Considered an essential activity, the production coming from slaughterhouses did not stop its activities in the midst of the new coronavirus pandemics (SARS COV-19) in Brazil. South and Southeast regions of Pará are examples of how such activity is associated to the worldwide production circuit. Nevertheless, the spatial circulation of the supplies coming from the slaughterhouses becomes one of the covid-19 transmission vectors, due to the intense mobility of workers in the sector.

Using public transport systems has been reported to be a possible vector of virus transmission during epidemics. In this context, this article aims to analyze the spatial correlation between public transportation users and COVID-19 cases, using Recife (PE) as a case study. Using spatial analysis, the Moran I Global and Local index were calculated, and global and geographically weighted regression models were estimated for the months of March to June 2020, considering neighborhoods in Recife as a spatial unit of analysis.

As the coronavirus disease 2019 (COVID-19) spreads worldwide, epidemiological models have been employed to evaluate possible scenarios and gauge the efficacy of proposed interventions. Considering the complexity of disease transmission dynamics in cities, stochastic epidemic models include uncertainty in their treatment of the problem, allowing the estimation of the probability of an outbreak, the distribution of epidemic magnitudes, and their expected duration.

Objective: COVID-19 diagnosis is a critical problem, mainly due to the lack or delay in the test results. We aimed to obtain a model to predict SARS-CoV-2 infection in suspected patients reported to the Brazilian surveillance system. Methods: We analysed suspected patients reported to the National Surveillance System that corresponded to the following case definition: patients with respiratory symptoms and fever, who travelled to regions with local or community transmission or who had close contact with a suspected or confirmed case.

Brazil currently has one of the fastest-growing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemics in the world. Because of limited available data, assessments of the impact of nonpharmaceutical interventions (NPIs) on this virus spread remain challenging. Using a mobility-driven transmission model, we show that NPIs reduced the reproduction number from >3 to 1 to 1.6 in São Paulo and Rio de Janeiro. Sequencing of 427 new genomes and analysis of a geographically representative genomic dataset identified >100 international virus introductions in Brazil.