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Superspreaders and their role in epidemics: a stochastic modeling approach

Abstract

Superspreader events have played a pivotal role in recent emerging diseases. In disease outbreak studies, host heterogeneity based on demographic (e.g. age, sex, vaccination status) and environmental (e.g. climate, urban/rural residence, clinics) factors are critical for the spread of infectious diseases, such as Ebola and Middle East Respiratory Syndrome (MERS). In epidemic models, the transmission rate, denoted by beta, is equivalent to the product of the probability of successfully transmitting the disease and the contact rate. These transmission rates can vary as demographic and environmental factors are altered naturally or due to modified behaviors in response to the implementation of public health strategies. In this work, we explore the effect of demographic and environmental variability on human-to-human disease transmission rates among superspreaders (individuals with high transmission rates). This work is done in collaboration with Linda J.S Allen, Christina Edholm, Anarina Murillo, Xueying Wang, Angela Peace, Nika Shakiba, and Blessing Emerenini.

People

Funding Source

American Institute of Mathematics - Structured Quartet Research Ensembles (SQuaREs)

Project Period

2020-2020