ABSTRACT
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.
ABSTRACT
Interrupted time series analyses (ITSA) were performed to measure the impact of social distancing policies (instituted 22/03/2020) and subsequent mandatory masking in the community (instituted 04/05/2020) on the incidence and effective reproductive number (Rt) of COVID-19 in Sao Paulo State, Brazil. Overall, the impact of social distancing both on incidence and Rt was greater than the incremental effect of mandatory masking. Those findings may reflect either a small impact of face masking or the loosening of social distancing after mandatory use of masks.
ABSTRACT
Public health policies to contain the spread of COVID-19 rely mainly on non-pharmacological measures. Those measures, especially social distancing, are a challenge for developing countries, such as Brazil. In Sao Paulo, the most populous state in Brazil (45 million inhabitants), most COVID-19 cases up to April 18th were reported in the Capital and metropolitan area. However, the inner municipalities, where 20 million people live, are also at risk. As governmental authorities discuss the loosening of measures for restricting population mobility, it is urgent to analyze the routes of dispersion of COVID-19 in those municipalities. In this ecological study, we use geographical models of population mobility as patterns for spread of SARS-Cov-2 infection. Based on surveillance data, we identify two patterns: one by contiguous diffusion from the capital metropolitan area and other that is hierarchical, with long-distance spread through major highways to cities of regional relevance. We also modelled the impact of social distancing strategies in the most relevant cities, and estimated a beneficial effect in each and every setting studied. This acknowledgement can provide real-time responses to support public health strategies.
