Key Investigator: Louisa R. Beck
Since 1987, NASA Ames Research Center, in collaboration with university and health agency scientists, has been conducting research on the ecology of the *Anopheles albimanus* mosquito, a key vector of human malaria in the coastal areas of southern Chiapas, Mexico. The field research focused on the relationship of An. albimanus to environmental variables associated with regional landscape elements. The results indicated the importance of flooded pastures and transitional wetlands for larval habitat, and cattle pastures for bloodmeal sources. The remote sensing research involved identifying and mapping these landscape elements, along with eight others, using multitemporal Landsat Thematic Mapper (TM) data (Fig. 1) . NASA ER-2 aircraft imagery was used to create a map of human settlements, from which 40 villages were randomly selected. These villages were used in a study to examine the relationship between landscape elements and mosquito-human contact risk (i.e., malaria risk). A geographic information system (GIS) was used to calculate the proportion of each landscape element within a 1-km area surrounding each village (Fig. 2) . This 1-km radius was based on the typical flight range of an adult, female An. albimanus mosquito; within this flight range, she must find a bloodmeal, resting site, and larval habitat in order to successfully reproduce. All 40 villages were sampled weekly for mosquito abundance for approximately three months.
The relationships between mosquito abundance and the landscape proportions were investigated using statistical analyses. These analyses indicated that the most important landscape elements in terms of explaining mosquito abundance were the proportions of transitional wetlands and unmanaged pasture. Using these two landscape elements as predictors, we were able to correctly distinguish villages with high and low mosquito abundance, with an overall accuracy of 90%. The model developed using these functions is currently being tested in another area of the Chiapas coastal plain in order to assess the model's accuracy and portability. The landscape approach, which integrates remotely sensed data and GIS capabilities to identify villages with high mosquito-human contact risk, provides a promising tool for malaria surveillance programs. In general, this approach could be applied to other diseases in areas where the landscape variables critical to disease transmission are known, and these elements can be detected using remote sensing.
COLLABORATORS: Centro de Investigacion de Paludismo, Mexico; Uniformed Services University of the Health Sciences; University of California, Davis; California State University, Fresno; University of Texas Health Sciences Center, Houstorl.
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