Logistical feasibility and potential benefits of a population-wide passive-immunotherapy program during an influenza pandemic

Proc Natl Acad Sci U S A. 2010 Feb 16;107(7):3269-74. doi: 10.1073/pnas.0911596107. Epub 2010 Feb 1.


Treatment strategies for severe cases of pandemic influenza have focused on antiviral therapies. In contrast, passive immunotherapy with convalescent blood products has received limited attention. We consider the hypothesis that a passive-immunotherapy program that collects plasma from a small percentage of recovered adults can harvest sufficient convalescent plasma to treat a substantial percentage of severe cases during a pandemic. We use a mathematical model to estimate the demand and supply of passive immunotherapy during an influenza pandemic in Hong Kong. If >5% of 20- to 55-year-old individuals recovered from symptomatic infection donate their plasma (donor percentage > 5%), >67% of severe cases can be offered convalescent plasma transfusion (treatment coverage > 67%) in a moderately severe epidemic (R (0) < 1.4 with 0.5% of symptomatic cases becoming severe). A donor percentage of 5% is comparable to the average blood donation rate of 38.1 donations per 1,000 people in developed countries. Increasing the donor percentage above 15% does not significantly boost the convalescent plasma supply because supply is constrained by plasmapheresis capacity during most stages of the epidemic. The demand-supply balance depends on the natural history and transmission dynamics of the disease via the epidemic growth rate only. Compared to other major cities, Hong Kong has a low plasmapheresis capacity. Therefore, the proposed passive-immunotherapy program is a logistically feasible mitigation option for many developed countries. As such, passive immunotherapy deserves more consideration by clinical researchers regarding its safety and efficacy as a treatment for severe cases of pandemic influenza.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Blood Donors / statistics & numerical data*
  • Disease Outbreaks / prevention & control*
  • Hong Kong / epidemiology
  • Humans
  • Immunization, Passive / methods*
  • Influenza, Human / epidemiology*
  • Influenza, Human / prevention & control
  • Influenza, Human / transmission*
  • Models, Theoretical