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Geospatial Analysis in Public Health Spatial Cluster Detection M.J. College, Jalgaon India September 22-26, 2008 Glen D. Johnson New York State Department of Health and The University at Albany School of Public Health Department of Environmental Health Sciences Acknowledgement:
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Spatial Cluster Detection
M.J. College, Jalgaon IndiaSeptember 22-26, 2008
Glen D. Johnson
New York State Department of Health
The University at Albany School of Public Health
Department of Environmental Health Sciences
Some of the following graphics on cluster detection are compliments of
Tom Talbot, MSPH
of the New York State Department of Health
- co-teaches “GIS in Public Health” with Glen Johnson and Frank Boscoe at the University at Albany, S.U.N.Y.
Public Health Definition
… as must be considered for all spatial statistics and mapping/visualization
- the Modifiable Area Unit Problem (MAUP)
Following is an example of how the scan statistic algorithm delineates all possible circular clusters, based on census blocks in the city of Albany …
A likelihood ratio is then computed for every circular window, where each window represents a potential spatial cluster.
For example, assuming a Poisson distribution of counts, the likelihood ratio is proportional to …
for observed cases cand expected cases E[c] inside the search window, and C total observed cases throughout the region, including within the search window.
The circle with the maximum likelihood ratio is then identified as the most likely cluster, and all others are rank-ordered below the maximum.
A null distribution of maximum likelihood ratios is obtained by repeating the analysis on a randomized version of the data, obtaining the max. likelihood ratio, and repeating this exercise for, say, 999 times.
A p-value is obtained for each circle by comparing it’s likelihood ratio to the simulated null distribution.So, for a likelihood ratio whose rank is R within the simulated null values, then the p-value = R/(# simulations +1).
Note that E[c] = n*C/Nfor population n in the circle and total number of cases and Population = C and N respectively
or for covariate category i
(an “indirect standardization”)
or E[c] may even be predicted from a regression model.
Recent advancements in the spatial scan statistic aimed at overcoming the restriction of the rather arbitrary shape of circular clusters