants and mental health parameters. Demographic characteristics associated with lower psychological impact were male gender whereas age younger than 30 years and students were associated with higher psychological impact. Participants who have children were associated with lower stress, anxiety and depression whereas participants with higher education, single and separated status were associated with higher stress, anxiety and depression. Staying with 6 or more people and those who were employed were associated with lower anxiety and depression.

https://doi.org/10.1371/journal.pone.0246824.t001

S2 Table shows the frequency of physical symptoms that resemble COVID-19 infection and there were significant differences among all countries. During the COVID-19 pandemic, the most common physical symptoms reported by general population in the 7 countries were headache (23.13%), cough (21.86%) and sore throat (19.29%). About 8.13% of respondents consulted General Practitioner (GP); 2.69% were hospitalized; 3.89% were tested positive for COVID-19 and 57.1% had a health insurance. Pakistani had the significantly highest proportion of respondents consulted GP (27.5%), hospitalized (16.4%), receiving COVID-19 test (17.2%) and being isolated (17.8%). Table 2 shows the association between physical symptoms and mental health outcomes. The physical symptoms that were significantly associated with higher scores in all mental health outcomes (IES-R and DASS-21 subscales) including rhinitis and persistent fever with cough or breathing difficulties. Chills or rigors, headache and nausea or vomiting were associated with higher DASS-21 stress and anxiety scores. Myalgia, cough, dizziness and sore throat were associated with higher score of IES-R. Usage of medical services such as seeing a doctor, hospitalization, recent COVID-19 testing, quarantine, poor rating of health status that were significantly associated with higher scores in all mental health outcomes (IES-R and DASS-21 subscales). History of chronic illness were significantly associated with higher DASS-21 subscale scores. Having medical insurance coverage was associated with higher IES-R scores.

https://doi.org/10.1371/journal.pone.0246824.t002

S3 Table shows the belief of route of transmission among participants in 7 MICs and there were significant differences among all countries. Out of all participants, there were a small number of participants who did not agree with transmission of COVID-19 being via droplets (10.34%) and contaminated objects (17.21%). It is interesting to note that China (60.5%) and Vietnam (59.8%) demonstrated significantly higher percentage of participants who believed in airborne transmission compared to .64.76% of participants from the other five countries who did not agree that COVID-19 was airborne transmitted.

Participants expressing confident and very confident in their doctors diagnosing COVID-19 were very high in Malaysia (93.8%) and China (92.9%); level of confidence was much lower in Iran (65.5%) and Pakistan (62.6%). About 50.26% of participants reported that they were likely and very likely to contract COVID-19, with Malaysian participants demonstrating the highest perceived risk of COVID-19 (72.8%) whilst the Filipino demonstrated the highest proportion of participants believing that they would not contract COVID-19 (53.2%). About 89.8% of Thai participants believed that they would survive if contracted with COVID-19 while the Pakistani had the highest proportion who believed that they would not survive COVID-19 (15.4%). About 78.43% of participants were satisfied with health information related to COVID-19; Vietnamese participants reported the highest proportion of satisfaction (97.5%). About 77.38% of participants were worried their family members contracting COVID-19. Pakistani participants reported the highest proportion of people who faced discrimination (42.7%). About 44.68% of participants spent more than 2 hours per day to view information on COVID-19 with Filipino participants having the highest proportion for spending more than 2 hours per day to view information (47.2%).

Table 3 shows the association between knowledge and concerns related to COVID-19 and mental health parameters. Agreement with airborne, contact with contaminated objects and droplet transmission was associated with higher DASS-21 in all subscales. Likelihood of contracting COVID-19, discrimination against by other countries and contact with people infected with COVID-19 were associated with higher IES-R or DASS-21 scores. Confidence in one’s own doctor diagnosing COVID-19, high likelihood of survival if infected with COVID-19 and spent less than two hours per day to monitor information relating to COVID-19 were associated with lower level of IES-R or DASS-21 scores.

https://doi.org/10.1371/journal.pone.0246824.t003

S4 Table shows the prevalence of precautionary measures and there were significant differences among 7 MICs (p<0.001). High percentages were reported by participants covering their mouth and nose after sneezing (98.0%), avoided sharing utensils (90.8%), practised hand hygiene (98.9%), washed hand after touching contaminated objects (96.2%), and wear face masks (93.5%). All Vietnamese participants (100%) responded wearing a face mask. About 68% of respondents felt that people were too worried about COVID-19 with Malaysia (90.5%), Thailand (90.5%) and Pakistan (86.6%) as the top three countries. Approximately 53% of respondents spent 20–24 hours per day at home; with China (84.7%), Iran (73.5%) and Philippines (55%) as the top three countries.

Table 4 shows the association between precautionary measures related to COVID-19 and mental health parameters. Avoidance of sharing cutlery dealing meals was associated with higher anxiety and depression. In contrast, hand hygiene practice was associated with lower IES-R and DASS-21 in all subscales. Wearing a face mask was associated with lower levels of stress and depression. Worries about COVID-19 was associated with significantly higher levels of DASS-21 in all subscales. Shorter duration of homestay was associated with higher levels of anxiety, depression and stress as compared to those who stayed at home for 20–24 hours per day.

https://doi.org/10.1371/journal.pone.0246824.t004

S5 Table compares the health information needs of participants from 7 MICs and there were significant differences among 7 MICs. The Chinese had the highest proportion who wanted to understand the symptoms of COVID-19 (91.6%), the prevention method (93.7%), effectiveness of drugs and vaccines (94.1%), number of infected cases and location (95.9%), travel advice (96.9%), mode of transmission (94.5%), required regular information update (92.7%) and personalized information (96.8%). The Iranians had the highest proportion who sought advices regarding treatment methods (90.4%) and Malaysians had the highest proportion who wanted to understand local outbreaks (94.2%).

