My research lies at the intersection of mathematical modeling, dynamical systems, and theoretical ecology, focusing on developing mathematical frameworks to understand the transmission dynamics of disease, particularly those spread by mosquitoes. Motivated by pressing global health challenges due to diseases like malaria, dengue, and Zika virus, I aim to uncover fundamental properties of disease transmission processes and to advance the mathematical theory used in their analysis. By combining tools from differential equations, bifurcation theory, and stochastic processes with novel computational techniques, my work bridges mathematics and ecology.
How will climate change impact mosquito-borne disease? Which regions should expect to see more outbreaks in the future? Will some regions with high levels of transmission of dengue or malaria see fewer outbreaks because of climate change? Across many disciplines and across the world, many researchers are working to answer these urgent questions. My approach to these questions places the focus on the traits and behavior of the vertebrate host - humans or other animals - instead of solely on the mosquito vector.
Global climate change will almost surely shift temperature regimes and facilitate the invasion of mosquitoes and the pathogens they vector into new regions. Our understanding of the thermal niche of mosquitoes and their pathogens is mostly determined from laboratory experiments which focus only on mosquitoes and not on the vertebrate host (human or animal) which forms the other half of the transmission equation. By explicitly incorporating host traits and behavior into transmission models, we found that the thermal niche - the temperatures at which outbreaks can occur - and the thermal optimum - the temperature where outbreak risk is highest - are both dependent on the traits of the host species in question, in particular the population density of the host and its tolerance towards mosquito biting (Dahlin et al., 2024). This suggests that more data is needed on traits of host populations in order to assess the impact of climate change on mosquito-borne disease.
As we have seen with the COVID-19 pandemic, our behavior plays a large role in the probability, magnitude, and duration of outbreaks. I am interested in understanding how movement or avoidance behaviors affect disease transmission. There are two avenues of research I am pursuing in these theme:
How do grouping behaviors, which may vary throughout the day or season, drive or suppress transmission in clustered communities?
How effective are defensive behaviors against biting vectors at suppressing vector-borne disease outbreaks?
While the spread of pathogens transcends geographical boundaries, the management of infectious diseases typically occurs within distinct geopolitical boundaries. In Howerton, Dahlin, et al. 2023, we investigated the extent to which different governance structures affect the costs associated with infectious disease suppression in two-patch systems using an optimal control framework. We compared results from a model of cholera and a separate model of Ebola, to understand the interplay between transmission mode, governance structure, and the optimal control of outbreaks. We found that the governance structure has a meaningful impact on the allocation of resources and burden of cases, although the difference in total costs is minimal. Understanding how governance structure affects both the optimal control functions and epidemiological outcomes is therefore crucial for the effective management of infectious diseases going forward.
Preprints:
9. Dahlin, Kyle, Michael A. Robert, and Lauren M. Childs. 2025. “Once Bitten, Twice Shy: A Modeling Framework for Incorporating Heterogeneous Mosquito Biting into Transmission Models.” arXiv [q-Bio.PE]. arXiv. https://doi.org/10.48550/arXiv.2503.10585
8. Gibbs, Theo L., Kyle Dahlin, Joe Brennan, Cynthia B. Silveira, and Lisa C. McManus. 2024. “Coexistence of Bacteria with a Competition-Colonization Tradeoff on a Dynamic Coral Host.” bioRxiv. https://doi.org/10.1101/2024.09.15.612558.
7. Dahlin, Kyle J-M, Suzanne M. O’Regan, John Paul Schmidt, Barbara A. Han, and John M. Drake. 2024. “Fast-Lived Vertebrate Hosts Exhibit Higher Potential for Mosquito-Borne Parasite Transmission.” bioRxiv. https://doi.org/10.1101/2024.10.21.619438.
Published Articles:
6. Dahlin, Kyle J-M, Elisa Van Cleemput, Subodh Adhikari, Karen Castillioni, and Lynette R. Strickland. 2025. “Simulated Biodiversity Hotspots from Traditional Ecological Knowledge and Western Metrics Do Not Always Overlap.” Communications Earth & Environment 6 (1): 1–9. https://doi.org/10.1038/s43247-025-02309-x.
5. Dahlin, Kyle, Suzanne M. O’Regan, Barbara A. Han, John Paul Schmidt, and John M. Drake. 2024. “Impacts of Host Availability and Temperature on Mosquito‐borne Parasite Transmission.” Ecological Monographs, March. https://doi.org/10.1002/ecm.1603.
4. Howerton, Emily, Kyle Dahlin, Christina J. Edholm, Lindsey Fox, Margaret Reynolds, Brandon Hollingsworth, George Lytle, Melody Walker, Julie Blackwood, and Suzanne Lenhart. 2023. “The Effect of Governance Structures on Optimal Control of Two-Patch Epidemic Models.” Journal of Mathematical Biology 87 (5): 74. https://doi.org/10.1007/s00285-023-02001-8.
3. Drake, John M., Kyle Dahlin, Pejman Rohani, and Andreas Handel. 2021. “Five Approaches to the Suppression of SARS-CoV-2 without Intensive Social Distancing.” Proceedings of the Royal Society B: Biological Sciences 288 (1949): 20203074. https://doi.org/10.1098/rspb.2020.3074.
2. Dahlin, Kyle, and Zhilan Feng. 2019. “Modeling the Population Impacts of Avian Malaria on Hawaiian Honeycreepers: Bifurcation Analysis and Implications for Conservation.” Mathematical Biosciences 318 (December): 108268. https://doi.org/10.1016/j.mbs.2019.108268.
1. Dahlin, Kyle, E. Koenig, A. Laubmeier, A. Wehn, and K. Rios-Soto (2012). Competition Model between the Invasive Sahara Mustard and Native Plants in the Sonoran Desert. Mathematical and Theoretical Biology Institute Technical Reports 09-01M 2012.