A spatio-temporal description of COVID-19 cases in East Borneo using improved geographically and temporally weighted regression (I-GTWR)

Sifriyani -, Idris Mandang, Fidia Deny Tisna Amijaya, Miftahus Sholihin, Andrea Tri Rian Dani

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).

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Published: 2022-08-15

How to Cite this Article:

Sifriyani -, Idris Mandang, Fidia Deny Tisna Amijaya, Miftahus Sholihin, Andrea Tri Rian Dani, A spatio-temporal description of COVID-19 cases in East Borneo using improved geographically and temporally weighted regression (I-GTWR), Commun. Math. Biol. Neurosci., 2022 (2022), Article ID 78

Copyright © 2022 Sifriyani -, Idris Mandang, Fidia Deny Tisna Amijaya, Miftahus Sholihin, Andrea Tri Rian Dani. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Commun. Math. Biol. Neurosci.

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