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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="editorial" dtd-version="1.1" specific-use="sps-1.9" xml:lang="pt">
  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">Arq Bras Cardiol</journal-id>
      <journal-id journal-id-type="publisher-id">abc</journal-id>
      <journal-title-group>
        <journal-title>Arquivos Brasileiros de Cardiologia</journal-title>
        <abbrev-journal-title abbrev-type="publisher">Arq. Bras. Cardiol.</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">0066-782X</issn>
      <issn pub-type="epub">1678-4170</issn>
      <publisher>
        <publisher-name>Sociedade Brasileira de Cardiologia - SBC</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id" specific-use="scielo-v3">dpdQbrScHy6b3sVkSWVsjMd</article-id>
      <article-id pub-id-type="publisher-id" specific-use="scielo-v2">S0066-782X2020000700988</article-id>
      <article-id pub-id-type="publisher-id">abc.20200445</article-id>
      <article-id pub-id-type="doi">10.36660/abc.20200445</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Editorial</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Covid-19 no Brasil: Aprendendo a Andar no Escuro sem Deixar Nada para Tr&#225;s</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-6726-5324</contrib-id>
          <name>
            <surname>Fernandes</surname>
            <given-names>Juliano Lara</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label>1</label>
        <institution content-type="orgname">Radiologia Cl&#237;nica de Campinas</institution>
        <addr-line>
          <named-content content-type="city">Campinas</named-content>
          <named-content content-type="state">SP</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">Radiologia Cl&#237;nica de Campinas, Campinas, SP - Brasil</institution>
      </aff>
      <aff id="aff2">
        <label>2</label>
        <institution content-type="orgname">Instituto de Ensino e Pesquisa Jose Michel Kalaf</institution>
        <addr-line>
          <named-content content-type="city">Campinas</named-content>
          <named-content content-type="state">SP</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">Instituto de Ensino e Pesquisa Jose Michel Kalaf,Campinas, SP &#8211; Brasil</institution>
      </aff>
      <author-notes>
        <corresp id="c01"> Correspond&#234;ncia: Juliano Lara Fernandes Radiologia Cl&#237;nica de Campinas &#8211; Av. Jos&#233; de Souza Campos, 840. CEP 13092123, Campinas, SP - Brasil E-mail: <email>jlaraf@terra.com.br</email>
				</corresp>
      </author-notes>
      <pub-date date-type="pub" publication-format="electronic">
        <day>03</day>
        <month>07</month>
        <year>2020</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <month>06</month>
        <year>2020</year>
      </pub-date>
      <volume>114</volume>
      <issue>6</issue>
      <fpage>988</fpage>
      <lpage>991</lpage>
      <permissions>
        <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/" xml:lang="en">
          <license-p> This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. </license-p>
        </license>
      </permissions>
      <kwd-group xml:lang="pt">
        <kwd>Coronavirus, COVID-19</kwd>
        <kwd>Pandemia</kwd>
        <kwd>Doen&#231;a Catastr&#243;fica/mortalidade</kwd>
        <kwd>Hospitaliza&#231;&#227;o/economia</kwd>
        <kwd>Equidade no Acesso aos Servi&#231;os de Sa&#250;de</kwd>
        <kwd>Testes Diagn&#243;sticos/m&#233;todos</kwd>
        <kwd>Equipamento de Prote&#231;&#227;o Individual</kwd>
        <kwd>M&#225;scaras</kwd>
        <kwd>Ventiladores Mec&#226;nicos</kwd>
      </kwd-group>
      <counts>
        <fig-count count="0"/>
        <table-count count="2"/>
        <equation-count count="0"/>
        <ref-count count="22"/>
        <page-count count="3"/>
      </counts>
    </article-meta>
  </front>
  <body>
    <disp-quote>
      <p>
        <italic>&#8220;Se Voc&#234; Tem Altos e Baixos, Celebre, pois Significa que est&#225; Vivo!&#8221;</italic>
      </p>
    </disp-quote>
    <p>A pandemia pelo SARS-CoV-2 teve seu primeiro caso no Brasil em 04/02/2020 no estado de S&#227;o Paulo. Como um verdadeiro meteoro, praticamente paralisou o planeta sem que tiv&#233;ssemos uma medida terap&#234;utica mais efetiva para combater o v&#237;rus al&#233;m de pr&#225;ticas utilizadas globalmente apenas d&#233;cadas ou at&#233; centenas de anos atr&#225;s, com n&#237;vel de evid&#234;ncia moderna muito pouco robusta.<sup><xref ref-type="bibr" rid="B1">1</xref></sup> O Brasil teve a vantagem de antevis&#227;o da pandemia por estar algumas semanas atr&#225;s dos seus pares asi&#225;ticos e europeus, podendo identificar erros e acertos desses pa&#237;ses na sua prepara&#231;&#227;o para enfrentar o problema.</p>
    <p>Assim, descobrimos meio por acaso que temos o terceiro maior n&#250;mero de leitos de UTI do mundo, perdendo apenas para EUA e Alemanha,<sup><xref ref-type="bibr" rid="B2">2</xref></sup> mas tamb&#233;m nos deparamos com enorme heterogeneidade entres estados, limita&#231;&#227;o e burocracia para aquisi&#231;&#227;o de equipamentos de prote&#231;&#227;o individual e kits de testagem. Isso fez com que algumas op&#231;&#245;es de abordagem da pandemia adotadas em outros pa&#237;ses n&#227;o pudessem ser reproduzidas aqui, seja pela impossibilidade de um <italic>lockdown</italic> num pa&#237;s continental, seja pela agilidade e custos necess&#225;rios para se fazer a identifica&#231;&#227;o dos casos transmissores. Al&#233;m disso, a limita&#231;&#227;o do n&#250;mero de testes a serem realizados nos deixou sem um guia preciso sobre o momento em que a pandemia se encontrava, dificultando muito o planejamento para aloca&#231;&#227;o eficiente dos escassos recursos de forma correta e no tempo certo.</p>
