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Citation

Zivich, Paul N.; Volfovsky, Alexander; Moody, James W.; & Aiello, Allison E. (2021). Assortativity Can Lead to Bias in Epidemiologic Studies of Contagious Outcomes: a Simulated Example in the Context of Vaccination. American Journal of Epidemiology, 190(11), 2442-2452. PMCID: PMC8799903

Abstract

Assortativity is the tendency of individuals connected in a network to share traits and behaviors. Through simulations, we demonstrated the potential for bias resulting from assortativity by vaccination, where vaccinated individuals are more likely to be connected with other vaccinated individuals. We simulated outbreaks of a hypothetical infectious disease and vaccine on a randomly generated network and a contact network of university students living on-campus. We varied protection of the vaccine to the individual, transmission potential of vaccinated-but-infected individuals, and assortativity by vaccination. We compared a traditional approach, which ignores the structural features of a network, to simple approaches which summarized information from the network. The traditional approach resulted in biased estimates of the unit-treatment effect when there was assortativity by vaccination. Several different approaches that included summary measures from the network reduced bias and improved confidence interval coverage. Through simulations, we showed the pitfalls of ignoring assortativity by vaccination. While our example is described in terms of vaccines, our results apply more widely to exposures for contagious outcomes. Assortativity should be considered when evaluating exposures for contagious outcomes.

URL

https://doi.org/10.1093/aje/kwab167

Reference Type

Journal Article

Year Published

2021

Journal Title

American Journal of Epidemiology

Author(s)

Zivich, Paul N.
Volfovsky, Alexander
Moody, James W.
Aiello, Allison E.

Article Type

Regular

PMCID

PMC8799903

Continent/Country

United States of America

State

Nonspecific

ORCiD

Aiello - 0000-0001-7029-2537
Zivich - 0000-0002-9932-1095