COVID-19: Adaptation of a model to predict healthcare resource needs in Valle del Cauca, Colombia

Abstract

Background: Valle del Cauca is the region with the fourth-highest number of COVID-19 cases in Colombia (>50,000 on September 7, 2020). Due to the lack of anti-COVID-19 therapies, decision-makers require timely and accurate data to estimate the incidence of disease and the availability of hospital resources to contain the pandemic. Methods: We adapted an existing model to the local context to forecast COVID-19 incidence and hospital resource use assuming different scenarios: (1) the implementation of quarantine from September 1st to October 15th (average daily growth rate of 2%); (2-3) partial restrictions (at 4% and 8% growth rates); and (4) no restrictions, assuming a 10% growth rate. Previous scenarios with predictions from June to August were also presented. We estimated the number of new cases, diagnostic tests required, and the number of available hospital and intensive care unit (ICU) beds (with and without ventilators) for each scenario. Results: We estimated 67,700 cases by October 15th when assuming the implementation of a quarantine, 80,400 and 101,500 cases when assuming partial restrictions at 4% and 8% infection rates, respectively, and 208,500 with no restrictions. According to different scenarios, the estimated demand for reverse transcription-polymerase chain reaction tests ranged from 202,000 to 1,610,600 between September 1st and October 15th. The model predicted depletion of hospital and ICU beds by September 20th if all restrictions were to be lifted and the infection growth rate increased to 10%. Conclusion: Slowly lifting social distancing restrictions and reopening the economy is not expected to result in full resource depletion by October if the daily growth rate is maintained below 8%. Increasing the number of available beds provides a safeguard against slightly higher infection rates. Predictive models can be iteratively used to obtain nuanced predictions to aid decision-making

Management of hospital beds and ventilators in the Gauteng province, South Africa, during the COVID-19 pandemic

“…During each wave of the COVID-19 pandemic health-care systems have developed strategies to optimize the available healthcare resources and provide necessary care to COVID-19 patients. Studies have been conducted in many countries to predict the increased demand for healthcare resources and to determine whether these resources are adequate for providing essential services to COVID-19 patients throughout the pandemic with a focus on the burden of COVID-19 on ward beds, ICU beds and ventilators [11][12][13][14][15][16].…”

“…Barrett et al [12] used an individual based simulation model to predict the number of days to resource depletion and the number of excess deaths due to resource depletion in Ontario, Canada. Irragori et al [13] adapted the Ontario model to predict the healthcare resources demand for PCR tests and the resource depletion date in Valle del Cauca region in Colombia. Noronha et al [14] estimated the healthcare demand for hospital resources (general ward, ICU beds and ventilators) and hospital occupancy rates during the COVID-19 pandemic for all regions in Brazil.…”