• 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%.


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.


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.

figure 1

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 ).

figure 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%).

figure 3

A meta-analysis of the prevalence of fever

figure 4

A meta-analysis of the prevalence of cough

figure 5

A meta-analysis of the prevalence of dyspnea

figure 6

A meta-analysis of the prevalence of fatigue or myalgia

figure 7

A meta-analysis of the prevalence of headache

figure 8

A meta-analysis of the prevalence of gastrointestinal disorders

figure 9

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

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Israel Júnior Borges do Nascimento & Milena Soriano Marcolino

Medical College of Wisconsin, Milwaukee, WI, USA

Israel Júnior Borges do Nascimento

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

Dónal P. O’Mathúna

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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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An Introduction to COVID-19

Simon james fong.

4 Department of Computer and Information Science, University of Macau, Taipa, Macau, China

Nilanjan Dey

5 Department of Information Technology, Techno International New Town, Kolkata, West Bengal India

Jyotismita Chaki

6 School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu India

A novel coronavirus (CoV) named ‘2019-nCoV’ or ‘2019 novel coronavirus’ or ‘COVID-19’ by the World Health Organization (WHO) is in charge of the current outbreak of pneumonia that began at the beginning of December 2019 near in Wuhan City, Hubei Province, China [1–4]. COVID-19 is a pathogenic virus. From the phylogenetic analysis carried out with obtainable full genome sequences, bats occur to be the COVID-19 virus reservoir, but the intermediate host(s) has not been detected till now.

A Brief History of the Coronavirus Outbreak

A novel coronavirus (CoV) named ‘2019-nCoV’ or ‘2019 novel coronavirus’ or ‘COVID-19’ by the World Health Organization (WHO) is in charge of the current outbreak of pneumonia that began at the beginning of December 2019 near in Wuhan City, Hubei Province, China [ 1 – 4 ]. COVID-19 is a pathogenic virus. From the phylogenetic analysis carried out with obtainable full genome sequences, bats occur to be the COVID-19 virus reservoir, but the intermediate host(s) has not been detected till now. Though three major areas of work already are ongoing in China to advise our awareness of the pathogenic origin of the outbreak. These include early inquiries of cases with symptoms occurring near in Wuhan during December 2019, ecological sampling from the Huanan Wholesale Seafood Market as well as other area markets, and the collection of detailed reports of the point of origin and type of wildlife species marketed on the Huanan market and the destination of those animals after the market has been closed [ 5 – 8 ].

Coronaviruses mostly cause gastrointestinal and respiratory tract infections and are inherently categorized into four major types: Gammacoronavirus, Deltacoronavirus, Betacoronavirus and Alphacoronavirus [ 9 – 11 ]. The first two types mainly infect birds, while the last two mostly infect mammals. Six types of human CoVs have been formally recognized. These comprise HCoVHKU1, HCoV-OC43, Middle East Respiratory Syndrome coronavirus (MERS-CoV), Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) which is the type of the Betacoronavirus, HCoV229E and HCoV-NL63, which are the member of the Alphacoronavirus. Coronaviruses did not draw global concern until the 2003 SARS pandemic [ 12 – 14 ], preceded by the 2012 MERS [ 15 – 17 ] and most recently by the COVID-19 outbreaks. SARS-CoV and MERS-CoV are known to be extremely pathogenic and spread from bats to palm civets or dromedary camels and eventually to humans.

COVID-19 is spread by dust particles and fomites while close unsafe touch between the infector and the infected individual. Airborne distribution has not been recorded for COVID-19 and is not known to be a significant transmission engine based on empirical evidence; although it can be imagined if such aerosol-generating practices are carried out in medical facilities. Faecal spreading has been seen in certain patients, and the active virus has been reported in a small number of clinical studies [ 18 – 20 ]. Furthermore, the faecal-oral route does not seem to be a COVID-19 transmission engine; its function and relevance for COVID-19 need to be identified.

For about 18,738,58 laboratory-confirmed cases recorded as of 2nd week of April 2020, the maximum number of cases (77.8%) was between 30 and 69 years of age. Among the recorded cases, 21.6% are farmers or employees by profession, 51.1% are male and 77.0% are Hubei.

However, there are already many concerns regarding the latest coronavirus. Although it seems to be transferred to humans by animals, it is important to recognize individual animals and other sources, the path of transmission, the incubation cycle, and the features of the susceptible community and the survival rate. Nonetheless, very little clinical knowledge on COVID-19 disease is currently accessible and details on age span, the animal origin of the virus, incubation time, outbreak curve, viral spectroscopy, dissemination pathogenesis, autopsy observations, and any clinical responses to antivirals are lacking among the serious cases.

How Different and Deadly COVID-19 is Compared to Plagues in History

COVID-19 has reached to more than 150 nations, including China, and has caused WHO to call the disease a worldwide pandemic. By the time of 2nd week of April 2020, this COVID-19 cases exceeded 18,738,58, although more than 1,160,45 deaths were recorded worldwide and United States of America became the global epicentre of coronavirus. More than one-third of the COVID-19 instances are outside of China. Past pandemics that have existed in the past decade or so, like bird flu, swine flu, and SARS, it is hard to find out the comparison between those pandemics and this coronavirus. Following is a guide to compare coronavirus with such diseases and recent pandemics that have reformed the world community.

Coronavirus Versus Seasonal Influenza

Influenza, or seasonal flu, occurs globally every year–usually between December and February. It is impossible to determine the number of reports per year because it is not a reportable infection (so no need to be recorded to municipality), so often patients with minor symptoms do not go to a physician. Recent figures placed the Rate of Case Fatality at 0.1% [ 21 – 23 ].

There are approximately 3–5 million reports of serious influenza a year, and about 250,000–500,000 deaths globally. In most developed nations, the majority of deaths arise in persons over 65 years of age. Moreover, it is unsafe for pregnant mothers, children under 59 months of age and individuals with serious illnesses.

The annual vaccination eliminates infection and severe risks in most developing countries but is nevertheless a recognized yet uncomfortable aspect of the season.

In contrast to the seasonal influenza, coronavirus is not so common, has led to fewer cases till now, has a higher rate of case fatality and has no antidote.

Coronavirus Versus Bird Flu (H5N1 and H7N9)

Several cases of bird flu have existed over the years, with the most severe in 2013 and 2016. This is usually from two separate strains—H5N1 and H7N9 [ 24 – 26 ].

The H7N9 outbreak in 2016 accounted for one-third of all confirmed human cases but remained confined relative to both coronavirus and other pandemics/outbreak cases. After the first outbreak, about 1,233 laboratory-confirmed reports of bird flu have occurred. The disease has a Rate of Case Fatality of 20–40%.

Although the percentage is very high, the blowout from individual to individual is restricted, which, in effect, has minimized the number of related deaths. It is also impossible to monitor as birds do not necessarily expire from sickness.

In contrast to the bird flu, coronavirus becomes more common, travels more quickly through human to human interaction, has an inferior cardiothoracic ratio, resulting in further total fatalities and spread from the initial source.

Coronavirus Versus Ebola Epidemic

The Ebola epidemic of 2013 was primarily centred in 10 nations, including Sierra Leone, Guinea and Liberia have the greatest effects, but the extremely high Case Fatality Rate of 40% has created this as a significant problem for health professionals nationwide [ 27 – 29 ].

Around 2013 and 2016, there were about 28,646 suspicious incidents and about 11,323 fatalities, although these are expected to be overlooked. Those who survived from the original epidemic may still become sick months or even years later, because the infection may stay inactive for prolonged periods. Thankfully, a vaccination was launched in December 2016 and is perceived to be effective.

In contrast to the Ebola, coronavirus is more common globally, has caused in fewer fatalities, has a lesser case fatality rate, has no reported problems during treatment and after recovery, does not have an appropriate vaccination.

Coronavirus Versus Camel Flu (MERS)

Camel flu is a misnomer–though camels have MERS antibodies and may have been included in the transmission of the disease; it was originally transmitted to humans through bats [ 30 – 32 ]. Like Ebola, it infected only a limited number of nations, i.e. about 27, but about 858 fatalities from about 2,494 laboratory-confirmed reports suggested that it was a significant threat if no steps were taken in place to control it.

In contrast to the camel flu, coronavirus is more common globally, has occurred more fatalities, has a lesser case fatality rate, and spreads more easily among humans.

Coronavirus Versus Swine Flu (H1N1)

Swine flu is the same form of influenza that wiped 1.7% of the world population in 1918. This was deemed a pandemic again in June 2009 an approximately-21% of the global population infected by this [ 33 – 35 ].

Thankfully, the case fatality rate is substantially lower than in the last pandemic, with 0.1%–0.5% of events ending in death. About 18,500 of these fatalities have been laboratory-confirmed, but statistics range as high as 151,700–575,400 worldwide. 50–80% of severe occurrences have been reported in individuals with chronic illnesses like asthma, obesity, cardiovascular diseases and diabetes.

In contrast to the swine flu, coronavirus is not so common, has caused fewer fatalities, has more case fatality rate, has a longer growth time and less impact on young people.

Coronavirus Versus Severe Acute Respiratory Syndrome (SARS)

SARS was discovered in 2003 as it spread from bats to humans resulted in about 774 fatalities. By May there were eventually about 8,100 reports across 17 countries, with a 15% case fatality rate. The number is estimated to be closer to 9.6% as confirmed cases are counted, with 0.9% cardiothoracic ratio for people aged 20–29, rising to 28% for people aged 70–79. Similar to coronavirus, SARS had bad results for males than females in all age categories [ 36 – 38 ].

Coronavirus is more common relative to SARS, which ended in more overall fatalities, lower case fatality rate, the even higher case fatality rate in older ages, and poorer results for males.

Coronavirus Versus Hong Kong Flu (H3N2)

The Hong Kong flu pandemic erupted on 13 July 1968, with 1–4 million deaths globally by 1969. It was one of the greatest flu pandemics of the twentieth century, but thankfully the case fatality rate was smaller than the epidemic of 1918, resulting in fewer fatalities overall. That may have been attributed to the fact that citizens had generated immunity owing to a previous epidemic in 1957 and to better medical treatment [ 39 ].

In contrast to the Hong Kong flu, coronavirus is not so common, has caused in fewer fatalities and has a higher case fatality rate.

Coronavirus Versus Spanish Flu (H1N1)

The 1918 Spanish flu pandemic was one of the greatest occurrences of recorded history. During the first year of the pandemic, lifespan in the US dropped by 12 years, with more civilians killed than HIV/AIDS in 24 h [ 40 – 42 ].

