On the influenza vaccination policy through mathematical modeling

Abstract

Objectives: Aimed at mitigating influenza transmission, this study assessed the timing of the vaccination program and took vaccine capacity, strain mismatch and priority group into consideration. Methods: An age-structured dynamic transmission model was fitted to the laboratory data of the national influenza surveillance system to reconstruct a baseline scenario with which the vaccination scenarios of interest could be compared. Outcome measures were defined as the impacts on the seasonal epidemic: decompression of the epidemic peak, reduction of the epidemic burden and change of the epidemic peak time. Results: It was found that vaccine capacity building, although indispensable, could not guarantee substantial impact on the seasonal influenza epidemic. Vaccine mismatch might greatly offset vaccine capacity building. Notably, advance vaccine distribution could compensate for some vaccine underperformance. In the case of a well-matched vaccine, advance vaccine distribution could even exploit its utility. Conclusions: This study indicated that timely vaccine distribution should be put high on the agenda of seasonal influenza control policies. It provided a tangible platform for the policymakers to evaluate health policy impacts and to enhance risk communication with the public through mathematical modeling.

Keywords

• Influenza
• Vaccination
• Timing
• Transmission
• Modeling