Framework For Optimal Global Vaccine Stockpile Design For Vaccine-Preventable Diseases: Application To Measles And Cholera Vaccines As Contrasting Examples

Keywords

Dynamic modeling; measles; stockpile; vaccine; vaccine-preventable disease

Abstract

Managing the dynamics of vaccine supply and demand represents a significant challenge with very high stakes. Insufficient vaccine supplies can necessitate rationing, lead to preventable adverse health outcomes, delay the achievements of elimination or eradication goals, and/or pose reputation risks for public health authorities and/or manufacturers. This article explores the dynamics of global vaccine supply and demand to consider the opportunities to develop and maintain optimal global vaccine stockpiles for universal vaccines, characterized by large global demand (for which we use measles vaccines as an example), and nonuniversal (including new and niche) vaccines (for which we use oral cholera vaccine as an example). We contrast our approach with other vaccine stockpile optimization frameworks previously developed for the United States pediatric vaccine stockpile to address disruptions in supply and global emergency response vaccine stockpiles to provide on-demand vaccines for use in outbreaks. For measles vaccine, we explore the complexity that arises due to different formulations and presentations of vaccines, consideration of rubella, and the context of regional elimination goals. We conclude that global health policy leaders and stakeholders should procure and maintain appropriate global vaccine rotating stocks for measles and rubella vaccine now to support current regional elimination goals, and should probably also do so for other vaccines to help prevent and control endemic or epidemic diseases. This work suggests the need to better model global vaccine supplies to improve efficiency in the vaccine supply chain, ensure adequate supplies to support elimination and eradication initiatives, and support progress toward the goals of the Global Vaccine Action Plan.

Publication Date

7-1-2016

Publication Title

Risk analysis : an official publication of the Society for Risk Analysis

Volume

36

Issue

7

Number of Pages

1487-1509

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1111/risa.12265

Socpus ID

84978531263 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84978531263

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