Spatial Modelling tools to integrate public health and environmental science, illustrated with infectious cryptosporidiosis

Contemporary spatial modelling tools can help examine how environmental exposures such as climate and land use together with socio-economic factors sustain infectious disease transmission in humans. Spatial methods can account for interactions across global and local scales, geographic clustering and continuity of the exposure surface, key characteristics of many environmental influences. Using cryptosporidiosis as an example, this review illustrates how, in resource rich settings, spatial tools have been used to inform targeted intervention strategies and forecast future disease risk with scenarios of environmental change. When used in conjunction with molecular studies, they have helped determine location-specific infection sources and environmental transmission pathways. There is considerable scope for such methods to be used to identify data/infrastructure gaps and establish a baseline of disease burden in resource-limited settings. Spatial methods can help integrate public health and environmental science by identifying the linkages between the physical and socio-economic environment and health outcomes. Understanding the environmental and social context for disease spread is important for assessing the public health implications of projected environmental change.