ECONOMIC CHARACTERISTICS AS PREDICTORS OF COVID-19 INFECTION, RECOVERY, AND DEATH RATES

Authors

  • Ade Heryana Universitas Esa Unggul
  • Wiku Adisasmito Universitas Indonesia
  • Cicilya Candi Universitas Indonesia

DOI:

https://doi.org/10.17501/24246735.2024.9102

Keywords:

Poverty, Income, Industry, Epidemic prevention strategy, Socio-economic determinants

Abstract

The Covid-19 pandemic provided lesson-learnt that ineffective epidemic control was took place when it is only prioritized on individual level and disregard the regional level. This research aims to identify the regional economic characteristics as a basis to districts/cities level pandemic control. This study analyzed infection, recovery, and death cases during the peak wave of the Delta variant on 26 May to 15 July 2021. Data were collected from 128 cities/districts of Java-Bali isles. Multivariate Analysis of Variance (MANOVA) model was applied to investigate the correlation between intercorrelated health outcomes such as infection, recovery and death cases with regional economic characteristics. The results were divided into three economic characteristic domains that significantly affected the pandemic severity. Firstly, poverty characteristic as poor people density each 10.000 km2 is prevention factor for infectious cases and risk factor for recovery cases. Second, income characteristics i.e. informal worker’s income and formal worker’s wage are the predictors for pandemic severity. Informal worker’s income is risk factor for infectious and death cases, meanwhile formal worker’s is prevention factor for death case. Third, industry characteristic significantly is the predictor for infection and recovery case. Infection case could be prevented by the regional characteristics involve workforce ratio, trade and service workforce, and middle-up enterprise. Recovery case could be prevented by workforce density characteristic and more in risky by trade and service workforce, and middle-up enterprise characteristics. This research provided the basic framework to determine non-pharmaceutical interventions as pandemic countermeasures including mobility and social interaction restriction, work from home, centralized isolation facilities, and empowering hospitalization and intensive-care resources.

Downloads

Download data is not yet available.

Author Biography

Wiku Adisasmito, Universitas Indonesia

Professor of Health Policy Universitas Indonesia

References

Aguilar-Palacio, I., Maldonado, L., Malo, S., Sánchez-Recio, R., Marcos-Campos, I., Magallón-Botaya, R., & Rabanaque, M. J. (2021). COVID-19 Inequalities: Individual and Area Socioeconomic Factors (Aragón, Spain). International Journal of Environmental Research and Public Health, 18(2), 6607.

Batty, G. D., Deary, I. J., Luciano, M., Altschul, D. M., Kivimäki, M., & Gale, C. R. (2020). Psychosocial factors and hospitalisations for COVID-19: Prospective cohort study based on a community sample. Brain, Behavior, and Immunity, 89, 569–578.

Bolcato, M., Aurilio, M. T., Aprile, A., Mizio, G. di, Pietra, B. Della, & Feolla, A. (2021). Take-Home Messages from the COVID-19 Pandemic: Strengths and Pitfalls of the Italian National Health Service from a Medico-Legal Point of View. Healthcare, 9(1), 1–13.

Bratianu, C. (2020). Toward understanding the complexity of the COVID-19 crisis: A grounded theory approach. Management and Marketing, 15(s1), 410–423. https://doi.org/10.2478/mmcks-2020-0024

Bwire, G., Munier, A., Ouedraogo, I., Heyerdahl, L., Komakech, H., Kagirita, A., Wood, R., Mhlanga, R., Njanpop-Lafourcade, B., Malimbo, M., Makumbi, I., Wandawa, J., Gessner, B. D., Orach, C. G., & Mengel, M. A. (2017). Epidemiology of cholera outbreaks and socio-economic characteristics of the communities in the fishing villages of Uganda: 2011-2015. PLoS Neglected Tropical Diseases, 11(3), 2011–2015. https://doi.org/10.1371/journal.pntd.0005407

