Dissertation

Improving Mathematical, Computational, and Analytical Tools for Epidemic Outbreak Preparedness and Response

Kummer, Allisandra G

2025

Overview

Mathematical, computational, and analytical models have been widely used to improve the understanding infectious disease spread and evaluate the impact on public health. Our aim is to improve upon the state-of-the-art approaches by designing modeling tools that integrate new data sources on human host and pathogen vector behaviors. First, we examined the ecological and environmental drivers of arboviral disease spread to inform mosquito control operations by addressing: i) when mosquito control strategies need to be deployed and ii) how to design mosquito control strategies to prevent and mitigate outbreaks. To understand when control strategies need deployed, we developed a forecasting platform that provides precise and accurate real-time forecasts of Aedes aegypti relative abundance to improve situational awareness. To guide the design of mosquito control strategies, we developed a model accounting for mosquito diel activity to evaluate the entomological and epidemiological effects of adulticide spraying at different times of the day in Miami-Dade County, FL, and Brownsville, TX. We used as a case study. Second, we examined the role of social contact patterns in shaping the spread of respiratory infectious disease by addressing: i) how heterogeneities in contact patterns shape the heterogeneities in infectious diseases, ii) how social contact networks impact the estimation of key transmission parameters, and iii) how changes in contact patterns over time affect epidemic dynamics. To investigate the impact of heterogeneities in contacts on the epidemiology of respiratory infectious diseases, we collected and analyzed primary data on the contact patterns of a representative sample of the US population. To estimate the extent to which social clusters, such as households, determine key epidemiological parameters, we developed a multi-scale model that combines within-host viral dynamics and between-hosts pathogen transmission. To demonstrate how changes in contact patterns over time affect epidemic dynamics, we developed statistical and mathematical models to determine whether contact patterns in Shanghai, China, follow a seasonal trend and their impact on influenza seasonality. Our findings show how integrating new data streams into modeling tools can improve our understanding of the epidemiology of infectious diseases as well as providing actionable insights for public health decision making.

• Publisher: ProQuest Dissertations & Theses
• Subject: Epidemiology / Health care management / Public health
• ISBN: 9798286428694