ArticleNature communications2020
Substantial underestimation of SARS-CoV-2 infection in the United States.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 209 papers, 6 of them syntheses that pooled it.
What it found
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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.
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.
Who cites it
209 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Determining the timing of respiratory syncytial virus (RSV) epidemics: a systematic review, 2016 to 2021; method categorisation and identification of influencing factors.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2024Pooled it
- Prevalence of SARS-CoV-2 infection among oral health care workers worldwide: A meta-analysis.Community dentistry and oral epidemiology · 2023Pooled it
- Impaired glucose regulation, SARS-CoV-2 infections and adverse COVID-19 outcomes.Translational research : the journal of laboratory and clinical medicine · 2022Pooled it
- Fatigue and cognitive impairment in Post-COVID-19 Syndrome: A systematic review and meta-analysis.Brain, behavior, and immunity · 2022Pooled it
- Prevalence of Coronavirus Disease 2019 (COVID-19) in Different Clinical Stages before the National COVID-19 Vaccination Programme in Malaysia: A Systematic Review and Meta-Analysis.International journal of environmental research and public health · 2022Pooled it
- Current evidence for COVID-19 therapies: a systematic literature review.European respiratory review : an official journal of the European Respiratory Society · 2021Pooled it
- Safety and immunogenicity of the FINLAY-FR-1A vaccine in COVID-19 convalescent participants: an open-label phase 2a and double-blind, randomised, placebo-controlled, phase 2b, seamless, clinical trial.The Lancet. Respiratory medicine · 2022Trial
- Multi-event dynamic capture-recapture model for big data: Estimating undetected COVID-19 cases in British Columbia, Canada.Infectious Disease Modelling · 2026Article
- Characteristics of COVID-19 cases and factors associated with disease severity in Lao People's Democratic Republic: a nationwide study.BMC infectious diseases · 2026Observational
- Early Detection Intervals for Evaluating Event-Based Surveillance System: Reference Dataset Development Study.JMIR public health and surveillance · 2026Article
- COVID-19 related brain MRI changes and anticipated long-term dementia risk: A front-door-criterion-inspired approach.Annals of epidemiology · 2026Article
- Comparison of Mental Illness Comorbidity Pre-Pandemic vs. Pandemic-Era and Associations with Clinical and Demographic Characteristics for Virginia Public Hospital Inpatient Discharges with a Substance Use Disorder.International journal of environmental research and public health · 2026Article
- Article
- Comparing Multiple Imputation Methods to Address Missing Patient Demographics in Immunization Information Systems: Retrospective Cohort Study.JMIR public health and surveillance · 2025Article
- Solid Evidence and Liquid Gold: Trade-Offs of Processing Settled Solids, Whole Influent, or Centrifuged Influent for Codetecting Viral, Bacterial, and Eukaryotic Pathogens in Wastewater.Environmental science & technology · 2025Article
- Back-projection improves inference from sparsely sampled genomic surveillance data.bioRxiv : the preprint server for biology · 2025Article
- A Retrospective Study of the Effects of COVID-19 Non-Pharmaceutical Interventions on Influenza in Canada.Infectious disease reports · 2025Article
- Simulation-based inference of the time-dependent reproduction number from temporally aggregated and under-reported disease incidence time series data.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- Seroepidemiological investigation of SARS-CoV-2 infection and risk factors in Indonesia before mass COVID-19 vaccination.Narra J · 2025Article
- Interpretation of indoor air surveillance for respiratory infections: a prospective longitudinal observational study in a childcare setting.EBioMedicine · 2025Observational
149 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic response. Confirmed COVID-19 case counts in the U.S. do not capture the total burden of the pandemic because testing has been primarily restricted to individuals with moderate to severe symptoms due to limited test availability. Here, we use a semi-Bayesian probabilistic bias analysis to account for incomplete testing and imperfect diagnostic accuracy. We estimate 6,454,951 cumulative infections compared to 721,245 confirmed cases (1.9% vs. 0.2% of the population) in the United States as of April 18, 2020. Accounting for uncertainty, the number of infections during this period was 3 to 20 times higher than the number of confirmed cases. 86% (simulation interval: 64-99%) of this difference is due to incomplete testing, while 14% (0.3-36%) is due to imperfect test accuracy. The approach can readily be applied in future studies in other locations or at finer spatial scale to correct for biased testing and imperfect diagnostic accuracy to provide a more realistic assessment of COVID-19 burden.
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Registered trials
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.