A Spatial Model of the Social Vulnerability Index for Vaccine COVID-19 in Java, Indonesia

Abstract

The COVID-19 vaccine coverage in Indonesia remains low, with uneven distribution across Java, while COVID-19 cases continue to pose a public health concern. This study seeks to develop a spatial model using the Social Vulnerability Index (SVI) approach to identify the spatial pattern of COVID-19 vaccination and the factors influencing it in Java. The study adopts an ecological design with a spatial approach, encompassing 118 districts/cities. The dataset used in this research focuses on the coverage of COVID-19 vaccination for the second dose, spanning from March 15, 2021, to January 11, 2022. Spatial statistical techniques such as spatial autocorrelation and Geographically Weighted Regression were employed to analyze the data. The findings reveal that the Human Development Index, unemployment rate, and housing conditions significantly impact the spatial distribution of COVID-19 vaccine coverage, indicating the presence of spatial interaction among regions. Socioeconomic factors emerged as key variables influencing the study outcomes. Given that enhancing the community's economy requires time, interventions tailored to the prevailing conditions are necessary. Therefore, interventions to increase COVID-19 vaccine coverage should prioritize health promotion efforts, particularly in areas with low socioeconomic conditions.

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