Vaccines and the evolution of antibiotic resistance: elucidating transmission mechanisms and public health impact using deep sequencing of Streptococcus pneumoniae and mathematical models

Vaccines can, in principle, alleviate antibiotic resistance by preventing infections and reducing the need for antibiotic use.

However, the impact of pneumococcal conjugate vaccines (PCVs) on antibiotic resistant disease is unclear because resistance in non-targeted serotypes is increasing and we do not understand the mechanisms driving this phenomenon.

To overcome this issue , we have assembled a multidisciplinary team to leverage an ongoing three-year Phase IV cluster-randomised PCV trial in Vietnam which will provide unparalleled predictive power to calculate the long-term consequences of PCV on resistant infection.

First, we will develop a suite of novel bioinformatics tools to determine antibiotic susceptibility using deep sequence data that will allow us to evaluate both the dynamic changes in antibiotic resistance in the three years following PCV introduction and, for the first time, the frequency of resistant–sensitive strain co-colonisation.

Second, we will analyse surveys to evaluate the longitudinal impact of PCV on antibiotic use.

Third, we will integrate these results into a mathematical modelling approach to disentangle the mechanisms driving pneumococcal resistance. We will use this calibrated model to predict the long-term effect of PCV on pneumococcal resistance. Our results will, for the first time, accurately predict the wider health impact of PCVs.