ABSTRACT
The continued uptake of electronic health information technologies across high- and low-resource settings alike [1, 2] reflects an increasing recognition of the valuable contributions of data-driven decision making throughout the healthcare sector. The wealth of spatially referenced disease data these systems provide, coupled with the ready availability of remote sensing image products and powerful geographical information system (GIS) packages for desktop computers, makes possible the production of high-resolution disease risk maps for use by multiple potential stakeholders. These include national disease control programs, responsible for resource allocation decisions and the assessment of past intervention efficacies within country; supra-national organizations (such as the World Health Organization (WHO) and the Global Fund), concerned with the same issues in the context of funding decisions made largely at the inter-country level; and individual citizens, interested in the performance of their local community health system or the risks of foreign travel. Corresponding examples from the field of malariology are the use of disease maps by national malaria control programs to guide the allocation of community health workers or to better target indoor residual spraying [3]; the evaluation of progress towards the United Nations (UN) Millennium Development Goal (6C) to ‘halt by 2015 and begin to reverse the incidence of malaria’ through cartographic disease burden estimation across sub-Saharan Africa [3, 4]; and the inclusion of detailed sub-national risk maps in government guidelines for travellers to malarious regions [6].
