Mapping and Clustering COVID-19 Cases in Kudus District
DOI:
https://doi.org/10.12928/dpphj.v19i1.11392Keywords:
Coronavirus disease 2019, Spatial, Clustering, Kudus DistrictAbstract
Background: Kudus District contributed the high case fatality rate (10%) of Coronavirus Disease at the end of 2020 in Central Java Province, one of the provinces which was the center of Coronavirus Disease transmission in Indonesia. Spatial analysis is useful for identifying areas of grouping or clusters of cases that indicate high risk areas so that prevention measures can be developed specifically in those areas. This study aimed to map and identify clusters of Coronavirus Disease cases in Kudus District. Method: An observational method with a case study design was conducted involving all confirmed cases of Coronavirus Disease from January to April 2021 in Kota Subdistrict, totaling 257 cases. Spatial analysis included overlay and buffering processed using ArcGIS, and clustering processed using SaTScan. Results: The study results showed that cases tended to be spread evenly across all villages, with the highest number of cases (8.2%) observed in Mlati Norowito Village. Spatial analysis revealed that the majority of cases were concentrated in villages with a population density of 8,001-12,000 people/km2 (51.7%) and villages with a number of social assistance recipients of 801-1,200 (36.6%), residing less than 250 meters from health care facilities (50.5%) and less than 250 meters from public facilities (59.14%), and four secondary clusters of Coronavirus Disease cases were identified. Conclusion: A higher cases of Coronavirus Disease were identified in villages with a high population density, a large number of social assistance recipients, close proximity to health care and public facilities, and four secondary clusters were identified.
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