ArticleCommunications medicine2022
Estimating the COVID-19 infection fatality ratio accounting for seroreversion using statistical modelling.
Article in Communications medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled 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.
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
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Dynamics of SARS-CoV-2 seroassay sensitivity: a systematic review and modelling study.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2023Pooled it
- Agreement between seroprevalence- and model-based estimates of COVID-19 burden.Global health action · 2026Article
- An agent-based model of the effects of limited vaccination on novel respiratory infections.Journal of clinical epidemiology · 2026Article
- A Bayesian estimator of the real-time case fatality rate in emerging pandemic to inform public health policy-making.BMC infectious diseases · 2026Article
- Estimating the incidence of SARS-CoV-2 infections by jointly modelling seroprevalence, hospitalization and mortality data, February 2020 - January 2021, Belgium.Archives of public health = Archives belges de sante publique · 2026Article
- COVID-19, infection fatality rate (IFR) implied by the serology, antibody, testing in New York City.Infectious Disease Modelling · 2026Article
- Mobility-driven synthetic contact matrices as a scalable solution for real-time pandemic response modeling.Nature communications · 2026Article
- Article
- One parameter stochastic distribution of ratio for cross-disciplinary applications: system reliability, healthcare, and energy consumption.Journal of applied statistics · 2026Article
- The Mathematics of Serocatalytic Models With Applications to Public Health Data.Statistics in medicine · 2025Article
- Identification of undetected SARS-CoV-2 infections by clustering of Nucleocapsid antibody trajectories.Nature communications · 2025Article
- Serodynamics: A primer and synthetic review of methods for epidemiological inference using serological data.Epidemics · 2024Review
- Estimating geographic variation of infection fatality ratios during epidemics.Infectious Disease Modelling · 2024Article
- Estimating SARS-CoV-2 seroprevalence.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2023Article
- Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context.Nature communications · 2023Article
- Alternative epidemic indicators for COVID-19 in three settings with incomplete death registration systems.Science advances · 2023Article
- Estimating infection fatality risk and ascertainment bias of COVID-19 in Osaka, Japan from February 2020 to January 2022.Scientific reports · 2023Article
- Population-Level Relative Effectiveness of the COVID-19 Vaccines and the Contribution of Naturally Acquired Immunity.The Journal of infectious diseases · 2023Article
- Article
- The two-stage molecular scenery of SARS-CoV-2 infection with implications to disease severity: An in-silico quest.Frontiers in immunology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
22 authors.
Funding
Abstract
Background: The infection fatality ratio (IFR) is a key statistic for estimating the burden of coronavirus disease 2019 (COVID-19) and has been continuously debated throughout the COVID-19 pandemic. The age-specific IFR can be quantified using antibody surveys to estimate total infections, but requires consideration of delay-distributions from time from infection to seroconversion, time to death, and time to seroreversion (i.e. antibody waning) alongside serologic test sensitivity and specificity. Previous IFR estimates have not fully propagated uncertainty or accounted for these potential biases, particularly seroreversion. Methods: We built a Bayesian statistical model that incorporates these factors and applied this model to simulated data and 10 serologic studies from different countries. Results: We demonstrate that seroreversion becomes a crucial factor as time accrues but is less important during first-wave, short-term dynamics. We additionally show that disaggregating surveys by regions with higher versus lower disease burden can inform serologic test specificity estimates. The overall IFR in each setting was estimated at 0.49-2.53%. Conclusion: We developed a robust statistical framework to account for full uncertainties in the parameters determining IFR. We provide code for others to apply these methods to further datasets and future epidemics.
Indexed as
Identifiers
What OpenQuestion holds
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.