    <p>A solu&#231;&#227;o para isso foi adotar estrat&#233;gias pr&#243;prias que permitissem caminharmos no escuro, mas tendo ao menos uma ideia mais pr&#243;xima sobre em que altura do caminho est&#225;vamos. Tal informa&#231;&#227;o &#233; essencial para decis&#245;es importantes que impactam n&#227;o s&#243; a parte econ&#244;mica do pa&#237;s, mas tamb&#233;m toda a cadeia de sa&#250;de da popula&#231;&#227;o, que se viu privada de acessos ambulatoriais e tratamentos eletivos por conta da pandemia. Os modelos matem&#225;ticos epidemiol&#243;gicos te&#243;ricos se mostraram pouco capazes de predizer nossos n&#250;meros reais, seja por superestimar a letalidade da doen&#231;a que parece se comportar mais pr&#243;ximo de 0.2-0.5%,<sup><xref ref-type="bibr" rid="B3">3</xref></sup> seja por usar dados de pandemias passadas com outras din&#226;micas de transmiss&#227;o. Interessantemente, os modelos que mais se prestaram a modelar em que altura da pandemia estamos vieram de estrat&#233;gias de ajuste de curvas ou modelos bayseanos utilizando dados j&#225; existentes em outros pa&#237;ses ou com base nos dados preliminares que j&#225; t&#237;nhamos em nossas curvas.<sup><xref ref-type="bibr" rid="B4">4</xref> , <xref ref-type="bibr" rid="B5">5</xref></sup> Esses modelos apareceram de forma relativamente espont&#226;nea e fora de grupos de pesquisa tradicionais, mas se revelaram mais assertivos em determinar diversos momentos da pandemia.<sup><xref ref-type="bibr" rid="B6">6</xref></sup></p>
    <p>De forma mais simplificada, mas tamb&#233;m utilizando dados de como a pandemia se comportou previamente em outros pa&#237;ses, buscamos analisar os gr&#225;ficos de casos novos por dia de 30 pa&#237;ses com os maiores n&#250;meros de casos de Covid-19, de acordo com os seguintes crit&#233;rios: pa&#237;ses que j&#225; haviam atingido um pico m&#225;ximo e apresentavam ao menos 5 dias de queda ou estabiliza&#231;&#227;o dos casos novos di&#225;rios.<sup><xref ref-type="bibr" rid="B7">7</xref></sup> A China foi exclu&#237;da pois concentrou num dia posterior milhares de casos anteriores; Brasil foi exclu&#237;do por ser objeto da aplica&#231;&#227;o do resultado. Foram inclu&#237;dos 5 pa&#237;ses que n&#227;o tiveram isolamento mandat&#243;rio. Dos 30 pa&#237;ses, 18 j&#225; foram considerados como tendo conclu&#237;do o ciclo completo da pandemia, com n&#250;mero de casos novos di&#225;rios &lt;70% do pico de casos novos por dia. Utilizando a data do 1&#186;, 100&#186; e 200&#186; caso ou 10&#186;<sup>o</sup> &#243;bito, foram determinados os tempos entre essas datas e o pico de casos novos/dia da doen&#231;a. A partir desses resultados, observou-se que 95% dos pa&#237;ses estudados apresentavam seus picos 55&#177;8 dias do 1&#186; caso, 31&#177;5 dias do 100&#186; caso, 27&#177;5 dias do 200&#186; caso e 19&#177;4 dias do 10&#186; &#243;bito. Com esse dado, seria poss&#237;vel se estabelecer qual seriam os picos de casos novos, &#243;bitos e uso do sistema hospitalar em diversos estados e cidades do pa&#237;s, mesmo sem se ter a certeza do n&#250;mero exato de casos pela subnotifica&#231;&#227;o, com base no comportamento da pandemia em pa&#237;ses com os mais distintos sistemas de sa&#250;de e medidas de mitiga&#231;&#227;o do v&#237;rus. As datas de pico de &#243;bitos foram estabelecidas a partir de 14 dias do pico de casos e do uso do sistema hospitalar a partir de 26 dias do pico de casos, tendo em vista os tempos de incuba&#231;&#227;o, manifesta&#231;&#227;o de sintomas, interna&#231;&#227;o e eventual piora cl&#237;nica da doen&#231;a.<sup><xref ref-type="bibr" rid="B8">8</xref></sup> Com essas premissas, estimamos os diversos picos em cada um dos estados brasileiros com os maiores n&#250;meros de casos, mostrados na <xref ref-type="table" rid="t1">Tabela 1</xref> (limitado apenas &#224; previs&#227;o a partir do 100&#186; caso para exemplificar o modelo). O que n&#227;o se consegue prever com nenhum desses modelos &#233; a parte descendente da curva, mais r&#225;pida em alguns locais e muito mais lenta &#8212; exibindo um plat&#244; &#8212; em outros, demandando leitos hospitalares por tempo mais prolongado, um poss&#237;vel efeito de virul&#234;ncia distinta do v&#237;rus ap&#243;s in&#250;meras muta&#231;&#245;es.<sup><xref ref-type="bibr" rid="B9">9</xref></sup></p>
    <p>
      <table-wrap id="t1">
        <label>Tabela 1</label>
        <caption>
          <title>&#8211; Previs&#227;o de picos estaduais de casos novos/dia, &#243;bitos e uso hospitalar baseado em modelagem de 30 pa&#237;ses (mostrado apenas com estimativa a partir do 100&#186; caso). Dados estimados para efeito de pesquisa, pendentes de modifica&#231;&#227;o e verifica&#231;&#227;o</title>
        </caption>
        <table frame="hsides" rules="groups">
          <colgroup width="10%">
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
          </colgroup>
          <thead>
            <tr>
              <th align="left">Estado</th>
              <th>1&#186; Caso</th>
              <th>100&#186; Caso</th>
              <th>200&#186; Caso</th>
              <th>10&#186; &#211;bito</th>
              <th>Pico 100&#186; caso</th>
              <th>IC95% inf.</th>
              <th>IC95% sup</th>
              <th>Pico &#211;bitos (100)</th>
              <th>Pico Hospitalar (100)</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td>SP (Reg Metrop)</td>
              <td align="center">04/fev</td>
              <td align="center">02/mar</td>
              <td align="center">06/mar</td>
              <td align="center">06/mar</td>
              <td align="center">02/abr</td>
              <td align="center">28/mar</td>
              <td align="center">06/abr</td>
              <td align="center">16/abr</td>
              <td align="center">28/abr</td>
            </tr>
            <tr>
              <td>CE</td>
              <td align="center">14/fev</td>
              <td align="center">07/mar</td>
              <td align="center">10/mar</td>
              <td align="center">15/mar</td>
              <td align="center">07/abr</td>
              <td align="center">02/abr</td>
              <td align="center">11/abr</td>
              <td align="center">21/abr</td>
              <td align="center">03/mai</td>
            </tr>
            <tr>
              <td>GO</td>
              <td align="center">02/mar</td>
              <td align="center">08/mar</td>
              <td align="center">11/mar</td>
              <td align="center">26/mar</td>
              <td align="center">08/abr</td>
              <td align="center">03/abr</td>
              <td align="center">12/abr</td>
              <td align="center">22/abr</td>
              <td align="center">04/mai</td>
            </tr>
            <tr>
              <td>SC</td>
              <td align="center">28/fev</td>
              <td align="center">14/mar</td>
              <td align="center">17/mar</td>
              <td align="center">04/abr</td>
              <td align="center">14/abr</td>
              <td align="center">09/abr</td>
              <td align="center">18/abr</td>
              <td align="center">28/abr</td>
