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Potential Biases Arising from Epidemic Dynamics in Observational Seroprotection Studies

Authors
  • Kahn, Rebecca1, 1
  • Kennedy-Shaffer, Lee1, 1
  • Grad, Yonatan H1
  • Robins, James M1, 1
  • Lipsitch, Marc1, 1, 1
  • 1 Harvard TH Chan School of Public Health, USA , (United States)
Type
Published Article
Journal
American Journal of Epidemiology
Publisher
Oxford University Press
Publication Date
Sep 01, 2020
Identifiers
DOI: 10.1093/aje/kwaa188
PMID: 32870977
PMCID: PMC7499481
Source
PubMed Central
Keywords
License
Unknown

Abstract

The extent and duration of immunity following SARS-CoV-2 infection are critical outstanding questions about the epidemiology of this novel virus, and studies are needed to evaluate the effects of serostatus on reinfection. Understanding the potential sources of bias and methods to alleviate biases in these studies is important for informing their design and analysis. Confounding by individual-level risk factors in observational studies like these is relatively well appreciated. Here, we show how geographic structure and the underlying, natural dynamics of epidemics can also induce noncausal associations. We take the approach of simulating serologic studies in the context of an uncontrolled or a controlled epidemic, under different assumptions about whether prior infection does or does not protect an individual against subsequent infection, and using various designs and analytic approaches to analyze the simulated data. We find that in studies assessing whether seropositivity confers protection against future infection, comparing seropositive individuals to seronegative individuals with similar time-dependent patterns of exposure to infection, by stratifying or matching on geographic location and time of enrollment, is essential to prevent bias.

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