Speaker
Description
Demography and social structures shape many aspects of an infectious disease outbreak in a population – from host susceptibility and exposure to transmission and health outcomes. However, the social forces that shape human behavior are difficult to quantify and often omitted from mathematical epidemiological models. In this talk, I will discuss some recent work using data from surveys to parameterize infectious disease models to capture heterogeneities in disease outcomes.
Bibliography
@article{feehan2021quantifying,
title={{Quantifying population contact patterns in the United States during the COVID-19 pandemic}},
author={Feehan, Dennis M and Mahmud, Ayesha S},
journal={Nature communications},
volume={12},
number={1},
pages={893},
year={2021},
publisher={Nature Publishing Group UK London}
}
@article{breen2022novel,
title={{Novel estimates reveal subnational heterogeneities in disease-relevant contact patterns in the United States}},
author={Breen, Casey F and Mahmud, Ayesha S and Feehan, Dennis M},
journal={PLOS Computational Biology},
volume={18},
number={12},
pages={e1010742},
year={2022},
publisher={Public Library of Science San Francisco, CA USA}
}
@article{roubenoff2023evaluating,
title={{Evaluating primary and booster vaccination prioritization strategies for COVID-19 by age and high-contact employment status using data from contact surveys}},
author={Roubenoff, Ethan and Feehan, Dennis and Mahmud, Ayesha S},
journal={Epidemics},
volume={43},
pages={100686},
year={2023},
publisher={Elsevier}
}
@article{soria2026partisan,
title={{Partisan differences in health behaviors can impact respiratory disease dynamics}},
author={Soria, Chris and Dor{\'e}lien, Audrey M and Feehan, Dennis M and Mahmud, Ayesha S},
journal={medRxiv},
pages={2026--01},
year={2026},
publisher={Cold Spring Harbor Laboratory Press}
}
