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Protective Population Behavior Change in Outbreaks of Emerging Infectious Disease

Undergraduate #249
Discipline: Mathematics and Statistics
Subcategory: Mathematics and Statistics

Evans Lodge - Calvin College
Co-Author(s): John M. Drake, University of Georgia, Athens, GA



In outbreaks of emerging infectious disease, public health interventions aim at increasing the speed with which infected individuals are removed from the susceptible population, limiting opportunities for secondary infection. Isolation, hospitalization, and barrier-nursing practices are crucial for controlling disease spread in these contexts. Ebola virus disease (EVD), Severe Acute Respiratory Syndrome (SARS), and Middle East Respiratory Syndrome (MERS) are all caused by zoonotic viruses that have spread in significant international outbreaks in the past, and we hypothesize that different geographies, political environments, and public health infrastructures will reveal distinct behavior development rates in different outbreaks. Here, we use patient-level data from the 2014-2015 Liberian Ebola epidemic, 2003 Hong Kong SARS epidemic, 2014 Saudi Arabia MERS outbreaks, and 2015 South Korea MERS outbreak to quantify changing removal rates, burial practices, contact tracing, and other measures of protective behavior change. Using the removal rate, γ, as a measure of protective behavior change allows direct comparison of health behavior development in different outbreaks and locations. Robust regression analysis and analyses of covariance are used to estimate the rate at which γ increases in each outbreak by epidemic week and serial interval. Measured interactions between models show that mean removal rates varied within a factor of three, falling between the 2003 Hong Kong SARS outbreak and the 2014-2015 Ebola epidemic in Liberia. This research is important for disease modelers and epidemiologists interested in social responses to emerging infections, where removal rates and public health behaviors change dramatically as disease prevalence increases throughout an epidemic. We hope to expand this analysis to include the 2003 SARS outbreak in Singapore in order to directly compare distinct locations of the worldwide SARS outbreak.

Funder Acknowledgement(s): National Science Foundation

Faculty Advisor: John M. Drake,

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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