Regardless of the name, the epidemic did not necessarily arise in Spain; wartime censors in Germany, the United States, the United Kingdom and France blocked news of the disease, but Spain did not, creating the misleading perception that more cases and fatalities had occurred relative to its neighbours

This strain of H1N1 eventually affected more than 500 million men, or 27% of the world’s population at the moment, and had deaths of between 40 and 50 million. At the end of 1920, 1.7% of the world’s people had expired of this illness, including an exceptionally high death rate for young adults aged between 20 and 40 years.

In contrast to the Spanish flu, coronavirus is not so common, has caused in fewer fatalities, has a higher case fatality rate, is more harmful to older ages and is less risky for individuals aged 20–40 years.

Coronavirus Versus Common Cold (Typically Rhinovirus)

Common cold is the most common illness impacting people—Typically, a person suffers from 2–3 colds each year and the average kid will catch 6–8 during the similar time span. Although there are more than 200 cold-associated virus types, infections are uncommon and fatalities are very rare and typically arise mainly in extremely old, extremely young or immunosuppressed cases [ 43 , 44 ].

In contrast to the common cold, coronavirus is not so prevalent, causes more fatalities, has more case fatality rate, is less infectious and is less likely to impact small children.

Reviews of Online Portals and Social Media for Epidemic Information Dissemination

As COVID-19 started to propagate across the globe, the outbreak contributed to a significant change in the broad technology platforms. Where they once declined to engage in the affairs of their systems, except though the possible danger to public safety became obvious, the advent of a novel coronavirus placed them in a different interventionist way of thought. Big tech firms and social media are taking concrete steps to guide users to relevant, credible details on the virus [ 45 – 48 ]. And some of the measures they’re doing proactively. Below are a few of them.

Facebook started adding a box in the news feed that led users to the Centers for Disease Control website regarding COVID-19. It reflects a significant departure from the company’s normal strategy of placing items in the News Feed. The purpose of the update, after all, is personalization—Facebook tries to give the posts you’re going to care about, whether it is because you’re connected with a person or like a post. In the virus package, Facebook has placed a remarkable algorithmic thumb on the scale, potentially pushing millions of people to accurate, authenticated knowledge from a reputable source.

Similar initiatives have been adopted by Twitter. Searching for COVID-19 will carry you to a page highlighting the latest reports from public health groups and credible national news outlets. The search also allows for common misspellings. Twitter has stated that although Russian-style initiatives to cause discontent by large-scale intelligence operations have not yet been observed, a zero-tolerance approach to network exploitation and all other attempts to exploit their service at this crucial juncture will be expected. The problem has the attention of the organization. It also offers promotional support to public service agencies and other non-profit groups.

Google has made a step in making it better for those who choose to operate or research from home, offering specialized streaming services to all paying G Suite customers. Google also confirmed that free access to ‘advanced’ Hangouts Meet apps will be rolled out to both G Suite and G Suite for Education clients worldwide through 1st July. It ensures that companies can hold meetings of up to 250 people, broadcast live to up to about 100,000 users within a single network, and archive and export meetings to Google Drive. Usually, Google pays an additional $13 per person per month for these services in comparison to G Suite’s ‘enterprise’ membership, which adds up to a total of about $25 per client each month.

Microsoft took a similar move, introducing the software ‘Chat Device’ to help public health and protection in the coronavirus epidemic, which enables collaborative collaboration via video and text messaging. There’s an aspect of self-interest in this. Tech firms are offering out their goods free of charge during periods of emergency for the same purpose as newspapers are reducing their paywalls: it’s nice to draw more paying consumers.

Pinterest, which has introduced much of the anti-misinformation strategies that Facebook and Twitter are already embracing, is now restricting the search results for ‘coronavirus’, ‘COVID-19’ and similar words for ‘internationally recognized health organizations’.

Google-owned YouTube, traditionally the most conspiratorial website, has recently introduced a connection to the World Health Organization virus epidemic page to the top of the search results. In the early days of the epidemic, BuzzFeed found famous coronavirus conspiratorial videos on YouTube—especially in India, where one ‘explain’ with a false interpretation of the sources of the disease racketeered 13 million views before YouTube deleted it. Yet in the United States, conspiratorial posts regarding the illness have failed to gain only 1 million views.

That’s not to suggest that misinformation doesn’t propagate on digital platforms—just as it travels through the broader Internet, even though interaction with friends and relatives. When there’s a site that appears to be under-performing in the global epidemic, it’s Facebook-owned WhatsApp, where the Washington Post reported ‘a torrent of disinformation’ in places like Nigeria, Indonesia, Peru, Pakistan and Ireland. Given the encrypted existence of the app, it is difficult to measure the severity of the problem. Misinformation is also spread in WhatsApp communities, where participation is restricted to about 250 individuals. Knowledge of one category may be readily exchanged with another; however, there is a considerable amount of complexity of rotating several groups to peddle affected healing remedies or propagate false rumours.

Preventative Measures and Policies Enforced by the World Health Organization (WHO) and Different Countries

Coronavirus is already an ongoing epidemic, so it is necessary to take precautions to minimize both the risk of being sick and the transmission of the disease.

WHO Advice [ 49 ]

  • Wash hands regularly with alcohol-based hand wash or soap and water.
  • Preserve contact space (at least 1 m/3 feet between you and someone who sneezes or coughs).
  • Don’t touch your nose, head and ears.
  • Cover your nose and mouth as you sneeze or cough, preferably with your bent elbow or tissue.
  • Try to find early medical attention if you have fatigue, cough and trouble breathing.
  • Take preventive precautions if you are in or have recently go to places where coronavirus spreads.

The first person believed to have become sick because of the latest virus was near in Wuhan on 1 December 2019. A formal warning of the epidemic was released on 31 December. The World Health Organization was informed of the epidemic on the same day. Through 7 January, the Chinese Government addressed the avoidance and regulation of COVID-19. A curfew was declared on 23 January to prohibit flying in and out of Wuhan. Private usage of cars has been banned in the region. Chinese New Year (25 January) festivities have been cancelled in many locations [ 50 ].

On 26 January, the Communist Party and the Government adopted more steps to contain the COVID-19 epidemic, including safety warnings for travellers and improvements to national holidays. The leading party has agreed to prolong the Spring Festival holiday to control the outbreak. Universities and schools across the world have already been locked down. Many steps have been taken by the Hong Kong and Macau governments, in particular concerning schools and colleges. Remote job initiatives have been placed in effect in many regions of China. Several immigration limits have been enforced.

Certain counties and cities outside Hubei also implemented travel limits. Public transit has been changed and museums in China have been partially removed. Some experts challenged the quality of the number of cases announced by the Chinese Government, which constantly modified the way coronavirus cases were recorded.

Italy, a member state of the European Union and a popular tourist attraction, entered the list of coronavirus-affected nations on 30 January, when two positive cases in COVID-19 were identified among Chinese tourists. Italy has the largest number of coronavirus infections both in Europe and outside of China [ 51 ].

Infections, originally limited to northern Italy, gradually spread to all other areas. Many other nations in Asia, Europe and the Americas have tracked their local cases to Italy. Several Italian travellers were even infected with coronavirus-positive in foreign nations.

Late in Italy, the most impacted coronavirus cities and counties are Lombardia, accompanied by Veneto, Emilia-Romagna, Marche and Piedmonte. Milan, the second most populated city in Italy, is situated in Lombardy. Other regions in Italy with coronavirus comprised Campania, Toscana, Liguria, Lazio, Sicilia, Friuli Venezia Giulia, Umbria, Puglia, Trento, Abruzzo, Calabria, Molise, Valle d’Aosta, Sardegna, Bolzano and Basilicata.

Italy ranks 19th of the top 30 nations getting high-risk coronavirus airline passengers in China, as per WorldPop’s provisional study of the spread of COVID-19.

The Italian State has taken steps like the inspection and termination of large cultural activities during the early days of the coronavirus epidemic and has gradually declared the closing of educational establishments and airport hygiene/disinfection initiatives.

The Italian National Institute of Health suggested social distancing and agreed that the broader community of the country’s elderly is a problem. In the meantime, several other nations, including the US, have recommended that travel to Italy should be avoided temporarily, unless necessary.

The Italian government has declared the closing (quarantine) of the impacted areas in the northern region of the nation so as not to spread to the rest of the world. Italy has declared the immediate suspension of all to-and-fro air travel with China following coronavirus discovery by a Chinese tourist to Italy. Italian airlines, like Ryan Air, have begun introducing protective steps and have begun calling for the declaration forms to be submitted by passengers flying to Poland, Slovakia and Lithuania.

The Italian government first declined to permit fans to compete in sporting activities until early April to prevent the potential transmission of coronavirus. The step ensured players of health and stopped event cancellations because of coronavirus fears. Two days of the declaration, the government cancelled all athletic activities owing to the emergence of the outbreak asking for an emergency. Sports activities in Veneto, Lombardy and Emilia-Romagna, which recorded coronavirus-positive infections, were confirmed to be temporarily suspended. Schools and colleges in Italy have also been forced to shut down.

Iran announced the first recorded cases of SARS-CoV-2 infection on 19 February when, as per the Medical Education and Ministry of Health, two persons died later that day. The Ministry of Islamic Culture and Guidance has declared the cancellation of all concerts and other cultural activities for one week. The Medical Education and Ministry of Health has also declared the closing of universities, higher education colleges and schools in many cities and regions. The Department of Sports and Culture has taken action to suspend athletic activities, including football matches [ 52 ].

On 2 March 2020, the government revealed plans to train about 300,000 troops and volunteers to fight the outbreak of the epidemic, and also send robots and water cannons to clean the cities. The State also developed an initiative and a webpage to counter the epidemic. On 9 March 2020, nearly 70,000 inmates were immediately released from jail owing to the epidemic, presumably to prevent the further dissemination of the disease inside jails. The Revolutionary Guards declared a campaign on 13 March 2020 to clear highways, stores and public areas in Iran. President Hassan Rouhani stated on 26 February 2020 that there were no arrangements to quarantine areas impacted by the epidemic and only persons should be quarantined. The temples of Shia in Qom stayed open to pilgrims.

South Korea

On 20 January, South Korea announced its first occurrence. There was a large rise in cases on 20 February, possibly due to the meeting in Daegu of a progressive faith community recognized as the Shincheonji Church of Christ. Any citizens believed that the hospital was propagating the disease. As of 22 February, 1,261 of the 9,336 members of the church registered symptoms. A petition was distributed calling for the abolition of the church. More than 2,000 verified cases were registered on 28 February, increasing to 3,150 on 29 February [ 53 ].

Several educational establishments have been partially closing down, including hundreds of kindergartens in Daegu and many primary schools in Seoul. As of 18 February, several South Korean colleges had confirmed intentions to delay the launch of the spring semester. That included 155 institutions deciding to postpone the start of the semester by two weeks until 16 March, and 22 institutions deciding to delay the start of the semester by one week until 9 March. Also, on 23 February 2020, all primary schools, kindergartens, middle schools and secondary schools were declared to postpone the start of the semester from 2 March to 9 March.

