Spatial Epidemiology: Spatial Clustering and Vulnerability

This chapter introduces a method for combining the use of multiple software packages and open-source datasets to identify unusual clusters of high disease rates and explore the socio-economic and environmental characteristics of physical landscapes that may explain high rates. The

software discussed in this chapter includes SaTScan (a free epidemiological spatial cluster analysis package), ArcGIS Pro v2.8.6 (a GIS software), and open access alternatives, such as QGIS. SaTScan is used to identify disease

clusters from epidemiological datasets. Open-source datasets, such as the UK Index of Multiple Deprivation, can then be used to explain possible determinants of cluster location as well as visualise the possible drivers of vulnerability using maps. The methods used in this chapter facilitate understanding of the potential drivers of vulnerability and contagion transmission within a community. This analytical approach enables better

targeting of service delivery and support for communities that are the most heavily affected by disease. The chapter concludes with advanced statistical and spatial methods, including producing a predictive spatial layer.