179100 Geographical patterns of malaria - can climate alter malaria patterns in the Amazon?

Monday, October 27, 2008

Sarah Olson, BS BA , Department of Population Health and the Nelson Institute, University of Wisconsin-Madison, Madison, WI
Jonathan A. Patz, MD, MPH , University of Wisconsin - Madison, Madison, WI
Ron Gagnon , Department of Population Health, University of Wisconsin-Madison, Madison, WI
Jon Foley , Center for Sustainability and the Global Environment (SAGE), University of Wisconsin-Madison, Madison, WI
Jean-François Guegan , Research Institute for Development, Montpellier cedex 5, France
Eric Elguero , Research Institute for Development, Montpellier cedex 5, France
Laurent Durieux , Research Institute for Development, Montpellier cedex 5, France
Michael T. Coe , The Woods Hole Research Center, Falmouth, MA
The World Health Organization, estimates that 42% of malaria cases are “associated with policies and practices regarding land use, deforestation, water resource management, settlement siting and modified house design”. This estimate was drawn from expert opinion and studies performed at small scales, but little research has investigated the cumulative impacts of land use and land cover changes occurring in the Amazon Basin on malaria. Much less is understood about the impact of changing land use and subsequent precipitation regimes on malaria risk. To understand how land use practices may alter malaria patterns in the Basin we present an analysis of municipio (n=755) malaria case data and monthly precipitation patterns in the 1990s. Climate data originated from the CRU TS 2.1 half-degree grid resolution climate data set. We present a hierarchical (random coefficients) log-linear Poisson model relating malaria incidence to precipitation and river hydrology for both municipos and states. Our findings regarding precipitation run counter to global temperature driven malaria predictions for the Basin. At the Basin scale precipitation and cases show strong relationships. Precipitation and cases are asynchronous across the period of observation, but detailed inspection of states and individual municipios reveal geographic dependencies of precipitation, river hydrology, and malaria incidence.

Learning Objectives:
1. Recognize hydrology as an important driver of malaria in the Amazon Basin. 2. Analyze performance of global malaria models in the Amazon

Keywords: Developing Countries, Environmental Health

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have carried out the majority of research on this project
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.