South Korea’s economy is expected to expand by 1.9%, down from 2.1%. The State has given 136.7 billion won funding to local councils. The State has also coordinated the purchase of masks and other sanitary supplies. Entertainment Company SM Entertainment is confirmed to have contributed five hundred million won in attempts to fight the disease.

In the kpop industry, the widespread dissemination of coronavirus within South Korea has contributed to the cancellation or postponement of concerts and other programmes for kpop activities inside and outside South Korea. For instance, circumstances such as the cancellation of the remaining Asian dates and the European leg for the Seventeen’s Ode To You Tour on 9 February 2020 and the cancellation of all Seoul dates for the BTS Soul Tour Map. As of 15 March, a maximum of 136 countries and regions provided entry restrictions and/or expired visas for passengers from South Korea.

The overall reported cases of coronavirus rose significantly in France on 12 March. The areas with reported cases include Paris, Amiens, Bordeaux and Eastern Haute-Savoie. The first coronaviral death happened in France on 15 February, marking it the first death in Europe. The second death of a 60-year-old French national in Paris was announced on 26 February [ 54 ].

On February 28, fashion designer Agnès B. (not to be mistaken with Agnès Buzyn) cancelled fashion shows at the Paris Fashion Week, expected to continue until 3 March. On a subsequent day, the Paris half-marathon, planned for Sunday 1 March with 44,000 entrants, was postponed as one of a series of steps declared by Health Minister Olivier Véran.

On 13 March, the Ligue de Football Professional disbanded Ligue 1 and Ligue 2 (France’s tier two professional divisions) permanently due to safety threats.

Germany has a popular Regional Pandemic Strategy detailing the roles and activities of the health care system participants in the case of a significant outbreak. Epidemic surveillance is carried out by the federal government, like the Robert Koch Center, and by the German governments. The German States have their preparations for an outbreak. The regional strategy for the treatment of the current coronavirus epidemic was expanded by March 2020. Four primary goals are contained in this plan: (1) to minimize mortality and morbidity; (2) to guarantee the safety of sick persons; (3) to protect vital health services and (4) to offer concise and reliable reports to decision-makers, the media and the public [ 55 ].

The programme has three phases that may potentially overlap: (1) isolation (situation of individual cases and clusters), (2) safety (situation of further dissemination of pathogens and suspected causes of infection), (3) prevention (situation of widespread infection). So far, Germany has not set up border controls or common health condition tests at airports. Instead, while at the isolation stage-health officials are concentrating on recognizing contact individuals that are subject to specific quarantine and are tracked and checked. Specific quarantine is regulated by municipal health authorities. By doing so, the officials are seeking to hold the chains of infection small, contributing to decreased clusters. At the safety stage, the policy should shift to prevent susceptible individuals from being harmed by direct action. By the end of the day, the prevention process should aim to prevent cycles of acute treatment to retain emergency facilities.

United States

The very first case of coronavirus in the United States was identified in Washington on 21 January 2020 by an individual who flew to Wuhan and returned to the United States. The second case was recorded in Illinois by another individual who had travelled to Wuhan. Some of the regions with reported novel coronavirus infections in the US are California, Arizona, Connecticut, Illinois, Texas, Wisconsin and Washington [ 56 ].

As the epidemic increased, requests for domestic air travel decreased dramatically. By 4 March, U.S. carriers, like United Airlines and JetBlue Airways, started growing their domestic flight schedules, providing generous unpaid leave to workers and suspending recruits.

A significant number of universities and colleges cancelled classes and reopened dormitories in response to the epidemic, like Cornell University, Harvard University and the University of South Carolina.

On 3 March 2020, the Federal Reserve reduced its goal interest rate from 1.75% to 1.25%, the biggest emergency rate cut following the 2008 global financial crash, in combat the effect of the recession on the American economy. In February 2020, US businesses, including Apple Inc. and Microsoft, started to reduce sales projections due to supply chain delays in China caused by the COVID-19.

The pandemic, together with the subsequent financial market collapse, also contributed to greater criticism of the crisis in the United States. Researchers disagree about when a recession is likely to take effect, with others suggesting that it is not unavoidable, while some claim that the world might already be in recession. On 3 March, Federal Reserve Chairman Jerome Powell reported a 0.5% (50 basis point) interest rate cut from the coronavirus in the context of the evolving threats to economic growth.

When ‘social distance’ penetrated the national lexicon, disaster response officials promoted the cancellation of broad events to slow down the risk of infection. Technical conferences like E3 2020, Apple Inc.’s Worldwide Developers Conference (WWDC), Google I/O, Facebook F8, and Cloud Next and Microsoft’s MVP Conference have been either having replaced or cancelled in-person events with internet streaming events.

On February 29, the American Physical Society postponed its annual March gathering, planned for March 2–6 in Denver, Colorado, even though most of the more than 11,000 physicist attendees already had arrived and engaged in the pre-conference day activities. On March 6, the annual South to Southwest (SXSW) seminar and festival planned to take place from March 13–22 in Austin, Texas, was postponed after the city council announced a local disaster and forced conferences to be shut down for the first time in 34 years.

Four of North America’s major professional sports leagues—the National Hockey League (NHL), National Basketball Association (NBA), Major League Soccer (MLS) and Major League Baseball (MLB) —jointly declared on March 9 that they would all limit the media access to player accommodations (such as locker rooms) to control probable exposure.

Emergency Funding to Fight the COVID-19

COVID-19 pandemic has become a common international concern. Different countries are donating funds to fight against it [ 57 – 60 ]. Some of them are mentioned here.

China has allocated about 110.48 billion yuan ($15.93 billion) in coronavirus-related funding.

Foreign Minister Mohammad Javad Zarif said that Iran has requested the International Monetary Fund (IMF) of about $5 billion in emergency funding to help to tackle the coronavirus epidemic that has struck the Islamic Republic hard.

President Donald Trump approved the Emergency Supplementary Budget Bill to support the US response to a novel coronavirus epidemic. The budget plan would include about $8.3 billion in discretionary funding to local health authorities to promote vaccine research for production. Trump originally requested just about $2 billion to combat the epidemic, but Congress quadrupled the number in its version of the bill. Mr. Trump formally announced a national emergency that he claimed it will give states and territories access to up to about $50 billion in federal funding to tackle the spread of the coronavirus outbreak.

California politicians approved a plan to donate about $1 billion on the state’s emergency medical responses as it readies hospitals to fight an expected attack of patients because of the COVID-19 pandemic. The plans, drawn up rapidly in reaction to the dramatic rise in reported cases of the virus, would include the requisite funds to establish two new hospitals in California, with the assumption that the state may not have the resources to take care of the rise in patients. The bill calls for an immediate response of about $500 million from the State General Fund, with an additional about $500 million possible if requested.

India committed about $10 million to the COVID-19 Emergency Fund and said it was setting up a rapid response team of physicians for the South Asian Association for Regional Cooperation (Saarc) countries.

South Korea unveiled an economic stimulus package of about 11.7 trillion won ($9.8 billion) to soften the effects of the biggest coronavirus epidemic outside China as attempts to curb the disease exacerbate supply shortages and drain demand. Of the 11,7 trillion won expected, about 3.2 trillion won would cover up the budget shortfall, while an additional fiscal infusion of about 8.5 trillion won. An estimated 10.3 trillion won in government bonds will be sold this year to fund the extra expenditure. About 2.3 trillion won will be distributed to medical establishments and would support quarantine operations, with another 3.0 trillion won heading to small and medium-sized companies unable to pay salaries to their employees and child care supports.

The Swedish Parliament announced a set of initiatives costing more than 300 billion Swedish crowns ($30.94 billion) to help the economy in the view of the coronavirus pandemic. The plan contained steps like the central government paying the entire expense of the company’s sick leave during April and May, and also the high cost of compulsory redundancies owing to the crisis.

In consideration of the developing scenario, an updating of this strategy is planned to take place before the end of March and will recognize considerably greater funding demands for the country response, R&D and WHO itself.

Artificial Intelligence, Data Science and Technological Solutions Against COVID-19

These days, Artificial Intelligence (AI) takes a major role in health care. Throughout a worldwide pandemic such as the COVID-19, technology, artificial intelligence and data analytics have been crucial in helping communities cope successfully with the epidemic [ 61 – 65 ]. Through the aid of data mining and analytical modelling, medical practitioners are willing to learn more about several diseases.

Public Health Surveillance

The biggest risk of coronavirus is the level of spreading. That’s why policymakers are introducing steps like quarantines around the world because they can’t adequately monitor local outbreaks. One of the simplest measures to identify ill patients through the study of CCTV images that are still around us and to locate and separate individuals that have serious signs of the disease and who have touched and disinfected the related surfaces. Smartphone applications are often used to keep a watch on people’s activities and to assess whether or not they have come in touch with an infected human.

Remote Biosignal Measurement

Many of the signs such as temperature or heartbeat are very essential to overlook and rely entirely on the visual image that may be misleading. However, of course, we can’t prevent someone from checking their blood pressure, heart or temperature. Also, several advances in computer vision can predict pulse and blood pressure based on facial skin examination. Besides, there are several advances in computer vision that can predict pulse and blood pressure based on facial skin examination.

Access to public records has contributed to the development of dashboards that constantly track the virus. Several companies are designing large data dashboards. Face recognition and infrared temperature monitoring technologies have been mounted in all major cities. Chinese AI companies including Hanwang Technology and SenseTime have reported having established a special facial recognition system that can correctly identify people even though they are covered.

IoT and Wearables

Measurements like pulse are much more natural and easier to obtain from tracking gadgets like activity trackers and smartwatches that nearly everybody has already. Some work suggests that the study of cardiac activity and its variations from the standard will reveal early signs of influenza and, in this case, coronavirus.

Chatbots and Communication

Apart from public screening, people’s knowledge and self-assessment may also be used to track their health. If you can check your temperature and pulse every day and monitor your coughs time-to-time, you can even submit that to your record. If the symptoms are too serious, either an algorithm or a doctor remotely may prescribe a person to stay home, take several other preventive measures, or recommend a visit from the doctor.

Al Jazeera announced that China Mobile had sent text messages to state media departments, telling them about the citizens who had been affected. The communications contained all the specifics of the person’s travel history.

Tencent runs WeChat, and via it, citizens can use free online health consultation services. Chatbots have already become important connectivity platforms for transport and tourism service providers to keep passengers up-to-date with the current transport protocols and disturbances.

Social Media and Open Data

There are several people who post their health diary with total strangers via Facebook or Twitter. Such data becomes helpful for more general research about how far the epidemic has progressed. For consumer knowledge, we may even evaluate the social network group to attempt to predict what specific networks are at risk of being viral.

