Use of GIS-based spatial modeling approach to characterize the spatial patterns of malaria mosquito vector breeding habitats in northwestern Thailand

Abstract

We sampled 291 bodies of water for Anopheles larvae around three malaria-endemic villages of Ban Khun Huay, Ban Pa Dae, and Ban Tham Seau, Mae Sot district, Tak Province, Thailand during August 2001-December 2002 and collected 4,387 larvae from 12 categories of breeding habitat types. We modeled surface slope and wetness indices to identify the extent and spatial pattern of potential mosquito breeding habitats by digitizing base topographical maps of the study site and overlaying them with coordinates for each larval habitat. Topographical contours and streamlines were incorporated into the Geographical Information System (GIS). We used Global Positioning System (GPS) instruments to locate accurately each field observed breeding habitat, and produced a 30-m spatial resolution Digital Elevation Model (DEM). The slope (of less than 12 degrees) and wetness (more than 8 units) derived from spatial modeling were positively associated with the abundance of major malaria vectors An. dirus, An. maculatus, An. minimus, and An. sawadwongporni. These associations permit real-time monitoring and possibly forecasting of the distributions of these four species, enabling public health agencies to institute control measures before the mosquitos emerge as adults and transmit disease.