To estimate the reporting rates of coronavirus disease 2019 (COVID-19) cases for Brazil as a whole and states. We estimated the actual number of COVID-19 cases using the reported number of deaths in Brazil and each state, and the expected case-fatality ratio from the World Health Organization. Brazil's expected case-fatality ratio was also adjusted by the population's age pyramid. Therefore, the notification rate can be defined as the number of confirmed cases (notified by the Ministry of Health) divided by the number of expected cases (estimated from the number of deaths). The reporting rate for COVID-19 in Brazil was estimated at 9.2% (95%CI 8.8% - 9.5%), with all the states presenting rates below 30%. São Paulo and Rio de Janeiro, the most populated states in Brazil, showed small reporting rates (8.9% and 7.2%, respectively). The highest reporting rate occurred in Roraima (31.7%) and the lowest in Paraiba (3.4%). The results indicated that the reporting of confirmed cases in Brazil is much lower as compared to other countries we analyzed. Therefore, decision-makers, including the government, fail to know the actual dimension of the pandemic, which may interfere with the determination of control measures.

The importance of the residential class in the consumption of electricity in the Brazilian Electric System (BES) can be recognized by its quantitative size, as it, in 2013, concentrates 27% of the total consumption and 85% among all consumers. Also, in this class are the main public policies such as subsidies for consumer units inhabited by low-income families, labelling and increased energy efficiency of appliances used in the home and others. This paper aims to model and forecast the Brazilian residential energy consumption, up to 2050, with Pegels exponential smoothing techniques. In addition to the forecasts with the best model in sample, an optimization procedure of the model's hyper parameters is carried out in order to adjust the projections provided by the Energy Research Company (ERC). The results obtained show that it is possible to predict satisfactorily the electricity consumption for the proposed horizon with minimum error in sample. And the exercise of optimization proved to be important for providing level and trend equations for the official expectations regarding the residential electricity consumption in Brazil