A reusable model of pangenome selection informs optimal surveillance strategies over vaccine introductions.

A model incorporating negative frequency-dependent selection accurately predicts pneumococcal vaccine replacement dynamics, guiding surveillance strategies across diverse regions.

• Why it matters: Understanding how pneumococcal populations adapt after vaccine introduction is vital to improve vaccine design and prevent serotype replacement, which can undermine vaccine effectiveness.
• What they did: The authors developed a mathematical model based on the Wright-Fisher framework, integrating genomic and demographic factors, and tested it with genomic data from Nepal, the US, and the UK, focusing on NFDS effects.
• The result: The model successfully replicated observed replacement patterns, identified region-specific genes under NFDS, and demonstrated that prioritizing sample size over frequency enhances surveillance efficiency, enabling better prediction and management of vaccine impact.