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Effectiveness of COVID-19 vaccination on reduction of hospitalizations and deaths in elderly patients in Rio Grande do Norte, Brazil

<p><strong>Data Repository&nbsp;</strong></p> <p><strong>Dataset name:</strong> covid19_rn-br.csv&nbsp;</p> <p><strong>Version: </strong>1.0&nbsp;</p> <p><strong>Data collection period:</strong> 04/2020 - 08/2021&nbsp;</p> <p><strong>Dataset Characteristics: </strong>Multivalued&nbsp;</p> <p><strong>Number of Instances:</strong> 12,635</p> <p><strong>Number of Attributes: </strong>16</p> <p><strong>Missing Values:</strong> Yes&nbsp;</p> <p><strong>Area(s): </strong>Health</p> <p><strong>Sources:</strong>&nbsp;</p> <p>- <em>Primary</em>:&nbsp;</p> <ul> <li>RegulaRN (<a href="https://regulacao.saude.rn.gov.br/sala-situacao/sala_publica/">https://regulacao.saude.rn.gov.br/sala-situacao/sala_publica/</a>).</li> </ul> <p>- <em>Secondary</em>:&nbsp;</p> <ul> <li>RN Mais Vacina (<a href="https://rnmaisvacina.lais.ufrn.br/cidadao/">https://rnmaisvacina.lais.ufrn.br/cidadao/</a>).</li> </ul> <p><strong>Description:</strong> The covid19_rn-br.csv dataset is composed of data from individuals who were hospitalized due to the Sars-CoV-2 virus. The data comes from the ecosystem of services that includes the regulatory system for clinical and critical beds related to Covid-19 (RegulaRN) and the vaccination system against Covid-19 that records the data of the general population (RN Mais Vacina) from Rio Grande do Norte state, Brazil. This dataset provides elementary data to analyze the impact of vaccination on patients hospitalized in the state. Table 1 presents the dictionary used during the data analysis.</p> <p>&nbsp;</p> <p><strong>Table 1: </strong>Description of Dataset Features.&nbsp;</p> <table> <tbody> <tr> <td> <p><strong>Attributes&nbsp;</strong></p> </td> <td> <p><strong>Description&nbsp;</strong></p> </td> <td> <p><strong>datatype&nbsp;</strong></p> </td> <td> <p><strong>Value</strong></p> </td> </tr> <tr> <td> <p><strong>usp</strong></p> </td> <td> <p>Unified Score for Prioritization scale, which combines the parameters described in the quick Sequential Organ Failure Assessment (qSOFA), the Charlson Comorbidity Index (CCI), the Clinical Frailty Scale (CFS) and The Karnofsky Performance Status scores</p> </td> <td> <p>Numerical</p> </td> <td> <p>2.0. 3.0, 4.0, 5.0, 6.0+</p> </td> </tr> <tr> <td> <p><strong>age</strong></p> </td> <td> <p>Informs the patient&#39;s age</p> </td> <td> <p>Numerical.</p> </td> <td> <p>integer value for age</p> </td> </tr> <tr> <td> <p><strong>outcome</strong></p> </td> <td> <p>Informs the outcome of the hospitalized patient after leaving the hospital</p> </td> <td> <p>Categorical</p> </td> <td> <p>&ldquo;Discharge&rdquo; or &ldquo;Death&quot;</p> </td> </tr> <tr> <td> <p><strong>comorbidities</strong></p> </td> <td> <p>Informs if the patient has comorbidities</p> </td> <td> <p>Categorical.</p> </td> <td> <p>&ldquo;Yes&rdquo; or &ldquo;No&rdquo;</p> </td> </tr> <tr> <td> <p><strong>vaccine</strong></p> </td> <td> <p>Informs which type of vaccine was applied to the patient</p> </td> <td> <p>Categorical</p> </td> <td> <p>&ldquo;Vaccine #1&rdquo;, &ldquo;Vaccine #2&rdquo; or NaN</p> </td> </tr> <tr> <td> <p><strong>bed_date_admission</strong>&nbsp;</p> </td> <td> <p>Informs the date the patient was hospitalized</p> </td> <td> <p>Date</p> </td> <td> <p>Date</p> </td> </tr> <tr> <td> <p><strong>bed_date_outcome</strong></p> </td> <td> <p>Informs the date that the patient left the hospital bed</p> </td> <td> <p>Date</p> </td> <td> <p>Date</p> </td> </tr> <tr> <td> <p><strong>length_hospitalization</strong></p> </td> <td> <p>Informs the number of days that the patient was hospitalized</p> </td> <td> <p>Numerical</p> </td> <td> <p>An integer value for days</p> </td> </tr> <tr> <td> <p><strong>interval_d1_hospitalization</strong></p> </td> <td> <p>Informs the interval (in days) that the patient had between the first dose and admission</p> </td> <td> <p>Numerical</p> </td> <td> <p>An integer value for days or NaN</p> </td> </tr> <tr> <td> <p><strong>interval_d2_hospitalization</strong></p> </td> <td> <p>Informs the interval (in days) that the patient had between the second dose and admission</p> </td> <td> <p>Numerical</p> </td> <td> <p>An integer value for days or NaN</p> </td> </tr> <tr> <td> <p><strong>dt_d1</strong></p> </td> <td> <p>Informs the date of application of the patient&#39;s first dose</p> </td> <td> <p>Date</p> </td> <td> <p>Date or NaN</p> </td> </tr> <tr> <td> <p><strong>dt_d2</strong></p> </td> <td> <p>Informs the patient&#39;s second dose application date</p> </td> <td> <p>Date</p> </td> <td> <p>Date or NaN</p> </td> </tr> <tr> <td> <p><strong>comorbidities_txt</strong></p> </td> <td> <p>Informs patients&#39; comorbidities</p> </td> <td> <p>Categorical</p> </td> <td> <p>Free text or NaN</p> </td> </tr> <tr> <td> <p><strong>immunization</strong></p> </td> <td> <p>It informs the patient&#39;s immunization level according to the number of doses received and the interval (in days) of application of these doses</p> </td> <td> <p>Categorical</p> </td> <td> <p>&ldquo;Partially&rdquo;, &ldquo;Fully&rdquo; or &ldquo;Not vaccinated&rdquo;</p> </td> </tr> <tr> <td> <p><strong>health_professionals</strong></p> </td> <td> <p>Informs if the patient is a health professional</p> </td> <td> <p>Boolean</p> </td> <td> <p>0 or 1</p> </td> </tr> <tr> <td> <p><strong>age_group</strong></p> </td> <td> <p>Informs the age group of the hospitalized patient according to their age</p> </td> <td> <p>Categorical</p> </td> <td> <p>0-19, 20-49, 50-59, 60-69, 70-79, 80-89, 90+</p> </td> </tr> </tbody> </table> <p>&nbsp;</p> <p><strong>Article</strong>: Effectiveness of COVID-19 vaccination on reduction of hospitalizations and deaths in elderly patients in Rio Grande do Norte, Brazil</p> <p><br> <strong>Authors</strong>: Ana Isabela L.&nbsp;Sales-Moioli, Leonardo J. Galv&atilde;o-Lima, Talita K. B. Pinto, Pablo H. Cardoso, Rodrigo D. Silva; Felipe Fernandes, Ingridy M. P. Barbalho, Fernando L. O. Farias, Nicolas V. R. Veras, Daniele M. S. Barros; Agnaldo S. Cruz; Ion G. M. Andrade; L&uacute;cio Gama and Ricardo A. M. Valentim</p>