Bangladesh: A risk map was developed and geographic risk factors identified in Southern Bangladesh using a Bayesian approach. Malaria is quite widespread in this region. The map predicted high prevalence areas, located along the north-eastern areas and central part of the study area. Low to moderate prevalence areas were predicted in the south-western, south-eastern and central regions. Individual age and nearness to fragmented forest were associated with malaria prevalence after adjusting the spatial auto-correlation.
A Bayesian analytical approach using multiple enabling technologies (geographic information systems, global positioning systems, and remote sensing) provided a strategy to characterise spatial heterogeneity in malaria risk at a fine scale.
Even in the most hyper endemic region of Bangladesh there is substantial spatial heterogeneity in risk. Areas that are predicted to be at high risk, based on the environment but that have not been reached by surveys are identified.
The infection status (positives and negatives) was modelled using a Bernoulli distribution. Maps of the posterior distributions of predicted prevalence were developed in GIS system.
Source: Malaria Journal
