Modeling Seasonal Malaria Transmission

A Methodology Connecting Regional Temperatures to Mosquito and Parasite Developmental Traits


  • Olivia Prosper Department of Mathematics, University of Tennessee Knoxville Author
  • Katharine Gurski Department of Mathematics, Howard University Author
  • Miranda I. Teboh-Ewungkem Department of Mathematics, Lehigh University Author
  • Angela Peace Department of Mathematics and Statistics, Texas Tech University Author
  • Zhilan Feng Department of Mathematics, Purdue University Author



Malaria, Seasonal, Temperature-dependent, Non-autonomous, Cubic splines, Data


Increasing temperatures have raised concerns over the potential effect on disease spread. Temperature is a well known factor affecting mosquito population dynamics and the development rate of the malaria parasite within the mosquito, and consequently, malaria transmission. A sinusoidal wave is commonly used to incorporate temperature effects in malaria models, however, we introduce a seasonal malaria framework that links data on temperature-dependent mosquito and parasite demographic traits to average monthly regional temperature data, without forcing a sinusoidal fit to the data. We introduce a spline methodology that maps temperature-dependent mosquito traits to time-varying model parameters. The resulting non-autonomous system of differential equations is used to study the impact of seasonality on malaria transmission dynamics and burden in a high and low malaria transmission region in Malawi. We present numerical simulations illustrating how temperature shifts alter the entomological inoculation rate and the number of malaria infections in these regions.







How to Cite

Modeling Seasonal Malaria Transmission: A Methodology Connecting Regional Temperatures to Mosquito and Parasite Developmental Traits. (2023). Letters in Biomathematics, 10(1), 3-27.

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