Canadian company BlueDot analyses far more than just social network data: for instance, global activities of more than four billion passengers on international flights per year; animal, human and insect population data; satellite environment data and relevant knowledge from health professionals and journalists, across 100,000 news posts per day covering 65 languages. This strategy was so successful that the corporation was able to alert clients about coronavirus until the World Health Organization and the Centers for Disease Control and Prevention notified the public.

Automated Diagnostics

COVID-19 has brought up another healthcare issue today: it will not scale when the number of patients increases exponentially (actually stressed doctors are always doing worse) and the rate of false-negative diagnosis remains very high. Machine learning therapies don’t get bored and scale simply by growing computing forces.

Baidu, the Chinese Internet company, has made the Lineatrfold algorithm accessible to the outbreak-fighting teams, according to the MIT Technology Review. Unlike HIV, Ebola and Influenza, COVID-19 has just one strand of RNA and it can mutate easily. The algorithm is also simpler than other algorithms that help to determine the nature of the virus. Baidu has also developed software to efficiently track large populations. It has also developed an Ai-powered infrared device that can detect a difference in the body temperature of a human. This is currently being used in Beijing’s Qinghe Railway Station to classify possibly contaminated travellers where up to 200 individuals may be checked in one minute without affecting traffic movement, reports the MIT Review.

Singapore-based Veredus Laboratories, a supplier of revolutionary molecular diagnostic tools, has currently announced the launch of the VereCoV detector package, a compact Lab-on-Chip device able to detect MERS-CoV, SARS-CoV and COVID-19, i.e. Wuhan Coronavirus, in a single study.

The VereCoV identification package is focused on VereChip technology, a Lab-on-Chip device that incorporates two important molecular biological systems, Polymerase Chain Reaction (PCR) and a microarray, which will be able to classify and distinguish within 2 h MERS-CoV, SARS-CoV and COVID-19 with high precision and responsiveness.

This is not just the medical activities of healthcare facilities that are being charged, but also the corporate and financial departments when they cope with the increase in patients. Ant Financials’ blockchain technology helps speed-up the collection of reports and decreases the number of face-to-face encounters with patients and medical personnel.

Companies like the Israeli company Sonovia are aiming to provide healthcare systems and others with face masks manufactured from their anti-pathogenic, anti-bacterial cloth that depends on metal-oxide nanoparticles.

Drug Development Research

Aside from identifying and stopping the transmission of pathogens, the need to develop vaccinations on a scale is also needed. One of the crucial things to make that possible is to consider the origin and essence of the virus. Google’s DeepMind, with their expertise in protein folding research, has rendered a jump in identifying the protein structure of the virus and making it open-source.

BenevolentAI uses AI technologies to develop medicines that will combat the most dangerous diseases in the world and is also working to promote attempts to cure coronavirus, the first time the organization has based its product on infectious diseases. Within weeks of the epidemic, it used its analytical capability to recommend new medicines that might be beneficial.

Robots are not vulnerable to the infection, and they are used to conduct other activities, like cooking meals in hospitals, doubling up as waiters in hotels, spraying disinfectants and washing, selling rice and hand sanitizers, robots are on the front lines all over to deter coronavirus spread. Robots also conduct diagnostics and thermal imaging in several hospitals. Shenzhen-based firm Multicopter uses robotics to move surgical samples. UVD robots from Blue Ocean Robotics use ultraviolet light to destroy viruses and bacteria separately. In China, Pudu Technology has introduced its robots, which are usually used in the cooking industry, to more than 40 hospitals throughout the region. According to the Reuters article, a tiny robot named Little Peanut is distributing food to passengers who have been on a flight from Singapore to Hangzhou, China, and are presently being quarantined in a hotel.

Colour Coding

Using its advanced and vast public service monitoring network, the Chinese government has collaborated with software companies Alibaba and Tencent to establish a colour-coded health ranking scheme that monitors millions of citizens every day. The mobile device was first introduced in Hangzhou with the cooperation of Alibaba. This applies three colours to people—red, green or yellow—based on their transportation and medical records. Tencent also developed related applications in the manufacturing centre of Shenzhen.

The decision of whether an individual will be quarantined or permitted in public spaces is dependent on the colour code. Citizens will sign into the system using pay wallet systems such as Alibaba’s Alipay and Ant’s wallet. Just those citizens who have been issued a green colour code will be permitted to use the QR code in public spaces at metro stations, workplaces, and other public areas. Checkpoints are in most public areas where the body temperature and the code of individual are tested. This programme is being used by more than 200 Chinese communities and will eventually be expanded nationwide.

In some of the seriously infected regions where people remain at risk of contracting the infection, drones are used to rescue. One of the easiest and quickest ways to bring emergency supplies where they need to go while on an epidemic of disease is by drone transportation. Drones carry all surgical instruments and patient samples. This saves time, improves the pace of distribution and reduces the chance of contamination of medical samples. Drones often operate QR code placards that can be checked to record health records. There are also agricultural drones distributing disinfectants in the farmland. Drones, operated by facial recognition, are often used to warn people not to leave their homes and to chide them for not using face masks. Terra Drone uses its unmanned drones to move patient samples and vaccination content at reduced risk between the Xinchang County Disease Control Center and the People’s Hospital. Drones are often used to monitor public areas, document non-compliance with quarantine laws and thermal imaging.

Autonomous Vehicles

At a period of considerable uncertainty to medical professionals and the danger to people-to-people communication, automated vehicles are proving to be of tremendous benefit in the transport of vital products, such as medications and foodstuffs. Apollo, the Baidu Autonomous Vehicle Project, has joined hands with the Neolix self-driving company to distribute food and supplies to a big hospital in Beijing. Baidu Apollo has also provided its micro-car packages and automated cloud driving systems accessible free of charge to virus-fighting organizations.

Idriverplus, a Chinese self-driving organization that runs electrical street cleaning vehicles, is also part of the project. The company’s signature trucks are used to clean hospitals.

This chapter provides an introduction to the coronavirus outbreak (COVID-19). A brief history of this virus along with the symptoms are reported in this chapter. Then the comparison between COVID-19 and other plagues like seasonal influenza, bird flu (H5N1 and H7N9), Ebola epidemic, camel flu (MERS), swine flu (H1N1), severe acute respiratory syndrome, Hong Kong flu (H3N2), Spanish flu and the common cold are included in this chapter. Reviews of online portal and social media like Facebook, Twitter, Google, Microsoft, Pinterest, YouTube and WhatsApp concerning COVID-19 are reported in this chapter. Also, the preventive measures and policies enforced by WHO and different countries such as China, Italy, Iran, South Korea, France, Germany and the United States for COVID-19 are included in this chapter. Emergency funding provided by different countries to fight the COVID-19 is mentioned in this chapter. Lastly, artificial intelligence, data science and technological solutions like public health surveillance, remote biosignal measurement, IoT and wearables, chatbots and communication, social media and open data, automated diagnostics, drug development research, robotics, colour coding, drones and autonomous vehicles are included in this chapter.

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  • 14 November 2023

How our memories of COVID-19 are biased — and why it matters

You have full access to this article via your institution.

Hospital workers wearing PPE watch a protest through a hospital window

The COVID-19 vaccination polarized opinion — and our memories. Credit: Arindam Shivaani/NurPhoto via Getty

Lives are still being lost to COVID-19 every day. And for many left with debilitating after-effects of the disease, it remains a very real, immediate experience. But for many others, the circumstances of the pandemic are becoming a matter of memory. These memories might still be fresh and painful, or more distant and neutralized by the passage of time. Either way, they are almost undoubtedly unreliable.

This is not, in itself, a surprise: that different people can have very different memories of the same past events, and that pre-existing biases can influence these memories, is an established facet of human psychology. But a series of studies reported in a paper 1 this month in Nature shows that our impressions of the COVID-19 pandemic’s severity, as well as of measures taken to limit the disease’s spread, are reliably skewed by a related factor: our vaccination status.

The results give pause for thought as countries exercise their collective memories to examine how authorities handled the pandemic and what should be done differently next time. “When looking back, we should all be aware that we have biased memories,” says Cornelia Betsch at the University of Erfurt in Germany, an author of the Nature paper. “You could be right or wrong. I could be right or wrong. Or, most likely, we’re all wrong.”

research abstract on covid 19

Can giant surveys of scientists fight misinformation on COVID, climate change and more?

Betsch and her colleagues’ project involved surveying more than 10,000 people across 11 countries. For one study, they resurveyed German adults who had been asked in summer 2020 or winter 2020–21 to estimate their risk of SARS-CoV-2 infection, asking them to recall their earlier answers. They embarked on the project in late 2022, after a journalist commented during a conference that people who opposed vaccination seemed to be shifting their narrative of the pandemic. The authors’ analysis revealed that unvaccinated individuals who identified strongly with their unvaccinated status were more likely to remember their earlier estimation of the risk as lower than it actually was. Conversely, and more markedly, those who had been vaccinated overestimated their earlier perception of their risk of catching the disease.

As with any study, there are caveats. The data were collected online, and most of the countries sampled are wealthy and in the Northern Hemisphere. The study did not evaluate the effect of the different pandemic policies enacted in different regions. The researchers also surveyed only adults. At this stage, there is no way of knowing how children will remember the pandemic when they are older — or how those memories might colour their decisions should another pandemic occur when they are adults.

Memory bias has been observed in other politically charged settings, including recall of COVID-19 vaccine misinformation 2 , the campaign surrounding Ireland’s 2018 referendum on legalizing abortion 3 and the 2021 US Capitol riots 4 . Such bias feeds polarization. Communication is difficult when shared memories diverge. It can influence discussions at every level: within families, in the media and within governments and other authorities.

research abstract on covid 19

Pioneers of mRNA COVID vaccines win medicine Nobel

The conclusions of the latest study are highly relevant to investigations such as the ongoing inquiry into the United Kingdom’s handling of COVID-19, a process that has been garnering headlines in the past weeks. Those overseeing such investigations must recognize that personal recollections are clouded by bias. In drawing conclusions about which pandemic interventions were warranted or effective and which were not, it is imperative that investigators rely as much as possible on hard data and evidence.

Many of the conflicts we struggle with today stem from how we view past events now, rather than how we experienced them then. The divergence in our collective memory is also likely to be a significant factor in future pandemics, determining, for example, whether individuals are willing to comply with the associated public-health mandates. How to counter these effects in the future must be a subject for more research today.

