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Research Paper | Statistics | Nigeria | Volume 12 Issue 8, August 2023
Bayesian Approach to Modelling Malaria Incidence in Pregnant Women in ADO-ODO/OTTA, Ogun State, Nigeria
Abstract: The protection of pregnant women living in malaria-endemic countries has been of particular interest to many National Malaria Control Programmes because, in spite of interventions, there have been much reported cases of mortality of pregnant women including infant mortality due to malaria. This study presents a Bayesian approach to model the incidence of malaria in pregnant women in Ado-Odo /Otta, Ogun State, Nigeria. The study focuses on the impact of gravidity, gestation period, and age on the probability of malaria incidence. The Bayesian inference for logistic regression models was derived using a Markov Chain Monte Carlo MCMC method. The results indicate that gestation and gravidity significantly affect the malaria status of pregnant women, with the incidence of malaria being higher during the first and third trimesters of gestation. The study provides a new perspective on the modelling of malaria incidence in pregnant women using a Bayesian approach.
Keywords: Malaria Incidence, Gravidity, Gestation period, Pregnant Women, Bayesian Approach, Logistics Regression Models, Markov Chain Monte Carlo
Edition: Volume 12 Issue 8, August 2023,
Pages: 907 - 911