Modeling determinant of COVID-19 mortality in Indonesia

Muhammad Fajar, Stephanie Magdhalena, Sri Hartini and Zelani Nurfalah

MPRA Paper from University Library of Munich, Germany

Abstract: This study aims to examine the determinants of mortality-related to COVID-19 in Indonesia. Generalized additive models (GAM) was used for modeling the relationship between COVID-19-related deaths and predictor variables. Information used in this study was sourced from Badan Pusat Statistik (BPS Statistics Indonesia), Ministry of Health, and the Indonesian COVID-19 Task Force. The results obtained from GAM are statistically valid. Out of the eight predicting variables used in the analysis, six were significant and two were non-significant at 95 percent confidence interval. The significant variables are GRDP per capita, the proportion of population aged 60 years and over, life expectancy at birth, number of hospitals, number of people with tuberculosis, and number of diabetics. The model can explain the variation of COVID-19-related deaths by 98.5 percent, while the remaining 1.5 percent is attributed to other factors lying outside the model. In summary, this study suggests increasing the number of health facilities, carrying out health development programs, implementing health protocols, and mobility restrictions with prioritizing populations of vulnerable age or those with comorbidities can reduce mortality-related to COVID-19.

Keywords: GAM; Covid-19; Determinant; Modeling Mortality; Indonesia (search for similar items in EconPapers)
JEL-codes: C14 C31 I10 I18 (search for similar items in EconPapers)
Date: 2020-09-30, Revised 2020-09-30
New Economics Papers: this item is included in nep-sea
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Published in International Journal of Scientific Research in Multidisciplinary Studies 9.6(2020): pp. 17-21

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