Nature 623 , 458 (2023)

doi: https://doi.org/10.1038/d41586-023-03434-3

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COVID-19 Vaccine: A comprehensive status report


  • 1 Department of Microbiology, Ram Lal Anand College, University of Delhi, Benito Juarez Road, New Delhi 110021, India.
  • 2 Department of Microbiology, Ram Lal Anand College, University of Delhi, Benito Juarez Road, New Delhi 110021, India. Electronic address: [email protected].
  • PMID: 32800805
  • PMCID: PMC7423510
  • DOI: 10.1016/j.virusres.2020.198114

The current COVID-19 pandemic has urged the scientific community internationally to find answers in terms of therapeutics and vaccines to control SARS-CoV-2. Published investigations mostly on SARS-CoV and to some extent on MERS has taught lessons on vaccination strategies to this novel coronavirus. This is attributed to the fact that SARS-CoV-2 uses the same receptor as SARS-CoV on the host cell i.e. human Angiotensin Converting Enzyme 2 (hACE2) and is approximately 79% similar genetically to SARS-CoV. Though the efforts on COVID-19 vaccines started very early, initially in China, as soon as the outbreak of novel coronavirus erupted and then world-over as the disease was declared a pandemic by WHO. But we will not be having an effective COVID-19 vaccine before September, 2020 as per very optimistic estimates. This is because a successful COVID-19 vaccine will require a cautious validation of efficacy and adverse reactivity as the target vaccinee population include high-risk individuals over the age of 60, particularly those with chronic co-morbid conditions, frontline healthcare workers and those involved in essentials industries. Various platforms for vaccine development are available namely: virus vectored vaccines, protein subunit vaccines, genetic vaccines, and monoclonal antibodies for passive immunization which are under evaluations for SARS-CoV-2, with each having discrete benefits and hindrances. The COVID-19 pandemic which probably is the most devastating one in the last 100 years after Spanish flu mandates the speedy evaluation of the multiple approaches for competence to elicit protective immunity and safety to curtail unwanted immune-potentiation which plays an important role in the pathogenesis of this virus. This review is aimed at providing an overview of the efforts dedicated to an effective vaccine for this novel coronavirus which has crippled the world in terms of economy, human health and life.

Keywords: COVID-19; Clinical Trials; Convalescent Plasma Therapy; Monoclonal Antibodies; SARS-CoV-2; Vaccine.

Copyright © 2020 Elsevier B.V. All rights reserved.

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  • Angiotensin-Converting Enzyme 2
  • Antibodies, Viral / biosynthesis*
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COVID-19 Research Articles Downloadable Database

March 19, 2020

Updated September 29, 2023

COVID-19 Research Guide Home

  • Research Articles Downloadable Database
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Important announcement:  

The CDC Database of COVID-19 Research Articles became a collaboration with the WHO to create the  WHO COVID-19 database  during the pandemic to make it easier for results to be searched, downloaded, and used by researchers worldwide.

The last version of the CDC COVID-19 database was archived and remain available on this website.  Please note that it has stopped updating as of October 9, 2020 and all new articles were integrated into the  WHO COVID-19 database .  The WHO Covid-19 Research Database was a resource created in response to the Public Health Emergency of International Concern (PHEIC). Its content remains searchable and spans the time period March 2020 to June 2023. Since June 2023, manual updates to the database have been discontinued.

If you have any questions, concerns, or problems accessing the WHO COVID-19 Database please email the CDC Library for assistance.

Materials listed in these guides are selected to provide awareness of quality public health literature and resources. A material’s inclusion does not necessarily represent the views of the U.S. Department of Health and Human Services (HHS), the Public Health Service (PHS), or the Centers for Disease Control and Prevention (CDC), nor does it imply endorsement of the material’s methods or findings.

Below are options to download the archive of COVID-19 research articles.  You can search the database of citations by author, keyword (in title, author, abstract, subject headings fields), journal, or abstract when available.  DOI, PMID, and URL links are included when available.

This database was last updated on October 9, 2020 .

  • The CDC Database of COVID-19 Research Articles is now a part of the WHO COVID-19 database .  Our new  search results are now being sent to the WHO COVID-19 Database to make it easier for them to be searched, downloaded, and used by researchers worldwide. The WHO Covid-19 Research Database was a resource created in response to the Public Health Emergency of International Concern (PHEIC). Its content remains searchable and spans the time period March 2020 to June 2023. Since June 2023, manual updates to the database have been discontinued.
  • To help inform CDC’s COVID-19 Response, as well as to help CDC staff stay up to date on the latest COVID-19 research, the Response’s Office of the Chief Medical Officer has collaborated with the CDC Office of Library Science to create a series called COVID-19 Science Update . This series, the first of its kind for a CDC emergency response, provides brief summaries of new COVID-19-related studies on many topics, including epidemiology, clinical treatment and management, laboratory science, and modeling. As of December 18, 2021, CDC has stopped production of the weekly COVID-19 Science Update.

Excel download:

  • Articles from August until October 9 2020 [XLS – 29 MB]
  • Articles from December 2019 through July 2020 [XLS – 45 MB]
  • The CDC Database of COVID-19 Research Articles is now a part of the WHO COVID-19 database .  Our new search results are now being sent to the WHO COVID-19 Database to make it easier for them to be searched, downloaded, and used by researchers worldwide.
  • October 8 in Excel [XLS – 1 MB]
  • October 7 in Excel [XLS – 1 MB]
  • October 6 in Excel [XLS – 1 MB]
  • Note the main Excel file can also be sorted by date added.

Citation Management Software (EndNote, Mendeley, Zotero, Refman, etc.)  download:

  • Part 1 [ZIP – 38 MB]
  • Part 2 [ZIP – 43 MB]
  • October 8 in citation management software format [RIS – 2 MB]
  • October 7 in citation management software format [RIS – 2 MB]
  • October 6 in citation management software format [RIS – 2 MB]
  • Note the main RIS file can also be sorted by date added.

The COVID-19 pandemic is a rapidly changing situation.  Some of the research included above is preliminary.  Materials listed in this database are selected to provide awareness of quality public health literature and resources. A material’s inclusion does not necessarily represent the views of the U.S. Department of Health and Human Services (HHS), the Public Health Service (PHS), or the Centers for Disease Control and Prevention (CDC), nor does it imply endorsement of the material’s methods or findings.

To access the full text, click on the DOI, PMID, or URL links.  While most publishers are making their COVID-19 content Open Access, some articles are accessible only to those with a CDC user id and password. Find a library near you that may be able to help you get access to articles by clicking the following links: https://www.worldcat.org/libraries OR https://www.usa.gov/libraries .

CDC users can use EndNote’s Find Full Text feature to attach the full text PDFs within their EndNote Library.  CDC users, please email Martha Knuth for an EndNote file of all citations.  Once you have your EndNote file downloaded, to get the full-text of journal articles listed in the search results you can do the following steps:

  • First, try using EndNote’s “Find Full-Text” feature to attach full-text articles to your EndNote Library.
  • Next, check for full-text availability, via the E-Journals list, at: http://sfxhosted.exlibrisgroup.com/cdc/az   .
  • If you can’t find full-text online, you can request articles via DocExpress, at: https://docexpress.cdc.gov/illiad/

The following databases were searched from Dec. 2019-Oct. 9 2020 for articles related to COVID-19: Medline (Ovid and PubMed), PubMed Central, Embase, CAB Abstracts, Global Health, PsycInfo, Cochrane Library, Scopus, Academic Search Complete, Africa Wide Information, CINAHL, ProQuest Central, SciFinder, the Virtual Health Library, and LitCovid.  Selected grey literature sources were searched as well, including the WHO COVID-19 website, CDC COVID-19 website, Eurosurveillance, China CDC Weekly, Homeland Security Digital Library, ClinicalTrials.gov, bioRxiv (preprints), medRxiv (preprints), chemRxiv (preprints), and SSRN (preprints).

Detailed search strings with synonyms used for COVID-19 are below.

Detailed search strategy for gathering COVID-19 articles, updated October 9, 2020 [PDF – 135 KB]

Note on preprints:   Preprints have not been peer-reviewed. They should not be regarded as conclusive, guide clinical practice/health-related behavior, or be reported in news media as established information.

Materials listed in these guides are selected to provide awareness of quality public health literature and resources. A material’s inclusion does not necessarily represent the views of the U.S. Department of Health and Human Services (HHS), the Public Health Service (PHS), or the Centers for Disease Control and Prevention (CDC), nor does it imply endorsement of the material’s methods or findings. HHS, PHS, and CDC assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by HHS, PHS, and CDC. Opinion, findings, and conclusions expressed by the original authors of items included in these materials, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of HHS, PHS, or CDC. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by HHS, PHS, or CDC.

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Featured Clinical Reviews

  • Contraception Selection, Effectiveness, and Adverse Effects: A Review JAMA Review December 28, 2021
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The New Crisis of Increasing All-Cause Mortality in US Children and Adolescents

  • 1 Department of Family Medicine and Population Health, Virginia Commonwealth University School of Medicine, Richmond
  • 2 Department of Pediatrics, Virginia Commonwealth University School of Medicine, Richmond
  • 3 Departments of Pediatrics and Epidemiology, University of Washington, and Seattle Children’s Research Institute, Seattle
  • 4 Editor, JAMA Network Open
  • Original Investigation Pediatric Mental Health Hospitalizations at Acute Care Hospitals in the US, 2009-2019 Mary Arakelyan, MPH; Seneca Freyleue, MS; Divya Avula, MPH; Jennifer L. McLaren, MD; A. James O’Malley, PhD; JoAnna K. Leyenaar, MD, PhD, MPH JAMA
  • Medical News & Perspectives Teen Girls Are Faring Worse Than Boys on Nearly All Mental Health Measures—Here’s Why Anita Slomski JAMA
  • Original Investigation Mental Health–Related Emergency Department Visits Among Youth Tanner J. Bommersbach, MD, MPH; Alastair J. McKean, MD; Mark Olfson, MD, MPH; Taeho Greg Rhee, PhD JAMA
  • Comment & Response Increasing All-Cause Mortality in US Children and Adolescents—Reply Steven H. Woolf, MD, MPH; Elizabeth R. Wolf, MD, MPH; Frederick P. Rivara, MD, MPH JAMA
  • Comment & Response Increasing All-Cause Mortality in US Children and Adolescents Janice C. Probst, PhD; Elizabeth L. Crouch, PhD; Peiyin Hung, PhD JAMA

Although life expectancy in industrialized countries has lengthened over the past century, increases in US life expectancy ceased after 2010, a trend attributed to rising mortality rates among individuals aged 25 to 64 years. 1 Although midlife mortality rates increased over the past decade, mortality rates among children and older adults continued to decrease. The COVID-19 pandemic altered this trend and resulted in a sharp increase in mortality among older adults, an unsurprising outcome. However, pediatric mortality rates also increased, and COVID-19 contributed little to this surge. This increase in all-cause pediatric mortality has ominous implications. A nation that begins losing its most cherished population—its children—faces a crisis like no other.