Table 5 shows the association between health information needs about COVID-19 and mental health parameters. Most additional information including information on COVID-19 symptoms, prevention, treatment advice, needs for regular updates, knowledge on local transmission, effectiveness on drugs and vaccines, number of infected people based on geographical locations, travel advice and transmission mode of COVID were associated with higher IES-R scores. In contrast, the need for more personalized information, information on the effectiveness of drugs and vaccines, travel advices, transmission mode were associated with significantly lower level of depression.

https://doi.org/10.1371/journal.pone.0246824.t005

The main findings of this first multinational population-based study in MICs in Asia during the COVID-19 pandemic are summarized as follows. First, Thai respondents reported the highest levels of IES-R and DASS-21 scores. Second, Pakistani respondents reported the second highest levels of DASS-21 scores. Comparatively, Vietnamese respondents reported the lowest levels in DASS-21 scores. Third, Iranian respondents demonstrated the lowest confidence in their doctors whilst Pakistani respondents had the highest proportion who believed they would not survive COVID-19 and reported discrimination.

Assessing COVID-19’s association with respondents’ mental health, the three most common physical symptoms associated with adverse mental health were headache, cough and sore throat. Risk factors associated with adverse mental health during the COVID-19 pandemic include age <30 years old, high education background, single and separated status, discrimination by other countries, contact with people with COVID-19 and worries about COVID-19. Protective factors for mental health during the COVID-19 pandemic include male gender, staying with children, staying with 6 or more people, employment, confidence in own’s doctors diagnosing COVID-19, high perceived likelihood of surviving COVID-19, spending less time on health information, hand hygiene practice and wearing a face mask. Importantly, these findings will be significantly helpful for healthcare administrators in Asia at the national and local community levels [ 24 ] when preparing for the next wave of COVID-19 outbreak and future pandemics [ 25 ].

Iran had the highest total reported COVID cases (386,658) and number of COVID cases per 1 million people (4,593), as well as the highest number of deaths from COVID (22,293) and deaths per 1 million people (265) [ 26 ]. Pakistan had the second highest number of cases (298,509) and deaths (6,342) [ 26 ]. Of the 7 MICs, Vietnam had the lowest total numbers and rates across all seven countries, with 1,049 reported cases, 35 deaths and rates of just 11 cases and 0.4 deaths per 1 million [ 26 ]. As a result, Vietnamese respondents reported the lowest IES-R and DASS-21 scores. Vietnam has adopted several strategies to combat COVID-19 including development of the action plan and response strategies to optimize the utilization of human resources and equipment [ 24 ]; address the health information needs based on the diverse socioeconomic, demographic, and ethnic factors [ 27 ]; re-design communication activities for a more effective dissemination of information related to the epidemic [ 28 ]; safeguarding the health of workforce [ 29 ] to ensure minimal impact on economy and involvement of the grassroot system and village health collaborators to combat pandemics [ 30 , 31 ].

Thailand recorded the second lowest number of total cases (3,444) and deaths (58), and similarly the second lowest case rates (49) and death rates (0.8) per 1 million [ 26 ]. Surprisingly, we found that Thailand was the country with the highest IES-R and DASS-21 depression scores. This could be due to the impact of COVID-19 on the economy in Thailand. Among all MICs in Asia, the disruption on COVID-19 pandemic is the most severe on Thailand economy, due to its reliance on tourism as compared to other MICs. For 2020, the International Monetary Fund has predicted Thailand’s GDP to be reduced by 6.7 percent which is highest among Asian countries [ 32 ]. Pakistan ranked second in terms of DASS-21 scores and number of COVID cases and deaths. The congruence between psychological parameters and epidemiology of COVID-19 in Pakistan was due to poor sanitation, lack of basic preventive measures, lack of proper testing and medical facilities. Pakistani health professionals started protesting and threatened to quit work due to lack of Personal Protective Equipment (PPE) [ 33 ]. Currently, the vaccination coverage in rural Pakistan remains unsatisfactory amid various barriers including price, hesitancy, and low level of awareness [ 34 ]. Eid-ul-Adha is an annual religious festival that could not be cancelled due to religious obligations and led to a sharp spike in COVID-19 cases [ 35 ]. The unpreparedness and contradictory policies resulted in an alarming high rate of COVID-19 spread and worsening mental health and discrimination faced by Pakistani people. Iranian respondents demonstrated lowest confidence in their doctors. The economic sanctions that prevented medical supplies, equipment and drugs from arriving in Iran could lead to low confidence among Iranians [ 36 ].

This study highlighted unique protective factors for mental health in MICs of Asia. In this study, more than 90% of respondents agreed to wear masks to prevent COVID-19. During the initial stage of COVID-19 pandemic, medical and public health experts from the US and some European countries believed that there was no direct evidence of airborne transmission of COVID-19 [ 37 ]. In contrast, respiratory clinicians and public health experts from Asia argued that lack of evidence does not equate to evidence of ineffectiveness of face masks [ 38 ]. The use of face masks by Asians have played an important role in controlling the spread of COVID-19 [ 39 ]. This study showed the association between the use of face mask and lower DASS-21 anxiety and depression scores. This finding might support the postulation that wearing face mask could offer psychological benefits, such as feeling less vulnerable to infection via perceived control [ 37 ]. Staying with children and more than 6 people in the same household were protective factors due to the values of family support among Asians. Compared with western countries, family support has a greater influence on reducing the risk of adverse mental health in Asia [ 10 ].

