摘要：SummaryNon-pharmacological interventions (NPIs), principally social distancing, in combination with effective vaccines, aspire to develop a protective immunity shield against pandemics and particularly against the COVID-19 pandemic. In this study, an agent-based network model with small-world topology is employed to find optimal policies against pandemics, including social distancing and vaccination strategies. The agents’ states are characterized by a variation of the SEIR model (susceptible, exposed, infected, recovered). To explore optimal policies, an equation-free method is proposed to solve the inverse problem of calibrating an agent’s infection rate with respect to the vaccination efficacy. The results show that prioritizing the first vaccine dose in combination with mild social restrictions, is sufficient to control the pandemic, with respect to the number of deaths. Moreover, for the same mild number of social contacts, we find an optimal vaccination ratio of 0.85 between older people of ages>65compared to younger ones.Graphical abstractDisplay OmittedHighlights•An epidemic model on networks is developed including lockdowns and vaccination strategies•An equation-free method is used to compute the microscopic infection rate•First dose prioritization controls the pandemic under mild contact restrictions•There is an optimum ratio of vaccinating ages >65 over the younger ones of 0.85Health sciences; Virology; Public health
