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

Abstract

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.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.

Schematic of the proposed passive immunotherapy program.

Fig. 2.

General demand-supply dynamics of passive immunotherapy under the proposed program. Key parameter values are basic reproductive number R0 = 1.4, donor percentage qD = 15% and lumped-demand parameter rTpH = 1.5%. (A) Daily demand and supply when the percentage of donors qualified for plasmapheresis is qS = 80% (case 1) and qS = 30% (case 2). The same colors for the two cases are used in B and C. (B) Daily number of severe cases treated (solid lines) and stockpile of CP built from supply surplus (dashed line). There is no CP stockpile in case 2. (C) The percentage of daily demand met. Over the course of the epidemic, 82% and 58% of total demand are met in case 1 and 2, respectively.

Fig. 3.

Treatment coverage in the base case. (A) Treatment coverage ρ when the donor percentage is qD = 15%. (B) Sensitivity of ρ against qD with R0 = 1.4 in the base case (Upper) and when the plasmapheresis and screening capacity are doubled (Lower). In general, increasing qD beyond 15% has little impact on the outcome.

Fig. 4.

Treatment coverage for 15,000 epidemic scenarios generated using Latin-hypercube sampling with different level of demand parameters (A–D). Initial epidemic growth rate is expressed as initial epidemic doubling time on the x axis for ease of interpretation. Each point corresponds to a randomly generated epidemic scenario and is colored with the associated treatment coverage. The relatively small amount of overlapping of different colors indicate that the treatment coverage is mostly determined by the abscissa (the doubling time) and ordinate (the supply parameter qSqD).

Fig. 5.

The impact of hyperimmune IVIG lead-time on treatment coverage. In general, treatment coverage decreases rapidly as TIVIG increases unless the epidemic growth rate is very slow.