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<!DOCTYPE html>
<html lang="en">
<head>
<!-- Basic Page Needs
–––––––––––––––––––––––––––––––––––––––––––––––––– -->
<meta charset="utf-8">
<title>O Brasil depois da vacina</title>
<meta name="description" content="">
<meta name="author" content="">
<!-- Mobile Specific Metas
–––––––––––––––––––––––––––––––––––––––––––––––––– -->
<meta name="viewport" content="width=device-width, initial-scale=1">
<!-- FONT
–––––––––––––––––––––––––––––––––––––––––––––––––– -->
<link href="//fonts.googleapis.com/css?family=Raleway:400,300,600" rel="stylesheet" type="text/css">
<!-- CSS
–––––––––––––––––––––––––––––––––––––––––––––––––– -->
<link rel="stylesheet" href="assets/css/lib/normalize.css">
<link rel="stylesheet" href="assets/css/lib/skeleton.css">
<link rel="stylesheet" href="assets/css/style.css">
<!-- STYLE FOR THE GEOVIS -->
<style>
path {
stroke: #222222;
stroke-opacity: 1;
stroke-width: 10em;
stroke-miterlimit: 4;
stroke-dasharray: none
}
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fill-opacity: 1.0 !important;
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<!-- SCRIPT FOR BOKEH RELATED VIS -->
<script type="text/javascript" src="https://cdn.bokeh.org/bokeh/release/bokeh-3.1.0.min.js"></script>
<script type="text/javascript" src="https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.1.0.min.js"></script>
<script type="text/javascript">
Bokeh.set_log_level("info");
</script>
</head>
<body>
<div class="container">
<div class="row">
<div class="two columns"></div>
<div class="ten columns" style="margin-top: 15%">
<h2>O Brasil depois da vacina</h2>
<h4>Uma Análise exploratória dos dados do <a
href="https://opendatasus.saude.gov.br/dataset?page=1">OpenDataSUS</a></h4><br>
<p>A vacinação no Brasil --- marcada por diversas polêmicas --- teve início dia 17 de janeiro de 2021. Essa
página apresenta uma análise exploratória dos números de ocupação de leitos Clínicos e de UTI no Brasil em
2022.</p>
<button type="button" class="collapsible"><em>Storytelling</em> com VIS</button>
<div class="content">
<br>
<p>Esta página é um projeto de <em>(Serious) Storytelling</em> usando conceitos de <strong>Visualização de
Dados e Informação</strong>. A ideia é focar na apresentação de fatos derivados de dados por meio de
visualizações (que, a partir de agora, serão carinhosamente referidas por VIS).</p>
<p>O <em>Storytelling</em> é importante pois nem sempre apenas uma VIS é suficiente para comunicar o que há
nos dados. Dados possuem senmântica e precisam de um contexto
para serem apresentados.</p>
<p>Não basta apenas entregar a VIS, queremos também extrair conhecimento dela. Queremos mostrá-la e
responder a pergunta <em>"e o que eu faço com isso?"</em></p>
<p>Foram selecionados os dados do <a
href="https://opendatasus.saude.gov.br/dataset/registro-de-ocupacao-hospitalar-covid-19">registro de
ocupação hospitalar do OpenDataSUS</a>.</p>
<p>As etapas do <em>storytelling</em> foram:</p>
<ol type="1">
<li><strong>Explorar os dados:</strong> Os dados foram coletados do site, e uma série de processamentos
foram feitos sobre eles, como o cálculo das médias móveis, filtragens, transformações e criação de campos
calculados. Um segmento dos dados foi utilizado para gerar as visualizações finais. A exploração permitiu
perceber que, apesar de 2022 já ter iniciado com uma grande parcela da população vacinada, o cenário ainda
foi alarmante durante o decorrer do ano.</li>
<li><strong>Conceber a estória:</strong> Identifiquei a linha geral da estória, que seria chamar a atenção
para o fato de que a ampla vacinação da população brasileira não pôs um ponto final nas mortes decorrentes
de COVID-19. Pensando nisso, refinei os dados, separando informações para gerar VIS que permitissem ver o
cenário estado a estado, região a região, e do país como um todo. A narrativa foi pensada para guiar o
leitor até a conclusão de que a pandemia ainda não acabou.</li>
<li><strong>Materializar a estória:</strong> Para materializar a estória, construí os seguintes artefatos.
