DOI
https://doi.org/10.25772/NZFF-9383
Author ORCID Identifier
0009-0001-8037-8569
Defense Date
2025
Document Type
Dissertation
Degree Name
Doctor of Philosophy
Department
Mathematical Sciences
First Advisor
Cheng Ly
Second Advisor
Michael A. Robert
Third Advisor
Suzanne Robertson
Fourth Advisor
Derek M. Johnson
Abstract
Dengue virus (DENV) causes over 390 million infections and around 40,000 deaths worldwide each year. DENV is primarily transmitted by the mosquito Aedes aegypti, and both the life cycle of these mosquitoes and DENV transmission are significantly impacted by temperature. In the temperate region of Central Argentina, where dengue outbreaks first began in 2009, outbreaks only occur following new introductions of DENV from other regions. Due to the relationships between temperature and DENV and temperature and Ae. aegypti, the risk of an outbreak changes throughout the year. Here, we develop and analyze mathematical models for both mosquito population dynamics and dengue fever spread. First, we present a non-autonomous ordinary differential equation model that includes temperature-dependent parameters associated with three mosquito life history traits to explore which temperature-dependent traits are most important for capturing mosquito egg count data. We expand our model by developing a stochastic continuous- time Markov chain model with temperature-dependent mosquito life history traits and DENV transmission-related parameters. With this model, we investigate the role of temperature—and increases therein—on seasonal variation in DENV transmission and outbreak risk. Lastly, we expand a deterministic analog of this model to include the effects of human movement on DENV transmission. For all three projects, we integrate climate, mosquito population survey, demographic, and/or dengue incidence data collected in the city of Córdoba, Argentina, which currently lies near the southernmost extremes of DENV transmission in the Western Hemisphere. We discuss the results of our work in the context of improving mosquito population and dengue epidemiological models to better understand drivers of DENV transmission and to inform mosquito control and dengue mitigation strategies in emerging regions.
Rights
© The Author
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
5-9-2025