The findings of this first multinational study have several implications for health and government policies. Firstly, the health authorities should offer psychological interventions to the general population who are at higher risk of developing adverse mental health including women, people younger than 30 years and single and separated status. High education background is a risk factor and online psychological interventions such as cognitive behaviour therapy (CBT) and mindfulness-based therapy could improve mental health for highly educated individual [ 40 ]. For countries with high IES-R scores (Thailand, China and Iran), online trauma-focused CBT that promotes trauma narration, problem solving related to problems associated with COVID-19 and home based relaxation could be helpful in reducing psychological impact [ 9 ]. Second, as physical symptoms resembling COVID-19 infection (e.g., rhinitis, persistent fever with cough, breathing difficulties) were associated with high IES-R and DASS-21 scores groups. There is an urgent need to develop accurate, rapid diagnostic tests in general practitioners’ clinics, community and rural settings [ 31 ]. A negative COVID-19 test result may alleviate anxiety, depression, stress and psychological impact. Enhancing the capacity of health system to combat COVID-19 may increase the confidence of public and improve mental health. Third, based on our findings, the WHO, governments and health authorities should provide regular updates on the effectiveness of vaccines and treatment methods. Mis-information related to the cause of COVID-19 [ 41 ], rumours [ 42 ] and inconsistent information [ 43 ] on COVID-19 symptoms, prevention, treatment and transmission mode were associated with negative psychological impact. Local governments, news agencies, professional and advocacy organisations should all provide health information and advices related to COVID-19 that are consistent with national guidelines and avoid mis-information [ 44 ]. It is important to identify group-specific demands would be helpful to provide proper information related to COVID-19 to fulfil the need of different population groups [ 27 ]. Various governments should offer relief packages to safeguard employment and economy to protect mental health. Additionally, the level of policy stringency in response to COVID-19 or pandemics, as measured by the Oxford Stringency Index, may influence mental health and should be moderated accordingly by respective governments [ 45 ].

This study has several limitations. First, the findings of this study were based on seven MICs in Asia and could not be generated to other countries. The study population had different sociodemographic characteristics as compared to the general population in the world due to sampling bias because only participants with Internet access could participate in this online survey. The respondent sampling method also compromised the representativeness of samples. The study population was female predominant (proportion of female in the study population: 67.76%; world population 49.58%) [ 46 ] and a high proportion of the study population possessed a university degree (85.6%). Thus, there is a potential risk of sampling bias because we could not reach out to potential respondents without Internet access. The second limitation was the cross-sectional nature of this study and inability to demonstrate cause and effect relationship. The third limitation was that we did not record demographic data regarding pre-existing mental illness of the study participants. The fourth limitation is that self-reported levels of psychological impact, anxiety, depression and stress may not always be aligned with objective assessment by mental health professionals. Nevertheless, psychological impact, anxiety, depression and stress are based on personal feelings, and self-reporting was paramount during the COVID-19 pandemic. The fifth limitation is that we did not study other aspects of the pandemic such as the potential threat of self-medication of hydroxychloroquine and cholorquine [ 47 ] and precautionary measures of walkthrough sanitization gates [ 48 ]. Lastly, we were unable to calculate the response rate. For potential respondents who were not keen to participate in the online survey, no response was recorded, and we could not collect any information from them.

Conclusions

In conclusion, this multi-national study across 7 MICs in Asia showed that Thai reported the highest mean IES-R and DASS-21 anxiety, depression and stress scores. In contrast, Vietnamese reported the lowest mean scores in IES-R and DASS-21 anxiety, depression and stress scales. The risk factors for adverse mental health include age < 30 years, high education background, single and separated status, discrimination by other countries, contact with people with COVID-19 and worries about COVID-19. The protective factors for mental health include male gender, staying with children, staying with 6 or more people, employment, confidence in own’s doctors diagnosing COVID-19, high perceived likelihood of surviving COVID-19, spending less time on health information, hand hygiene practice and wearing a face mask.

Supporting information

S1 table. comparison of demographics of the participants from seven countries..

https://doi.org/10.1371/journal.pone.0246824.s001

S2 Table. Physical symptoms resembling COVID-19 infection reported by the participants from seven countries.

https://doi.org/10.1371/journal.pone.0246824.s002

S3 Table. Comparison of knowledge related to COVID-19 in participants of the seven countries.

https://doi.org/10.1371/journal.pone.0246824.s003

S4 Table. Comparison of precautionary measures related to COVID-19 in the participants of the seven countries.

https://doi.org/10.1371/journal.pone.0246824.s004

S5 Table. Comparison of information needs about COVID-19 in the participants of the seven Asian countries.

https://doi.org/10.1371/journal.pone.0246824.s005

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Benjamin Thompson, Noah Baker and Traci Watson discuss some of 2020's most significant coronavirus research papers.

In the final Coronapod of 2020, we dive into the scientific literature to reflect on the COVID-19 pandemic. Researchers have discovered so much about SARS-CoV-2 – information that has been vital for public health responses and the rapid development of effective vaccines. But we also look forward to 2021, and the critical questions that remain to be answered about the pandemic.

