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COVID-19: Original Article
- Forecasting COVID-19 Transmission and Healthcare Capacity in Bali, Indonesia
- I Md Ady Wirawan, Pande Putu Januraga
- J Prev Med Public Health. 2020;53(3):158-163. Published online April 29, 2020
- DOI: https://doi.org/10.3961/jpmph.20.152
- 10,624 View
- 333 Download
- 12 Crossref
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Abstract
PDF - Objectives
In the current early phase of the coronavirus disease 2019 (COVID-19) outbreak, Bali needs to prepare to face the escalation of cases, with a particular focus on the readiness of healthcare services. We simulated the future trajectory of the epidemic under current conditions, projected the impact of policy interventions, and analyzed the implications for healthcare capacity.
Methods
Our study was based on the first month of publicly accessible data on new confirmed daily cases. A susceptible, exposed, infected, recovered (SEIR) model for COVID-19 was employed to compare the current dynamics of the disease with those predicted under various scenarios.
Results
The fitted model for the cumulative number of confirmed cases in Bali indicated an effective reproduction number of 1.4. Interventions have decreased the possible maximum number of cases from 71 125 on day 86 to 22 340 on day 119, and have prolonged the doubling time from about 9 days to 21 days. This corresponds to an approximately 30% reduction in transmissions from cases of mild infections. There will be 2780 available hospital beds, and at the peak (on day 132), the number of severe cases is estimated to be roughly 6105. Of these cases, 1831 will need intensive care unit (ICU) beds, whereas the number of currently available ICU beds is roughly 446.
Conclusions
The healthcare system in Bali is in danger of collapse; thus, serious efforts are needed to improve COVID-19 interventions and to prepare the healthcare system in Bali to the greatest extent possible. -
Summary
Citations
Citations to this article as recorded by
- Towards reliable forecasting of healthcare capacity needs: A scoping review and evidence mapping
Simon Grøntved, Mette Jørgine Kirkeby, Søren Paaske Johnsen, Jan Mainz, Jan Brink Valentin, Christina Mohr Jensen
International Journal of Medical Informatics.2024; 189: 105527. CrossRef - Health 4.0 architecture proposal for planning and management of a hospital emergency department
Lucas Caldas Danelon Lopes, Clóvis Neumann, Michael Machado
Procedia CIRP.2024; 126: 307. CrossRef - The Impacts of Medical Resources on Emerging Self-Limiting Infectious Diseases
Dayong Zhou, Liyan Gao, Qiuhui Pan, Mingfeng He
Applied Sciences.2022; 12(9): 4255. CrossRef - Transmission dynamics model and the coronavirus disease 2019 epidemic: applications and challenges
Jinxing Guan, Yang Zhao, Yongyue Wei, Sipeng Shen, Dongfang You, Ruyang Zhang, Theis Lange, Feng Chen
Medical Review.2022; 2(1): 89. CrossRef - Comprehensive Travel Health Education for Tour Guides: Protocol for an Exploratory Sequential Mixed Methods Research
Ni Made Sri Nopiyani, Pande Putu Januraga, I Md Ady Wirawan, I Made Bakta
JMIR Research Protocols.2022; 11(5): e33840. CrossRef - Seroprevalence of SARS-CoV-2 antibodies in Bali Province: Indonesia shows underdetection of COVID-19 cases by routine surveillance
Anak A. S. Sawitri, Putu C. D. Yuliyatni, Putu A. S. Astuti, Emita Ajis, Endang B. Prasetyowati, Husni, Juliette Morgan, Jennifer Mika, Catharina Y. Praptiningsih, Amalya Mangiri, Ester Mulyadi, Rintis Noviyanti, Leily Trianty, William A. Hawley, Gathsau
PLOS Global Public Health.2022; 2(8): e0000727. CrossRef - Correlation of Demographics, Healthcare Availability, and COVID-19 Outcome: Indonesian Ecological Study
Gede Benny Setia Wirawan, Pande Putu Januraga
Frontiers in Public Health.2021;[Epub] CrossRef - Perceived Social Norms as Determinants of Adherence to Public Health Measures Related to COVID-19 in Bali, Indonesia
Putu Ayu Indrayathi, Pande Putu Januraga, Putu Erma Pradnyani, Hailay Abrha Gesesew, Paul Russel Ward
Frontiers in Public Health.2021;[Epub] CrossRef - Prevalence of Depression, Anxiety, and Stress Among Repatriated Indonesian Migrant Workers During the COVID-19 Pandemic
Ngakan Putu Anom Harjana, Pande Putu Januraga, Putu Ayu Indrayathi, Hailay Abrha Gesesew, Paul Russell Ward
Frontiers in Public Health.2021;[Epub] CrossRef - Determinants of Mental Health and Practice Behaviors of General Practitioners During COVID-19 Pandemic in Bali, Indonesia: A Cross-sectional Study
Firman Parulian Sitanggang, Gede Benny Setia Wirawan, I Md Ady Wirawan, Cokorda Bagus Jaya Lesmana, Pande Putu Januraga
Risk Management and Healthcare Policy.2021; Volume 14: 2055. CrossRef - Improving Public Access to COVID-19 Pandemic Data in Indonesia for Better Public Health Response
Pande Putu Januraga, Ngakan Putu Anom Harjana
Frontiers in Public Health.2020;[Epub] CrossRef - Modeling the transmission dynamics of COVID-19 epidemic: a systematic review
Jinxing Guan, Yongyue Wei, Yang Zhao, Feng Chen
The Journal of Biomedical Research.2020; 34(6): 422. CrossRef
Original Articles- An Application of Delphi Method to the Assessment of Current Status of Cancer Research.
