RESUMO
BackgroundMass vaccination campaigns started in Brazil on January/2021 with CoronaVac followed by ChAdOx1 nCov-19, and BNT162b2 mRNA vaccines. Target populations initially included vulnerable groups such as people older than 80 years, with comorbidities, of indigenous origin, and healthcare workers. Younger age groups were gradually included. MethodsA national cohort of 66.3 million records was compiled by linking registry-certified COVID-19 vaccination records from the Brazilian National Immunization Program with information on severe COVID-19 cases and deaths. Cases and deaths were aggregated by state and age group. Mixed-effects Poisson models were used to estimate the rate of severe cases and deaths among vaccinated and unvaccinated individuals, and the corresponding estimates of vaccine effectiveness by vaccine platform and age group. The study period is from mid-January to mid-July 2021. ResultsEstimates of vaccine effectiveness preventing deaths were highest at 97.9% (95% CrI: 93.5-99.8) among 20-39 years old with ChAdOx1 nCov-19, at 82.7% (95% CrI: 80.7-84.6) among 40-59 years old with CoronaVac, and at 89.9% (87.8--91.8) among 40-59 years old with partial immunization of BNT162b2. For all vaccines combined in the full regimen, the effectiveness preventing severe cases among individuals aged 80+ years old was 35.9% (95% CrI: 34.9-36.9) which is lower than that observed for individuals aged 60-79 years (61.0%, 95% CrI: 60.5-61.5). ConclusionDespite varying effectiveness estimates, Brazils population benefited from vaccination in preventing severe COVID-19 outcomes. Results, however, suggest significant vaccine-specific reductions in effectiveness by age, given by differences between age groups 60-79 years and over 80 years.
RESUMO
Roughly six months into the COVID-19 pandemic, many countries have managed to contain the spread of the virus by means of strict containment measures including quarantine, tracing and isolation of patients as well strong restrictions on population mobility. Here we propose an extended SEIR model to explore the dynamics of containment and then explore scenarios for the local extinction of the disease. We present both the deterministic and stochastic version fo the model and derive the [R]0 and the probability of local extinction after relaxation (elimination of transmission) of containment, [P]0. We show that local extinctions are possible without further interventions, with reasonable probability, as long as the number of active cases is driven to single digits and strict control of case importation is maintained. The maintenance of defensive behaviors, such as using masks and avoiding agglomerations are also important factors. We also explore the importance of population immunity even when above the herd immunity threshold.
RESUMO
BackgroundBrazil detected community transmission of COVID-19 on March 13, 2020. In this study we identify which areas in the country are most vulnerable for COVID-19, both in terms of the risk of arrival of COVID-19 cases and the risk of sustained transmission. The micro-regions with higher social vulnerability are also identified. MethodsProbabilistic models were used to calculate the probability of COVID-19 spread from Sao Paulo and Rio de Janeiro, according to previous data available on human mobility in Brazil. We also perform a multivariate cluster analysis of socio-economic indices to identify areas with similar social vulnerability. ResultsThe results consist of a series of maps of effective distance, outbreak probability, hospital capacity and social vulnerability. They show areas in the North and Northeast with high risk of COVID-19 outbreak that are also highly vulnerable. InterpretationThe maps produced are useful for authorities in their efforts to prioritize actions such as resource allocation to mitigate the effects of the pandemic and may help other countries to use a similar approach to predict the virus route in their countries as well. FundingNo funding