              <td align="center">10/mai</td>
            </tr>
            <tr>
              <td>RJ</td>
              <td align="center">27/fev</td>
              <td align="center">15/mar</td>
              <td align="center">18/mar</td>
              <td align="center">18/mar</td>
              <td align="center">15/abr</td>
              <td align="center">10/abr</td>
              <td align="center">19/abr</td>
              <td align="center">29/abr</td>
              <td align="center">11/mai</td>
            </tr>
            <tr>
              <td>DF</td>
              <td align="center">26/fev</td>
              <td align="center">15/mar</td>
              <td align="center">18/mar</td>
              <td align="center">04/abr</td>
              <td align="center">15/abr</td>
              <td align="center">10/abr</td>
              <td align="center">19/abr</td>
              <td align="center">29/abr</td>
              <td align="center">11/mai</td>
            </tr>
            <tr>
              <td>BA</td>
              <td align="center">26/fev</td>
              <td align="center">16/mar</td>
              <td align="center">19/mar</td>
              <td>
							</td>
              <td align="center">16/abr</td>
              <td align="center">11/abr</td>
              <td align="center">20/abr</td>
              <td align="center">30/abr</td>
              <td align="center">12/mai</td>
            </tr>
            <tr>
              <td>RN</td>
              <td align="center">08/mar</td>
              <td align="center">18/mar</td>
              <td align="center">21/mar</td>
              <td align="center">07/abr</td>
              <td align="center">18/abr</td>
              <td align="center">13/abr</td>
              <td align="center">22/abr</td>
              <td align="center">02/mai</td>
              <td align="center">14/mai</td>
            </tr>
            <tr>
              <td>RS</td>
              <td align="center">09/mar</td>
              <td align="center">21/mar</td>
              <td align="center">25/mar</td>
              <td align="center">08/abr</td>
              <td align="center">21/abr</td>
              <td align="center">16/abr</td>
              <td align="center">25/abr</td>
              <td align="center">05/mai</td>
              <td align="center">17/mai</td>
            </tr>
            <tr>
              <td>MG</td>
              <td align="center">17/mar</td>
              <td align="center">23/mar</td>
              <td align="center">27/mar</td>
              <td align="center">02/abr</td>
              <td align="center">23/abr</td>
              <td align="center">18/abr</td>
              <td align="center">27/abr</td>
              <td align="center">07/mai</td>
              <td align="center">19/mai</td>
            </tr>
            <tr>
              <td>MT</td>
              <td align="center">19/mar</td>
              <td align="center">24/mar</td>
              <td align="center">27/mar</td>
              <td align="center">26/abr</td>
              <td align="center">24/abr</td>
              <td align="center">19/abr</td>
              <td align="center">28/abr</td>
              <td align="center">08/mai</td>
              <td align="center">20/mai</td>
            </tr>
            <tr>
              <td>PR</td>
              <td align="center">12/mar</td>
              <td align="center">26/mar</td>
              <td align="center">01/abr</td>
              <td align="center">06/abr</td>
              <td align="center">26/abr</td>
              <td align="center">21/abr</td>
              <td align="center">30/abr</td>
              <td align="center">10/mai</td>
              <td align="center">22/mai</td>
            </tr>
            <tr>
              <td>AM</td>
              <td align="center">18/mar</td>
              <td align="center">28/mar</td>
              <td align="center">01/abr</td>
              <td>
							</td>
              <td align="center">28/abr</td>
              <td align="center">23/abr</td>
              <td align="center">02/mai</td>
              <td align="center">12/mai</td>
              <td align="center">24/mai</td>
            </tr>
            <tr>
              <td>PE</td>
              <td align="center">12/mar</td>
              <td align="center">02/abr</td>
              <td align="center">05/abr</td>
              <td align="center">01/abr</td>
              <td align="center">03/mai</td>
              <td align="center">28/abr</td>
              <td align="center">07/mai</td>
              <td align="center">17/mai</td>
              <td align="center">29/mai</td>
            </tr>
            <tr>
              <td>MA</td>
              <td align="center">20/mar</td>
              <td align="center">05/abr</td>
              <td align="center">07/abr</td>
              <td align="center">06/abr</td>
              <td align="center">06/mai</td>
              <td align="center">01/mai</td>
              <td align="center">10/mai</td>
              <td align="center">20/mai</td>
              <td align="center">01/jun</td>
            </tr>
            <tr>
              <td>PA</td>
              <td align="center">18/mar</td>
              <td align="center">06/abr</td>
              <td align="center">10/abr</td>
              <td align="center">11/abr</td>
              <td align="center">07/mai</td>
              <td align="center">02/mai</td>
              <td align="center">11/mai</td>
              <td align="center">21/mai</td>
              <td align="center">02/jun</td>
            </tr>
            <tr>
              <td>PB</td>
              <td align="center">19/mar</td>
              <td align="center">11/abr</td>
              <td align="center">17/abr</td>
              <td align="center">09/abr</td>
              <td align="center">12/mai</td>
              <td align="center">07/mai</td>
              <td align="center">16/mai</td>
              <td align="center">26/mai</td>
              <td align="center">07/jun</td>
            </tr>
            <tr>
              <td>AL</td>
              <td align="center">10/mar</td>
              <td align="center">17/abr</td>
              <td align="center">21/abr</td>
              <td align="center">18/abr</td>
              <td align="center">18/mai</td>
              <td align="center">13/mai</td>
              <td align="center">22/mai</td>
              <td align="center">01/jun</td>
              <td align="center">13/jun</td>
