MATHEMATICAL MODELLING OF SPATIAL TRANSMISSION OF MALARIA
Abstract
ABSTRACT
This project presents an ideal mathematical model to analyze the spatial transmission of malaria, focusing on a large population size. The SEIR compartment model, which categorizes individuals into susceptible, exposed, infectious, and recovered classes, was employed to simulate the transmission dynamics of malaria. Using differential equations, the model explored the effects of infection rates, population dynamics, and intervention measures on malaria transmission. The basic reproduction number (R₀) was determined using the next-generation matrix approach, revealing that malaria transmission can be controlled when R₀ < 1, ensuring disease eradication. Conversely, and R₀ > 1 indicates sustained transmission. Numerical analysis of the model revealed how transmission peaks and lows vary over time and across different population sizes. The study also highlights the importance of vector control, early diagnosis, and effective treatment in managing malaria transmission.
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