Um repositório no GitHub com todo o código implementado, VIS geradas com o Bokeh, e a compilação das VIS
com anotações em uma página web, pronta para o <em>story share</em>.</li>
</ol>
<p>Embora o foco da página seja a estória, ao longo dela existem botões contando os aspectos de
<em>design</em> envolvidos (como o botão que você clicou para ver esse texto!).</p>
<hr>
</div>
<hr>
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style="fill: #FC8262; fill-opacity: 0.75;" />
</a></g>
</g>
</svg>
<div id="rondonia_popup" class="mypopup">
<h5>Rondônia</h5>
<p>267 mortes | 17º lugar</p>
</div>
<div id="acre_popup" class="mypopup">
<h5>Acre</h5>
<p>58 mortes | 25º lugar</p>
</div>
<div id="amazonas_popup" class="mypopup">
<h5>Amazonas</h5>
<p>787 mortes | 11º lugar</p>
</div>
<div id="roraima_popup" class="mypopup">
<h5>Roraima</h5>
<p>3 mortes | 27º lugar</p>
</div>
<div id="amapa_popup" class="mypopup">
<h5>Amapá</h5>
<p>13 mortes | 26º lugar</p>
</div>
<div id="tocantins_popup" class="mypopup">
<h5>Tocantins</h5>
<p>101 mortes | 24º lugar</p>
</div>
<div id="mato_grosso_popup" class="mypopup">
<h5>Mato Grosso</h5>
<p>212 mortes | 20º lugar</p>
</div>
<div id="goias_popup" class="mypopup">
<h5>Goiás</h5>
<p>161039 mortes | 1º lugar</p>
</div>
<div id="mato_grosso_do_sul_popup" class="mypopup">
<h5>Mato Grosso do Sul</h5>
<p>373 mortes | 14º lugar</p>
</div>
<div id="minas_gerais_popup" class="mypopup">
<h5>Minas Gerais</h5>
<p>20213 mortes | 3º lugar</p>
</div>
<div id="parana_popup" class="mypopup">
<h5>Paraná</h5>
<p>987 mortes | 10º lugar</p>
</div>
<div id="rio_grande_do_sul_popup" class="mypopup">
<h5>Rio Grande do Sul</h5>
<p>257 mortes | 18º lugar</p>
</div>
<div id="bahia_popup" class="mypopup">
<h5>Bahia</h5>
<p>1214 mortes | 8º lugar</p>
</div>
<div id="piaui_popup" class="mypopup">
<h5>Piauí</h5>
<p>211 mortes | 21º lugar</p>
</div>
<div id="ceara_popup" class="mypopup">
<h5>Ceará</h5>
<p>1023 mortes | 9º lugar</p>
</div>
<div id="rio_grande_do_norte_popup" class="mypopup">
<h5>Rio Grande do Norte</h5>
<p>216 mortes | 19º lugar</p>
</div>
<div id="alagoas_popup" class="mypopup">
<h5>Alagoas</h5>
<p>146 mortes | 22º lugar</p>
</div>
<div id="sergipe_popup" class="mypopup">
<h5>Sergipe</h5>
<p>132 mortes | 23º lugar</p>
</div>
<div id="distrito_federal_popup" class="mypopup">
<h5>Distrito Federal</h5>
<p>376 mortes | 13º lugar</p>
</div>
<div id="pernambuco_popup" class="mypopup">
<h5>Pernambuco</h5>
<p>1277 mortes | 6º lugar</p>
</div>
<div id="maranhao_popup" class="mypopup">
<h5>Maranhão</h5>
<p>281 mortes | 15º lugar</p>
</div>
<div id="para_popup" class="mypopup">
<h5>Pará</h5>
<p>1305 mortes | 5º lugar</p>
</div>
<div id="sao_paulo_popup" class="mypopup">
<h5>São Paulo</h5>
<p>5178 mortes | 4º lugar</p>
</div>
<div id="rio_de_janeiro_popup" class="mypopup">
<h5>Rio de Janeiro</h5>
<p>1256 mortes | 7º lugar</p>
</div>
<div id="espirito_santo_popup" class="mypopup">
<h5>Espírito Santo</h5>
<p>451 mortes | 12º lugar</p>
</div>
<div id="santa_catarina_popup" class="mypopup">
<h5>Santa Catarina</h5>
<p>40821 mortes | 2º lugar</p>
</div>
<div id="paraiba_popup" class="mypopup">
<h5>Paraíba</h5>
<p>270 mortes | 16º lugar</p>
</div>
<script>
const states = ['rondonia', 'acre', 'amazonas', 'roraima', 'amapa', 'tocantins', 'mato_grosso',
'goias', 'mato_grosso_do_sul', 'minas_gerais', 'parana', 'rio_grande_do_sul',
'bahia', 'piaui', 'ceara', 'rio_grande_do_norte', 'alagoas', 'sergipe',
'distrito_federal', 'pernambuco', 'maranhao', 'para', 'sao_paulo',
'rio_de_janeiro', 'espirito_santo', 'santa_catarina', 'paraiba'];
for (const state_name of states) {
document.getElementById(state_name + "_state").addEventListener("mouseover", evt => {
var popup = document.getElementById(state_name + "_popup");
var iconPos = document.getElementById(state_name + "_state").getBoundingClientRect();
// popup.style.left = (iconPos.left) + "px";
// popup.style.top = (window.scrollY + iconPos.top - 30) + "px";
popup.style.left = "100px";
popup.style.top = "900px";
popup.style.display = "block";
