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Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis
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Abstract
ABSTRACT BACKGROUND There is disagreement about the level of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We conducted a living systematic review and meta-analysis to address three questions: 1. amongst people who become infected with SARS-CoV-2, what proportion does not experience symptoms at all during their infection? 2. Amongst people with SARS-CoV-2 infection who are asymptomatic when diagnosed, what proportion will develop symptoms later? 3. What proportion of SARS-CoV-2 transmission is accounted for by people who are either asymptomatic throughout infection, or pre-symptomatic? METHODS AND FINDINGS We searched PubMed, Embase, bioRxiv and medRxiv using a database of SARS-CoV-2 literature that is updated daily, on 25 March 2020, 20 April 2020 and 10 June 2020. Studies of people with SARS-CoV-2 diagnosed by reverse transcriptase PCR that documented follow-up and symptom status at the beginning and end of follow-up, or modelling studies were included. One reviewer extracted data and a second verified the extraction, with disagreement resolved by discussion or a third reviewer. Risk of bias in empirical studies was assessed with an adapted checklist for case series and the relevance and credibility of modelling studies were assessed using a published checklist. We included a total of 94 studies. The overall estimate of the proportion of people who become infected with SARS-CoV-2 and remain asymptomatic throughout infection was 20% (95% CI 17-25) with a prediction interval of 3-67% in 79 studies that addressed this review question. There was some evidence that biases in the selection of participants influence the estimate. In seven studies of defined populations screened for SARS-CoV-2 and then followed, 31% (95% CI 26-37%, prediction interval 24-38%) remained asymptomatic. The proportion of people that is pre-symptomatic could not be summarised, owing to heterogeneity. The secondary attack rate was slightly lower in contacts of people with asymptomatic infection than those with symptomatic infection (relative risk 0.35, 95% CI 0.10-1.27). Modelling studies fit to data found a higher proportion of all SARS-CoV-2 infections resulting from transmission from pre-symptomatic individuals than from asymptomatic individuals. Limitations of the review include that most included studies were not designed to estimate the proportion of asymptomatic SARS-CoV-2 infections and were at risk of selection biases, we did not consider the possible impact of false negative RT-PCR results, which would underestimate the proportion of asymptomatic infections, and that the database does not include all sources. CONCLUSIONS The findings of this living systematic review of publications early in the pandemic suggest that most SARS-CoV-2 infections are not asymptomatic throughout the course of infection. The contribution of pre-symptomatic and asymptomatic infections to overall SARS-CoV-2 transmission means that combination prevention measures, with enhanced hand hygiene, masks, testing tracing and isolation strategies and social distancing, will continue to be needed. AUTHOR SUMMARY Why was this study done? ▪ The proportion of people who will remain asymptomatic throughout the course of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (covid-19), is not known. ▪ Studies that assess people at just one time point will overestimate the proportion of true asymptomatic infection because those who go on to develop covid-19 symptoms will be wrongly classified as asymptomatic, rather than pre-symptomatic. ▪ The amount, and infectiousness, of asymptomatic SARS-CoV-2 infection will determine what kind of measures will prevent transmission most effectively. What did the researchers do and find? ▪ We did a living systematic review through 10 June 2020, using automated workflows that speed up the review processes, and allow the review to be updated when relevant new evidence becomes available. ▪ Overall, in 79 studies in a range of different settings, 20% (95% confidence interval, CI 17–25%) of people with SARS-CoV-2 infection remained asymptomatic during follow-up, but biases in study designs limit the certainty of this estimate. ▪ We found some evidence that SARS-CoV-2 infection in contacts of people with asymptomatic infection is less likely than in contacts of people with symptomatic infection (relative risk 0.35, 95% CI 0.10-1.27). What do these findings mean? ▪ The findings of this living systematic review suggest that most SARS-CoV-2 infections are not asymptomatic throughout the course of infection. ▪ Future studies should be designed specifically to determine the true proportion of asymptomatic SARS-CoV-2 infections, using methods to minimise biases in the selection of study participants and ascertainment of symptom status during follow up. ▪ The contribution of pre-symptomatic and asymptomatic infections to overall SARS-CoV-2 trans
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Cited by
Sallis, R., Young, D. R., Tartof, S. Y., Sallis, J. F., Sall, J., Li, Q., Smith, G. N., & Cohen, D. A. (2021) · British Journal of Sports Medicine · doi:10.1136/bjsports-2021-104080 · Cited by 789
Miller, S. L., Nazaroff, W. W., Jimenez, J. L., Boerstra, A., Buonanno, G., Dancer, S. J., Kurnitski, J., Marr, L. C., Morawska, L., & Noakes, C. (2021) · Indoor Air · doi:10.1111/ina.12751 · Cited by 734
Virology, transmission, and pathogenesis of SARS-CoV-2
Cevik, M., Kuppalli, K., Kindrachuk, J., & Peiris, M. (2020) · BMJ · doi:10.1136/bmj.m3862 · Cited by 732
(2020) · doi:10.3138/jammi-2020-0030 · Cited by 664
Modeling transmission of SARS-CoV-2 Omicron in China
Cai, J., Deng, X., Yang, J., Sun, K., Liu, H., Chen, Z., Peng, C., Chen, X., Wu, Q., Zou, J., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01855-7 · Cited by 281
Metadata
- Authors
- Buitrago-Garcia, D., Egli-Gany, D., Counotte, M. J., Hossmann, S., Imeri, H., Ipekci, A. M., Salanti, G., & Low, N.
- Venue
- PLOS Medicine
- Publisher
- Public Library of Science (PLoS)
- Published
- 2020-09-22
- Volume
- 17
- Issue
- 9
- Pages
- e1003346
- ISSN
- 1549-1277 (ISSN-L)
- 1549-1676
- OpenAlex
- W3087248341
- Cited by
- 1,000
- References
- 8
- FWCI
- 8.52
- Type
- journal article
- Language
- en
- Open access
- gold
- Funders
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (320030_176233)
- European Union Horizon 2020 research and innovation programme (101003688)
- Swiss Government Excellence Scholarship (2019.0774)
- Swiss School of Public Health plus
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis. https://app.cochat.ai/papers/10.1371/journal.pmed.1003346
- The paper
- Buitrago-Garcia, D., Egli-Gany, D., Counotte, M. J., Hossmann, S., Imeri, H., Ipekci, A. M., Salanti, G., & Low, N. (2020). Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis. PLOS Medicine. https://doi.org/10.1371/journal.pmed.1003346
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.