Abstract
Disease maps are integral to spatial epidemiology and public health. The map appearance and analysis of corresponding data may both depend on a map projection used to transform the 3-dimensional world onto a 2-dimensional surface. Map projections necessarily introduce bias - an issue that has not received full attention in the literature. This study aims to demonstrate the impact map projections can have on spatial analysis and disease maps for public health. Case studies applied varying map projections, including the Lambert, Mercator and Robinson projections, to Israel, North Carolina and Southern Ontario as study areas. The effect of projections on various measures, estimates, tests and models was assessed. When the map projection was changed: (i) a distance in Israel increased by 30%; (ii) for Southern Ontario an areal size increased by almost 95%; Moran's I test switched from significant to not; and (iii) a single disease cluster in North Carolina converted into three distinct clusters. Visual bias in disease mapping is unavoidable and should be recognized. Disease maps and spatial analytical inferences, including disease clusters should be reported with their geographic projection. Using geographic coordinates can prevent analytical bias.
Published Version
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