Table 3 Data preprocessing steps for each software package to perform a space-time analysis starting with daily data as point events in an ESRI point shapefile and a polygon shapefile of census dissemination area boundaries
From: Review of software for space-time disease surveillance
Software | Type of Analysis | Required Data Structure | Data Preprocessing Steps |
|---|---|---|---|
SaTScan | Space-time cluster scan with Poisson model | • Case file with number of cases, date, and DA id • Population file with population, date, and DA id • Coordinates file with DA id, centroid X and Y coordinates | • Associate DA identifier with each point event • Calculate DA centroid coordinates |
ClusterSeer | Space-time cluster scan with Poisson model | • One table with population • One table with counts of cases for each location and date during study period | • Associate DA identifier with each point event • Calculate week numbers • Aggregate cases by week for each DA (zero counts included) |
GeoSurveillance | Univariate cusum on individual DAs |    • DA shapefile with counts of number of cases for each time period named and ordered sequentially in the table | • Calculate week numbers • Split point events into unique shapefiles for each week • Count number of events in each DA by week (zero counts included) • Calculate weekly counts as new fields |
R-Surveillance | Univariate cusum on individual DAs |    • Matrix of counts of cases with spatial locations as columns and time periods as rows | • Calculate week numbers • Split point events into unique shapefiles for each week • Count number of events in each DA by week (zero counts included) • Calculate weekly counts as new fields • Read table into R as matrix and transpose |