Predicting Hospital Demand During the COVID-19 Outbreak in Bogotá, Colombia

Area of Science:

• Epidemiology
• Public Health
• Health Systems Management

Background:

• Developing nations, including Colombia, face significant challenges in managing large-scale health crises like the COVID-19 pandemic due to limited healthcare infrastructure.
• Accurate resource allocation is critical for hospitals and clinics to effectively manage patient surges during pandemics.
• There is a pressing need for predictive models to estimate demand for Intensive Care Unit (ICU) and regular hospital beds.

Purpose of the Study:

• To develop and present a predictive model for estimating the demand for ICU and regular hospital beds in Bogotá, Colombia, during the COVID-19 pandemic.
• To inform resource management strategies for healthcare facilities facing unprecedented patient loads.
• To provide a tool for public health officials to anticipate healthcare needs.

Main Methods:

• Utilized a compartmental SEIR (Susceptible-Exposed-Infectious-Recovered) model adapted for COVID-19.
• Incorporated three infection categories: home care, severe (requiring regular beds), and critical (requiring ICU beds).
• Employed a time-varying transmission rate to account for government-imposed public health interventions over a six-month period.

Main Results:

• The model predicted a demand for 1,362 ICU beds and over 9,000 regular hospital beds in Bogotá by mid-November 2020.
• An estimated 67,866 active COVID-19 cases were projected by mid-November 2020.
• The projected death toll was estimated to reach 13,268 by the end of December 2020.

Conclusions:

• The projected demand for hospital beds significantly exceeds Bogotá's healthcare capacity, indicating a critical resource shortage.
• The developed SEIR model and accompanying interactive Shiny application serve as valuable tools for healthcare management in Colombia.
• Anticipated strengthening of lockdown measures may mitigate the predicted mortality rates, suggesting the importance of continued public health interventions.