- Young Ho Khang, Seok Jun Yoon, Gil Won Kang, Chang Yup Kim, Keun Young Yoo, Young Soo Shin
- Korean J Prev Med. 1998;31(4):844-856.
- 2,266 View
- 34 Download
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Abstract
PDF
- Globally, cancer research has been considered one of the most important field of biomedical researches. Recently, in Korea, there are increasing concerns about cancer research and the development of national cancer control programme. For the efficient investment in cancer research at the national level, strategic approach is needed based on the nationwide information about current status of research. However even the basic data on cancer research have not been systematically collected, and are not available when necessary. The aim of this study is to assess current status of cancer research. For this purpose, this study applied two round Delphi method in which fifteen experts in cancer research fields participated. They rated each items on the initial list at the first round, and modified their responses at the second round. Panels responded that pathogenesis of cancer, research and development of cancer drug, and oncogene, etc. are the most urgent and important research fields. They assessed national level of cancer research as being 49.6% of the world highest level. Coefficient of variation tended to be lowered with the iteration. Predictive stability was evaluated to be lower in items of urgency than in items of importance and research level. Although this study shares the same limitations in the selection of the experts with many other Delphi studies, it provides a primary data that would be required to plan the national strategy of the cancer research.
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Summary
- Trend and forecast of the medical care utilization rate, the medical expense per case and the treatment days per case in medical insurance program for employees by ARIMA model.
- Kyu Pyo Jang, Sin Kam, Jae Yong Park
- Korean J Prev Med. 1991;24(3):441-458.
- 2,240 View
- 43 Download
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Abstract
PDF
- The objective of this study was to provide basic reference data for stabilization scheme of medical insurance benefits through forecasting of the medical care utilization rate, the medical expense per case, and the treatment days per case in medical insurance program for government employees and private school teachers and for industrial workers. For the achievement of above objective, this study was carried out by Bos-Jenkins time series analysis (ARIMA Model), using monthly statistical data from Jan. 1979 to Dec. 1989, of medical insurance program for government employees and private school teachers and for industrial workers. The results are as follows; ARIMA model of the medical care utilization rate in medical insurance program for government employees and private school teachers was ARIMA (1, 1, 1) and it for outpatient in medical insurance program for industrial workers was ARIMA (1, 1, 1), while it for inpatient in medical insurance program for industrial workers was ARIMA (1, 0, 1). ARIMA model of the medical expense per case in medical insurance program for government employees and private school teachers and for outpatient in medical insurance program for industrial workers were ARIMA (1, 1, 0), while it for inpatient in medical insurance program for industrial workers was ARIMA (1, 0, 1). ARIMA model of the treatment days per case of both medical insurance program for government employees and private school teachers and industrial workers were ARIMA (1, 1, 1). Forecasting value of the medical care utilization rate for inpatient in medical insurance program for government employees and private school teachers was 0.0061 at dec. 1989, 0.0066 at dec. 1994 and it for outpatient was 0.280 at dec. 1989, 0.294 at dec. 1994, while it for inpatient in medical insurance program for industrial workers was 0.0052 at dec. 1989, 0.0056 at dec. 1994 and it for outpatient was 0.203 at dec. 1989, 0.215 at 1994. Forecasting value of the medical expense per case for inpatient in medical insurance program for government employees and private school teachers was 332,751 at dec. 1989, 354,511 at dec. 1994 and it for outpatient was 11,925 at dec. 1989, 12,904 at dec. 1994, while it for inpatient in medical insurance program for industrial workers was 281,835 at dec. 1989, 293,973 at dec. 1994 and it for outpatient was 11,599 at dec. 1989, 11,585 at 1994. Forecasting value of the treatment days per case for inpatient in medical insurance program for government employees and private school teachers was 13.79 at dec. 1989, 13.85 at dec. 1994 and it for outpatient was 5.03 at dec. 1989, 5.00 at dec. 1994, while it for inpatient in medical insurance program for industrial workers was 12.23 at dec. 1989, 12.85 at dec. 1994 and it for outpatient was 4.61 at dec. 1989, 4.60 at 1994.
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