感染症の多様な株ダイナミクスに対する適応的ワクチン接種およびサーベイランス検査戦略

The dynamic nature of epidemic diseases presents significant challenges for containment and healthcare resource allocation, particularly as viral strains evolve and outbreak conditions shift over time. While interventions such as testing, vaccination, and quarantine have been widely implemented, most models assess these strategies in isolation. However, we evaluate the combined impact of all aforementioned interventions and optimize resource allocation for maximum effectiveness. This study introduces an adaptive compartmental epidemiological model (SEIR) that integrates dynamic vaccination accessibility and diagnostic surveillance testing strategies, allowing for optimized intervention strategies in response to real-time outbreak progression and demographic variations. Simulation results demonstrate that vaccination effectively reduces infection peaks, while adaptive testing strategies delay peak occurrences and mitigate severity by continuously adjusting to outbreak dynamics and available healthcare resources. By integrating real-time surveillance, strategic testing allocation, and vaccination planning, this model provides a scalable and flexible framework for epidemic preparedness. These findings offer actionable insights for policymakers, guiding the development of robust surveillance systems, optimized resource distribution, and predictive epidemic control measures to mitigate future outbreaks.