Evidence map›Paper›PMID 34376550›Full record

SynthesisProceedings of the National Academy of Sciences of the United States of America2021

Asymptomatic SARS-CoV-2 infection: A systematic review and meta-analysis.

Pratha Sah, Meagan C Fitzpatrick, Charlotte F Zimmer, Elaheh Abdollahi, Lyndon Juden-Kelly, Seyed M Moghadas, Burton H Singer, Alison P Galvani

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 272 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
272citing papers in PubMed, 6 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

272 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Inferring the true number of SARS-CoV-2 infections in Japan.Journal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy · 2022
    Pooled it
  6. Pooled it
  7. Trial
  8. Cost and cost-effectiveness of four different SARS-CoV-2 active surveillance strategies: evidence from a randomised control trial in Germany.The European journal of health economics : HEPAC : health economics in prevention and care · 2023
    Trial
  9. Trial
  10. Trial
  11. Economic evaluation of wastewater surveillance in Ontario, Canada, using COVID-19 as a case study.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2026
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

212 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Pratha SahCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.ORCID 0000-0001-8936-5871
Meagan C FitzpatrickCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.
Charlotte F ZimmerCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.
Elaheh AbdollahiAgent-Based Modelling Laboratory, York University, Toronto, ON M3J 1P3, Canada.
Lyndon Juden-KellyAgent-Based Modelling Laboratory, York University, Toronto, ON M3J 1P3, Canada.
Seyed M MoghadasAgent-Based Modelling Laboratory, York University, Toronto, ON M3J 1P3, Canada.
Burton H SingerEmerging Pathogens Institute, University of Florida, Gainesville, FL 32610 bhsinger@epi.ufl.edu.ORCID 0000-0002-5295-5971
Alison P GalvaniCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520.

Funding

Accelerating viral outbreak detection in US cities using mechanistic models, machine learning and diverse geospatial dataR01AI151176 · NIAID · YALE UNIVERSITY · PI GALVANI, ALISON P, MEYERS, LAUREN ANCEL · 2020 to 2024
$3.9M
NIAID NIH HHS R01 AI151176NIH HHS 1R01 AI151176-01
6 · The paper itself

Abstract

Quantification of asymptomatic infections is fundamental for effective public health responses to the COVID-19 pandemic. Discrepancies regarding the extent of asymptomaticity have arisen from inconsistent terminology as well as conflation of index and secondary cases which biases toward lower asymptomaticity. We searched PubMed, Embase, Web of Science, and World Health Organization Global Research Database on COVID-19 between January 1, 2020 and April 2, 2021 to identify studies that reported silent infections at the time of testing, whether presymptomatic or asymptomatic. Index cases were removed to minimize representational bias that would result in overestimation of symptomaticity. By analyzing over 350 studies, we estimate that the percentage of infections that never developed clinical symptoms, and thus were truly asymptomatic, was 35.1% (95% CI: 30.7 to 39.9%). At the time of testing, 42.8% (95% prediction interval: 5.2 to 91.1%) of cases exhibited no symptoms, a group comprising both asymptomatic and presymptomatic infections. Asymptomaticity was significantly lower among the elderly, at 19.7% (95% CI: 12.7 to 29.4%) compared with children at 46.7% (95% CI: 32.0 to 62.0%). We also found that cases with comorbidities had significantly lower asymptomaticity compared to cases with no underlying medical conditions. Without proactive policies to detect asymptomatic infections, such as rapid contact tracing, prolonged efforts for pandemic control may be needed even in the presence of vaccination.

Indexed as

Asymptomatic InfectionsCOVID-19HumansSARS-CoV-2asymptomatic fractioncomorbiditynovel coronaviruspresymptomaticsilent transmission

Identifiers

PMID34376550
PMCPMC8403749

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.