Mathematical modelling of malaria spread in response to climate variability in Sudan

Abstract

Malaria continues to represent a significant public health concern in Sudan‎, ‎with cases rising over 40% from 2015 to 2020‎. ‎This research investigates how climate change affects malaria transmission patterns using a mathematical model in an ordinary differential equation framework‎. ‎The analysis involves calculating the basic reproduction number and evaluating the system's qualitative properties to gain insights into disease dynamics‎. ‎Additionally‎, ‎a sensitivity analysis is conducted to evaluate how climatic conditions‎, ‎e.g.‎, ‎rainfall and temperature, influence key model parameters‎. ‎Statistical approaches are utilized to estimate parameters‎ ‎and calibrate the model using empirical data from Sudan‎, ‎ensuring consistency between the model and observed trends‎. ‎Numerical simulations demonstrate the growing influence of climate variability on the spatial distribution of malaria vectors and the transmission progression over time‎. ‎The study establishes a strong association between climatic changes and the exacerbation of malaria prevalence in Sudan‎. ‎These findings emphasize the urgent need for climate-adaptive strategies‎, ‎including improved vector control‎, ‎strengthened surveillance systems‎, ‎and climate-resilient public health interventions‎, ‎to address the increased risks posed by changing environmental conditions‎. ‎The research provides valuable insights to inform evidence-based policies aimed at reducing malaria transmission in Sudan and other regions that are experiencing similar challenges due to climate change‎.