            </tr>
            <tr>
              <td>PI</td>
              <td align="center">19/mar</td>
              <td align="center">17/abr</td>
              <td align="center">21/abr</td>
              <td align="center">18/abr</td>
              <td align="center">18/mai</td>
              <td align="center">13/mai</td>
              <td align="center">22/mai</td>
              <td align="center">01/jun</td>
              <td align="center">13/jun</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN1">
            <p>
              <italic>IC: intervalo de confian&#231;a</italic>
            </p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
    </p>
    <p>Mas se estamos acostumados a sempre nos guiar por n&#250;meros mais precisos na cardiologia, como saber se as estimativas est&#227;o corretas e checar se n&#227;o desviamos dos n&#250;meros reais? Para isso, buscamos nas fontes oficiais dados que nos permitem inferir e conferir esses c&#225;lculos. Infelizmente, ao menos at&#233; esta data da pandemia, criou-se uma confus&#227;o tremenda na forma de divulga&#231;&#227;o de dados que fez com que a interpreta&#231;&#227;o da fase da pandemia no pa&#237;s fosse muito prejudicada. Devido aos atrasos na verifica&#231;&#227;o das infec&#231;&#245;es pelo SARS-CoV-2, muitos casos foram notificados com dias e at&#233; semanas de atraso, fazendo com que os &#243;rg&#227;os oficiais soltassem n&#250;meros de registros confirmados como n&#250;meros de ocorr&#234;ncias reais no dia, confundindo os boletins de imprensa e causando muitas vezes alarmes desnecess&#225;rios, sobretudo quando n&#250;meros acumulados de finais de semana e feriados eram anunciados nas ter&#231;as-feiras na compila&#231;&#227;o atrasada.<sup><xref ref-type="bibr" rid="B10">10</xref></sup> Para tentar ent&#227;o entender os n&#250;meros, &#233; necess&#225;rio tentar checar fontes diversas com n&#250;meros ajustados e, sobretudo, buscar na informa&#231;&#227;o dos &#243;bitos uma estat&#237;stica um pouco mais realista do que ocorre no pa&#237;s, dado que essa m&#233;trica &#233; muito mais robusta do ponto de vista de notifica&#231;&#227;o apesar de refletir o que se passou 14 dias atr&#225;s. Neste sentido, destaco aqui a importante contribui&#231;&#227;o dos dados registrados no Portal da Transpar&#234;ncia, organizado pela Associa&#231;&#227;o Nacional de Registradores de Pessoas Naturais, que permite um acompanhamento mais acurado do n&#250;mero de &#243;bitos por Covid-19 ou suspeitos na data real da ocorr&#234;ncia e n&#227;o do registro.<sup><xref ref-type="bibr" rid="B11">11</xref></sup> Junto com esse dado, as informa&#231;&#245;es de monitoriza&#231;&#227;o das interna&#231;&#245;es por S&#237;ndromes Respirat&#243;rias Agudas Graves atrav&#233;s do sistema InfoGripe tamb&#233;m auxiliaram a cont&#237;nua monitoriza&#231;&#227;o das tend&#234;ncias e confirma&#231;&#227;o ou n&#227;o das previs&#245;es realizadas.<sup><xref ref-type="bibr" rid="B12">12</xref></sup></p>
    <p>Apesar de todas essas ferramentas &#224; disposi&#231;&#227;o, as medidas implantadas de isolamento social foram tomadas de forma bastante controversa, muitas vezes n&#227;o se entendendo a fase do ciclo da pandemia em que est&#225;vamos, com ado&#231;&#227;o tardia e &#224;s vezes seguindo um curso adotado sem apresentar dados s&#243;lidos que justificassem as medidas tomadas. Dado a grande diferen&#231;a entre estrutura de recursos encontrada no pa&#237;s e fases da pandemia em cada estado, certamente os graus de isolamento deveriam ser bastante distintos visto que cada medida individualmente ou em conjunto tem reflexos diferentes na redu&#231;&#227;o da transmiss&#227;o viral. Neste sentido, devemos tamb&#233;m lembrar do princ&#237;pio de Pareto, onde 20% do que fazemos atinge 80% do resultado: a aplica&#231;&#227;o correta de um distanciamento social bem feito, com redu&#231;&#227;o de 25% do original, permite a manuten&#231;&#227;o da resposta eficaz de transmiss&#227;o uma vez reduzido inicialmente o R0.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> Logo, medidas relativamente simples de ensino da popula&#231;&#227;o de lavagem de m&#227;os, distanciamento, m&#225;scaras, etc., sendo bem aplicadas, podem muitas vezes ser superior a tentativas de medidas mais dr&#225;sticas mas executadas de forma desorganizada e sem o entendimento da popula&#231;&#227;o onde ela &#233; feita sem preparo adequado.</p>
    <p>A decis&#227;o do que fazer e em que momento da pandemia atuar &#233; crucial para que n&#227;o transformemos o objetivo de salvar vidas numa frase apenas apelativa com resultados consolidados que resultam em mais mortes que vidas salvas. Os efeitos de segunda e terceira ordem que ocorrem em qualquer terapia muitas vezes podem ser mais nocivos que o pr&#243;prio tratamento, especialmente quando este &#233; executado sem o devido planejamento. Muito comum em situa&#231;&#245;es onde uma centraliza&#231;&#227;o tenta simplificar processos extremamente complexos e que envolvem cadeias m&#250;ltiplas (como temos num exemplo famoso da fabrica&#231;&#227;o de um simples l&#225;pis),<sup><xref ref-type="bibr" rid="B14">14</xref></sup> o efeito final pode ser exatamente o oposto do que perseguimos. E aqui temos v&#225;rias situa&#231;&#245;es onde um prolongamento desnecess&#225;rio de medidas de confinamento podem levar a maior n&#250;mero de mortes que pela pr&#243;pria doen&#231;a. No momento em que este artigo &#233; escrito, o n&#250;mero de &#243;bitos no pa&#237;s pela Covid-19 &#233; de cerca de 10.000 pacientes e temos quase 45 dias de medidas de isolamento. Devido &#224; uma redu&#231;&#227;o prevista de 30% de angioplastias prim&#225;rias, aumento de tempos de transfer&#234;ncia e reinterna&#231;&#245;es por s&#237;ndromes coron&#225;rias agudas n&#227;o atendidas,<sup><xref ref-type="bibr" rid="B15">15</xref> - <xref ref-type="bibr" rid="B17">17</xref></sup> estima-se um excesso de mortes cardiovasculares de mais de 3.000 mortes neste per&#237;odo. Perdas de consultas ambulatoriais de diversas especialidades elevam o risco de &#243;bitos em at&#233; 1.5x, somando a este excesso outras 9.000 mortes desnecess&#225;rias.<sup><xref ref-type="bibr" rid="B18">18</xref></sup> O aumento de 1% do desemprego ou queda do Produto Interno Bruto por si s&#243; est&#227;o associados a aumento de &#243;bitos de at&#233; 1.63x na popula&#231;&#227;o economicamente ativa, adicionando a essa soma mais 3.500 &#243;bitos em excesso.<sup><xref ref-type="bibr" rid="B19">19</xref></sup> C&#225;lculos de mortalidade por falha de terapias para neoplasias e perdas diagn&#243;sticas no Brasil ainda n&#227;o existem mas, nos EUA e Inglaterra, as mortes em excesso foram calculadas em 34.000 e 6.000, respectivamente.<sup><xref ref-type="bibr" rid="B20">20</xref></sup> Todas essas mortes est&#227;o associadas a diversas causas, mas sobretudo pela falta de acesso em tempo aos sistemas de sa&#250;de sobrecarregados e focados apenas numa causa de mortalidade. Esses ser&#227;o os &#243;bitos invis&#237;veis da pandemia e do isolamento por n&#227;o terem sido previstos como efeitos secund&#225;rios &#224;s medidas unifocais.</p>
