Convalescent plasma (CP) transfusion, also known as passive immunotherapy, refers to the approach of infusing patients with plasma donated from recovered patients. Ever since the first empirical use during the 1917-1918 Spanish flu pandemic, the therapy has been employed as an interim approach during various epidemic/pandemic outbreaks before the development of any clinically proven medications. On March 24, 2020, the US Food and Drug Administration (FDA) announced an emergency IND (eIND) process to allow individual physicians to treat patients with serious COVID-19 disease with convalescent plasma. On April 7, 2020, the FDA announced a National Expanded Access Protocol administered through the Mayo Clinic, which enables a wider range of adults to be treated with convalescent plasma. Lately, there are a number of FDA-approved multicenter clinical trials ongoing, as well as other regions around the world.

The population-wide implementation of passive immunotherapy program requires the coordination of donor screening and selection, plasma collection and stockpiling, as well as treatment authorization and delivery. We developed a mathematical model that couples the disease transmission with treatment-donation-stockpile dynamics for an optimal implementation of CP therapy to examine potential benefits and complications in the logistic realization of this therapy in a large-scale population. In this talk, I will present the application of our model in simulating the use of population-wide CP therapy during the COVID-19 outbreak in Italy and Hubei province, China.

Co-authors: Xiaodan Sun (Xi’an Jiaotong University, China), Nicola Bragazzi (York University), Jianhong Wu (York University).

Huo, Xi and Sun, Xiaodan and Bragazzi, Nicola Luigi and Wu, Jianhong, Effectiveness and Feasibility of Convalescent Blood Transfusion to Reduce COVID-19 Fatality Ratio (April 11, 2020). Available at SSRN: https://ssrn.com/abstract=3573611 or http://dx.doi.org/10.2139/ssrn.3573611

Xi Huo is an Assistant Professor in the Department of Mathematics, University of Miami. She got her Ph.D. in Mathematics from Vanderbilt University in 2014, then she joined the Laboratory for Industrial and Applied Mathematics (LIAM) at York University as a postdoctoral researcher. Her research interests include developing mathematical theory in structured differential equations models, as well as the applications in infectious diseases and antimicrobial resistance.