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International Journal of Latest Research in Science and Technology

DOI:10.29111/ijlrst   ISRA Impact Factor:3.35

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STATISTICAL ANALYSIS OF RISK FACTORS OF MALARIA RELATED IN-HOSPITAL MORTALITY: A CASE STUDY AT BUSHULO MAJOR HEALTH CENTER, HAWASSA

Research Paper Open Access

International Journal of Latest Research in Science and Technology Vol.4 Issue 5, pp 32-42,Year 2015

STATISTICAL ANALYSIS OF RISK FACTORS OF MALARIA RELATED IN-HOSPITAL MORTALITY: A CASE STUDY AT BUSHULO MAJOR HEALTH CENTER, HAWASSA

Chala Gemechu Gute , Dr.O.Chandrasekhara Reddy,Ayele Taye, Dr.K.Vasudeva Rao

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Received : 22 September 2015; Accepted : 05 October 2015 ; Published : 31 October 2015

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Abstract

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; so that modeling and simulating the related risk factors. The data were taken from hospital records at Bushulo major health center from June 2009 to June 2012, Hawassa. 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 simulation analysis age, residence, time from symptom onset to diagnoses, type of malaria species diagnosed, body temperature in the last diagnoses, malaria complicated, pregnancy cases, total length of stay in hospitalization, referral status and season when patient diagnosed, were found to be statistically significant at 5% level of significance. The classical logistic regression analysis could select the first eight of these as significant predictors. Model comparison also revealed that, the Bayesian modeling approach has given estimates of the parameters with smaller standard error values showing that, with appropriate choice of prior distributions, the Bayesian modeling approach might lead to a more accurate estimation than the classical approach. It can be concluded from this study that the most contributing risk factors of malaria related in-hospital mortality in the health center are under five age group, rural resident, P.falciprum type of malaria species, having malaria complicated cases, longer time (days) from symptoms onset to diagnoses, wet season, high body temperature in the last diagnoses, women of pregnancy cases, shorter time (days) of stay in hospitalization.

Key Words   
Bayesian, Logistic regression, Malaria, Risk factors, In-hospital mortality Bushulo

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To cite this article

Chala Gemechu Gute , Dr.O.Chandrasekhara Reddy,Ayele Taye, Dr.K.Vasudeva Rao , " Statistical Analysis Of Risk Factors Of Malaria Related In-hospital Mortality: A Case Study At Bushulo Major Health Center, Hawassa ", International Journal of Latest Research in Science and Technology . Vol. 4, Issue 5, pp 32-42 , 2015

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