Read More About

Woolf SH , Wolf ER , Rivara FP. The New Crisis of Increasing All-Cause Mortality in US Children and Adolescents. JAMA. 2023;329(12):975–976. doi:10.1001/jama.2023.3517

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  • Published: 07 November 2023

24-Hour movement behaviours research during the COVID-19 pandemic: a systematic scoping review

  • Danqing Zhang 1   na1 ,
  • Sitong Chen 2   na1 ,
  • José Francisco López-Gil 3 ,
  • Jintao Hong 4 ,
  • Fei Wang 5 &
  • Yang Liu 1 , 6  

BMC Public Health volume  23 , Article number:  2188 ( 2023 ) Cite this article

267 Accesses

Metrics details

Many studies examining 24-hour movement behaviours based on the 24-Hour Movement Guidelines (24HMG) have been published during the COVID-19 pandemic. However, no comprehensive reviews summarized and synthesized the evidence concerning studies using 24HMG. The aim of this scoping review was to synthesize the evidence from the 24HMG studies published during the pandemic.

Three electronic databases (Web of Science, PubMed, EBSCO) were utilized to conduct a literature search. The search procedure adhered to the guidelines set by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Initially, a total of 1339 research articles published in peer-reviewed journals were screened. After eliminating 461 duplicates, 878 articles remained. The titles and/or abstracts of these articles were then cross-checked, and 25 articles were included. Subsequently, two authors independently assessed full-text of articles based on the pre-defined inclusion and exclusion criteria, resulting in the final selection of 16 articles that met the inclusion criteria. Study characteristics (e.g., study population, study design, measurement) were extracted and then summarized. According to the Viable Integrative Research in Time-use Research (VIRTUE) epidemiology, the included studies were further classified into different but interrelated study domains (e.g., composition, determinants, health outcomes).

The majority of included articles focused on children and adolescents as study population. This study primarily demonstrated that a low prevalence of meeting the 24HMG among children and adolescents during the COVID-19 pandemic. There has been a decline in the percentage of individuals meeting the 24HMG compared to the pre-COVID-19 period. The majority of included studies focused on sociodemographic factors when examining the correlates of meeting the 24HMG, while a few studies assessed factors of other domains, such as social, cultural, and environmental aspects.

The COVID-19 pandemic had an impact on healthy 24-hour movement behaviours in children and adolescents. In conjunction with the studies conducted during the COVID-19 pandemic, more studies were encouraged to explore the correlates of meeting the 24HMG and the associated health benefits in wider ranges of populations.

Peer Review reports


The coronavirus disease 2019 (COVID-19) causes a high morbidity and mortality rate and severely affects the world [ 1 ]. The World Health Organization (WHO) announced COVID-19 as a pandemic in March 2020. To prevent and limit the possible spread of COVID-19, the governments of some countries issued a series of restrictive measures [ 2 , 3 , 4 , 5 ], including the suspension of school, work organized sports activities and meetings (though allowing for outdoor activities), and implementing national quarantine, restricting the movement of the entire population [ 6 , 7 ]. The COVID-19 pandemic has particularly affected people’s lives and health behaviour [ 3 ], including home isolation and restrictions on activity accessibility, resulting in significant alterations in daily activities [ 8 , 9 ]. In addition, the COVID-19 pandemic also increased kinds of risk disease [ 10 , 11 ]. These circumstances were similar to those of prior disasters [ 12 ]. One of the possible reasons for this was the change in lifestyle behaviour after the disaster [ 2 ]. Confronted with unparalleled challenges and disruptions to their daily lives, individuals often adapt their routines, habits, and activities. These adaptations can manifest in diverse aspects of lifestyle behavior, including decreased physical activity (PA), modified dietary patterns, and disrupted sleep schedules. Consequently, such modifications in lifestyle behavior can exert a profound and enduring influence on individuals’ overall health and well-being. Additional research is warranted to acquire a comprehensive understanding of the precise changes in lifestyle behavior triggered by the COVID-19 pandemic.

Not surprisingly, it has been well documented that the COVID-19 pandemic has significant impacts on individuals’  PA [ 14 , 15 , 16 ], sedentary behaviour (SB) [ 17 , 18 , 19 ] and sleep [ 20 , 21 , 22 ] (these three behaviours were collectively called 24-hour movement behaviours). During the COVID-19 pandemic, people’s PA levels have shown massive declines [ 14 , 15 , 16 ], while SB has shown substantial increases [ 17 , 18 , 19 ], primarily owing to social-distancing and lockdown measures [ 19 ]. In terms of sleep, studies have shown a longer duration of sleep time and daytime sleepiness [ 20 , 21 , 22 ] and adverse changes to sleep patterns and bedtime routines during the home confinement period [ 20 ]. These negative changes influence individuals’ health and wellbeing [ 3 ].

Given that PA, SB and sleep are co-dependent health behaviours and their combined health effects should be given more research attention rather than focusing on either of them, it is recommended that researchers integrate PA, SB and sleep for efficient health promotion [ 23 , 24 ]. A well-developed paradigm for 24-hour movement behaviours research was to adopt the 24-hour movement guidelines (24HMG). Researchers have developed and launched the Canadian 24HMG for populations across the life course [ 24 , 25 , 26 ]. The guidelines mainly have quantifiable recommendations on PA, SB and sleep, supported by robust scientific evidence. Based on this, an increasing number of studies have begun using 24HMG to study PA, SB and sleep in combination [ 27 , 28 , 29 ], as it can help provide an integrative perspective to study movement behaviours at the population level.

Some studies have been conducted using the 24HMG before the COVID-19 pandemic, which examined the prevalence of meeting the 24HMG [ 30 , 31 , 32 , 33 , 34 , 35 ] and the secular trends [ 28 , 31 , 36 , 37 , 38 , 39 ], correlates of meeting the 24HMG [ 30 , 32 , 33 , 35 , 40 ], and the associations between meeting the 24HMG and health outcomes [ 28 , 41 , 42 , 43 , 44 ]. According to the Framework for Viable Integrative Research in Time-Use (VIRTUE) Epidemiology, those studies can be categorized into some research areas, time-use compositions, determinants and health outcomes [ 45 ].

Given the importance of integrating PA, SB and sleep, a number of studies have investigated the prevalence of meeting the 24HMG during COVID-19 [ 7 , 46 , 47 , 48 ]. Furthermore, some of the studies repeatedly measured the prevalence of meeting the 24HMG prior to and during COVID-19, enabling researchers to examine the trends of 24HMG adherence. Jáuregui et al. found that the prevalence of meeting the 24HMG was significantly lower than that before COVID-19 [ 49 ]. Another study by Angel et al. also had similar research findings, indicated that the percentage of participants meeting the 24HMG has decreased from 3.3 to 0.2% [ 50 ]. Despite these studies, there was no synthesized study to review the changes in the prevalence of meeting the 24HMG before and during the pandemic. Such studies were needed not only because of 24-hour movement behaviours associated health outcomes but also to assist with the development of public health interventions when confronting similar public health events.

In addition to the changes in the prevalence of meeting the 24HMG, little was known about which factors (categorization of factors based on VIRTUE framework) were associated with the integrated 24-hour movement behaviours during the COVID-19 pandemic. Therefore, the main aim of this review was to synthesize the evidence concerning research using the 24HMG during the COVID-19 pandemic.

This study aimed to conduct a systematic scoping review to summarize the evidence concerning the 24HMG research conducted during the COVID-19 pandemic.

Data source and search strategy

To ensure a nonbiased and complete review, we searched the following electronic databases from 1 to 2020 to 30 November 2022: Web of Science, EBSCO, and PubMed. Several keywords were employed for the literature search in each database: “24-h*”, “24 hour”, “24-hour”, “Movement Behavio*”, “Sleep*”, “Screen”, “Physical Activity”, “Guideline*”, “recommendation*”, “COVID-19” “Coronavirus Disease”, “Coronavirus”, “SARS-CoV-2” and “nCoV”. In the Web of Science, EBSCO, and PubMed, we divided all search terms into three categories: (24-h* OR 24 h OR 24-hour OR Movement Behavio* OR Sleep* OR Screen OR Physical Activity) AND (Guideline* OR recommendation*) AND (COVID-19 OR Coronavirus Disease OR Coronavirus OR SARS-CoV-2 OR nCoV). Due to the differences in databases, field tags of “Title”, “Abstract” and “Title/Abstract” were used in combination during document retrieval (Supplementary material). To obtain the final number of studies included in this review, all of the retrieved articles were independently screened and assessed by two authors. If there were any differences regarding inclusion, a third author was invited to join the discussion and make a decision.

Eligibility criteria

The inclusion criteria for screening articles were as follows: (1) documents contained search terms and were published from 1 to 2020 to 30 November 2022; (2) study sample related to human beings, and they were acceptable if the subjects were in poor physical condition (disability or disorder); (3) the results reported combined 24-hour movement behaviours using the guidelines (PA or SB and sleep) focused on people who had COVID-19 at the time of the study; and (4) articles written in English.

The exclusion criteria were as follows: (1) studies that met the inclusion criteria but had duplicates between databases; (2) case studies, master’s/doctoral dissertations, conference papers and abstracts, reviews, brief reports and letters, protocol, commentary, and qualitative study; and (3) studies that did not report the percentage adherence to the 24HMG during the COVID-19 pandemic.

Data extraction and data items

The following information was extracted and summarized from the final included studies by two authors: (1) basic information of study (authors, published year, published journal, author countries/organization); (2) sample characteristics of study (sociodemographic, subjects, age group and sex of subjects, simple size and population, countries/country of study conducted); (3) study design and method (study design: cross-sectional study/longitudinal study, survey method: single/mixed method); (4) measurements (self-report, interview, device-based measurement, proxy report); (5) categorizations of research areas in line with the VIRTUE framework (including three types of content in this study: outcomes, correlates/determinants, time-use composition of 24-hour movement behaviours with COVID-19); (6) findings (prevalence of meeting % the 24HMG during COVID-19 and changes % of meeting the 24HMG with COVID-19). EXCEL 2019 was used to categorize these variables.

Coding of studies and summary

The code “D- * ” indicates studies that reported a significant decrease (%) in meeting the 24HMG between before and during the COVID-19 pandemic period. The code “D-” indicates studies that reported a nonsignificant decrease (%) or reported decreased outcomes (%) but did not report the p value. The code “I + ” indicates studies that reported a nonsignificant increase (%). The code “NC” indicates studies that reported no change (%) in meeting the 24HMG between before, and during the COVID-19 pandemic period. The “Summary” contains a code to summarize the state of studies for meeting the 24HMG. If the study contained fewer than three outcomes, the trend could not be summarized.

