Najmah, Najmah (2020) Predicitive modeling, empowering women, and COVID-19 in South Sumatra, Indonesia (Similarity). Turnitin Universitas Sriwijaya, ASEAN J. of Community Engagement. (Submitted)
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Abstract
The Coronavirus disease (COVID-19) has spread to almost all provinces in Indonesia, including South Sumatra. Epidemiological models are required to provide evidence for public health policymakers to mitigate the virus. The aim of this study is: 1) to create a prediction model for COVID-19 cases in South Sumatra to help inform about public health policy and 2) to reflect on women’s experiences to provide solutions for mitigating the impact of COVID-19. This study uses quantitative and qualitative methods. A quantitative modeling approach called Susceptible–Infected–Recovered (SIR) model is used to predict COVID-19 cases in South Sumatra. The assumption used is that every four days, a doubling of COVID-19 cases is observed, with an average of 15 days for recovery. The sources of data are reports from the South Sumatra Provincial Government and the Ministry of Health of the Republic of Indonesia (MOH RI). Qualitative data are obtained through a feminist participatory action research project, which is focused on children’s experiences of COVID-19. Reflective analysis is conducted to develop insights into how to empower women with respect to mitigating COVID-19. Results show that COVID-19 cases in South Sumatra are still underreported, with only 5%–10% of the total estimated COVID-19 cases being reported. Modeling indicates that over 1,000 people had COVID-19 by the end of April, reaching over 150,000 by the end of May, and over a third of South Sumatra’s population is likely to be infected by the end of June. Multiple interventions are needed to reduce cases and flatten the curve. Women are key to flattening this curve and must be empowered to undertake actions from a familial base.
| Item Type: | Other |
|---|---|
| Subjects: | #3 Repository of Lecturer Academic Credit Systems (TPAK) > Results of Ithenticate Plagiarism and Similarity Checker |
| Divisions: | 10-Faculty of Public Health > 13201-Public Health (S1) |
| Depositing User: | Mrs Najmah Najmah |
| Date Deposited: | 26 Nov 2022 05:06 |
| Last Modified: | 26 Nov 2022 05:06 |
| URI: | http://repository.unsri.ac.id/id/eprint/82061 |
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