    <p>O que vir&#225; nas pr&#243;ximas semanas e meses est&#225; al&#233;m da vis&#227;o aqui proposta e vai depender em muito de como vamos decidir sair desta crise sanit&#225;ria, mais cedo ou de forma mais tardia. Os gastos j&#225; altos com as doen&#231;as cr&#244;nicas provavelmente v&#227;o aumentar muito nos pr&#243;ximos meses,<sup><xref ref-type="bibr" rid="B21">21</xref></sup> sobrecarregando um governo j&#225; com excesso de d&#237;vida. O desemprego e queda de renda levar&#227;o muitos brasileiros a migrarem para um Sistema &#218;nico de Sa&#250;de j&#225; inchado e com a demanda reprimida nestes meses. Ao mesmo tempo, outras solu&#231;&#245;es que aumentem a efici&#234;ncia do sistema v&#227;o ser aprimoradas como j&#225; foram neste curto espa&#231;o de tempo, como receitas digitais e telemedicina.<sup><xref ref-type="bibr" rid="B22">22</xref></sup> Esse aumento de produtividade m&#233;dica pode aliviar em parte esses aumentos de demanda e custos, fazendo com que nosso sistema de sa&#250;de consiga demonstrar a resili&#234;ncia e efetividade que fez com que, apesar de todas as dificuldades, tenhamos uma mortalidade por milh&#227;o at&#233; 10x menor que outros pa&#237;ses europeus na mesma fase da doen&#231;a. O que sabemos &#233; que estaremos prontos para novos desafios, pois foram sempre os otimistas que nos surpreenderam ao mostrar como a inventividade humana &#233; capaz de se sobrepor a obst&#225;culos.</p>
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  <sub-article article-type="translation" id="TRen" xml:lang="en">
    <front-stub>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Editorial</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Covid-19 in Brazil: Learning How to Walk in the Dark Without Leaving Anything Behind</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-6726-5324</contrib-id>
          <name>
            <surname>Fernandes</surname>
            <given-names>Juliano Lara</given-names>
          </name>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
          <xref ref-type="aff" rid="aff2001">
            <sup>2</sup>
          </xref>
        </contrib>
      </contrib-group>
      <aff id="aff1001">
        <label>1</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">Radiologia Cl&#237;nica de Campinas, Campinas, SP - Brazil</institution>
      </aff>
      <aff id="aff2001">
        <label>2</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">Instituto de Ensino e Pesquisa Jose Michel Kalaf, Campinas, SP &#8211; Brazil</institution>
      </aff>
      <author-notes>
        <corresp id="c01001">Mailing Address: Juliano Lara Fernandes Radiologia Cl&#237;nica de Campinas &#8211; Av. Jos&#233; de Souza Campos, 840. Postal Code 13092123, Campinas, SP - Brazil E-mail: jlaraf@terra.com.br</corresp>
      </author-notes>
      <kwd-group xml:lang="en">
        <kwd>Coronavirus</kwd>
        <kwd>COVID-19</kwd>
        <kwd>Pandemics</kwd>
        <kwd>Catastr&#243;fica Illness/mortality</kwd>
        <kwd>Hospitalization/economics</kwd>
        <kwd>Equity in Access to Health Services</kwd>
        <kwd>Diagnostic Tests/methds</kwd>
        <kwd>Personal Protective Equipment</kwd>
        <kwd>Masks</kwd>
        <kwd>Ventilators Mechanical</kwd>
      </kwd-group>
    </front-stub>
    <body>
      <disp-quote>
        <p>
          <italic>&#8220;If you have ups and downs, celebrate it because it means you&#8217;re alive!&#8221;</italic>
        </p>
      </disp-quote>
      <p>The SARS-CoV-2 pandemic had its first case in Brazil on February 4, 2020 in the state of S&#227;o Paulo. Like a real meteor, it practically paralyzed the planet without a more effective therapeutic approach to fight the virus, in addition to practices adopted worldwide only decades or even hundreds of years ago, with a very low level of robust modern evidence.<sup><xref ref-type="bibr" rid="B1">1</xref></sup> Brazil had the advantage of previewing the pandemic as it was a few weeks behind its Asian and European peers, so it was able to identify the hits and failures of these countries in their preparation to face the problem.</p>
      <p>We have then found out by chance that we have the world&#8217;s third biggest number of ICU beds, second only to the USA and Germany,<sup><xref ref-type="bibr" rid="B2">2</xref></sup> but we are also faced with an enormous heterogeneity between states, limitations and bureaucracy for the purchase of personal protective equipment and testing kits. This has prevented some pandemic approaches taken by other countries from being adopted here, either due to the impossibility of a lockdown in a continental country, or due to the speed and costs to identify the cases of transmission. Besides, limitations on the number of tests to be done has left us without a precise guide as to the spread of the pandemic, making it difficult to plan the timely, orderly and efficient allocation of scarce resources.</p>
      <p>The solution to that was to adopt our own strategies, which would allow us to walk in the dark while at least having a better idea of how far along the path we were. This information is essential for important decisions impacting not only the economic scenario of Brazil, but also the entire healthcare chain of a population that has been deprived of access to outpatient services and elective treatments due to the pandemic. Theoretical epidemiological mathematical models proved to be little capable of predicting our real figures, either because they overestimate the lethality of the disease that seems to stand closer to 0.2&#8211;0.5%,<sup><xref ref-type="bibr" rid="B3">3</xref></sup> or because they are based on data from past pandemics with other transmission dynamics. Interestingly, the models that were most suitable for modeling at what point in the pandemic we are resulted from curve adjustment strategies or Baysean models using data from other countries or based on the preliminary data that we already had on our curves.<sup><xref ref-type="bibr" rid="B4">4</xref> , <xref ref-type="bibr" rid="B5">5</xref></sup> These models appeared relatively spontaneously and outside traditional research groups, but proved to be more assertive in determining different moments of the pandemic.<sup><xref ref-type="bibr" rid="B6">6</xref></sup></p>
