A spatio-temporal description of COVID-19 cases in East Borneo using improved geographically and temporally weighted regression (I-GTWR)
Abstract
At the end of 2019, the world was impacted by a deadly viral phenomenon referred to as COVID-19. The Indonesian government quickly implemented Large-Scale Social Restrictions (LSSR) to prevent the spread and transmission of COVID-19. However, various violations are often committed by the community towards LSSR, which are specifically caused by economic inequality. This study was focused on spatial and temporal modelling of the COVID-19 cases in East Borneo Province by identifying the contributing factors. This study aimed to develop an analytical program to estimate the parameters of the Improved-Geographically and Temporal Weighted Regression (I-GTWR), which accommodates the interaction of the spatial-temporal distance function. Moreover, this study was also intended to develop an I-GTWR model for the COVID-19 data for each Regency/City of East Borneo Province by considering the spatial-temporal diversity and adding the interaction of the spatial-temporal distance function to the weighting matrix, and determining the factors that influence of COVID-19 cases in East Borneo Province, based on regional variations by applying I-GTWR. Map and model exploration had succeeded in identifying different patterns of factors that affected of COVID-19 cases at each location and time. The I-GTWR method had proven to be more appropriate in describing the contributing factors of COVID-19 cases in East Borneo Province in 2020-2021. This was indicated by a higher R-Square value, a decrease in the Root Means Squared Error (RMSE).
Commun. Math. Biol. Neurosci.
ISSN 2052-2541
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