Chakraborty, A., Khan, S. U., Hasnat, M. A., Parveen, S., Islam, M. S., Mikolon, A., Chakraborty, R. K., Ahmed, B. N., Ara, K., Haider, N., Zaki, S. R., Hoffmaster, A. R., Rahman, M., Luby, S. P., & Hossain, M. J. (2012). Anthrax outbreaks in Bangladesh, 2009-2010. American Journal of Tropical Medicine and Hygiene, 86(4), 703–710. https://doi.org/10.4269/ajtmh.2012.11-0234

Collins, S. R., Davis, K., Doty, M. M., & Ho, A. (2004). Wages, health benefits, and workers’ health. Issue Brief (Commonwealth Fund), 788, 1–16.

Contreras, Z., Ngo, V., Pulido, M., Washburn, F., Meschyan, G., Gluck, F., Kuguru, K., Reporter, R., Curley, C., Civen, R., Terashita, D., Balter, S., & Halai, U. A. (2021). Industry sectors highly affected by worksite outbreaks of coronavirus disease, Los Angeles County, California, USA, march 19-September 30, 2020. Emerging Infectious Diseases, 27(7), 1769–1775. https://doi.org/10.3201/eid2707.210425

Demenech, L. M., Dumith, S. de C., Vieira, M. E. C. D., & Neiva-Silva, L. (2020). Income inequality and risk of infection and death by COVID-19 in Brazil. Revista Brasilleria de Epidemiologia, 23(E200095), 1–12.

Demirer, I., & Pförtner, T. K. (2023). The Covid-19 pandemic as an accelerator of economic worries and labor-related mental health polarization in Germany? A longitudinal interacted mediation analysis with a difference-in-difference comparison. SSM - Population Health, 23(April). https://doi.org/10.1016/j.ssmph.2023.101469

Dorn, F., Khailaie, S., Stoeckli, M., Binder, S. C., Mitra, T., Lange, B., Lautenbacher, S., Peichl, A., Vanella, P., Wollmershäuser, T., Fuest, C., & Meyer-Hermann, M. (2023). The common interests of health protection and the economy: evidence from scenario calculations of COVID-19 containment policies. European Journal of Health Economics, 24(1), 67–74. https://doi.org/10.1007/s10198-022-01452-y

Eichenbaum, A., & Tate, A. D. (2022). Health Inequity in Georgia During the COVID-19 Pandemic: An Ecological Analysis Assessing the Relationship Between County-Level Racial/Ethnic and Economic Polarization Using the ICE and SARS-CoV-2 Cases, Hospitalizations, and Deaths in Georgia as of Octob. Health Equity, 6(1), 230–239. https://doi.org/10.1089/heq.2021.0118

Esen, E., & Çelik Keçili, M. (2022). Economic Growth and Health Expenditure Analysis for Turkey: Evidence from Time Series. Journal of the Knowledge Economy, 13(3), 1786–1800. https://doi.org/10.1007/s13132-021-00789-8

Gulumbe, B. H., Aminu, U., Liman, U. U., Abdulrahim, A., & Kalgo, Z. M. (2023). Recurring Outbreaks of Lassa Fever in Nigeria: Understanding the Root Causes and Strategies for the Future. Sudan Journal of Medical Sciences, 18(2), 257–264. https://doi.org/10.18502/sjms.v18i2.13608

Hessels, J., Rietveld, C. A., & van der Zwan, P. (2020). The Relation Between Health and Earnings in Self-Employment. Frontiers in Psychology, 11(May), 1–11. https://doi.org/10.3389/fpsyg.2020.00801

Ioannidis, J. P. A. (2022). The end of the COVID-19 pandemic. European Journal of Clinical Investigation, 52(6), 1–12. https://doi.org/10.1111/eci.13782

Khan, M. A., Kabir, K. H., Hasan, K., Sultana, R., Hoque, F., Al Imran, S., & Karmokar, S. (2022). Households’ Socioeconomic Vulnerability Assessment Due to COVID-19 Outbreak: A Web-Based Survey in Bangladesh. Electronic Journal of General Medicine, 19(3). https://doi.org/10.29333/ejgm/11797

Kjøllesdal, M., Skyrud, K., Gele, A., Arnesen, T., Kløvstad, H., Diaz, E., & Indseth, T. (2022). The correlation between socioeconomic factors and COVID-19 among immigrants in Norway: a register-based study. Scandinavian Journal of Public Health, 50(1), 52–60.

