Objective: To describe the methods used in a rapid review of the literature and to present the main epidemiological parameters that describe the transmission of SARS-Cov-2 and the illness caused by this virus, coronavirus disease 2019 (COVID-19).Methods: This is a methodological protocol that enabled a rapid review of COVID-19 epidemiological parameters.Findings: The protocol consisted of the following steps: definition of scope; eligibility criteria; information sources; search strategies; selection of studies; and data extraction. Four reviewers and three supervisors conducted this review in 40 days. Of the 1,266 studies found, 65 were included, mostly observational and descriptive in content, indicating relative homogeneity as to the quality of the evidence. The variation in the basic reproduction number, between 0.48 and 14.8; and the median of the hospitalization period, between 7.5 and 20.5 days stand out as key findings.Conclusion: We identified and synthesized 10 epidemiological parameters that may support predictive models and other rapid reviews to inform modeling of this and other future public health emergencies.

Resumo Objetivo: Caracterizar os casos com notificação pós-óbito da tuberculose no Brasil em 2014. Métodos: Estudo descritivo dos casos de tuberculose com notificação pós-óbito. Os dados são resultantes da vinculação do Sistema de Informação de Agravos de Notificação (Sinan-TB) com o Sistema de Informações sobre Mortalidade (SIM), e foram descritos segundo causa básica de óbito: tuberculose, aids e outras. Resultados: Nos 2.703 casos de tuberculose com notificação pós-óbito, observou-se maior proporção de pessoas do sexo masculino (73,5%), com mais de 39 anos de idade (80,8%), com escolaridade <8 anos de estudo (66,5%), de raça/cor da pele negra e parda (62,8%), que adoeceram de tuberculose na forma clínica pulmonar (75,2%); também prevaleceram notificações pelo serviço público (57,6%) e em municípios com índice de desenvolvimento humano >0,7 (66,6%). Conclusão: As características descritas das pessoas notificadas pós-óbito e a magnitude desse desfecho sugerem fragilidades dos serviços de atenção e vigilância da tuberculose

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Background In Brazil, malaria is caused mainly by the Plasmodium vivax and Plasmodium falciparum species. Its transmission occurs in endemic and non-endemic areas. Malaria geography in Brazil has retracted and is now concentrated in the North region. The Brazilian Amazon region accounts for 99% of Brazil's cases. Brazil’s extra-Amazon region has a high frequency of imported cases and in 2019 presented a mortality rate 123 times higher than the Amazon region. Extra-Amazon cases present risks of reintroduction. This study aims to characterize the epidemiological scenario for malaria in the extra-Amazon region of Brazil from 2011 to 2020 with a two-year forecast. Methods Time-series study with description of malaria cases and deaths registered in Brazilian extra-Amazon region from 2011 to 2020. Public data from the Notifiable Diseases Information System (Sinan) and the Mortality Information System (SIM) were used. Descriptive analysis, incidence, and notification rates were calculated. Flow charts analysed the flux between Places of Probable Infection (PI) and places of notification. The prediction model utilized a multiplicative Holt-winters model for trend and seasonality components. Results A total of 6849 cases were registered. Cases were predominantly white males with 9 to 11 years of education, mostly between 30 and 39 years old. Imported cases accounted for 78.9% of cases. Most frequent occupations for imported cases are related to travelling and tourism activities. Among autochthonous cases, there is a higher frequency of agriculture and domestic economic activities. In the period there were 118 deaths due to malaria, of which 34.7% were caused by P. falciparum infections and 48.3% were not specified. The most intense flows of imported cases are from Amazonas and Rondônia to São Paulo, Rio de Janeiro, and Paraná. The prediction estimates around 611 cases for each of the following two years. Conclusion The time series allows a vast epidemiological visualization with a short-term prediction analysis that supports public health planning. Government actions need to be better directed in the extra-Amazon region so the objective of eliminating malaria in Brazil is achieved. Carrying out quality assessments for information systems and qualifying personnel is advisable. Malaria outside the Amazon region is mainly due to imported cases and delay in diagnosis is associated with a higher fatality rate. Better strategies to diagnose and treat suspected cases can lead to lower risk of deaths and local outbreaks that will be important for achieving malaria elimination in Brazil.