Estimating the Maximum Capacity of COVID-19 Cases Manageable per Day Given a Health Care System's Constrained Resources

Background: The coronavirus disease 2019 (COVID-19) pandemic originated in China in late 2019 and continues to spread globally (1).At the time of writing, there were nearly 2 million COVID-19 cases causing approximately 110 000 deaths across more than 200 affected countries and territories (2).As some health care systems approach collapse, a pressing need exists for tools modeling the capacity of acute and critical care systems during the COVID-19 pandemic.Objective: To develop an online tool to estimate the maximum number of COVID-19 cases that could be managed per day within the catchment area served by a health care system, given acute and critical care resource availability.Methods: We modeled steady-state patient-flow dynamics constrained by the number of acute care beds, critical care beds, and mechanical ventilators available for COVID-19 -infected patients seeking health care during the pandemic.Parameters for patient-flow dynamics were extracted from evolving data on COVID-19 and assumptions based on expert guidance.We used the package shiny within R, version 3.5.3(R Foundation for Statistical Computing), to create the interactive tool.The tool determines the maximum number of COVID-19 cases that could be managed per day within the catchment area served by a health care system, where the rate of patients with COVID-19 who are being admitted or transferred to acute care or critical care or requiring mechanical ventilation ("patients in") equals the maximum daily turnover of each of those resources available for patients with COVID-19 ("patients out").These estimates represent the maximum steadystate constraints imposed by these limited resources being managed by a health care system or hospital.Resources available for patients with COVID-19 should account for the proportion of existing staffed resources that could be made maximally available to support patients with COVID-19 plus any additional staffed surge capacity.The tool first calculates the maximum daily turnover of acute care beds, critical care beds, and mechanical ventilators available for patients with COVID-19 by taking the maximally available number of each of those resources for these patients and dividing it by the expected duration of their use for patients with COVID-19.On the basis of published data, the average length of stay in acute care and critical care was set at 11 and 9 days, respectively, whereas the average length of time for mechanical ventilation was set at 9 days (1, 3, 4).The tool then calculates the population-weighted age-stratified probabilities of COVID-19 cases requiring acute care hospitalization and critical care, and in the base case assumes that 70% of critical care patients will be mechanically ventilated (3-5).Finally, the maximum number of new COVID-19 cases per day that a health care system could manage is calculated by dividing the daily turnover of maximally available acute care beds, critical care beds, or mechanical ventilators by the