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A Novel Coronavirus from Patients with Pneumonia in China, 2019 - New England Journal of Medicine, 24 January

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China - The Lancet , 24 January

A pneumonia outbreak associated with a new coronavirus of probable bat origin - Nature , 3 February

A new coronavirus associated with human respiratory disease in China - Nature , 3 February

Temporal dynamics in viral shedding and transmissibility of COVID-19 - Nature Medicine , 15 April

Spread of SARS-CoV-2 in the Icelandic Population - New England Journal of Medicine , 11 June

High SARS-CoV-2 Attack Rate Following Exposure at a Choir Practice — Skagit County, Washington, March 2020 - Morbidity & Mortality Weekly Report , 15 August

Respiratory virus shedding in exhaled breath and efficacy of face masks - Nature Medicine , 3 April

Aerosol and Surface Stability of SARS-CoV-2 as Compared with SARS-CoV-1 - New England Journal of Medicine , 13 April

Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period - Science , 22 May

Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe - Nature, 8 June

The effect of large-scale anti-contagion policies on the COVID-19 pandemic - Nature , 8 June

Retraction—Hydroxychloroquine or chloroquine with or without a macrolide for treatment of COVID-19: a multinational registry analysis - The Lancet, 20 June

A Randomized Trial of Hydroxychloroquine as Postexposure Prophylaxis for Covid-19 - New England Journal of Medicine , 3 June

Association Between Administration of Systemic Corticosteroids and Mortality Among Critically Ill Patients With COVID-19 - JAMA , 2 September

Immunological memory to SARS-CoV-2 assessed for greater than six months after infection - bioRxiv, 16 November

Coronavirus Disease 2019 (COVID-19) Re-infection by a Phylogenetically Distinct Severe Acute Respiratory Syndrome Coronavirus 2 Strain Confirmed by Whole Genome Sequencing - Clinical Infectious Diseases , 25 August

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Virome Sequencing Identifies H5N1 Avian Influenza in Wastewater from Nine Cities

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Avian influenza (serotype H5N1) is a highly pathogenic virus that emerged in domestic waterfowl in 1996. Over the past decade, zoonotic transmission to mammals, including humans, has been reported. Although human to human transmission is rare, infection has been fatal in nearly half of patients who have contracted the virus in past outbreaks. The increasing presence of the virus in domesticated animals raises substantial concerns that viral adaptation to immunologically naïve humans may result in the next flu pandemic. Wastewater-based epidemiology (WBE) to track viruses was historically used to track polio and has recently been implemented for SARS-CoV2 monitoring during the COVID-19 pandemic. Here, using an agnostic, hybrid-capture sequencing approach, we report the detection of H5N1 in wastewater in nine Texas cities, with a total catchment area population in the millions, over a two-month period from March 4 th to April 25 th , 2024. Sequencing reads uniquely aligning to H5N1 covered all eight genome segments, with best alignments to clade 2.3.4.4b. Notably, 19 of 23 monitored sites had at least one detection event, and the H5N1 serotype became dominant over seasonal influenza over time. A variant analysis suggests avian or bovine origin but other potential sources, especially humans, could not be excluded. We report the value of wastewater sequencing to track avian influenza.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This work was supported by S.B. 1780, 87th Legislature, 2021 Reg. Sess. (Texas 2021) (E.B., A.W.M., and J.F.P.), NIH/NIAID (Grant number U19 AI44297) (A.W.M.), Baylor College of Medicine Melnick Seed (A.W.M) and Alkek Foundation Seed (J.F.P.), and Pandemic Threat Technology Center (P.A.P.).

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Data Availability

All data produced are available online at https://zenodo.org/doi/10.5281/zenodo.11175923 and NCBI SRA BioProject: PRJNA966185

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A Descriptive Study of COVID-19–Related Experiences and Perspectives of a National Sample of College Students in Spring 2020

Alison k. cohen.

a Department of Public and Nonprofit Administration, School of Management, University of San Francisco, San Francisco, California

Lindsay T. Hoyt

b Department of Psychology, Fordham University, New York, New York

Brandon Dull

Associated data.

This is one of the first surveys of a USA-wide sample of full-time college students about their COVID-19–related experiences in spring 2020.

We surveyed 725 full-time college students aged 18–22 years recruited via Instagram promotions on April 25–30, 2020. We inquired about their COVID-19–related experiences and perspectives, documented opportunities for transmission, and assessed COVID-19's perceived impacts to date.

Thirty-five percent of participants experienced any COVID-19–related symptoms from February to April 2020, but less than 5% of them got tested, and only 46% stayed home exclusively while experiencing symptoms. Almost all (95%) had sheltered in place/stayed primarily at home by late April 2020; 53% started sheltering in place before any state had an official stay-at-home order, and more than one-third started sheltering before any metropolitan area had an order. Participants were more stressed about COVID-19's health implications for their family and for American society than for themselves. Participants were open to continuing the restrictions in place in late April 2020 for an extended period of time to reduce pandemic spread.

Conclusions

There is substantial opportunity for improved public health responses to COVID-19 among college students, including for testing and contact tracing. In addition, because most participants restricted their behaviors before official stay-at-home orders went into effect, they may continue to restrict movement after stay-at-home orders are lifted, including when colleges reopen for in-person activities, if they decide it is not yet prudent to circulate freely. The public health, economic, and educational implications of COVID-19 are continuing to unfold; future studies must continue to monitor college student experiences and perspectives.

Implications and Contribution

Researchers surveyed a national sample (n = 725) of full-time college students in the USA about their coronavirus disease 2019–related experiences in spring 2020. College students are already restricting their behaviors to protect population health, but more must be done to reduce opportunities for coronavirus disease 2019 transmission by college students.

The novel COVID-19 pandemic's impact on college students is unprecedented. College students are a priority population for health promotion and disease prevention [ 1 ], and universities are unique settings that can affect the health of a larger segment of the population. College campuses are densely populated, with students living in close proximity to others; this means that college students can efficiently transmit communicable diseases (such as influenza, or COVID-19), creating hot zones for transmission [ 2 ].