Data selection

The search procedure followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 51 ], and the flowchart was presented in Fig.  1 . A total of 1339 articles were searched from three databases (392 articles from EBSCO, 594 articles from PubMed and 353 articles from Web of Science). A total of 878 articles remained after removing 461 duplicates by checking the title and/or abstract. Furthermore, based on the inclusion and exclusion criteria, two authors screened 25 full-text articles for the final selection. Finally, 16 studies [ 5 , 6 , 46 , 47 , 49 , 50 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 ] met the inclusion criteria for this review.

figure 1

PRISMA flowchart for study selection

Characteristics of studies and sample

Figure  2 illustrated populations from nineteen different countries extracted from fifteen included studies. Five studies focused on populations from Canada [ 5 , 6 , 47 , 54 , 55 ]. Three studies targeted populations from Spain [ 50 , 59 , 60 ] and China [ 58 , 60 , 61 ]. Two studies included populations from Bangladesh [ 57 , 60 ], the United States [ 49 , 60 ], Saudi Arabia [ 52 , 53 ], Sweden [ 56 , 60 ]. In addition, three studies included populations from different countries [ 49 , 59 , 60 ], of which populations from fourteen countries (Australia, India, Indonesia, Malaysia, Morocco, Pakistan, Sri Lanka, Vietnam, Japan, Chile, Mexico, Sweden, China and Brazil) were all extracted from one study [ 60 ], López-Gil’s study [ 59 ] included populations from Spain and Brazil, and Jáuregui’s study [ 49 ] included populations from Chile, Mexico, and the United States.

figure 2

Number of publications involved in studies using 24-hour movement guidelines during the COVID-19 pandemic by country from the included studies of this review

The characteristics of the studies included in this review were summarized in Table  1 . In terms of study design, ten studies (62.5%) were cross-sectional designs [ 5 , 6 , 49 , 52 , 53 , 55 , 56 , 57 , 58 , 59 , 61 ], and four studies (25.0%) were repeated cross-sectional designs [ 47 , 50 , 52 , 54 ]. Two studies (12.5%) were longitudinal in design [ 46 , 60 ]. In regard to sample size, two studies (12.5%) had a sample size under 100 [ 54 , 57 ], four studies (25.0%) had a sample size between 100 and 1000 [ 46 , 50 , 56 , 60 ], and ten studies (62.5%) had a sample size above 1000 [ 5 , 6 , 47 , 50 , 52 , 53 , 54 , 55 , 59 , 61 ]. Regarding age groups, seven studies (43.8%) included preschool students (under 5 ys) [ 46 , 49 , 56 , 57 , 59 , 60 , 61 ]. Ten studies (62.5%) included children (aged 5–13 ys) [ 5 , 6 , 47 , 50 , 52 , 53 , 54 , 55 , 59 , 61 ], and seven studies (43.8%) included adolescents (aged 14–17 ys) [ 5 , 6 , 47 , 50 , 54 , 55 , 59 ]. Only one study (6.3%) targeted adults (18 + ys) [ 58 ]. Fifteen studies (93.8%) assessed the general population [ 5 , 6 , 46 , 47 , 49 , 50 , 52 , 53 , 55 , 56 , 57 , 58 , 59 , 60 , 61 ], and only one study (6.3%) assessed people with disability or disorder [ 54 ].

Measurement and Assessment of studies

The measurement and assessment methods used in the studies were provided in Fig.  3 . Eleven studies used a single method [ 5 , 6 , 47 , 49 , 50 , 52 , 53 , 55 , 58 , 59 , 61 ], of which Nine studies applied a proxy report assessment [ 5 , 6 , 47 , 49 , 52 , 53 , 55 , 59 , 61 ] and two studies applied a self-report measurement [ 50 , 58 ]. Additionally, ten studies used mixed methods, of which five studies applied a proxy report assessment [ 46 , 54 , 56 , 57 , 60 ], three studies [ 46 , 56 , 57 ] used a device-based measurement (accelerometer), and two studies [ 50 , 58 ] applied an interview measurement.

figure 3

Number of studies according to the measurement and assessment used. Notes: single method refers to only use one measure tool in study survey; mixed methods refer to use ≥ 2 measure tools in study survey

Categorization of studies using the 24-hour movement guidelines

Table  2 shows that the studies from the perspective of the VIRTUE framework. Three research areas (outcomes, correlates/determinants, and time-use composition) were considered in this review. In regard to outcomes, ten studies (62.5%) included sociodemographics (e.g., gender/sex, age, region, urban/rural, country income level) [ 5 , 47 , 49 , 52 , 53 , 55 , 56 , 57 , 59 , 60 ]. Three study [ 6 , 54 , 60 ] included behaviours/lifestyle (e.g., outdoor activity) [ 6 ], disability [ 54 ], environment (e.g., presence of outdoor space within house compound) [ 60 ], and social and cultural factors (e.g., the parent’s concern about the child’s movement behaviour, receiving any support from their childcare center, the parent’s perceived ability to support the child in having healthy movement behaviours, the parent’s perceived level of stress, the parent’s perceived level of exhaustion) [ 60 ]. Regarding the research area of correlates/determinants, two studies focused on psychological factors (e.g., depression, anxiety and stress) [ 58 , 61 ]. In the research area of time-use composition, all included studies assessed the prevalence of meeting the 24HMG. Eight studies (50.0%) included trends in meeting the 24HMG [ 46 , 47 , 49 , 50 , 52 , 54 , 59 , 60 ], of which two studies [ 46 , 50 ] included different numbers of participants meeting the 24HMG.

Levels and chagnes in the prevalence of meeting the 24-hour movement guidelines

As shown in Fig.  4 , seventeen outcomes were extracted from sixteen included studies (one study included two outcomes). Thirteen (76.5%) results (from twelve studies) [ 5 , 6 , 47 , 49 , 50 , 52 , 53 , 54 , 55 , 57 , 59 , 60 ] showed that the prevalence of meeting the 24HMG was under 5% during the COVID-19 pandemic, of which two studies reported a percentage less than 1% [ 50 , 54 ]. Four studies reported that more than 10% of the population (13.4%, 15.1%, 19.4%, and 27.9%, respectively) met the 24HMG during the COVID-19 pandemic period [ 46 , 56 , 58 , 61 ]. During the pandemic, the highest prevalence of meeting the 24HMG was 27.0% [ 58 ], and the lowest was 0.0% [ 54 ].

figure 4

Prevalence of meeting 24-hour movement guidelines during the COVID-19 reported by studies. Note: CI: IOA = cluster 1: increase outdoor activity; C2: DOA = cluster 2: decrease outdoor activity

As shown in Table  3 , eight outcomes from seven studies reported that the percentage of the population meeting the 24HMG was decreased [ 46 , 47 , 49 , 50 , 52 , 59 , 60 ], of which half of the studies [ 47 , 49 , 50 , 52 ] reported a significant decrease from prior to and during the COVID-19 pandemic. Three studies showed a decrease of more than 3% [ 49 , 50 , 59 ]. One study reported a percentage of 0.0% with no change [ 54 ]. Nonsignificant increases were reported both in children and youth (only girls) [ 47 ].

The aim of this review was to synthesize the evidence from studies using the 24HMG during the COVID-19 pandemic, presenting a knowledge map and research landscape. The main findings of this review were as follows: first, the number of studies using the 24HMG was very limited (n = 16), with most of the studies targeting children and adolescents as study population, and most of the studies used subjective measures and were cross-sectional (n = 14) and conducted in Western countries. Second, most studies found that during the COVID-19 pandemic, the prevalence of meeting the 24HMG was very low (11 studies reported below 4%), and it declined greatly compared with the prevalence before the COVID-19 pandemic. Third, according to the VIRTUE framework, studies focusing on the prevalence of meeting the 24HMG and the trends, as well as sociodemographic correlates of the prevalence, were dominant across the included studies. Evidence synthesized from this review can help inform future research development and policymakers to implement effective approaches against public health events.

Overall status of studies and study characteristics

The findings of this review demonstrated a very limited number of studies using the 24HMG during the COVID-19 pandemic. Compared with studies investigating the prevalence of meeting the PA, SB, or sleep guidelines [ 30 , 31 , 32 , 33 , 34 , 35 ] in insolation, the number was largely lower, which in part reflects less research attention and interest in 24HMG studies. Some possible reasons can be proposed. The first one was that research within 24HMG has had a relatively short history compared with PA, SB and sleep studies in insolation, so the number of 24HMG studies cannot be as large as possible. Second, it might be difficult to collect data on PA, SB and sleep simultaneously during the COVID-19 pandemic. Despite the limited number, those included studies could also advance the knowledge around health behaviour research during the pandemic and provide evidence to refine the 24HMG in the future.

The majority of the studies included in this review were cross-sectional and conducted in Western countries. Similar findings on PA or SB studies in insolation were found [ 7 ], which is consistent with the current review. This was likely because a cross-sectional study may be the most economical and feasible study design during the COVID-19 pandemic period. During the isolation period, it was very challenging to conduct longitudinal and interventional studies on 24-hour movement behaviours owing to social distancing and lockdown. Additionally, some measures against the pandemic also had impacts on measures used by the studies included in this review. As observed in this review, most of the included studies used subjective measures to collect data on movement behaviours, which was likely due to social distancing and lockdown as well [ 8 , 9 ]. However, with the increasing use of device-based measures of movement behaviours, such as mobile phones or some other individually used technological devices (e.g., smartphones, wearable activity monitors) [ 62 , 63 ], future research should consider utilizing these devices to capture more accurate data on movement behaviours [ 7 , 63 ].

Researchers from Western countries were the main contributors to 24HMG studies during the COVID-19 pandemic. Previous studies have shown that research in PA [ 15 ] and SB research [ 7 ], and even sleep research [ 34 ], mainly comes from Western countries [ 7 , 34 , 64 ], which can to some extent explain this finding in our review. Such a bias has been observed in other health-related fields [ 65 ]. Similarly, research bias was also found in terms of the study population. In the current review, all the included studies focused on children and adolescents. This was likely due to two reasons, of which the first was that children and adolescents were the prioritized studied population in PA-related research [ 66 ] and the second was that the first 24HMG was designed for children and adolescents [ 24 ]. However, the first 24HMG for adults was released in 2020 [ 24 ]. Collectively, the above reasons could explain why the included studies prioritized children and adolescents rather than adults or other study populations.

Low levels of 24-hour movement behaviours

The results indicated a low prevalence of meeting the 24HMG (most of the included studies reported below 5%) in children and adolescents during the COVID-19 pandemic, and a significant decline in the prevalence was found compared with the pre-COVID-19 pandemic. This finding was expected on the basis of previous studies and evidence bases. Owing to social distancing and lockdown policies during the COVID-19 pandemic, individuals’ low levels of PA [ 14 , 15 , 16 ], high levels of SB [ 17 , 18 , 19 ] and worse sleep [ 50 ] jointly contributed to the low prevalence of meeting the 24HMG in children and adolescents. The implementation of restrictions has resulted in a rise in “stay-at-home” holidays. A previous study indicated that children’s sleep, SB, and PA exhibit lower levels of regulation on unstructured days (e.g., school holidays) in comparison to structured days (e.g., school days) [ 67 ]. Furthermore, this lack of regulation has been associated with a rise in the prevalence of children having electronic screen devices in their bedrooms, leading to inadequate sleep duration and PA [ 52 ].

