Mitigating direct and indirect costs of unexpected pandemics: a parallel vaccination strategy utilizing agent-based simulation

The prioritization of individuals for vaccination based on limited resources and decision-making time—primarily focusing on age groups—overlooks the broader impacts of lockdown policies on the economy and psychological well-being. This study emphasizes the need to draw lessons from epidemic disasters to inform future responses and policies, highlighting the importance of considering wider societal and economic implications in vaccination prioritization strategies. Therefore, we present a strategy that considers both pharmaceutical and non-pharmaceutical interventions, including two-dose vaccination, partial lockdowns, face mask usage, and a new prioritization approach, aimed at minimizing social costs, economic impacts, and psychological effects (e.g. depression) of lockdown policies, using Covid-19 as a case study. We explore prioritization of retail units alongside age groups to investigate vaccination strategies that enhance socio-economic effectiveness. Additionally, we estimate the required vaccine doses by accounting for the efficacy of the first and second doses and their impact on controlling the epidemic. We apply an agent-based model to simulate a hypothetical community, parameterized with demographic and social characteristics inspired by Iran, to evaluate the effects of parallel vaccination and non-pharmaceutical interventions. The results show that vaccinating businesses and age groups simultaneously leads to lower social, economic, and psychological costs of lockdown policies.