To the best of our knowledge, we conducted one of the first national surveys to learn what full-time college students' COVID-19–related experiences in the United States of America (USA) were in spring 2020, during the USA's first peak of COVID-19 and when colleges and universities transitioned to remote learning [ 3 ]. This study offers insight into college students' health (e.g., COVID-19 symptoms), psychosocial, and economic experiences, as well as their perspectives on COVID-19, that can inform the COVID-19 approaches of public health officials, policy makers, and higher education leaders.

Study sample

We recruited via Instagram to create a sample of full-time college students aged 18–22 years (mean age: 20.0 years, standard deviation: 1.3) from across the USA. Although internet access disparities have historically been a concern when recruiting internet-based samples [ 4 ], being a full-time college student in April 2020 required some internet access, owing to remote learning. Recruitment and enrollment outcomes from previous research indicate that Instagram is an effective strategy to reach diverse youth, given the ability to target ads based on user data and the pervasiveness of social media [ 5 , 6 ]. In fall 2019, more than 80% of college students used Instagram, their most preferred social media platform [ 7 ]; as digital activity has increased during the pandemic [ 8 ], this proportion is now likely even higher.

Instagram promotions are regular posts (i.e., a photo or video with caption and hashtags) that are typically used to increase brand awareness (e.g., likes, views, shares) and/or sales (e.g., links to merchandise on a website) among a targeted audience. We used Instagram promotions to advertise this study using our Instagram Business Profile account (@3dyouthresearch), which operates via Facebook Ad Manager. We selected the number of days the promotion should run and the amount of money to spend per day. We could also select a more targeted audience, including by age, gender, and location, as well as by “interests” (e.g., hobbies, events). Prices were based on cost per click and determined according to Instagram's internal algorithms, incorporating factors such as the selected audience and ad feedback.

We used four Instagram promotions over 5 days. Each promotion included either (a) the CDC image of the coronavirus [ 9 ] or (b) a photo of an empty classroom. Promotions used similar text (i.e., “College Students: Complete an online survey about your experiences during the COVID-19 pandemic. Earn a $10 gift card!”) and a similar set of hashtags (e.g., #covid_19, #earnmoneyfromhome, #campusclosed). The first two promotions (age target: 18–22 years; gender: male or female; geographic location: USA) ran from April 24 to 27, 2020, and each reached (i.e., was seen by) more than 12,800 people. We then created two additional promotions that reached more than 6,000 young adults (aged 18–22 years) in the USA, targeting specific geographic locations (e.g., cities with high proportions of people of color, rural states) and diverse colleges (e.g., names of Hispanic-serving institutions and historically black colleges and universities as “Interests”); one of these two promotions specifically targeted men because women are more likely to participate in survey research [ 10 ]. We spent $150 on the first round of promotions (April 25–27, 2020) and an additional $119 on the second round of promotions (April 28–29, 2020, which was cut short given that we reached capacity).

The four promotions were viewed 41,101 times (because views were summed across ads, some people may have viewed more than one promotion), and 2,887 individuals clicked on the link to the screening questionnaire. Of those, 1,590 nonduplicated individuals started the screening questionnaire (which determined status as a full-time USA college student aged 18–22 years), which was 55.1% of those who viewed the screening questionnaire; and 1,331 nonduplicated individuals completed the screening questionnaire (83.7% of those who started the screening questionnaire). Most (n = 1,225, 92.0%) qualified for the study and provided informed consent. To further confirm current college student status, participants provided a .edu email address in the screening questionnaire, to which we sent a link to the full survey. Participants completed the survey via Qualtrics until we reached maximum capacity (n = 725); the median time to complete the survey was 34.5 minutes (interquartile range: 26.6–47.4 minutes). All participants received a $10 Amazon.com gift card within three business days of survey completion; we had a maximum capacity of 725 participants owing to the funds available for incentives. Data collection occurred from April 25, 2020, to April 30, 2020; we prioritized completing data collection before any reopening began (some locations in the USA began to reopen on May 1, 2020).

The study was approved by the Fordham University Institutional Review Board.

Survey measures

We designed most of the survey measures ( Appendix Table 1 ); we also used items from the Stop AAPI Hate Survey [ 11 ] to measure discrimination.

Data analyses

Descriptive statistics and chi-square tests were calculated in Stata (StataCorp, College Station, TX), version 16.1. Confidence intervals (95% CIs) were calculated using http://vassarstats.net/prop1.html .

Our study sample (n = 725) included a relatively even distribution of students by year in school and had racial/ethnic, gender, sexual orientation, political affiliation, and socioeconomic position diversity ( Table 1 ). Participants came from all 50 USA states and Washington DC. Our study was not as diverse as the national full-time college student population [ 12 , 13 ]; this may be because we restricted our sample to full-time college students aged 18–22 years.

Table 1

Study sample demographic characteristics (n = 725)

Race/ethnicity proportions add up to more than 100% because participants could select all categories with which they identified. For the national data, 3.7% of all full-time college students in the U.S. identified two or more races.

The family household income comparison data were only available for students who are dependents of their families, whereas our data include both students who were dependents and students who were financially independent.

National data on full-time college students came from multiple sources. College year, race/ethnicity, gender, immigration status, financial aid, family income, first-generation status, and financial independence data were from the U.S. Department of Education, National Center for Education Statistics, Higher Education General Information Survey and the 2015–16 National Postsecondary Student Aid Study. Sexual orientation data were from the National Survey of Student Engagement (2017). Political party data came from the 2018 Survey of America's College Students, Panetta Institute for Public Policy.

