Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys
- University of Colorado Boulder, United States
- Colorado State University, United States
- Harvard TH Chan School of Public Health, United States
- Princeton University, United States
- Harvard T H Chan School of Public Health, United States
Abstract
Establishing how many people have been infected by SARS-CoV-2 remains an urgent priority for controlling the COVID-19 pandemic. Serological tests that identify past infection can be used to estimate cumulative incidence, but the relative accuracy and robustness of various sampling strategies has been unclear. We developed a flexible framework that integrates uncertainty from test characteristics, sample size, and heterogeneity in seroprevalence across subpopulations to compare estimates from sampling schemes. Using the same framework and making the assumption that seropositivity indicates immune protection, we propagated estimates and uncertainty through dynamical models to assess uncertainty in the epidemiological parameters needed to evaluate public health interventions, and found that sampling schemes informed by demographics and contact networks outperform uniform sampling. The framework can be adapted to optimize serosurvey design given test characteristics and capacity, population demography, sampling strategy, and modeling approach, and can be tailored to support decision-making around introducing or removing interventions.
Data availability
Reproduction code is open source and provided by the authors at github.com/LarremoreLab/covid_serological_sampling
Article and author information
Author details
Daniel B Larremore
C Jessica E Metcalf
Funding
Morris-Singer Fund for the Center for Communicable Disease Dynamics
- Stephen M Kissler
- Caroline Buckee
- Yonatan H Grad
National Cancer Institute (1U01CA261277-01)
- Daniel B Larremore
- Yonatan H Grad
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Larremore et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys
eLife 10:e64206.
https://doi.org/10.7554/eLife.64206
Further reading
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- Medicine
- Microbiology and Infectious Disease
- Epidemiology and Global Health
- Immunology and Inflammation
eLife has published articles on a wide range of infectious diseases, including COVID-19, influenza, tuberculosis, HIV/AIDS, malaria and typhoid fever.
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- Epidemiology and Global Health
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