HR: 1340h
AN: H33F-1700    [Abstracts]
TI: Simulation of the Impact of Climate Variability on Malaria Transmission in the Sahel
AU: * Bomblies, A
EM: bomblies@mit.edu
AF: Massachusetts Institute of Technology, MIT 48-216 15 Vassar St., Cambridge, MA 02139, United States
AU: Eltahir, E
EM: eltahir@mit.edu
AF: Massachusetts Institute of Technology, MIT 48-216 15 Vassar St., Cambridge, MA 02139, United States
AU: Duchemin, J
EM: duchemin@cermes.org
AF: Centre de Recherche Medicale et Sanitaire (Pasteur Institute), BP 10887, Niamey, 10887, Niger
AB: A coupled hydrology and entomology model for simulation of malaria transmission and malaria transmitting mosquito population dynamics is presented. Model development and validation is done using field data and observations collected at Banizoumbou and Zindarou, Niger spanning three wet seasons, from 2005 through 2007. The primary model objective is the accurate determination of climate variability effects on village scale malaria transmission. Malaria transmission dependence on climate variables is highly nonlinear and complex. Temperature and humidity affect mosquito longevity, temperature controls parasite development rates in the mosquito as well as subadult mosquito development rates, and precipitation determines the formation and persistence of adequate breeding pools. Moreover, unsaturated zone hydrology influences overland flow, and climate controlled evapotranspiration rates and root zone uptake therefore also influence breeding pool formation. High resolution distributed hydrologic simulation allows representation of the small-scale ephemeral pools that constitute the primary habitat of Anopheles gambiae mosquitoes, the dominant malaria vectors in the Niger Sahel. Remotely sensed soil type, vegetation type, and microtopography rasters are used to assign the distributed parameter fields for simulation of the land surface hydrologic response to precipitation and runoff generation. Predicted runoff from each cell flows overland and into topographic depressions, with explicit representation of infiltration and evapotranspiration. The model's entomology component interacts with simulated pools. Subadult (aquatic stage) mosquito breeding is simulated in the pools, and water temperature dependent stage advancement rates regulate adult mosquito emergence into the model domain. Once emerged, adult mosquitoes are tracked as independent individual agents that interact with their immediate environment. Attributes relevant to malaria transmission such as gonotrophic state, infected and infectious states, age, and location relative to human population are tracked for each individual. The model operates at a resolution consistent with the characteristic scale of relevant ecological processes. Microhabitat exploitation and spatial structure of the mosquito population surrounding villages is reproduced in this manner. The resulting coupled model predicts not only malaria transmission's response to interannual climate variability, but can also evaluate land use change effects on malaria transmission. The late Professor Andrew Spielman of the Harvard School of Public Health provided medical entomology expertise and was a part of this effort.
UR: http://web.mit.edu/bomblies/www/project.htm
DE: 1616 Climate variability (1635, 3305, 3309, 4215, 4513)
DE: 1630 Impacts of global change (1225)
DE: 1640 Remote sensing (1855)
DE: 1807 Climate impacts
DE: 1834 Human impacts
SC: Hydrology [H]
MN: 2007 Fall Meeting