COVID-19 = coronavirus disease 2019.

In late April 2020, most participants were living with at least one parent (e.g., 73.4% (95% CI: 70.1%–76.5%), living with their mother(s) and/or step-mother(s)) ( Appendix Table 2 ). On average, participants lived with 2.9 other people. Seventeen percent (95% CI: 13.8%–20.7%) of those living with siblings and/or cousins were providing childcare and/or schooling assistance for any younger children in their household, but this varied by gender: 22.2% (95% CI: 9.0%–45.2%) of nonbinary, genderqueer, and transgender participants (n = 18), 19.6% (95% CI: 15.4%–24.6%) of female participants (n = 281), and only 11.7% (95% CI: 7.5%–17.7%) of male participants (n = 154) provided such care ( p -value for chi-square test of female and gender minority participants vs. males = .03).

For many, their current living arrangements differed from their typical college housing. Because the 2020 Census was also unfolding during spring 2020, we asked participants if they knew if they were counted in the 2020 Census; 67.7% (95% CI: 64.2%–71.0%) said yes, 26.3% (95% CI: 23.3%–29.7%) did not know, and 6% (95% CI: 4.4%–7.9%) said no. The 491 who said yes were counted a total of 534 times. The most common overlaps were being counted both at their college dorm and their family's household (n = 31) and at both an off-campus residence and family household (n = 10).

COVID-19 health experiences

Symptoms and testing.

More than one-third of participants (35.3%, 95% CI: 31.9%–38.9%) experienced COVID-19–related symptoms (as established by the CDC [ 14 ] and/or emerging research) since February 2020. Among those who experienced any symptoms (n = 256), 4.7% (95% CI: 2.7%–8.0%) got tested for COVID-19, 9.8% (95% CI: 6.7%–14.0%) attempted to get tested but were not successful and 85.6% (95% CI: 80.1%–89.3%) did not attempt to get tested. Of the 12 people who experienced symptoms and got tested, two tested positive, nine tested negative, and one did not yet have results. (Among those who did not experience any symptoms (n = 469), .9% (95% CI: .3%–2.2%) were tested for COVID-19, .6% (95% CI: .02%–1.9%) attempted to get tested but were not tested, and 98.5% (95% CI: 97.0%–99.3%) did not attempt to get tested. Of the four people who did not have symptoms but got tested for COVID-19, one tested positive, two tested negative, and one did not yet have results.)

Behaviors when symptomatic

Among those who had any symptoms (n = 256), 46.9% (95% CI: 40.9%–53.0%) stayed at home exclusively while they had symptoms ( Table 2 ). An additional 35.5% (95% CI: 29.9%–41.2%) stayed at home more than usual (but not exclusively). Nevertheless, many were still in public: 30.1% (95% CI: 24.8%–36.0%) reported attending class, 14.5% (95% CI: 10.7%–19.3%) went to work, and 13.7% (95% CI: 10.0%–18.4%) attended social gatherings. Only 16.4% (95% CI: 12.4%–21.4%) sought health care (remotely and/or in person).

Table 2

Activities of participants who had any COVID-19–related symptoms (n = 256) while experiencing symptoms

Opportunities for COVID-19 transmission

Social contact.

Participants attended a variety of in-person social gatherings of different sizes since March 1, 2020 ( Table 3 ). For most group categories (250+, 50–249, 10–49 people), academic programming was the most common type of gathering (e.g., 47.5% (95% CI: 40.4%–54.8%) of the 181 ≥ 250-person gatherings). For gatherings of 2–9 people (not including people from the participant's household), social events were the most common activity.

Table 3

Attendance at in-person social gatherings since March 1, 2020

Almost two-thirds of participants (62.8%, 95% CI: 59.2%–66.2%) traveled ≥50 miles at least once in March 2020, for a total of 531 trips ( Appendix Table 3 ). In comparison, only 15.2% (95% CI: 12.7%–18.0%) of participants traveled ≥50 miles at least once in April 2020, for a total of 108 trips. In both March and April 2020, the majority of these trips were by car: 65.0% (95% CI: 60.8%–68.9%) of trips in March and 89.8% (95% CI: 82.7%–94.2%) of trips in April.

Approximately three-quarters (77.2%, 95% CI: 74.1%–80.1%) of participants reported behaviors in compliance with CDC-recommended social distancing (i.e., 6 feet away from anyone outside your household) over the last 4 weeks (effectively, April 2020) ( Table 4 ). Notably, 25.0% (95% CI: 22.0%–28.3%) reported being within 6 feet of family and friends for whom they were not providing care. Participants also estimated the number of people of whom they had been within 6 feet across different categories and had the most uncertainty for the number of essential workers to whom they were exposed. Only 4.3% (95% CI: 3.0%–6.0%) of participants were in close contact with people they knew to have COVID-19 symptoms.

Table 4

Physical distancing behaviors in April 2020

When calculating the number of contacts, if participants provided a range (e.g., 50–100), we took the midpoint (e.g., 75); if participants only offered a lower range (e.g., “20+”), we used the lower range number (e.g., 20). If participants did not offer a number (e.g., “unknown” or “a lot”), we did not include these responses, so these are underestimates.

