Relative Risk Estimation for Malaria Disease Mapping in Malaysia based on Stochastic SIR-SI Model
Keywords:
malaria disease, disease mapping, relative risk estimation, SIR-SI model, stochastic modelAbstract
Disease mapping is a study on the geographical distribution of a disease to represent the epidemiology data spatially. The production of maps is important to identify areas that deserve closer scrutiny or more attention. In this study, a mosquito-borne disease called Malaria is the focus of our application. Malaria disease is caused by parasites of the genus Plasmodium and is transmitted to people through the bites of infected female Anopheles mosquitoes. Precautionary steps need to be considered in order to avoid the malaria virus from spreading around the world, especially in the tropical and subtropical countries, which would subsequently increase the number of Malaria cases. Thus, the purpose of this paper is to discuss a stochastic model employed to estimate the relative risk of malaria disease in Malaysia. The outcomes of the analysis include a Malaria risk map for all 13 states and 3 federal territories in Malaysia, revealing the high and low risk areas of Malaria occurrences.
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