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Mapping and Clustering COVID-19 in Kudus District 1Department of Public Health Faculty of Health Sciences Universitas Jenderal Soedirman, Indonesia Abstract Background: Kudus District contributed many confirmed cases of coronavirus disease 2019 (COVID-19) (3,567 cases) with the high case fatality rate (10%) at the end of 2020 in Central Java Province, one of the provinces which was the center of COVID-19 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 COVID-19 cases in Kudus District. Methods: An observational method with a case study design was conducted involving all confirmed cases of COVID-19 for the period January-April 2021 in Kota Subdistrict, which was the epicenter of COVID-19 in Kudus District, 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 in all villages, the most cases (8.2%) are in Mlati Norowito Village. The results of spatial analysis showed that the majority of cases were in villages with a population density of 8001-12,000 people/km2 (51.7%) and villages with a number of social assistance recipients of 801-1200 people (36.6%), residing less than 250 m from health care facilities (50.5%) and less than 250 m from public facilities (59.14%), and 4 secondary clusters of COVID-19 cases were identified. Conclusions: More cases of COVID-19 were found in villages that had a high population density, a large number of social assistance recipients, lived close to health care facilities and public facilities, and 4 secondary clusters were identified. Keywords: Coronavirus disease 2019- Spatial- Clustering- Kudus District Topic: Communicable and non communicable disease |
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