Residential scene classification for gridded population sampling in developing countries using deep convolutional neural networks on satellite imagery.

Background: Conducting surveys in low- and middle-income countries is often challenging because many areas lack a complete sampling frame, have outdated census information, or have limited data available for designing and selecting a representative sample. Geosampling is a probability-based, gridded population sampling method that addresses some of these issues by using geographic information system (GIS) tools to create logistically manageable area units for sampling. GIS grid cells are overlaid to partition a country's existing administrative boundaries into area units that vary in size from 50 m × 50 m to 150 m × 150 m.

Synthesized Population Databases: A Geospatial Database of US Poultry Farms.

The pervasive and potentially severe economic, social, and public health consequences of infectious disease in farmed animals require that plans be in place for a rapid response. Increasingly, agent-based models are being used to analyze the spread of animal-borne infectious disease outbreaks and derive policy alternatives to control future outbreaks. Although the locations, types, and sizes of animal farms are essential model inputs, no public domain nationwide geospatial database of actual farm locations and characteristics currently exists in the United States.

Impact of spatial clustering on disease transmission and optimal control.

Spatial heterogeneities and spatial separation of hosts are often seen as key factors when developing accurate predictive models of the spread of pathogens. The question we address in this paper is how coarse the resolution of the spatial data can be for a model to be a useful tool for informing control policies. We examine this problem using the specific case of foot-and-mouth disease spreading between farms using the formulation developed during the 2001 epidemic in the United Kingdom.

A national, geographic database of CDC-funded HIV prevention services: development challenges and potential applications.

Background: From 2000-2002, the Centers for Disease Control and Prevention (CDC) funded a study that was designed to improve the information available to program planners about the geographic distribution of CDC-funded HIV prevention services provided by community-based organizations (CBOs). Program managers at CDC recognized the potential of a geographic information system (GIS) to organize and analyze information about HIV prevention services and they made GIS a critical component of the study design. The primary objective of this study was to construct a national, geographically-referenced database of HIV prevention services provided by CDC-funded CBOs.