Uncertainty in mapping malaria epidemiology: implications for control.
Malaria is a location-specific, dynamic infectious disease transmitted by mosquitoes to humans and is influenced by environmental, vector, parasite, and host factors. The principal purposes of malarial epidemiology are 1) to describe the malarial distribution in space and time along with the physical, biologic, and social etiologic factors and 2) to guide control objectives for either modeling impact or measuring progress of control tactics. Mapping malaria and many of its causative factors has been achieved on many different levels from global distribution to biologic quantitative trait localization in humans, parasites, and mosquitoes. Despite these important achievements, a large degree of uncertainty still exists on the annual burden of malarial cases. Accurate, sensitive detection and treatment of asymptomatic reservoirs important to infectious transmission are additional components necessary for future control measures. Presently spurred by the leadership and funding of Bill and Melinda Gates, the malarial community is developing and implementing plans for elimination of malaria. The challenge for malariologists is to digitally integrate and map epidemiologic factors and intervention measures in space and time to target effective, sustainable control alongside research efforts.
Sullivan
David
D
The Malaria Research Institute, W. Harry Feinstone Department of Molecular Microbiology and Immunology, The Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD 21205, USA. dsulliva@jhsph.edu
D000818:Animals; D003140:Communicable Disease Control / Q000379:methods* / Q000458:organization & administration; D016021:Epidemiologic Studies; D040362:Geographic Information Systems; D006801:Humans; D055256:Infectious Disease Incubation Period; D016778:Malaria, Falciparum / Q000453:epidemiology* / Q000517:prevention & control; D009032:Mosquito Control; D010963:Plasmodium falciparum; D016133:Polymerase Chain Reaction; D035501:Uncertainty