Fig 1.
Overview of the study area in Uttar Pradesh, India, which covers Fatehpur and Chandauli district.
The red dots represent the distribution of the mapped leprosy index cases registered from 2014 to 2020. Base layers from https://sedac.ciesin.columbia.edu/data/set/india-india-village-level-geospatial-socio-econ-1991-2001/data-download.
Fig 2.
Overview of the different steps in the contextualized spatial approach with the input and output by step.
Step 1 is the preliminary analysis using the Global Moran’s I, Heatmap and the DBSCAN tool with the data of 2014–2017. The output of the Global Moran’s I and Heatmap are used for the selection of parameters of the DBSCAN (arrows). Step 2 is the expert consultation during which the preliminary results are discussed followed by decisions that have been taken as criteria on cluster definition. Step 3 is the development of context specific cluster maps for the PEP interventions. Minpt: minimum number of points in a cluster; PEP: post-exposure prophylaxis; HH: household.
Fig 3.
The contextualized clusters and the statistical cluster villages in Chandauli district (top left) and Fatehpur district (top right), and a zoom-in of clustering in a rural area in Chandauli (bottom left) and in an urban area in Fatehpur (bottom right). The bright red areas are the contextualized clusters identified in the contextualized spatial approach and the pink areas are the significant statistical cluster villages identified by Local Moran’s I. The zoom-in of the rural area shows that both approaches are able to identify clusters. Base layers from https://sedac.ciesin.columbia.edu/data/set/india-india-village-level-geospatial-socio-econ-1991-2001/data-download.
Table 1.
The results of two approaches compared.
Table 2.
The implications for PEP interventions of two approaches compared.