We also asked about exposure to prepared food obtained, by themselves and/or members of their household, via pickup or delivery. In the last 4 weeks, more than half of participants (54.8%, 95% CI: 51.1%–58.4%) reported that neither they nor any household members had food delivered, 29.0% (95% CI: 25.8%–32.4%) had delivery 1–3 times, and 16.3% (95% CI: 13.8%–19.1%) had delivery at least once per week. Pickup was more common: in the last 4 weeks, 22.8% (95% CI: 19.9%–25.6%) never picked up food, 45.8% (95% CI: 42.2%–49.4%) collected pickup 1–3 times, and 31.4% (95% CI: 28.2%–34.9%) collected pickup at least once per week.

Hygiene behaviors

Participants generally followed public health guidance when the survey was conducted, but incompletely ( Appendix Table 4 ). For example, more than three-quarters of people reported never coughing or sneezing into their hands or without covering their mouth at all, and almost half reported never touching their eyes, nose, and/or mouth without first washing their hands when outside their home. Approximately half (50.8%, 95% CI: 47.1%–54.4%) always wore a face mask or covering in public. However, while 72.5% (95% CI: 69.2%–75.7%) reported always washing their hands for the recommended duration of ≥20 seconds and/or using hand sanitizer that is ≥60% alcohol after being in a public place, only 37.6% (95% CI: 34.2%–41.2%) always do so after blowing their nose, and only 31.3% (95% CI: 28.0%–34.8%) always do so after coughing or sneezing.

Sheltering in place

Almost all (94.8%, 95% CI: 92.9%–96.2%) participants had sheltered in place or stayed at home (leaving only for essential services, essential work, and/or exercise) in spring 2020. Among those who had sheltered in place at any time (n = 687), 98.3% (95% CI: 97.0%–99.0%) were currently doing so when they completed the survey. Of the 1.8% (95% CI: 1.0%–3.0%) who had stopped sheltering in place, approximately half had stopped in the first half of April and the rest had stopped in the second half of April.

More than half of participants (53.1%, 95% CI: 49.5%–56.7%) started sheltering in place before any state had an official stay-at-home order (California was the first, on March 19), and more than one-third started sheltering in place before any region had an official stay-at-home order (the San Francisco Bay Area was the first, on March 17) ( Table 5 ). Most participants (81.1%, 95% CI: 78.1%–83.8%) last ate at a dine-in setting before any municipality or state had an official stay-at-home order (before March 17).

Table 5

Timing of sheltering in place and eating in dine-in settings (n = 725)

Psychosocial and economic experiences

Perceived impact.

Participants who received financial aid for college were more concerned about COVID-19's economic (chi-square test p -value = .01) and emotional (chi-square test p -value = .01) impacts on their lives than those who did not receive financial aid, but the daily responsibility impacts were relatively similar (chi-square test p -value = .25) ( Appendix Table 5 ). Less than one-quarter of participants (24.2% [95% CI: 20.7%–28.2%] of those receiving financial aid [n = 495] and 21.7% [95% CI: 16.9%–27.5%] of those not receiving financial aid [n = 230]) reported that COVID-19 had changed their postcollege career plans.

Level of stress

More than one-third of the sample agreed (9.8%, 95% CI: 7.8%–12.2%) or somewhat agreed (29.2%, 95% CI: 26.1%–32.7%) with the statement, “I am so anxious about COVID-19 that I can't pay attention to anything else.” We also asked participants about their level of stress regarding COVID-19's health, educational, and economic implications, for themselves, their families, and American society ( Appendix Table 6 ). Participants were much more concerned about COVID-19's health implications for their families and for American society than themselves, but much more concerned about COVID-19's educational implications for themselves than for their families (and slightly more concerned about themselves than American society). They were most concerned about COVID-19's economic implications for American society, then their families, and then themselves.

Most participants (61.7%, 95% CI: 58.1%–65.1%) were employed in February 2020, but only 32.4% (95% CI: 29.1%–35.9%) were currently employed (i.e., in late April 2020). More than half (52.6%, 95% CI: 47.9%–57.2%) of those employed in February 2020 (n = 447) were no longer employed in late April 2020%; 8.3% (95% CI: 5.6%–12.1%) of those who were not employed in February 2020 (n = 278) were employed in late April 2020 (some participants mentioned, for example, taking on gig work as a food delivery driver). Among those who were employed in both February 2020 and late April 2020 (n = 212), 44.8% (95% CI: 38.3%–51.5%) had had their take-home pay decreased owing to the COVID-19 pandemic.

Discrimination

Relatively few (9.2%, 95% CI: 7.3%–11.6%) reported experiencing discrimination related to the coronavirus outbreak. Most of the people who reported experiencing discrimination (n = 67) were Asian or Asian-American (65.7%; 95% CI: 53.7%–75.9%). Of the people who experienced discrimination (n = 67), 62.7% (95% CI: 50.7%–73.3%) suspected it was because of their race/ethnicity, 16.4% (95% CI: 9.4%–27.1%) suspected it was because of their face mask or clothing, and the rest suspected it was because of gender, language, religion, food, or something else.

Perspectives about COVID-19

Participants were very open to continuing current restrictions (i.e., restrictions as of April 25–30, 2020) to reduce pandemic spread. Only 2.3% (95% CI: 1.5%–3.7%) wanted the current restrictions to be lifted immediately. Approximately one-third (36.5%, 95% CI: 33.0%–40.0%) thought the restrictions should be lifted in the next month, 23.6% (95% CI: 20.6%–26.8%) thought the restrictions should be lifted in 1–2 months, 9.9% (95% CI: 8.0%–12.3%) thought the restrictions should be lifted in >2 months, and 27.7% (95% CI: 24.6%–31.1%) thought the restrictions should be lifted only once a vaccine or treatment became available.

