Rogerson's spatial pattern surveillance technique
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Indications/Recommendations for use: This is a surveillance method for detecting changes in spatial pattern in cases over time relative to the population-at-risk. The location of new cases is monitored as they occur with the objective of detecting emerging clusters shortly after they occur.
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Description: This method represents a cumulative sum statistic and procedure for the monitoring of changes in spatial pattern for observations processed sequentially.
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Test statistic: Rogerson developed a cusum approach by modifying the Tango statistic.
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Null Hypothesis:
The number of cases in each subregion is a Poisson random variable with expected value equal to the population-at-risk multiplied by the average (or expected) disease frequency.
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Ho:
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Alternative Hypothesis:
The number of cases in each region is not distributed as a Poisson random variable.
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Ha:
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GeoMed Inputs:
Region-level data with a centroid coordinate and population-at-risk size per subregion; Date of diagnosis/illness for each case; Cluster scale parameter; Batch size for cumulating the mean of Z(i); A constant reference value k; A predetermined decision level h
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GeoMed Outputs:
Tabled information includes observed and expected proportion of cases in each region; Line plot of cumulative sum of cases versus observation date of diagnosis/disease-onset
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Example Analysis
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Reference:
Rogerson, P.A., 1997, Surveillance systems for monitoring the development of spatial patterns, Statistics in Medicine, 16:2081-2093
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