Global Journal of Environmental Science and Technology

Viewing Options:  View Full Article - PDF     Download Full Article - PDF

Modelling climate induced relative malaria incidence in the major sub climatic zones of Uganda


Ssemwanga Mohammed1, Majaliwa Mwanjalolo Jackson Gilbert2, Araya Alemie1, Amanuel Zenebe1, and John Gathenya3



Abstract

 

 

Accepted 19th June, 2015

 

Malaria is widespread in Africa and causes untold mortality and morbidity. It's sensitive to climate and this has raised considerable concern over the implications of climate change on future disease risk. The problem of malaria vectors (Anopheles mosquitoes) shifting from their known locations to invade new zones is of important concern. The objectives of this paper were to; i) established relationship between climate and malaria incidence, ii) develop climate induced malaria incidence zonal models, and iii) project malaria incidence occurrence in the major sub climatic zones of Uganda. Correlation and regression analysis was used to determine the climate drivers of malaria incidence and built models using GenStat 14th edition. Climate data were downscaled using Statistical Downscaling Model (SDSM v 5.1.1) and HadCM3 B1 scenarios, and using the zonal models. Malaria incidence was projected. The results show that relative malaria incidence was most correlated with minimum temperature in Western and Northern regions (r=0.818 and r=0.651; respectively), and with relative humidity at 06:00 (r=0.692) in the Central region. Relative malaria incidence for the different zones can be modeled and predicted as; (R2adj=0.656) , (R2adj=0.581), 1 (R2adj = 0.404);  for the Western, Central and Northern regions; respectively. The projected malaria incidence is likely to gradually decrease from 2020s to 2040s, and then increase until 2090s across the three major sub climatic zones of Uganda with the western and northern regions experiencing the highest and lowest incidence respectively, in the business as usual scenario. However, these projected incidences will present similarities in terms of periodicity and the peaks that will be lagged from the cold/wet seasons with different regions presenting relatively different patterns and trends with peak malaria incidences.

 

Keywords: Climate change and malaria, models, malaria projections, and East Africa