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document.getElementById(state_name + "_state").addEventListener("mouseout", evt => {
var popup = document.getElementById(state_name + "_popup");
popup.style.display = "none";
});
}
</script>
</div>
</div><br>
<button type="button" class="collapsible"><em>Design</em> da VIS</button>
<div class="content">
<p>A VIS acima é interativa: a ação de colocar o mouse em cima de um estado (<em>hover</em>) apresenta um
texto com o seu nome, número de óbitos acumulados em 2022, e sua classificação no índice dos estados mais
acometidos (em valores absolutos) pela COVID-19. A cor de cada estado foi selecionada numa escala de
vermelhos, sendo que tons mais escuros indicam piores cenários. As cores foram selecionadas de forma
discreta, com base no rank dos estados. Então existem 26 tons diferentes de vermelho. A vantagem de
visualizar esses dados de maneira georreferenciada é a possibilidade de identificar a relação de um estado
com seus vizinhos.</p>
<strong>Domínio</strong>
<ul>
<li>Perfil: Leitores do site com interesse em dados de COVID-19</li>
<li>Objetivo: Apresentar o panorama geral do Brasil</li>
</ul>
<strong>Abstração de dados</strong>
<ul>
<li>Estrutura: Dados tabulares</li>
<li>Item dos dados: Georreferenciado (nome do estado), Quantitativo (total de mortes), Quantitativo (rank de
cada estado)</li>
</ul>
<strong>Abstração de tarefas</strong>
<ul>
<li>Comparar os diferentes estados</li>
</ul>
<strong>Designing the VIS</strong>
<ul>
<li>Variável visual: posição e cor</li>
<li>Tipo de descrição: hue</li>
</ul>
<hr>
</div>
<p>A vacina foi um passo fundamental no combate à COVID-19, mas não deveria ser vista como o único fator. Em
2022, o brasil enfrentou uma nova onda de casos, com altos índices de ocupações de leitos e, infelizmente,
altos números de óbitos mesmo com a imunização em progresso.</p>
<p>O mapa acima mostra a quantidade de óbitos por estado para casos confirmados, com uma cor mais escura para os
piores classificados. O estado de Goiás, primeiro na lista, teve um total de 161.039 vidas perdidas.</p>
<p>Santa Catarina foi o segundo estado que mais registrou 40.821 mortes, seguido de Minas Gerais, com 20.213
mortes.</p>
<hr>
<div id="'vis2">
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<button type="button" class="collapsible"><em>Design</em> da vis</button>
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<p>A VIS acima é altamente interativa: pode-se comparar até 3 linhas ao mesmo tempo (selecionando os dados na caixa de seleção), por meio de várias interações (pan horizontal, hover e zoom), com um minimapa de seleção para controlar o pan horizontal. A ideia é que --- uma vez que temos finalidade de fornecer uma análise exploratória --- possibilitar que o usuário escolha seus próprios dados para focar e ver se encontra correlações. Por padrão, o gráfico vem com a correlação foco do site: Ocupação de UTIs e número de óbitos. Para criação de todos os dados, foi calculada a média móvel (procedimento que se tornou padrão para visualizar esse tipo de dado, graças às notícias na televisão, e que são de conhecimento da maioria da população. Em termos técnicos, a média móvel é um filtro passa-baixa, que remove dos dados oscilações altas, evitando uma linha muito ruidosa e difícil de ser lida e comparada).</p>
<strong>Domínio</strong>
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<li>Objetivo: Explorar correlações</li>
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<strong>Abstração de dados</strong>
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<p>Os dados de ocupação de leitos, tanto Clínicos quanto de UTI, mostram uma correlação com o número de óbitos
decorrentes de COVID-19 (apenas para casos confirmados).</p>
<p>O alarmante número de ocupações, mesmo com as medidas públicas para disponibilização de leitos improvisados
em todo o território nacional, suporta a hipótese de que não bastava a vacina para resolver o problema: foi