Participants had more trust in more local levels of government (i.e., state more than federal, local more than state) for doing everything possible to prevent the spread of COVID-19 and providing trustworthy information about COVID-19 ( Appendix Table 7 ). Nevertheless, for each level of government, a relatively small proportion of participants had complete trust.

Participants also expressed some optimism ( Appendix Figure 1 ). More than three-quarters (78.9%, 95% CI: 75.8%–81.7%) were inspired by seeing how other people are working hard to respond to this crisis, and almost half (49.5%, 95% CI: 45.9%–53.2%) agreed that we are all in this together and feel more connected to the rest of the country. They also noted the power of politicians, with 89.5% (95% CI: 87.1%–91.6%) noticing how consequential political leaders' decisions are for people's everyday life through this pandemic. They also saw the helpful things that young people like them could do for their communities in times like this (73.3% [95% CI: 70.0%–76.3%] agreed).

This is one of the first national studies of full-time college students in the COVID-19 era and provides an important first look at diverse young adult (aged 18–22 years) college students' COVID-19–related experiences and perspectives.

Public health implications

We found that a low proportion of college students with COVID-19 symptoms got tested and that less than half of those with symptoms stayed at home exclusively while symptomatic. Furthermore, students' hygiene behaviors in April 2020 suggest they are protecting themselves (e.g., washing their hands) but could do more to prevent transmission to others (e.g., wearing a mask). Returning to extensive in-person academic instruction will require widespread testing and contact tracing [ 15 ]. However, contact tracing among college students will be challenging and require creative solutions because students participate in a myriad of activities with many different people and participants struggled to recall the number of the people with whom they had close contact (within 6 feet).

Because many participants restricted their behaviors before official stay-at-home orders went into effect, they may continue to do so after stay-at-home orders are lifted per their own risk calculations. For example, more than one-quarter thought that the restrictions in place in late April 2020 (i.e., stay at home/shelter in place almost everywhere in the USA) should be maintained until a vaccine or treatment becomes available. This suggests that some students may not return to campus in person, if a vaccine or treatment is not yet available. In addition, because more than half of participants expressed high stress regarding their family's health, students may opt to stay on campus during some of the shorter breaks, rather than risk bringing COVID-19 home.

College students' behaviors changed rapidly this spring, leading to increased isolation from their established social and academic communities, and all domains of their lives were affected, including economically. We found that many participants were stressed owing to COVID-19. It will be essential to monitor the mental health sequelae of COVID-19.

Social implications

As unemployment skyrockets nationwide, college students are also affected: most of those employed in February 2020 were no longer employed in April 2020, and among those still employed, almost half were earning less. We anticipate that college student unemployment will increase further in the summer and also into the next academic year if fewer campus jobs exist. In addition, college students' educational and career plans may shift. Given the finding that students were largely inspired by others (including young people) who are working hard during the crisis, they may be inspired to join public service efforts for public health that others have recommended creating [ 16 ].

While relatively few participants reported experiencing discrimination related to COVID-19, most of the students who were discriminated against were Asian or Asian-American. As the COVID-19 pandemic continues, and as antiracism movements expand in response to George Floyd's death, it will be important to continue to monitor changes in racist attitudes, perceived discrimination, and who experiences discrimination.

We also note that the 2020 U.S. Census may overcount college students. We found that students who knew that they were counted reported being counted more than once, on average. This is likely because many college students had left campus by Census Day (April 1, 2020), but colleges still sent counts of students in dorms earlier that spring to the Census [ 17 ]. However, undercounts are also plausible, particularly for less privileged college students who may have been transient as they were determining a noncollege residence. This must be examined further to inform how 2020 U.S. Census data are used for resource allocation.

Limitations

We also note important limitations of this study. First, our survey population was more advantaged than all full-time college students. This may be because we used Instagram to recruit participants. It is possible that some of the most disadvantaged college students had very limited access to internet for their schoolwork and could not afford to use any of their internet bandwidth toward using Instagram or participating in our survey. Second, we restricted our sample to only full-time college students. Part-time college students may be even more negatively affected by COVID-19 because they are more likely to have had more COVID-19–related disruptions that increased financial and familial responsibilities; we encourage future researchers to specifically study this population. Third, owing to the breadth of topics covered, we did not measure all topics deeply. For example, we encourage future researchers to more comprehensively explore college students' employment patterns (including why students lost jobs), into summer 2020 (given emerging anecdotal reports of summer employment opportunities being lost) and the subsequent academic year.

In conclusion, the public health, economic, and educational implications of COVID-19 are continuing to unfold, in a rapidly changing world. COVID-19's impacts are occurring inequitably; we encourage future researchers to look at these outcomes by social factors. We encourage government leaders and leaders of institutions of higher education to use these findings to inform their planning for supporting college students in the COVID-19 era.

Conflicts of interest: The authors have no conflicts of interest to disclose.

Disclaimer: Study funders had no role in study design; data collection, interpretation, or analysis; writing the report; or the decision to submit this manuscript for publication. A.K.C. and L.T.H. wrote the first draft of the manuscript; no funding was provided to the authors or anyone else to produce the manuscript.

Supplementary data related to this article can be found at https://doi.org/10.1016/j.jadohealth.2020.06.009 .

Funding Sources

This research was supported by the University of San Francisco Jesuit Foundation, Fordham University's Office of Research, and University of San Francisco Faculty Development Funds. We would like to thank all of the students who participated in this study during an especially chaotic time. Finally, we thank Jane Hoffman Till for providing instrumental support to Hoyt's family so she could work on this study while daycare centers were closed owing to COVID-19.

Supplementary Data