Dazed and confused: How map projections affect disease map analysis and perception
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1
Department of Population Medicine, Ontario Veterinary College, University of Guelph, Canada
Map projections are an important step in disease mapping and spatial epidemiological data analysis. Disease mapping is a basic visualization approach in environmental and public health. However, the effect of map projections on the resulting disease maps and spatial data analysis has not received full attention.
The goal of this study is to highlight the importance of map projections on the analysis and perception of disease maps. Using maps of Israel and southern Ontario (Canada) under changing projections it is demonstrated how map projections affect shape and orientation of maps as well as distances measured on these maps. Distortions of distances between fixed locations are not generally noticeable to the map user.
Disease maps are directly and indirectly affected by map projections. Direct effects refer to distortions in orientation and shape of the visual appearance of disease maps. Indirect effects by map projections result from distorted distances which can be key elements of spatial regression models and further analytical methods, including Moran’s I coefficient and the spatial scan test.
For example, a 97 km distance on a map of Israel can change into a 127 km distance on map of seemingly the same shape by changing from the Robinson to the Lambert Equal Area Conic projection. Similar, the test for Moran’s I coefficient might result in p < 0.05 using human West Nile virus incidence data in southern Ontario under the Robinson and UTM17 projections. Or the result changes to p > 0.05, when the map is based on Lambert Equal Area Conic projection.
Disease maps, which visualize the results of spatial data analysis, are conditional on the specific map projection used. Lack of reporting of map projections in the spatial epidemiological literature prohibits full appraisal of research results as well as reproducibility of spatial epidemiological studies.
Keywords:
Spatial Epidemiology,
Bias (Epidemiology),
map projection,
Disease mapping,
spatial statistics,
West Nile virus
Conference:
GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data, Davis, United States, 8 Oct - 10 Oct, 2019.
Presentation Type:
Regular oral presentation
Topic:
Spatial methods for environmental & exposure epidemiology and climate change
Citation:
Berke
O
(2019). Dazed and confused: How map projections affect disease map analysis and perception.
Front. Vet. Sci.
Conference Abstract:
GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data.
doi: 10.3389/conf.fvets.2019.05.00013
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Received:
01 Jun 2019;
Published Online:
27 Sep 2019.
*
Correspondence:
Prof. Olaf Berke, Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, N1G 2W1, Canada, oberke@uoguelph.ca