Abstract
The article presents some aspects related to the COVID-19 pandemic in Brazil including public health, challenges facing healthcare workers and adverse impacts on the country's economy. Its main contribution is the availability of two web applications for online monitoring of the evolution of the pandemic in Brazil and South America. The applications provide the possibility to download data in different formats, view interactive maps and graphs of the cumulative confirmed cases, deaths and lethality rates, in addition to presenting plots of moving averages for states and municipalities. The predictions about new cases and new deaths caused by COVID-19, in states and regions of Brazil, are also reported using GAMLSS models. The forecasts can be easily used by public managers for effective decision-making.
Highlights
In December 2019, a doctor called Li Wenliang, who lived in Wuhan, China, was one of the first who identified the virus COVID-19
Based on data registered until 8 June 2021, it is possible to show evidence that new cases of COVID-19 are increasing in the following states: Alagoas, Bahia, Ceará, Maranhão, Mato Grosso do Sul, Mato Grosso, Minas Gerais, Paraíba, Paraná, Pernambuco, Piauí, Rio de Janeiro, Rio Grande do Norte, Roraima, São Paulo, Sergipe and Tocantins
When we analyze the data about new deaths, there is evidence that the number of new deaths are increasing in the following states: Alagoas, Bahia, Ceará, Goiás, Maranhão, Mato Grosso do Sul, Minas Gerais, Paraíba, Paraná, Pernambuco, Piauí, Rio de Janeiro, São Paulo and Sergipe
Summary
In December 2019, a doctor called Li Wenliang, who lived in Wuhan, China, was one of the first who identified the virus COVID-19. There are many factors that explain cases and deaths in a country such as the population density, percentage of the urban population, number of beds per hundred thousand inhabitants, human development index, Gini coefficient, poverty index, income per capita and life expectancy, the last one is the most important factor to yield higher death rates It is known, for example, that women are less likely than men to have fatal outcomes following coronavirus infection, the reasons for this sex difference remain unclear. The pandemic affected people who were already in expressive social vulnerability due to unemployment, poor housing conditions and difficulty in accessing health services Under these circumstances, it is possible to identify which factors contribute to a fast spread of the virus: they are linked to their pathogenic characteristics and to social and economic factors [5].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