      <p>In a simpler way, but also using data on how the pandemic has previously progressed in other countries, we analyzed the charts of new cases per day from 30 countries with the highest number of covid-19 cases according to the following criteria: countries had reached a peak and presented at least 5 days of decline or stabilization of new daily cases.<sup><xref ref-type="bibr" rid="B7">7</xref></sup> China was excluded as it concentrated thousands of previous cases on a later day; Brazil was excluded because it was subject to the application of the result. Five countries that did not have mandatory isolation were included. Of the 30 countries, 18 were considered to have completed the full pandemic cycle, with a number of new daily cases &lt;70% of the peak of new cases per day. Using the date of the 1<sup>st</sup>, 100<sup>th</sup>and 200<sup>th</sup>case or 10<sup>th</sup>death, the times between these dates and the peak of new cases/day were determined. From these results, it was found that 95% of the countries studied had their peaks 55&#177;8 days from the 1<sup>st</sup>case, 31&#177;5 days from the 100<sup>th</sup>case, 27&#177;5 days from the 200<sup>th</sup>case and 19&#177;4 days from the 10<sup>th</sup>death. With this data, it would have been possible to establish the peaks of new cases, deaths and use of the hospital system in different states and cities in Brazil, even without being sure of the exact number of cases due to underreporting, based on the behavior of the pandemic in countries with different healthcare systems and mitigation measures. Death peak dates were established after 14 days of peak of cases and use of the hospital system after 26 days of peak of cases, considering incubation times, manifestation of symptoms, hospitalization and potential clinical worsening.<sup><xref ref-type="bibr" rid="B8">8</xref></sup> With these criteria, we estimated the different peaks in each of the Brazilian states with the highest number of cases, as shown in <xref ref-type="table" rid="t1001">Table 1</xref> (limited only to the forecast from the 100<sup>th</sup>case to exemplify the model). What cannot be predicted with any of these models is the descending portion of the curve, faster in some places and much slower, showing a plateau in others, requiring hospital beds for longer times, a potential virulence effect that is different from the virus after many mutations.<sup><xref ref-type="bibr" rid="B9">9</xref></sup></p>
      <p>
        <table-wrap id="t1001">
          <label>Table 1</label>
          <caption>
            <title>&#8211; 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</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup width="10%">
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead>
              <tr>
                <th align="left">State</th>
                <th>1<sup>st</sup>Case</th>
                <th>100<sup>th</sup>Case</th>
                <th>200<sup>th</sup>Case</th>
                <th>10<sup>th</sup>Death</th>
                <th>Peak 100<sup>th</sup>Case</th>
                <th>Lower 95%CI</th>
                <th>Upper 95%CI</th>
                <th>Death Peaks (100)</th>
                <th>Hospital Peak (100)</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td>SP (Metrop. Area)</td>
                <td align="center">Feb 4<sup>th</sup></td>
                <td align="center">Mar 2<sup>nd</sup></td>
                <td align="center">Mar 6<sup>th</sup></td>
                <td align="center">Mar 6<sup>th</sup></td>
                <td align="center">Apr 2<sup>nd</sup></td>
                <td align="center">Mar 28<sup>th</sup></td>
                <td align="center">Apr 6<sup>th</sup></td>
                <td align="center">Apr 16<sup>th</sup></td>
                <td align="center">Apr 28<sup>th</sup></td>
              </tr>
              <tr>
                <td>CE</td>
                <td align="center">Feb 14<sup>th</sup></td>
                <td align="center">Mar 7<sup>th</sup></td>
                <td align="center">Mar 10<sup>th</sup></td>
                <td align="center">Mar 15<sup>th</sup></td>
                <td align="center">Apr 7<sup>th</sup></td>
                <td align="center">Apr 2<sup>nd</sup></td>
                <td align="center">Apr 11<sup>th</sup></td>
                <td align="center">Apr 21<sup>st</sup></td>
                <td align="center">May 3<sup>rd</sup></td>
              </tr>
              <tr>
                <td>GO</td>
                <td align="center">Mar 2<sup>nd</sup></td>
                <td align="center">Mar 8<sup>th</sup></td>
                <td align="center">Mar 11<sup>th</sup></td>
                <td align="center">Mar 26<sup>th</sup></td>
                <td align="center">Apr 8<sup>th</sup></td>
                <td align="center">Apr 3<sup>rd</sup></td>
                <td align="center">Apr 12<sup>th</sup></td>
                <td align="center">Apr 22<sup>nd</sup></td>
                <td align="center">May 4<sup>th</sup></td>
              </tr>
              <tr>
                <td>SC</td>
                <td align="center">Feb 28<sup>th</sup></td>
                <td align="center">Mar 14<sup>th</sup></td>
                <td align="center">Mar 17<sup>th</sup></td>
                <td align="center">Apr 4<sup>th</sup></td>
                <td align="center">Apr 14<sup>th</sup></td>
                <td align="center">Apr 9<sup>th</sup></td>
                <td align="center">Apr 18<sup>th</sup></td>
                <td align="center">Apr 28<sup>th</sup></td>
                <td align="center">May 10<sup>th</sup></td>
              </tr>
              <tr>
                <td>RJ</td>
                <td align="center">Feb 27<sup>th</sup></td>
                <td align="center">Mar 15<sup>th</sup></td>
                <td align="center">Mar 18<sup>th</sup></td>
                <td align="center">Mar 18<sup>th</sup></td>
                <td align="center">Apr 15<sup>th</sup></td>
