| Abstrakt: |
Pandemic COVID-19 caused economic, social, and political crises in the infected countries. Understanding the spatial distribution of disease COVID-19 cases can help predict global epidemics and, as a result, enhance public health policy. The purpose of this study was to investigate the temporal and spatial aspects of COVID-19 transmission, as well as the factors that influence it in 34 provinces in Indonesia from November 2020 until January 2021. COVID-19 confirmed case data, total population data, the number of beds in the hospital data, the number of people aged over 65 years data, the number of medical personnel data, and the area of the province data were gathered from 34 province. COVID-19's spatiotemporal properties were investigated utilizing Conditional Autoregressive Model (CAR) and hotspot. The spatial autocorrelation results of the incidence rate were acquired prior to the application of hotspots analysis. After that, hotspot analysis indices were used to precisely find high and low risk COVID-19 cluster in Indonesia. The high one are DKI Jakarta, West Java, Central Java, East Java, and Yogyakarta. [ABSTRACT FROM AUTHOR] |
