Serotype re-emergence and vaccine impact in the era of next-generation pneumococcal vaccines

Project Summary/Abstract There are 100+ serotypes of pneumococcus, and currently available pneumococcal conjugate vaccines (PCVs) protect against up to 20 of these serotypes. However, despite the use of PCVs for more than 20 years, there is still a considerable burden of pneumococcal disease in the United States. While PCVs have driven down the burden of many vaccine-targeted serotypes, other serotypes have emerged, and certain vaccine- targeted serotypes have re-emerged in recent years. The drivers of these dynamics, especially the re- emergence of vaccine-targeted serotypes, are not well-understood. The next several years will bring tremendous change to the pneumococcal vaccine field, with several next-generation PCVs that target up to 31 serotypes undergoing late-stage clinical development. These new PCVs cover additional serotypes but often have lower immunogenicity against the targeted serotypes. Understanding the drivers of serotype dynamics is essential to make informed decisions about which of the pneumococcal vaccines should be used in different age groups and populations. The proposed work will provide novel insights into the mechanisms driving serotype re-emergence and differences in impact between vaccines. We will use mathematical and statistical models to test specific hypotheses about the drivers of these patterns and will then evaluate real-world serotype patterns using newly collected colonization data linked with vaccination history. These insights will inform models of serotype dynamics that will be used to evaluate the potential impact of different strategies using currently available PCVs as well as new PCVs that are likely to become available in the next few years. This study is innovative in providing a novel understanding of the dynamics of pneumococcus and the tradeoffs of policies that would incorporate new PCVs. We will do this with an innovative mix of primary data on colonization and secondary data sources, combined with statistical and mathematical transmission models. The outcomes from this work will provide important insights that can be used by vaccine developers, healthcare providers, and policy-makers to inform how to optimally design and deploy new PCVs over the next several years.