Modeling the national pediatric vaccine stockpile: Supply shortages, health impacts and cost consequences

Abstract

Pediatric vaccine stockpiles have been in place in the U.S. since 1983 to address the potential disruption in supply of routine pediatric vaccines. Increases in the number of vaccines recommended for pediatric and adolescent patients have increased the cost of stocking and maintaining the stockpile. Based on a spreadsheet-based model ( VacStockpile) we developed, we estimated potential supply shortages of 14 stockpiled vaccines as of August 1, 2008 and its health and financial impacts under various shortage and stockpile scenarios. To illustrate the implications of policy options, we compared “high” to “low” stockpile scenarios. The high stockpile scenario ensures a 6-month vaccine supply to vaccinate all children according to recommended schedules. The low scenario comprised of 50% of the high scenario or existing stocks, whichever is smaller. For each vaccine, we used a weighted average of five shortage scenarios ranging from 0% to 100%, in 25% increments. Demand for each vaccine was based on current distribution or birth cohort size. The probabilities of shortages were based on number of manufacturers, market stability, history of manufacturing problems, and production complexity. CDC contract prices were used to estimate costs. Expert opinion and literature provided estimates of health impacts due to shortages. Applying the probabilities of shortages to all vaccines in a single year, the “low” scenario could cost $600 million, with 376,000 vaccine-preventable cases occurring and 1774 deaths. The “high” scenario could cost $2 billion, with an additional $1.6 billion initial stocking, and result in 7100 vaccine-preventable cases occurring and 508 deaths. Based on the assumptions in the model, there is the potential for large differences in outcomes between the scenarios although some outcomes could potentially be averted with measures such as catch-up campaigns after shortages. Using the VacStockpile policy makers can readily evaluate the implications of assumptions and decide which set of assumptions they wish to use in planning.