uma questão de políticas públicas, respostas eficientes e disponibilização de infraestrutura para cuidado
médico da população.</p>
<p>Á partir de 23 de Julho de 2022, quando a ocupação se tornou menor que 1000 (em clínicas) e 1580 (em UTIs), a
taxa de óbitos caiu drasticamente.</p>
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<button type="button" class="collapsible"><em>Design</em> da vis</button>
<div class="content">
<p>A VIS acima é interativa: um hover permite ver informações sobre cada estado. A ideia dessa VIS é apresentar, ao longo do tempo, o número de ocupações (que pode ser visto pelo tamanho das barras), assim como explicitar as regiões mais afetadas (por meio das frações das barras de tamanhos grandes). Aqui há um compromisso entre efetividade (bom uso das primitivas para mostrar a informação) e expressividade (mostrar todos os dados que precisam ser mostrados), uma vez que algumas barras ficam pequenas e é difícil identificar as regiões. Entretanto, o foco foi chamar a atenção que a região do Sudeste se destaca.</p>
<strong>Domínio</strong>
<ul>
<li>Perfil: Leitores do site com interesse em dados de COVID-19</li>
<li>Objetivo: Comparar</li>
</ul>
<strong>Abstração de dados</strong>
<ul>
<li>Estrutura: Dados tabulares</li>
<li>Item dos dados: Ordinal (regiões do Brasil), Ordinal (mês do ano (apresentados com enumeração de 1 a 12)), Quantitativo (Ocupação de leitos de UTI)</li>
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<strong>Abstração de tarefas</strong>
<ul>
<li>Comparar diferentes regiões ao longo do tempo</li>
</ul>
<strong>Designing the VIS</strong>
<ul>
<li>Variável visual: posição, cor</li>
<li>Tipo de descrição: barra e hue</li>
</ul>
<hr>
</div>
<p>A proporção entre as regiões do Brasil se mantiveram próximas. Para a região Sudeste, que contempla alguns
dos estados com maior número de mortos, a ocupação foi sempre a maior entre as regiões do Brasil. No mês de
Fevereiro, a região Sudeste sozinha correspondia a metade da ocupação total no Brasil.</p>
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<button type="button" class="collapsible"><em>Design</em> da vis</button>
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<p>A VIS acima tenta alinhar as diferentes métricas, sem se basear em médias móveis, e sim na soma dos valores absolutos para cada mês. A ideia é acompanhar a progressão de cada indicador, com um campo calculado sendo apresentado no último gráfico: a porcentagem de saídas do hospital correspondentes a óbitos. Chama a atenção que: ou a quantidade de óbitos é numericamente grande, ou é percentualmente grande.</p>
<strong>Domínio</strong>
<ul>
<li>Perfil: Leitores do site com interesse em dados de COVID-19</li>
<li>Objetivo: Comparar</li>
</ul>
<strong>Abstração de dados</strong>
<ul>
<li>Estrutura: Dados tabulares</li>
<li>Item dos dados: Ordinal (mês do ano (apresentados com enumeração de 1 a 12)), Quantitativo (soma dos valores para cada mês)</li>
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<li>Comparar diferentes indicadores ao longo do tempo</li>
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<strong>Designing the VIS</strong>
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<li>Variável visual: posição, cor</li>
<li>Tipo de descrição: barra e hue</li>
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<p>Ao longo do tempo, podemos ver que houve um grande número de altas durante a primeira metade do ano, com uma proporção de óbitos de aproximadamente 10%. Após Julho, quando os índices de ocupação diminuíram, vemos uma redução (numérica) do número de altas e óbitos --- comportamento esperado, já que esse número deve responder à quantidade de ocupação.</p>
<p>Curiosamente, quando o número de ocupação diminuiu para a metade, a porcentagem de óbitos entre pacientes internados confirmados dobrou.</p>
<p>Mesmo com a redução significativa no número de ocupações e número de óbitos, durante o ano inteiro, o menor valor de ocupação mensal de UTIs no Brasil foi de mais ded 120.000 pessoas.</p>
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