Modelling infectious diseases to support public health decisions

This talk presents modelling work developed in close collaboration with public health agencies to support decision making and recommendations for different French health authorities and committees. I will first discuss our recent model of chikungunya transmission that incorporates fine-scale variation in mosquito exposure. After being validated against the 2005–2006 chikungunya outbreak in Réunion Island, this model correctly anticipated both the timing and magnitude of the 2025 outbreak nearly two months in advance. Retrospective forecasts of the 2023 Paraguay outbreak showed similarly strong performance, highlighting the value of accounting for exposure heterogeneity when supporting public health responses to arbovirus epidemics. I will then present work conducted with the French National Authority for Health to reassess meningococcal vaccination strategies in France. Using an age-structured model of serogroups B, W and Y, we estimated the long-term impact of alternative vaccination strategies. The optimal ACWY strategy involves vaccination in infants and adolescents, supported by a catch-up campaign up to age 25, leading to substantial reductions in disease burden. In contrast, for serogroup B vaccination, results showed a limited impact, with the overall reduction of IMD-B cases remaining below 20% in all studied scenarios, even in the long term. This evaluation informed the discussions of the Technical Vaccination Committee regarding the vaccination strategy
for meningococcus and was included in the recommendations of the French National Authority for Health, endorsed by the Ministry of Health. Finally, I will briefly mention an evaluation of the national antiviral stockpile carried out with the High Council for Public Health to support preparedness planning. Together, these projects show how mathematical models can guide evidence-based decisions across diverse public health priorities.