Policy optimization for multi-variant COVID-19 pandemic under unequal isolation and booster shot

COVID-19 continues to impact health, economies, and societies globally, with ongoing concerns about new waves and variant complexities. Effective policies, such as vaccination and isolation, are crucial for minimizing infections and mitigating socio-economic impacts. With the limited budget availability, it is important to design a policy to minimize not only infection but also negative impacts on economic and social. This study uses a System Dynamics (SD) model to analyze multi-variant COVID-19 spread, focusing on booster shots, vaccine supply rates, and isolation rates. Simulations with the United States case, considering the Alpha, Delta, and Wuhan variants, reveal key insights: (1) The base policy of vaccination and isolation controls Wuhan and Alpha but not Delta. (2) Adding boosters suppress infections and unemployment but struggles against Delta with current rates. (3) Prioritizing vaccines for the unvaccinated people is more effective than boosting the vaccinated ones. (4) Unequal isolation outperforms equal isolation. (5) Two policies suppress all variants: increased vaccines plus enhanced isolation, and these plus boosters. (6) Economic constraints favor increased vaccines and enhanced isolation without boosters, while boosters can accelerate control otherwise. Finally, desirability-based optimization is performed for determining isolation rate for each virus variant, vaccine supply rate, and booster shot option under conflicting objectives.