Assessing the Trade-Off between Voluntary and Forced Interventions to Control the Emergence of Recurring Pandemics—An Evolutionary Game-Theoretic Modeling

In this study, we aim to examine the dynamics of diseases by employing both voluntary and forced control strategies backed by evolutionary game theory (EGT). The impact of quarantine is investigated through our suggested framework provided that a partial adoption of voluntary vaccination is observed at the earlier stage. The combined and individual effect of dual preventive provisions are visualized through SEIR-type epidemic model. Additionally, the effect of coercive control policies’ efficacy on individual vaccination decision is illustrated through the lens of EGT. We also consider the cost associated with vaccination and quarantine. The numerical simulations shown in our work emphasize how important it is to put quarantine rules in place to stop the spread of infection. These restrictions imposed by the government can be relieving, especially during times when a sizable section of the populace is reluctant to get vaccinated because of its ineffectiveness or excessive cost. We also show when and under what circumstances one policy works better than the other. How these policies’ compliance rates should be calculated is therefore becomes a focal point of discussion. We support this claim by producing phase diagrams for three different evolutionary outcomes throughout our investigation and changing the two crucially important pick-up rate parameters, one connected with the quarantine policy and the other is related to the isolation policy, in various directions. We then additionally examine the efficacy and cost associated with different policy adaption. This model effectively highlights the importance of dual provisional safety in understanding public health issues by using the mean-field approximation technique, which aligns with the well-known imitation protocol known as individual-based risk assessment dynamics.