Vaccination efforts in Brazil: scenarios and perspectives under a mathematical modeling approach

An agent-based model is proposed to access the impact of vaccination strategies to halt the COVID-19 spread. The model is parameterized using data from Sao Paulo State, Brazil. It was considered the two vaccines that are already approved for emergency use in Brazil, the CoronaVac vaccine developed by the Chinese bio-pharmaceutical company Sinovac and the Oxford-AstraZeneca vaccine (ChadOx1) developed by Oxford University and the British laboratory AstraZeneca. Both of them are two-dose schemes, but the efficacy and the interval between doses are different. We found that even in the worst scenario, in which the vaccine does not prevent infection either severe symptoms, the number of deaths decreases from 122 to 99 for CoronaVac application and to 80 for ChadOx1 administration. The same patterns have been seen in hospitalizations. Nevertheless, we show that when a low risk perception occurs, the reduction values decrease between 2% to 4%. Moreover, the increase of disease prevalence also jeopardizes immunization, showing the importance of the mitigation measures maintenance. On the other hand, doubling the vaccination rate would be able to significantly decrease the disease outcomes, reducing deaths by up to 74.4%. In conclusion, vaccination, along with non-pharmaceutical measures, is key to the control of COVID-19 in Brazil.

Evaluating the effects of re-opening plans on dynamics of COVID-19 in SP

Coronavirus disease 2019 (COVID-19) was declared a pandemic by the World Health Organization in early March 2020. In Brazil, Sao Paulo is the most affected state, comprising about 20% of the countrys cases. With no vaccine available to date, distancing measures have been taken to reduce virus transmission. To reduce the pandemics effect on the economy, the government of Sao Paulo has proposed a plan consisting of five phases of the gradual re-opening of activities. In this context, we have developed a mathematical model to simulate the gradual re-opening plan on the transmission dynamics of COVID-19, in the city of Sao Paulo. The model shows that a precipitous reopening can cause a higher peak of the disease, which may compromise the local health system. Waiting for the reduction in the incidence of infected individuals for at least 15 days to phase transition is the most efficient strategy compared to the fixed-period scenario at each phase of the re-opening plan.