Spatial and Temporal Analysis of COVID-19 Cases in West Java, Indonesia and Its Influencing Factors

Delima Istio Prawiradhani Putri (), Dwi Agustian (), Lika Apriani and Ridwan Ilyas
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Delima Istio Prawiradhani Putri: Epidemiology Study Program, Faculty of Medicine, Universitas Padjadjaran, Jalan Eyckman No. 38 Gedung RSP Unpad Lantai 4, Bandung 40161, Indonesia
Dwi Agustian: Division Epidemiology and Biostatistics, Department of Public Health, Faculty of Medicine, Universitas Padjadjaran, Jalan Ir. Soekarno KM. 21, Jatinangor, Sumedang 45363, Indonesia
Lika Apriani: Division Epidemiology and Biostatistics, Department of Public Health, Faculty of Medicine, Universitas Padjadjaran, Jalan Ir. Soekarno KM. 21, Jatinangor, Sumedang 45363, Indonesia
Ridwan Ilyas: Informatics Department, Faculty of Science and Informatics, Universitas Jenderal Achmad Yani, Jalan Terusan Jenderal Sudirman, Cimahi 40531, Indonesia

IJERPH, 2023, vol. 20, issue 4, 1-14

Abstract: Coronavirus Disease 2019 (COVID-19) spread quickly and reached epidemic levels worldwide. West Java is Indonesia’s most populous province and has a high susceptibility to the transmission of the disease, resulting in a significant number of COVID-19 cases. Therefore, this research aimed to determine the influencing factors as well as the spatial and temporal distribution of COVID-19 in West Java. Data on COVID-19 cases in West Java obtained from PIKOBAR were used. Spatial distribution was described using a choropleth, while the influencing factors were evaluated with regression analysis. To determine whether COVID-19s policies and events affected its temporal distribution, the cases detected were graphed daily or biweekly with information on those two variables. Furthermore, the cumulative incidence was described in the linear regression analysis model as being significantly influenced by vaccinations and greatly elevated by population density. The biweekly chart had a random pattern with sharp decreases or spikes in cumulative incidence changes. Spatial and temporal analysis helps greatly in understanding distribution patterns and their influencing factors, specifically at the beginning of the pandemic. Plans and strategies for control and assessment programs may be supported by this study material.

Keywords: COVID-19; Indonesia; spatial pattern; temporal; vaccine COVID-19 (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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