New tools for epidemiology: a space odyssey

Geographical Information Systems (GIS) facilitate access to epidemiological data through visualization and may be consulted for the development of mathematical models and analysis by spatial statistics. Variables such as land-cover, land-use, elevations, surface temperatures, rainfall etc. emanating from earth-observing satellites, complement GIS as this information allows the analysis of disease distribution based on environmental characteristics. The strength of this approach issues from the specific environmental requirements of those causative infectious agents, which depend on intermediate hosts for their transmission. The distribution of these diseases is restricted, both by the environmental requirements of their intermediate hosts/vectors and by the ambient temperature inside these hosts, which effectively govern the speed of maturation of the parasite. This paper discusses the current capabilities with regard to satellite data collection in terms of resolution (spatial, temporal and spectral) of the sensor instruments on board drawing attention to the utility of computer-based models of the Earth for epidemiological research. Virtual globes, available from Google and other commercial firms, are superior to conventional maps as they do not only show geographical and man-made features, but also allow instant import of data-sets of specific interest, e.g. environmental parameters, demographic information etc., from the Internet.

Exploring the association between Trypanosoma cruzi infection in rural communities and environmental changes in the southern Gran Chaco

The association between land use and land cover changes between 1979-2004 in a 2.26-million-hectare area south of the Gran Chaco region and Trypanosoma cruzi infection in rural communities was analysed. The extent of cultural land, open and closed forests and shrubland up to 3,000 m around rural communities in the north, northwest and west of the province of Córdoba was estimated using Landsat satellite imagery. The T. cruzi prevalence was estimated with a cross-sectional serological survey conducted in the rural communities. The land cover showed the same patterns in the 1979, 1999 and 2004 satellite imagery in both the northwest and west regions, with shrinking regions of cultured land and expanding closed forests away from the community. The closed forests and agricultural land coverage in the north region showed the same trend as in the northwest and west regions in 1979 but not in 1999 or 2004. In the latter two years, the coverage remote from the communities was either constant or changed in opposite ways from that of the northwest and west regions. The changes in closed forests and cultured vegetation alone did not have a significant, direct relationship with the occurrence of rural communities with at least one person infected by T. cruzi. This study suggests that the overall decrease in the prevalence of T. cruzi is a consequence of a combined effect of vector control activities and changes in land use and land cover.

Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach

Remote sensing and geographical information technologies were used to discriminate areas of high and low risk for contracting kala-azar or visceral leishmaniasis. Satellite data were digitally processed to generate maps of land cover and spectral indices, such as the normalised difference vegetation index and wetness index. To map estimated vector abundance and indoor climate data, local polynomial interpolations were used based on the weightage values. Attribute layers were prepared based on illiteracy and the unemployed proportion of the population and associated with village boundaries. Pearson's correlation coefficient was used to estimate the relationship between environmental variables and disease incidence across the study area. The cell values for each input raster in the analysis were assigned values from the evaluation scale. Simple weighting/ratings based on the degree of favourable conditions for kala-azar transmission were used for all the variables, leading to geo-environmental risk model. Variables such as, land use/land cover, vegetation conditions, surface dampness, the indoor climate, illiteracy rates and the size of the unemployed population were considered for inclusion in the geo-environmental kala-azar risk model. The risk model was stratified into areas of "risk"and "non-risk"for the disease, based on calculation of risk indices. The described approach constitutes a promising tool for microlevel kala-azar surveillance and aids in directing control efforts.