Lan, F.-Y., Wei, C.-F., Hsu, Y.-T., Christiani, D. C., & Kales, S. N. (2020). Work-related COVID-19 transmission in six Asian countries/areas: A follow-up study. PLoS ONE, 15(5), e0233588.

Lancaster, E., Byrd, K., Ai, Y., & Lee, J. (2022). Socioeconomic status correlations with confirmed COVID-19 cases and SARS-CoV-2 wastewater concentrations in small-medium sized communities. Environmental Research, 215(114290). https://doi.org/10.1016/j.envres.2022.114290

Lorenz, C., Bermudi, P. M. M., de Aguiar, B. S., Failla, M. A., Toporcov, T. N., Chiaravalloti-Neto, F., & Barrozo, L. V. (2021). Examining socio-economic factors to understand the hospital case fatality rates of COVID-19 in the city of São Paulo, Brazi. Transactions of the Royal Society of Tropical Medicine and Hygiene, 115(11), 1282–1287.

Morgan, O. (2019). How decision makers can use quantitative approaches to guide outbreak responses. In Philosophical Transactions of the Royal Society B: Biological Sciences (Vol. 374, Issue 1776). Royal Society Publishing. https://doi.org/10.1098/rstb.2018.0365

Moti, U. G., & Goon, D. Ter. (2020). Novel coronavirus disease: A delicate balancing act between health and the economy. Pakistan Journal of Medical Sciences, 36(COVID19-S4), S134–S137. https://doi.org/10.12669/pjms.36.COVID19-S4.2751

Nwaru, C. A., Santosa, A., Franzén, S., & Nyberg, F. (2022). Occupation and COVID-19 diagnosis, hospitalisation and ICU admission among foreign-born and Swedish-born employees: a register-based study. Journal of Epidemiology & Community Health, 76(5), 440–447.

Pergolizzi, J. V., Lequang, J. A., Taylor, R., Wollmuth, C., Nalamachu, M., Varrassi, G., Christo, P., Breve, F., & Magnusson, P. (2021). Four pandemics: Lessons learned, lessons lost. Signa Vitae, 17(1), 1–5. https://doi.org/10.22514/sv.2020.16.0096

Sanders, J., & Balcom, C. (2021). Clinical leadership during the COVID-19 pandemic: Reflections and lessons learned. Healthcare Management Forum, 34(6), 316–319. https://doi.org/10.1177/08404704211044587

Wordlometer. (2024). Daily New Cases in Indonesia. Worldometer Coronavirus. https://www.worldometers.info/coronavirus/country/indonesia/

Zhao, P., & Yu, Z. (2021). Rural poverty and mobility in China: A national-level survey. Journal of Transport Geography, 93(May), 103083. https://doi.org/10.1016/j.jtrangeo.2021.103083

Zhu, Y., Bashir, S., & Marie, M. (2022). Assessing the Relationship between Poverty and Economic Growth: Does Sustainable Development Goal Can be Achieved? Environmental Science and Pollution Research, 29(19), 27613–27623. https://doi.org/10.1007/s11356-021-18240-5

Downloads

Published

2025-01-23

How to Cite

Heryana, A., Adisasmito, W., & Candi, C. (2025). ECONOMIC CHARACTERISTICS AS PREDICTORS OF COVID-19 INFECTION, RECOVERY, AND DEATH RATES. Proceedings of the International Conference on Public Health, 9(1), 13–25. https://doi.org/10.17501/24246735.2024.9102