ABC | Volume 114, Nº6, June 2020

Editorial Fernandes Covid-19: difficulties and prospects Arq Bras Cardiol. 2020; 114(6):988-991 But if we are used to being guided by more precise figures in cardiology, how do we know if the estimates are correct and if we have been drifting away from the actual figures? We have then looked for official sources that could allow us to infer and check these calculations. Unfortunately, at least until this date of the pandemic, there has been tremendous confusion regarding data reporting, which has caused the interpretation of the pandemic phase in Brazil to be greatly impaired. Due to delayed determination of SARS-CoV-2 infections, many cases have been reported days and even weeks late, causing the official authorities to report numbers of confirmed cases as numbers of actual daily cases, confusing press bulletins and often causing unnecessary fuss, especially when accumulated numbers of weekends and holidays were late announced on Tuesdays. 10 In order to try to understand the numbers, it is necessary to check different sources with adjusted numbers and, above all, to look for more realistic statistics on the information on deaths occurring in the country, as this metric is much more robust from the point of view of reporting despite reflecting what happened 14 days prior. In this regard, it is worth mentioning the important contribution of the data reported on the Transparency Portal organized by the National Association of Registrars of Vital Statistics, which allows a more accurate monitoring of the number of deaths from Covid-19 or suspected deaths on the actual date of the occurrence, rather than on the reporting date. 11 Along with this data, information on monitoring hospitalizations for Serious Acute Respiratory Syndromes through the InfoGripe system also helped to continuously monitor trends and confirm or not the forecasts made. 12 Despite all these tools at hand, the social isolation measures were taken in a very controversial way, often not considering the stage of the pandemic cycle we were at, with a late adoption, and sometimes following a course of action without presenting consistent data that would justify the measures taken. Given the great difference between the structure of resources found in the country and the phases of the pandemic in each state, the degrees of isolation should certainly be quite different since each measure individually or together has different effects on reducing viral transmission. In this sense, we must also remember the Pareto principle, where 20% of what we do reaches 80% of the result: the correct application of well-done social distancing, with 25% reduction from the original distancing, allows an effective transmission response to be maintained once R0 is initially reduced. 13 Therefore, relatively simple measures of advising the population to wash their hands, keeping away from others, wearing masks, etc., as long as they are well applied, can often be better than attempts at taking drastic yet disorderly actions not well understood by Table 1 – Prediction of state peaks of new cases/day, deaths and hospital use based on modeling from 30 countries (shown only with an estimate from the 100th case). Estimated data for research purposes, pending modification and verification State 1 st Case 100 th Case 200 th Case 10 th Death Peak 100 th Case Lower 95%CI Upper 95%CI Death Peaks (100) Hospital Peak (100) SP (Metrop. Area) Feb 4 th Mar 2 nd Mar 6 th Mar 6 th Apr 2 nd Mar 28 th Apr 6 th Apr 16 th Apr 28 th CE Feb 14 th Mar 7 th Mar 10 th Mar 15 th Apr 7 th Apr 2 nd Apr 11 th Apr 21 st May 3 rd GO Mar 2 nd Mar 8 th Mar 11 th Mar 26 th Apr 8 th Apr 3 rd Apr 12 th Apr 22 nd May 4 th SC Feb 28 th Mar 14 th Mar 17 th Apr 4 th Apr 14 th Apr 9 th Apr 18 th Apr 28 th May 10 th RJ Feb 27 th Mar 15 th Mar 18 th Mar 18 th Apr 15 th Apr 10 th Apr 19 th Apr 29 th May 11 th DF Feb 26 th Mar 15 th Mar 18 th Apr 4 th Apr 15 th Apr 10 th Apr 19 th Apr 29 th May 11 th BA Feb 26 th Mar 16 th Mar 19 th Apr 16 th Apr 11 th Apr 20 th Apr 30 th May 12 th RN Mar 8 th Mar 18 th Mar 21 st Apr 7 th Apr 18 th Apr 13 th Apr 22 nd May 2 nd May 14 th RS Mar 9 th Mar 21 st Mar 25 th Apr 8 th Apr 21 st Apr 16 th Apr 25 th May 5 th May 17 th MG Mar 17 th Mar 23 rd Mar 27 th Apr 2 nd Apr 23 rd Apr 18 th Apr 27 th May 7 th May 19 th MT Mar 19 th Mar 24 th Mar 27 th Apr 26 th Apr 24 th Apr 19 th Apr 28 th May 8 th May 20 th PR Mar 12 th Mar 26 th Apr 1 st Apr 6 th Apr 26 th Apr 21 st Apr 30 th May 10 th May 22 nd AM Mar 18 th Mar 28 th Apr 1 st Apr 28 th Apr 23 rd May 2 nd May 12 th May 24 th PE Mar 12 th Apr 2 nd Apr 5 th Apr 1 st May 3 rd Apr 28 th May 7 th May 17 th May 29 th MA Mar 20 th Apr 5 th Apr 7 th Apr 6 th May 6 th May 1 st May 10 th May 20 th Jun 1 st PA Mar 18 th Apr 6 th Apr 10 th Apr 11 th May 7 th May 2 nd May 11 th May 21 st Jun 2 nd PB Mar 19 th Apr 11 th Apr 17 th Apr 9 th May 12 th May 7 th May 16 th May 26 th Jun 7 th AL Mar 10 th Apr 17 th Apr 21 st Apr 18 th May 18 th May 13 th May 22 nd Jun 1 st Jun 13 th PI Mar 19 th Apr 17 th Apr 21 st Apr 18 th May 18 th May 13 th May 22 nd Jun 1 st Jun 13 th CI: confidence interval. 989