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Updated: Aug 19, 2026

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
A weather-driven model of malaria transmission
Moshe B Hoshen1, Andrew P Morse
1Virtual Population Laboratory, Department of Physics, University of Liverpool, Liverpool L69 7ZE, UK. hoshen@liv.ac.uk
Background:
Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission.
Methods:
This paper describes a mathematical-biological model of the parasite dynamics, comprising both the weather-dependent within-vector stages and the weather-independent within-host stages.
Results:
Numerical evaluations of the model in both time and space show that it qualitatively reconstructs the prevalence of infection.
Conclusion:
A process-based modelling structure has been developed that may be suitable for the simulation of malaria forecasts based on seasonal weather forecasts.
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