Mathematical model of COVID-19 intervention scenarios for SAo Paulo-Brazil

With COVID-19 surging across the world, understanding the effectiveness of intervention strategies on transmission dynamics is of primary global health importance. Here, we develop and analyze an epidemiological compartmental model using multi-objective genetic algorithm design optimization to compare scenarios related to strategy type, the extent of social distancing, time window, and personal protection levels on the transmission dynamics of COVID-19 in SAo Paulo, Brazil. The results indicate that the optimal strategy for SAo Paulo is to reduce social distancing over time with a stepping-down reduction in the magnitude of social distancing every 80-days. Our results also indicate that the ability to reduce social distancing depends on a 5-10% increase in the current percentage of people strictly following protective guidelines, highlighting the importance of protective behavior in controlling the pandemic. Our framework can be extended to model transmission dynamics for other countries, regions, states, cities, and organizations. Incidence of COVID-19 has been high in parts of South America including Brazil, and information on effective intervention strategies is needed. Here, the authors use mathematical modelling to show that reductions in social distancing should be made gradually to avoid a severe second peak of cases.

Automated summary

The optimal strategy for controlling COVID-19 transmission dynamics in Sao Paulo, Brazil involves gradually reducing social distancing over time with a stepping-down reduction every 80 days. Increasing the percentage of people strictly following protective guidelines by 5-10% is also crucial in reducing social distancing. This framework can be applied to model transmission dynamics in other regions and organizations.