Forecasting COVID-19 Transmission and Healthcare Capacity in Bali, Indonesia

J Prev Med Public Health. 2020 May;53(3):158-163. doi: 10.3961/jpmph.20.152. Epub 2020 Apr 29.

Abstract

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.

Keywords: COVID-19; Forecasting; Healthcare; Indonesia.

MeSH terms

  • Betacoronavirus
  • COVID-19
  • Communicable Disease Control / organization & administration
  • Coronavirus Infections / epidemiology*
  • Coronavirus Infections / prevention & control
  • Coronavirus Infections / transmission
  • Health Care Sector / organization & administration*
  • Health Care Sector / statistics & numerical data*
  • Health Policy
  • Humans
  • Indonesia / epidemiology
  • Models, Theoretical
  • Pandemics / prevention & control
  • Pneumonia, Viral / epidemiology*
  • Pneumonia, Viral / prevention & control
  • Pneumonia, Viral / transmission
  • SARS-CoV-2