                <td align="center">Apr 10<sup>th</sup></td>
                <td align="center">Apr 19<sup>th</sup></td>
                <td align="center">Apr 29<sup>th</sup></td>
                <td align="center">May 11<sup>th</sup></td>
              </tr>
              <tr>
                <td>DF</td>
                <td align="center">Feb 26<sup>th</sup></td>
                <td align="center">Mar 15<sup>th</sup></td>
                <td align="center">Mar 18<sup>th</sup></td>
                <td align="center">Apr 4<sup>th</sup></td>
                <td align="center">Apr 15<sup>th</sup></td>
                <td align="center">Apr 10<sup>th</sup></td>
                <td align="center">Apr 19<sup>th</sup></td>
                <td align="center">Apr 29<sup>th</sup></td>
                <td align="center">May 11<sup>th</sup></td>
              </tr>
              <tr>
                <td>BA</td>
                <td align="center">Feb 26<sup>th</sup></td>
                <td align="center">Mar 16<sup>th</sup></td>
                <td align="center">Mar 19<sup>th</sup></td>
                <td>
								</td>
                <td align="center">Apr 16<sup>th</sup></td>
                <td align="center">Apr 11<sup>th</sup></td>
                <td align="center">Apr 20<sup>th</sup></td>
                <td align="center">Apr 30<sup>th</sup></td>
                <td align="center">May 12<sup>th</sup></td>
              </tr>
              <tr>
                <td>RN</td>
                <td align="center">Mar 8<sup>th</sup></td>
                <td align="center">Mar 18<sup>th</sup></td>
                <td align="center">Mar 21<sup>st</sup></td>
                <td align="center">Apr 7<sup>th</sup></td>
                <td align="center">Apr 18<sup>th</sup></td>
                <td align="center">Apr 13<sup>th</sup></td>
                <td align="center">Apr 22<sup>nd</sup></td>
                <td align="center">May 2<sup>nd</sup></td>
                <td align="center">May 14<sup>th</sup></td>
              </tr>
              <tr>
                <td>RS</td>
                <td align="center">Mar 9<sup>th</sup></td>
                <td align="center">Mar 21<sup>st</sup></td>
                <td align="center">Mar 25<sup>th</sup></td>
                <td align="center">Apr 8<sup>th</sup></td>
                <td align="center">Apr 21<sup>st</sup></td>
                <td align="center">Apr 16<sup>th</sup></td>
                <td align="center">Apr 25<sup>th</sup></td>
                <td align="center">May 5<sup>th</sup></td>
                <td align="center">May 17<sup>th</sup></td>
              </tr>
              <tr>
                <td>MG</td>
                <td align="center">Mar 17<sup>th</sup></td>
                <td align="center">Mar 23<sup>rd</sup></td>
                <td align="center">Mar 27<sup>th</sup></td>
                <td align="center">Apr 2<sup>nd</sup></td>
                <td align="center">Apr 23<sup>rd</sup></td>
                <td align="center">Apr 18<sup>th</sup></td>
                <td align="center">Apr 27<sup>th</sup></td>
                <td align="center">May 7<sup>th</sup></td>
                <td align="center">May 19<sup>th</sup></td>
              </tr>
              <tr>
                <td>MT</td>
                <td align="center">Mar 19<sup>th</sup></td>
                <td align="center">Mar 24<sup>th</sup></td>
                <td align="center">Mar 27<sup>th</sup></td>
                <td align="center">Apr 26<sup>th</sup></td>
                <td align="center">Apr 24<sup>th</sup></td>
                <td align="center">Apr 19<sup>th</sup></td>
                <td align="center">Apr 28<sup>th</sup></td>
                <td align="center">May 8<sup>th</sup></td>
                <td align="center">May 20<sup>th</sup></td>
              </tr>
              <tr>
                <td>PR</td>
                <td align="center">Mar 12<sup>th</sup></td>
                <td align="center">Mar 26<sup>th</sup></td>
                <td align="center">Apr 1<sup>st</sup></td>
                <td align="center">Apr 6<sup>th</sup></td>
                <td align="center">Apr 26<sup>th</sup></td>
                <td align="center">Apr 21<sup>st</sup></td>
                <td align="center">Apr 30<sup>th</sup></td>
                <td align="center">May 10<sup>th</sup></td>
                <td align="center">May 22<sup>nd</sup></td>
              </tr>
              <tr>
                <td>AM</td>
                <td align="center">Mar 18<sup>th</sup></td>
                <td align="center">Mar 28<sup>th</sup></td>
                <td align="center">Apr 1<sup>st</sup></td>
                <td>
								</td>
                <td align="center">Apr 28<sup>th</sup></td>
                <td align="center">Apr 23<sup>rd</sup></td>
                <td align="center">May 2<sup>nd</sup></td>
                <td align="center">May 12<sup>th</sup></td>
                <td align="center">May 24<sup>th</sup></td>
              </tr>
              <tr>
                <td>PE</td>
                <td align="center">Mar 12<sup>th</sup></td>
                <td align="center">Apr 2<sup>nd</sup></td>
                <td align="center">Apr 5<sup>th</sup></td>
                <td align="center">Apr 1<sup>st</sup></td>
                <td align="center">May 3<sup>rd</sup></td>
                <td align="center">Apr 28<sup>th</sup></td>
                <td align="center">May 7<sup>th</sup></td>
                <td align="center">May 17<sup>th</sup></td>
                <td align="center">May 29<sup>th</sup></td>
              </tr>
              <tr>
                <td>MA</td>
                <td align="center">Mar 20<sup>th</sup></td>
                <td align="center">Apr 5<sup>th</sup></td>
                <td align="center">Apr 7<sup>th</sup></td>
                <td align="center">Apr 6<sup>th</sup></td>
                <td align="center">May 6<sup>th</sup></td>
                <td align="center">May 1<sup>st</sup></td>
                <td align="center">May 10<sup>th</sup></td>
                <td align="center">May 20<sup>th</sup></td>
                <td align="center">Jun 1<sup>st</sup></td>
              </tr>
              <tr>
                <td>PA</td>
                <td align="center">Mar 18<sup>th</sup></td>
                <td align="center">Apr 6<sup>th</sup></td>
                <td align="center">Apr 10<sup>th</sup></td>
                <td align="center">Apr 11<sup>th</sup></td>
