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Health/ point data (introduction)

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Health/ point data (introduction)
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15
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CC Attribution 3.0 Germany:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Production Year2023
Production PlaceWageningen

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Abstract
MOOD project coordinator Elena Arsevska is also a veterinary epidemiologist within Cirad in Montpellier, France. During the 2023 MOOD Summer School, she teached about the different types of spatial data, and provided some examples from real practice. Using the primary biliary cirrhosis (PBC) dataset from the sparr R package, she teached about basic spatial point pattern analysis and specifically, and allowed attendees to explore how to do the following: Divide our study zone into quadrants, followed by performing spatial randomness test Estimate and map kernel density to look for the density of cases in space Estimate and map relative risk (RR) to identify hotspots for higher density of cases over controls Save our RR (heat map) as a raster layer.
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