The Environmental Surveillance Core (ESC) serves as a resource for fleld studies planned in the Epidemiology, Vector Biology and Parasitology projects. It provides an environmental and spatial context for sampling designs used in these projects and a framework to help ensure that these projects are well integrated with one another. The ESC uses various spatially registered data bases that are linked within a geographic information systems (GIS) environment to provide its sen/ice. For example, high resolution remotely sensed (RS) data are used to enumerate and locate households in either rural or periurban environments (depending on sampling needs) to provide both a sampling frame and representative samples for conducting population based studies. These environmental data also can be used to generate up to date information on various features, such as transportation networks, and temperature and precipitation regimes that are otherwise unavailable for the region under study. The ESC also links the outcomes of the population based studies with spatio-temporally associated environmental data that are used in subsequent analyses by the projects to identify factors associated with aspects of malaria transmission and disease. Additionally, the ESC can provide new, appropriately downscaled data for individual projects to test hypotheses as new theories are developed. For example, the ESC provides the ability to generate hydrologic models of water movement across the landscape to identify where water will accumulate. The ESC can combine the model results with field observations to identify the optimal model and data inputs, for various measures of malaria risk. The ESC uses a web-based system to incorporate the data sets generated by the project leaders and provide a mechanism both to link all the project data and the environmental data within a single context for data transfer and visualization.
The Environmental Surveillance Core (ESC) provides an integrating framework for field studies in the Epidemiology, Vector Biology and Parasitology projects. It provides an explicit spatial framework for colocating collected data. In addition to providing a sampling iframe, it builds environmental databases that can be associated with the field study results and creates new data from environmental data that are ofthe appropriate spatial and temporal scales for local field studies.
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