Modelling Malaria Incidence in the Limpopo Province, South Africa: Comparison of Classical and Bayesian Methods of Estimation

International Journal of Environmental Research and Public Health
Makwelantle Asnath SehlabanaAlexander Boateng

Abstract

Malaria infects and kills millions of people in Africa, predominantly in hot regions where temperatures during the day and night are typically high. In South Africa, Limpopo Province is the hottest province in the country and therefore prone to malaria incidence. The districts of Vhembe, Mopani and Sekhukhune are the hottest districts in the province. Malaria cases in these districts are common and malaria is among the leading causes of illness and deaths in these districts. Factors contributing to malaria incidence in Limpopo Province have not been deeply investigated, aside from the general knowledge that the province is the hottest in South Africa. Bayesian and classical methods of estimation have been applied and compared on the effect of climatic factors on malaria incidence. Credible and confidence intervals from a negative binomial model estimated via Bayesian estimation and maximum likelihood estimation, respectively, were utilized in the comparison process. Overall assumptions underpinning each method were given. The Bayesian method appeared more robust than the classical method in analysing malaria incidence in Limpopo Province. The classical method identified rainfall and temperature during the night to be significan...Continue Reading

References

Feb 8, 2002·Nature·Jeffrey Sachs, Pia Malaney
Aug 8, 2008·Geospatial Health·L GosoniuT Smith
Aug 30, 2008·Malaria Journal·Annette A M GerritsenMartin P Grobusch
Nov 29, 2011·Asian Pacific Journal of Tropical Medicine·Farid ZayeriHasan Pirhosseini
Nov 9, 2017·International Journal of Environmental Research and Public Health·Abiodun M AdeolaTemitope C Adebayo-Ojo
Jun 15, 2019·International Journal of Environmental Research and Public Health·Gbenga J AbiodunJoel O Botai

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