Bayesian Modeling on Risk Factors of Malaria Related Mortality

Malaria is a major challenge to public health and socio-economic development worldwide and in sub -Saharan Africa in particular. It causes an estimated 300 to 500 million cases and 1.5 to 2.7 million deaths worldwide each year, of which 80% of the cases and 90% of the deaths occur in Sub-Saharan Africa. The main objective of this study was to identify the risk factors of malaria related in-hospital mortality. The data were taken from hospital records at Bushulo major health center from June 2007 to June 2010, Hawassa, Ethiopia. From a total of 6594 laboratory confirmed malaria positive in the health center, a sample of 539 patients were selected using stratified random sampling technique. The data were analyzed using the classical logistic regression and Bayesian Logistic regression approaches. In this effort the two approaches were compared using standard errors of model parameters. The results of the study showed that 78.5% of malaria patients were found to be discharged while the rest 21.5% died of malaria in the health center. From Bayesian logistic regression analysis.....

Autorentext

Chala Gemechu, MSc: Applied Statistics at Hawassa University. Lecturer at Debre Markos University, Ethiopia. Awraris Kassa,MPH: Epidemiology & Bio-statistics at University of Gondar. Head of Statistics Department at DebreMarkos University, Ethiopia.