Abstract
Background: COVID-19 Convalescent Plasma (CCP) is a promising treatment for COVID-19. Blood collectors have rapidly scaled up collection and distribution programs.
Methods: We developed a detailed simulation model of CCP donor recruitment, collection, production, and distribution processes. We ran our model using varying epidemic trajectories from 11 U.S. states and with key input parameters drawn from wide ranges of plausible values to identify key drivers of ability to scale collections capacity and meet demand for CCP.
Results: Utilization of available CCP collections capacity followed increases in COVID-19 hospital discharges with a lag. Utilization never exceeded 75% of available capacity in most simulations. Demand was met for most of the simulation period in most simulations, but a substantial portion of demand went unmet during early, sharp increases in hospitalizations. For epidemic trajectories that included multiple epidemic peaks, second wave demand could generally be met due to stockpiles established during the decline from an earlier peak. Apheresis machine capacity (number of machines) and probability that COVID-19 recovered individuals are willing to donate were the most important supply-side drivers of ability to meet demand. Recruitment capacity was important in states with early peaks.
Conclusions: Epidemic trajectory was the most important determinant of ability to meet demand for CCP, although our simulations revealed several contributing operational drivers of CCP program success.
Keywords: COVID-19; SARS-CoV-2; blood products; convalescent plasma; simulation modeling.
【저자키워드】 COVID-19, convalescent plasma, SARS-CoV-2, blood products, simulation modeling, 【초록키워드】 Probability, Epidemic, hospitalizations, Demand, trajectory, second wave, convalescent, recruitment, utilization, distribution, Blood, Donor, CCP, individual, hospital discharge, apheresis machine, identify, exceeded, increases in, driver, input parameter, scaled up, treatment for COVID-19, 【제목키워드】 convalescent, Factor, driving, insight,