<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0864-3466</journal-id>
<journal-title><![CDATA[Revista Cubana de Salud Pública]]></journal-title>
<abbrev-journal-title><![CDATA[Rev Cubana Salud Pública]]></abbrev-journal-title>
<issn>0864-3466</issn>
<publisher>
<publisher-name><![CDATA[Editorial Ciencias Médicas]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0864-34662021000300017</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Relación entre la tasa de letalidad por COVID-19 y los recursos hospitalarios]]></article-title>
<article-title xml:lang="en"><![CDATA[Relation between COVID-19 fatality rate and hospital resources]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[San-Martín-Roldán]]></surname>
<given-names><![CDATA[David]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Calzadilla-Núñez]]></surname>
<given-names><![CDATA[Aracelis]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
<xref ref-type="aff" rid="Aaf"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[San-Martín-Roldán]]></surname>
<given-names><![CDATA[Pablo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[López-Labarca]]></surname>
<given-names><![CDATA[Claudio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Díaz-Calzadilla]]></surname>
<given-names><![CDATA[Patricia]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Díaz-Narváez]]></surname>
<given-names><![CDATA[Víctor P.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Valparaíso Escuela de Obstetricia y Puericultura Facultad de Medicina]]></institution>
<addr-line><![CDATA[ Valparaíso]]></addr-line>
<country>Chile</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Bernardo O&#8217;Higgins Escuela de Medicina Facultad de Salud]]></institution>
<addr-line><![CDATA[ Santiago de Chile]]></addr-line>
<country>Chile</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Autónoma de Chile Facultad de Ciencias de la Salud ]]></institution>
<addr-line><![CDATA[ Santiago de Chile]]></addr-line>
<country>Chile</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Universidad de Chile Instituto de Nutrición y Tecnología de los Alimentos (INTA) ]]></institution>
<addr-line><![CDATA[ Santiago de Chile]]></addr-line>
<country>Chile</country>
</aff>
<aff id="Af5">
<institution><![CDATA[,Universidad de Atacama Facultad de Ciencias de la Salud Departamento Obstetricia y Puericultura]]></institution>
<addr-line><![CDATA[ Copiapó]]></addr-line>
<country>Chile</country>
</aff>
<aff id="Af6">
<institution><![CDATA[,Universidad Andres Bello Facultad de Odontología Departamento de Investigaciones]]></institution>
<addr-line><![CDATA[ Santiago de Chile]]></addr-line>
<country>Chile</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>09</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>09</month>
<year>2021</year>
</pub-date>
<volume>47</volume>
<numero>3</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_arttext&amp;pid=S0864-34662021000300017&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_abstract&amp;pid=S0864-34662021000300017&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_pdf&amp;pid=S0864-34662021000300017&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN  Introducción:  La tasa de letalidad por COVID-19 ha generado mucha preocupación entre los ciudadanos y los medios de comunicación con respecto a los números oficiales proporcionados por distintos gobiernos. La salud pública en la actualidad debe hacer frente a la pandemia más significativa del siglo xxi.  Objetivo:  Analizar la tasa de letalidad por COVID-19 y su relación con recursos hospitalarios críticos, en el contexto de la pandemia de la COVID-19.  Métodos:  Se analizó la tasa de letalidad sobre la base de datos oficiales. Se subestimó el número de casos para obtener una estimación más real del alcance de la infección, de los indicadores de recursos hospitalarios importantes (críticos) en transición pandémica que podrían elevar la tasa de letalidad posterior al estudio. Se emplearon curvas de tendencia exponencial doblemente suavizadas, distribución S y técnicas de regresión.  Resultados:  La curva que mejor explicó el comportamiento de fallecidos por COVID-19 en Chile fue una ecuación de regresión cúbica. La variable hospitalización básica se distribuyó como una curva S. Las variables hospitalización media, pacientes críticos, unidad tratamiento intensivo, unidad cuidado intensivo, ventiladores mecánicos totales y ventiladores mecánicos ocupados; se pudieron explicar mediante regresiones cúbicas. En todos los casos, los valores de R2 fueron superiores al 95 %.  Conclusiones:  El número de fallecidos seguirá en aumento. Se sugiere fortificar las unidades de hospitalización básica para imposibilitar el colapso de la red sanitaria. Es necesario seguir creciendo en términos de hospitalización de media complejidad, unidad tratamiento intensivo, unidad cuidado intensivo y número total de ventiladores mecánicos para asegurar el soporte sanitario.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT  Introduction:  The fatality rate by COVID-19 has generated a lot of concern among citizens and the media regarding the official numbers provided by different governments. Public health today must cope with the most significant pandemic of the twenty-first century.  Objective:  Analyze the fatality rate due to COVID-19 and its relation with critical hospital resources, in the context of the COVID-19 pandemic.  Methods: The fatality rate was analyzed on the basis of official data. The number of cases was underestimated to obtain a more real estimate of the extent of the infection, of the indicators of important (critical) hospital resources in pandemic transition that could raise the post-study fatality rate. Double-smoothed exponential trend curves, S-distribution and regression techniques were used.  Results:  The curve that best explained the behavior of COVID-19 deaths in Chile was a cubic regression equation. The basic hospitalization variable was distributed as an S-curve. The variables called mean hospitalization, critical patients, intensive treatment unit, intensive care unit, total mechanical ventilators and busy mechanical ventilators could be explained by cubic regressions. In all cases, R2 values were greater than 95 %.  Conclusions:  The number of deaths will continue to rise. It is suggested to fortify the basic hospitalization units to prevent the collapse of the health network. It is necessary to continue growing in terms of medium complexity hospitalization, intensive treatment unit, intensive care unit and total number of mechanical ventilators to ensure health support.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[COVID-19]]></kwd>
<kwd lng="es"><![CDATA[coronavirus]]></kwd>
<kwd lng="es"><![CDATA[2019-nCoV]]></kwd>
<kwd lng="es"><![CDATA[SARS-CoV2]]></kwd>
<kwd lng="es"><![CDATA[nuevo coronavirus]]></kwd>
<kwd lng="en"><![CDATA[COVID-19]]></kwd>
<kwd lng="en"><![CDATA[coronavirus]]></kwd>
<kwd lng="en"><![CDATA[2019-nCoV]]></kwd>
<kwd lng="en"><![CDATA[SARS-CoV2]]></kwd>
<kwd lng="en"><![CDATA[new coronavirus]]></kwd>
</kwd-group>
</article-meta>
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