12–17 Jul 2026
University of Graz
Europe/Vienna timezone

Incorporating thermal performance curves into population dynamic models for the West Nile vector, Culex pipiens

MS169-06
17 Jul 2026, 11:00
20m
15.02 - HS (University of Graz)

15.02 - HS

University of Graz

121

Speaker

Ben Bruncati (Virginia Tech, USA)

Description

Culex mosquitoes are a growing concern in North America given their ability to transmit diseases such as West Nile Virus and adapt their thermal tolerances. Culex pipiens, one species found in temperate environments, is predicted to continue to spread north and south of the equator as environmental conditions become more favorable. As climate change persists, it is of high importance to understand how temperature influences Culex pipiens life-history traits and what impacts this might have on transmission of West Nile and other pathogens. In this work, we explore potential functional forms of thermal performance curves (TPCs) for key traits of Culex pipiens by fitting TPCs to temperature-dependent trait data. We found the best-fitting TPCs for the following traits: age-specific mortality, fecundity, juvenile development, and survival to adulthood.
We then incorporated TPCs for each trait as a parameter function in a system of stage-structured differential equations of Culex pipiens population dynamics and we explored potential impacts on population dynamics of different TPC curves. Separately toggling both rates yielded notable differences in projected population counts and predicted peaks. We also compared the adult population projections from our model to surveillance data to find the best fitting model and see which fits were strongly supported by the data. Mathematical models such as ours are useful for predicting the potential population dynamics of Culex pipiens in specific geographic regions and for informing public health interventions. Further investigation is needed from additional data collection to explore other potential TPCs which may help to further improve these mathematical models.

Author

Ben Bruncati (Virginia Tech, USA)

Co-authors

Helle Aronson (Virginia Tech) Chloé Lahondère (Virginia Tech) Michael Robert (Virginia Tech)

Presentation materials

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