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Is There a Spatial Relation Between COVID-19 Incidents and Unemployment? A Case of East Java Province, Indonesia
Last modified: 2022-11-15
Abstract
The COVID-19 pandemic, despite being referred to as a health issue, has affected the labor market. Companies had to shut down or scale back activities due to the restrictions that were imposed. In addition to switching to remote work, employees frequently lost their jobs either temporarily or permanently. This study aims to analyze the spatial pattern of COVID-19 and the spatial pattern of unemployment, as well as analyze the spatial correlation of COVID-19 with unemployment in East Java Province using Moran Index analysis in the form of Univariate Moran's I and Bivariate Moran's I. The study results show that the spatial pattern of COVID-19 and the spatial pattern of unemployment in East Java Province are clustered, where districts with a high number of COVID-19 are surrounded by districts with an increased number of COVID-19. The situation with unemployment is similar, with areas with a high unemployment surrounded by areas with a high unemployment. The results of the spatial relationship between COVID-19 incidents and unemployment show a positive value, which means there is a spatial correlation between COVID-19 and unemployment in the districts of East Java Province. Where districts with a high number of COVID-19 are surrounded by districts with an increased number of unemployed, the government can provide policies related to lockdowns and the like to prevent the spread and transmission of the COVID-19 pandemic. So that when the number of COVID-19 case decreases, unemployment will also decrease due to the re-opening of businesses.