Background: Malaria is a major health challenge in sub-Saharan Africa with children under
5 being most vulnerable. Identifying regions of greater malarial burden is vital in targeting
interventions.
Methods: This study analysed malaria morbidity using data from the Malawi 2012 Malaria
Indicator Survey that were obtained from Demographic and Health Survey (DHS) program
website. These data captured malaria related information on children under 5. Poisson
regression was done to determine associations between outcome (number of children
under 5 with malaria in household) and explanatory variables. A Bayesian smoothing
approach was employed to adjust for spatial random effects on child related variables.
Results: There were 1878 households in 140 clusters. The number of children under five
was 1900. Spatially structured effects accounted for more than 90% of random effects as
these had a mean of 1.32 (95% Credible Interval (CI) = 0.37, 2.50) whilst spatially unstructured
had a mean of 0.10 (CI = 9.0 104
, 0.38). Spatially adjusted significant variables
were; type of place of residence (urban or rural) [posterior odds ratio (POR) = 2.06;
CI = 1.27, 3.34], not owning land [POR = 1.77; CI = 1.19, 2.64], not staying in a slum
[POR = 0.52; CI = 0.33, 0.83] and enhanced vegetation index [POR = 0.02; CI = 0.00, 1.08].
A trend was observed on usage of insecticide treated mosquito nets [POR = 0.80; CI = 0.63,
1.03].
Conclusion: This study showed that malaria is a disease of poverty. Enhanced vegetation
index was an important factor in malaria morbidity. The central region was identified as
the area with greatest disease burden.