The Effect of Region's Socio-Economic and Demographic Charateristic on Covid-19 Confirmed Cases and Deaths
DOI:
https://doi.org/10.21776/ub.jiae.2022.010.01.3Keywords:
Covid-19, coronavirus, Regional Socio-Economic, Regional DemographicAbstract
Covid-19 pandemic that has hit the world has made almost all countries limit the mobility of their residents to prevent the transmission of the Corona virus. Indonesia has also made similar efforts through Large-Scale Social Restrictions (PSBB). However, these efforts have not been optimal because they are faced with obstacles to the uneven distribution of the population and unfavorable socio-economic conditions. This study aims to analyze the effect of regional socio-economic and demographic characteristics on Covid-19 in terms of the number of confirmed cases and deaths. The analysis was conducted at the provincial level with a total of 34 observations and using multiple linear regression analysis. Socio-economic characteristics are approximated by the share of the province's GRDP, the percentage of the poor, and the Human Development Index (HDI). Demographic characteristics are approximated by population density and population projections. This study found that the high confirmed and death cases of Covid-19 were influenced by poor socio-economic conditions, as well as densely populated demographic conditions and a high population of an area. The results of this study also found a significant effect of the provincial GDRP share and HDI on socio-economic characteristics as well as population projections on demographic characteristics on confirmed and Covid-19 deaths cases in Indonesia.References
Algifari. (2002). Analisa Regresi Teori, Kasus dan Solusi, Edisi 2. Yogyakarta: BPFE.
Auler, A.C., Cassaro, F.A.M., da Silva, V.O., & Pires, L.F. (2020). Evidence That High Tempratures and Intermediate Relative Humidity Might Favor the Spread od Covid-19 in Tropical Climate: A Case Study for the Most Affected Brazilian Cities. The Science of the Total Environment. https://doi.org/10.1016/j. scitotenv.2020.139090.
Das, A., Ghosh, S., Das, K., Basu, T., Dutta, I., & Das, M. (2021). Living Environment Matters: Unravelling the Spatial Clustering of Covid-19 Hotspots in Kolkata Megacity, India. Sustainable Cities and Society.
Franco, L.S., Shanahan, D.F., & Fuller, R.A. (2017). A Review of the Benefits of Nature Expriences: More than meets the eye. International Journal of Environemental Research and Public Health. 14(8), 864. https://doi.org/ 10.3390/ijerph14080864.
Gujarati, D.N., & Porter, D.C. (2008). Basic Econometrics Fifth Edition. New York: McGraw-Hill, Inc.
Hauser, P.M., & Duncan, O.D. (1959). The Study of Population: An Inventory and Appraisal. Chicago: University of Chicago Press.
Kabisch, N., Haase, D., & van den Bosch, M. (2016). Adding Natural Areas to Social Indicators of Intra-Urban Health Inequalities Among Children: A Case Study From Berlin, Germany. International Journal of Environmental Research and Public Health. 13(8), 783. https://doi.org/10.3390/ijerph13080783.
Kephart, G., Vince, S.T., & David, R.M. (1998). Socioeconomic differences in the use of physician services in Nova Scotia. American Journal of Public Health.
Kodera, S., Rashed, E., & Hirata, A. (2020). Correlation Between Covid-19 Morbidity and Mortality Rates in Japan and Local Population Density, Temperature, and Absolute Humidity. International Journal of Environmental Research and Public Health. 17(15), 5477. https://doi.org/10. 3390 /ijerph17155477.
Kondo, M.C., Mueller, N., Locke, D.H., Roman, L.A., Rojas-Rueda, D., Schinasi, L.H., Nieuwenhuijsen, M.J. (2020). Health Impact Assessment of Philadelphia’s 2025 Tree Canopy Cover Goal. The Lancet Planetary Health. https://doi.org/10.1016/S2542-5196(20)30058-9.
Kuncoro, M. (2003). Metode Riset Untuk Bisnis dan Ekonomi. Jakarta: Erlangga.
Machmud, R. (2009). Pengaruh Kemiskinan Keluarga Pada Kejadian Pneumonia Balita di Indonesia. Kesmas: Jurnal Kesehatan Masyarakat Nasional (National Public Health Journal). 4(1), 36-41.
Mansour, S., Kindi, A.A., Al-Said, A., Al-Said, A., & Atkinson, P. (2021). Sociodemographic Determinants of Covid-19 Incidence Rates in Oman: Geospatial Modelling Using Multiscale Geographically Weighted Regression (MGWR). Sustainable Cities and Society. https://doi.org/10.1016/j.scs.20 20.102627.
Marmot, M., Allen, J., Goldbatt, P., Herd, E., & Morrison, J. (2020). Build Back Fairer: The Covid-19 Marmot Review The Pandemic, Socio-Economic, and Health Inequalities in England. London: Institute of Health Equity.
Purwana, R. (1999). Partikulat Rumah Sebagai Faktor Risiko Gangguan Pernapasan Anak Balita (Penelitian di Pekojan, Jakarta). Fakultas Kesehatan Masyarakat, Universitas Indonesia [Disertasi].
Renggapraptiwi, A. (2009). Kemiskinan Dalam Perkembangan Kota Semarang: Karakteristik dan Respon Kebijakan. Semarang: Universitas Diponegoro.
Sujana. (2001). Metode Stastik. Bandung: Tarsito.
UNESCO, & UN-WATER. (2020). United Nations World Water Development Report 2020: Water and Climate Change. Retrivied June 20th 2021, from www.unwater.org/publications/world-water-development-report-2020/.
Van den Bosch, M., & Sang, A.O. (2017). Urban Natural Environments as Nature-Based Solutions for Improved Public Health – A Systematic Review of Reviews. Environmental Research. https://doi.org /10.1016/j,envres.2015.05.040.
Zahrotunnimah. (2020). Langkah Taktis Pemerintah Daerah Dalam Pencegahan Virus Corona Covid-19 di Indonesia. Jurnal Sosial dan Budaya Syar’i. 7(3), 248.
Zain, S. (1995). Ekonometrika Dasar. Jakarta: Erlangga.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Journal of Indonesian Applied Economics
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