Despite four studies reported that the prevalence of meeting the 24HMG over 10% [ 46 , 56 , 58 , 61 ], overall low level was still exhibited. The potential reasons could be attributed to variations of survey population and study recruitment, with three studies specifically examining preschool children and one study concentrating on college students. In the case of preschool children, their limited awareness of the pandemic might influence the outcomes. Conversely, college students may have established similar daily routines, whether residing in dormitories or at home. Additionally, the study reported that the samples were recruited using a convenience sampling procedure [ 58 ], which may also influence the research findings.

Change of 24-hour movement behaviours

Our findings mainly suggested a significant decline in the prevalence of meeting the 24HMG before and after the COVID-19 pandemic, even though one study reported the findings of increasing prevalence in some subgroups of children and adolescents [ 47 ]. This difference may be attributed to variations in virus transmission waves and the implementation of strict lockdown policies across different countries, as well as differences in the timing of measurements in studies [ 47 , 50 ]. These findings indirectly illustrated the impact of pandemic restrictions on individuals’ 24-hour cycle behavior. There has been a perceived decline in young people’s behaviors following the COVID-19 pandemic, with significant changes observed in PA levels, recreational screen time, and sleep duration [ 50 ]. Given the measures against the COVID-19 pandemic, children and adolescents’ access to activity facilities and opportunities was reduced [ 69 ]. Moreover, owing to home quarantine, increased SB, including recreational screen time and domestic sitting time, has been observed [ 7 ]. These factors may also negatively impact on sleep [ 70 ]. Furthermore, the closure of schools during both strict and mild confinement reduces children and adolescents’ access to and opportunities for PA, such as physical education classes and organized PA [ 71 , 72 ]. Additionally, the COVID-19 pandemic has also been associated with a decrease in outdoor playtime among children and adolescents [ 5 , 73 ]. Spending less time outdoors has a substantial impact on PA and SB, further reducing the prevalence of meeting the 24HMG [ 5 ]. As the restrictions imposed due to the COVID-19 pandemic are gradually lifted, it is crucial to address and mitigate the negative impacts on 24-hour movement behaviours in youth. Future research should focus on understanding the long-term consequences of the pandemic on children and adolescents’ movement behaviors. This includes investigating the effectiveness of interventions aimed at promoting PA, reducing SB, and improving adherence to the 24HMG. Furthermore, it is imperative to investigate strategies that enhance access to recreational facilities, encourage outdoor play, and offer organized PA opportunities amidst persistent public health challenges. This will enable the development of evidence-based interventions and policies aimed at promoting the health and well-being of children and adolescents in the aftermath of the pandemic.

Research topics of the 24HMG studies during the pandemic

On the basis of the VIRTUE framework formulated by Pedisic et al. [ 45 ], we examined the research topic of included studies conducted during the COVID-19 pandemic. The findings suggested that studies on time-use compositions and correlates were predominant. This situation can also be observed in PA, SB and sleep epidemiology research in insolation [ 13 , 74 ], which was similar to our review. One possible explanation for this finding is that these two domains of study can be conducted with relatively low testing burden and are easier for researchers to design and perform. Given the constraints and limitations imposed by the pandemic, it is understandable that researchers gravitated towards areas where data collection and analysis could be carried out more easily. Among the time-use composition studies, numerous investigations have reported changes in the prevalence of meeting the 24HMG before and during the COVID-19 pandemic. However, it is equally important to direct research efforts towards examining the changes in post COVID-19 conditions. Such investigations would provide valuable insights into the impact of the pandemic on population health and inform strategies for the future. By expanding research beyond the immediate effects of the pandemic, we can gain a comprehensive understanding of the long-term implications on individuals’ time-use compositions and their adherence to the 24HMG. This knowledge will be crucial for developing targeted interventions and policies that promote healthier time-use behaviors in the post-pandemic era.

In terms of the correlates examined in the 24HMG studies conducted during the COVID-19 pandemic, the majority focused on sociodemographic factors, while a few studies assessed factors of other domains, such as social, cultural, and environmental factors. This finding is consistent with previous studies [ 34 ], partly because of relatively easy data collection on sociodemographic factors. Furthermore, this finding was also similar to the evidence from 24HMG research conducted before or after the COVID-19 pandemic [ 7 ]. This suggests that the emphasis on sociodemographic factors in 24HMG studies is not solely influenced by the pandemic but has been a prevailing trend in the field. Based on our review and the existing literature, it is evident that future studies should aim to explore a broader range of factors influencing 24HMG from different domains. By expanding the scope of investigation beyond sociodemographic factors, researchers can gain a more comprehensive understanding of the complex interplay between activity behavior and various contextual factors. This will contribute to a more nuanced understanding of the relationship between 24HMG and its determinants, ultimately informing interventions and strategies to improve individuals’ health and well-being.

Two study treated 24-hour movement behaviours as correlated and assessed their association with mental health outcomes among Chinese populations of preschool and university students [ 58 , 61 ]. In contrast, the number of studies conducted before or after the COVID-19 pandemic largely exceeded the number. Despite the limited number, evidence can also be used for future refinement and update of the 24HMG for children and adolescents. Based on prior evidence has demonstrated that the low prevalence of meeting the 24HMG was in part responsible for undesirable health outcomes in children and adolescents, such as psychological outcomes (e.g., depression and anxiety) [ 58 ] and physical outcomes (e.g., cardiometabolic risk and adiposity) [ 68 ]. Future research can adopt longitudinal designs to examine the long-term effects of 24-hour movement behaviours on mental health in different age group (preschool students, children and adolescents, and adults) By tracking individuals’ behaviors and mental health outcomes (at different stages before, during and after pandemic), researchers can gain insights into the potential causal relationships and identify whether these associations persist over time. This research will contribute to providing valuable recommendations for the future development of human behavior and psychology.

Strength and limitations

This study’s strengths included a comprehensive review of the prevalence of 24HMG during the pandemic and its analysis of the changes in 24HMG before and after the outbreak. Additionally, it provides a summary of the research topics based on the VIRTUE framework. However, there were some limitations that should be acknowledged. Firstly, most of the studies were cross-sectional studies, which had an impact on the change of meeting 24HMG during the COVID-19 pandemic. Secondly, the included English studies of this review were only searched in three common databases, written in other languages articles were not included. Thirdly, this study did not incorporate COVID-19 policies, however, it is beneficial to analyse the impact of policies on meeting 24HMG in the future study. Additionally, this study did not classify and review adherence to 24HMG among genders, countries with varying socioeconomic status, and different age groups. Future targeted reviews (e.g., focusing on children and adolescents) are also valuable as these would facilitate interventions or policy development. Finally, this study just summarized the research topics of 24-hour movement behaviours during the COVID-19 based on the VIRTUE framework. Future studies are recommended to explore (through systematic review, meta-analysis., etc.) the results of relationships between different factors and 24-hour movement behaviors based on VIRTUE framework.

This review summarized the evidence from studies using 24HMG during the COVID-19 pandemic, offering a knowledge base for future research and policy development. Based on the findings, the COVID-19 may tend to have a negative impact on the prevalence of meeting 24HMG among different age-group populations. According to the study characteristics and research domains, studies using the 24HMG have a large space for improvement in terms of study design, measurement protocols and study domains (e.g., correlates and health outcomes).

Data Availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.


24-Hour Movement Guidelines

Viable Integrative Research in Time-use Research

Physical activity

  • Sedentary behaviour

World Health Organization

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This study was supported by grants from the National Social Science Foundation of China (No. 19BTY077), the Program for Overseas High-level talents at Shanghai Institutions of Higher Learning, and Shanghai Key Laboratory of Human Performance (Shanghai University of Sport, No.11DZ2261100).

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Danqing Zhang and Sitong Chen contributed equally to this work.

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School of Physical Education, Shanghai University of Sport, Shanghai, 200438, China

Danqing Zhang & Yang Liu

Institute for Health and Sport, Victoria University, Melbourne, VIC, 8001, Australia

Sitong Chen

One Health Research Group, Universidad de Las Américas, Quito, 170124, Ecuador

José Francisco López-Gil

Shanghai Research Institute of Sports Science (Shanghai Anti-doping Agency), Shanghai, 200030, China

Jintao Hong

Kun Shan Lu Jia Senior High School, Jiangsu, 215331, China

Shanghai Research Centre for Physical Fitness and Health of Children and Adolescents, Shanghai University of Sport, Shanghai, 200438, China

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YL designed the study and drafted the framework of this study, DZ drafted the manuscript. DZ and FW extracted data and completed all figures and tables. JH revised figures, tables and manuscript. SC: designed the study, checked all data and edited the manuscript. JFLG edited the manuscript.

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Zhang, D., Chen, S., López-Gil, J.F. et al. 24-Hour movement behaviours research during the COVID-19 pandemic: a systematic scoping review. BMC Public Health 23 , 2188 (2023). https://doi.org/10.1186/s12889-023-17136-y

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research abstract on covid 19

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research abstract on covid 19

  • Research for Development Outputs

Research snapshot: misinformation and COVID-19 related health measures in displacement settings

This trial explored whether manipulating the source of public health information would shift attitudes, knowledge and behaviour.

This pilot randomized controlled trial (RCT), explored whether manipulating the source of public health information during the COVID-19 pandemic would shift the attitudes, knowledge and behaviour of refugees and internally displaced persons. While the research questions could not be answered, the study generated useful insights for researchers interested in similar questions.

Public health information is usually intended to influence people’s behaviour, but this outcome may depend on whether audiences perceive the source as trustworthy. Manipulating the source should therefore affect outcomes.

But, as this pilot study in Beni, Democratic Republic of the Congo (DRC) demonstrated, doing this is not easy. Attribution of attitude or behaviour changes to the source manipulation was not possible. Learning and recommendations for how source-labelled information can be delivered more effectively in humanitarian settings were documented for the benefit of those who might conduct similar evaluations in future. Researchers or humanitarian programme staff could use learning from this study to test their Theory of Change prior to conducting a similar evaluation.

This snapshot contains key messages, findings, implications for humanitarian policymakers and practitioners and recommendations for further research.

This research was supported by the Research for Health in Humanitarian Crises (R2HC) Programme.

Busara Center for Behavioral Economics. ‘Research snapshot: misinformation and COVID-19 related health measures in displacement settings’. Elrha, 2023

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