                <td align="center">May 7<sup>th</sup></td>
                <td align="center">May 2<sup>nd</sup></td>
                <td align="center">May 11<sup>th</sup></td>
                <td align="center">May 21<sup>st</sup></td>
                <td align="center">Jun 2<sup>nd</sup></td>
              </tr>
              <tr>
                <td>PB</td>
                <td align="center">Mar 19<sup>th</sup></td>
                <td align="center">Apr 11<sup>th</sup></td>
                <td align="center">Apr 17<sup>th</sup></td>
                <td align="center">Apr 9<sup>th</sup></td>
                <td align="center">May 12<sup>th</sup></td>
                <td align="center">May 7<sup>th</sup></td>
                <td align="center">May 16<sup>th</sup></td>
                <td align="center">May 26<sup>th</sup></td>
                <td align="center">Jun 7<sup>th</sup></td>
              </tr>
              <tr>
                <td>AL</td>
                <td align="center">Mar 10<sup>th</sup></td>
                <td align="center">Apr 17<sup>th</sup></td>
                <td align="center">Apr 21<sup>st</sup></td>
                <td align="center">Apr 18<sup>th</sup></td>
                <td align="center">May 18<sup>th</sup></td>
                <td align="center">May 13<sup>th</sup></td>
                <td align="center">May 22<sup>nd</sup></td>
                <td align="center">Jun 1<sup>st</sup></td>
                <td align="center">Jun 13<sup>th</sup></td>
              </tr>
              <tr>
                <td>PI</td>
                <td align="center">Mar 19<sup>th</sup></td>
                <td align="center">Apr 17<sup>th</sup></td>
                <td align="center">Apr 21<sup>st</sup></td>
                <td align="center">Apr 18<sup>th</sup></td>
                <td align="center">May 18<sup>th</sup></td>
                <td align="center">May 13<sup>th</sup></td>
                <td align="center">May 22<sup>nd</sup></td>
                <td align="center">Jun 1<sup>st</sup></td>
                <td align="center">Jun 13<sup>th</sup></td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN1001">
              <p>
                <italic>CI: confidence interval.</italic>
              </p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </p>
      <p>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.<sup><xref ref-type="bibr" rid="B10">10</xref></sup> 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.<sup><xref ref-type="bibr" rid="B11">11</xref></sup> 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.<sup><xref ref-type="bibr" rid="B12">12</xref></sup></p>
      <p>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.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> 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 the population concerned and without proper preparation.</p>
      <p>The decision of what to do and at what point in the pandemic is crucial so that we do not turn the goal of saving lives into a merely appealing pitch with consolidated results that result in more deaths than lives saved. The second and third order effects that occur in any therapy can often be more harmful than the treatment itself, especially when it is carried out without proper planning. Very common in situations where centralization tries to simplify extremely complex processes that involve multiple chains (as we have in a famous example of pencil making),<sup><xref ref-type="bibr" rid="B14">14</xref></sup> the final effect can be exactly the opposite of what we are pursuing. And here we have several situations where an unnecessary extension of confinement measures can lead to a greater number of deaths than from the disease itself. As of writing this, the number of deaths from Covid-19 in Brazil is about 10,000 patients and we have almost 45 days of isolation. Due to an expected 30% reduction in primary angioplasty surgeries, increased transfer times and rehospitalizations due to untreated acute coronary syndromes,<sup><xref ref-type="bibr" rid="B15">15</xref></sup> an excess of cardiovascular deaths of over 3,000 is estimated in this period. Missing outpatient visits of various specialties increases the risk of death by up to 1.5 times, adding to this excess another 9,000 unnecessary deaths.<sup><xref ref-type="bibr" rid="B18">18</xref></sup> The 1% increase in unemployment or the drop in Gross Domestic Product alone is associated with an increase in deaths of up to 1.63 times in the economically active population, adding another 3,500 excess deaths to this amount.<sup><xref ref-type="bibr" rid="B19">19</xref></sup> Mortality calculations due to failure of therapies for neoplasms and misdiagnoses in Brazil do not yet exist, but in the USA and England, excess deaths were estimated at 34,000 and 6,000 respectively.<sup><xref ref-type="bibr" rid="B20">20</xref></sup> All of these deaths are associated with several causes, mainly due to the lack of timely access to overburdened healthcare systems solely focused on one cause of mortality. These will be the invisible deaths of the pandemic and isolation because they were not predicted as the side effects to single-point measures.</p>
      <p>What will come in the next weeks and months is beyond the views expressed here and will depend, to a great extent, on how we will choose to defuse this health crisis, sooner or later. Expensive spending on chronic diseases is likely to increase dramatically in the coming months,<sup><xref ref-type="bibr" rid="B21">21</xref></sup> overburdening a government already in debt. Unemployment and declining income will lead many Brazilians to migrate to a Public Healthcare System already burdened from the demand repressed over these months. At the same time, other solutions to increase the efficiency of the systems will be improved as they have been in this short period of time, such as digital prescriptions and telemedicine.<sup><xref ref-type="bibr" rid="B22">22</xref></sup> This increase in medical productivity can partly alleviate these increases in demand and costs, making our healthcare system to demonstrate the resilience and effectiveness that has made us to witness a mortality per million up to 10 times less than other European countries at the same stage of the disease, despite all our difficulties. What we do know is that we will be ready for new challenges, as optimists have always surprised us as to how human inventiveness is capable of overcoming obstacles.</p>
    </body>
  </sub-article>
</article>
