Presentation (CTI)

OBJECTIVES: Economic evaluations in communicable diseases commonly use static or dynamic models to assess the impact of interventions. Static models capture only direct effects, while dynamic models include indirect effects like herd immunity. Although dynamic models offer a more comprehensive view, their use in health technology assessment (HTA) submissions remains limited. This study investigates justifications provided for using dynamic models in the economic evaluation of communicable disease therapies in UK and French HTA submissions.
METHODS: A targeted literature review identified all HTA appraisals related to communicable diseases and approved in France and the UK between 2016 and 2025 that either employed dynamic modelling or received criticism from the HTA body for not doing so. For each identified case, company justifications for the modelling approach used, along with the corresponding HTA body’s comments, whether in support, critique, or suggestion, were extracted and analyzed.
RESULTS: Thirteen HTA reports were reviewed: eight from HAS (France) and five from NICE (UK). Five used dynamic models, justified by their ability to capture direct and indirect (herd immunity) effects, complex epidemiological dynamics, and long-term impacts on disease and costs. HTA bodies acknowledged these strengths but raised concerns about uncertainty, data requirements, complexity, and lack of external validation. The remaining dossiers used static models, which the company deemed more appropriate for populations with low transmission potential, like the elderly. HAS favored static models for simplicity, consistency with influenza vaccine evaluations, and feasibility. Though conservative, these models may underestimate indirect benefits. In therapeutic areas like Hepatitis C, NICE was more inclined to highlight the limitations of static models, as they may underestimate the full impact of an intervention on preventing future infections.
CONCLUSIONS: This review can help manufacturers anticipate methodological expectations from HTA agencies. Early dialogue with HTA bodies, such as scientific advice, is key to identifying and addressing potential modelling challenges.