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Potential biases arising from epidemic dynamics in observational seroprotection studies

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 i...

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Autores principales: Kahn, Rebecca, Kennedy-Shaffer, Lee, Grad, Yonatan H., Robins, James M., Lipsitch, Marc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273253/
https://www.ncbi.nlm.nih.gov/pubmed/32511485
http://dx.doi.org/10.1101/2020.05.02.20088765
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author Kahn, Rebecca
Kennedy-Shaffer, Lee
Grad, Yonatan H.
Robins, James M.
Lipsitch, Marc
author_facet Kahn, Rebecca
Kennedy-Shaffer, Lee
Grad, Yonatan H.
Robins, James M.
Lipsitch, Marc
author_sort Kahn, Rebecca
collection PubMed
description 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 the efficacy of serostatus on 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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spelling pubmed-72732532020-06-07 Potential biases arising from epidemic dynamics in observational seroprotection studies Kahn, Rebecca Kennedy-Shaffer, Lee Grad, Yonatan H. Robins, James M. Lipsitch, Marc medRxiv Article 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 the efficacy of serostatus on 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. Cold Spring Harbor Laboratory 2020-05-06 /pmc/articles/PMC7273253/ /pubmed/32511485 http://dx.doi.org/10.1101/2020.05.02.20088765 Text en https://creativecommons.org/licenses/by/4.0/It is made available under a CC-BY 4.0 International license (https://creativecommons.org/licenses/by/4.0/)
spellingShingle Article
Kahn, Rebecca
Kennedy-Shaffer, Lee
Grad, Yonatan H.
Robins, James M.
Lipsitch, Marc
Potential biases arising from epidemic dynamics in observational seroprotection studies
title Potential biases arising from epidemic dynamics in observational seroprotection studies
title_full Potential biases arising from epidemic dynamics in observational seroprotection studies
title_fullStr Potential biases arising from epidemic dynamics in observational seroprotection studies
title_full_unstemmed Potential biases arising from epidemic dynamics in observational seroprotection studies
title_short Potential biases arising from epidemic dynamics in observational seroprotection studies
title_sort potential biases arising from epidemic dynamics in observational seroprotection studies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273253/
https://www.ncbi.nlm.nih.gov/pubmed/32511485
http://dx.doi.org/10.1101/2020.05.02.20088765
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