Abstract

Malaria is one of the most important diseases in tropical and subtropical areas, with sub-Saharan Africa including Malawi being the region most burdened. The region has the right combination of biotic and abiotic components, including socioeconomic, climatic and environmental factors that sustain transmission of the disease. Heterogeneity in these conditions across the country consequently leads to spatial variation in risk of the disease. Analysis of nationwide survey data that takes into account this spatial variation is crucial in a resource constrained country like Malawi for targeted allocation of scare resources in the fight against malaria. We used the 2010 Malaria Indicator Survey, which provides point referenced data for the analysis. Structured additive logistic regression models with spatial correlation were utilized to model the presence of parasitaemia in children while adjusting for child, household level and climatic covariates, environmental factors and personal interventions. The resultant model was then used to produce a malaria risk map for Malawi. Children from poor households were over twice at risk of malaria than those from the richest households (OR=2.07, CI: 1.72-2.78). However, the results indicated a possible nonlinear relationship. On the other hand, the youngest children aged between 0 and 1 year are about 76% less likely to contract malaria than children aged between 4 and 5 (OR=0.244,CI:0.196,0.281). Those aged between 3 and 4 are only 28% less likely to have malaria (OR=0.717, CI:0.667-0.818). There is a general increase in risk as the child approaches the age of five which could be explained by a decline in maternal immunity. Average total rainfall in the three months preceding the survey did not show a strong association with the disease risk while minimum temperatures shows an association with disease risk. The predicted malaria risk map produced by the model was in conformity with the expected disease pattern whereby central plain areas have higher risk than the high altitude districts in the north. Our risk maps show an improved estimation at local level than previous efforts which were based on limited data collected from small surveys. It is hoped that this study can help reveal areas that require more attention from the authorities in the continued fight against childhood malaria.

More details

School	: School of Natural and Applied Sciences
Issued Date	: 2012

Download full document