Factors driving availability of COVID ‐19 convalescent plasma: Insights from a demand, production, and supply model
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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.
Article activity feed
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SciScore for 10.1101/2020.10.25.20219170: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Despite these limitations, our analysis reveals key drivers of the ability to utilize capacity and meet demand for CCP during an epidemic.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find …
SciScore for 10.1101/2020.10.25.20219170: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Despite these limitations, our analysis reveals key drivers of the ability to utilize capacity and meet demand for CCP during an epidemic.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- No funding statement was detected.
- No protocol registration statement was detected.
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