<?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>0124-0064</journal-id>
<journal-title><![CDATA[Revista de Salud Pública]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. salud pública]]></abbrev-journal-title>
<issn>0124-0064</issn>
<publisher>
<publisher-name><![CDATA[Instituto de Salud Publica, Facultad de Medicina - Universidad Nacional de Colombia]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0124-00642020000300316</article-id>
<article-id pub-id-type="doi">10.15446/rsap.v22n3.87813</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Modelos matemáticos estimadores de la infección por COVID-19: consideraciones esenciales y proyecciones en Colombia]]></article-title>
<article-title xml:lang="en"><![CDATA[Mathematical models for COVID-19 infection estimation: essential considerations and projections in Colombia]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Bravo-Valero]]></surname>
<given-names><![CDATA[Antonio J.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Vera]]></surname>
<given-names><![CDATA[Miguel Á.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Huérfano-Maldonado]]></surname>
<given-names><![CDATA[Yoleidy K.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Simón Bolívar Facultad de Ciencias Básicas y Biomédicas ]]></institution>
<addr-line><![CDATA[Cúcuta ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Simón Bolívar Facultad de Ciencias Básicas y Biomédicas ]]></institution>
<addr-line><![CDATA[Cúcuta ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad de Los Andes  Grupo de Investigación en Procesamiento Computacional de Datos]]></institution>
<addr-line><![CDATA[San Cristóbal ]]></addr-line>
<country>Venezuela</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2020</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2020</year>
</pub-date>
<volume>22</volume>
<numero>3</numero>
<fpage>316</fpage>
<lpage>322</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0124-00642020000300316&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0124-00642020000300316&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0124-00642020000300316&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN  Objetivo Estimar el comportamiento de la infección por COVID-19 en Colombia mediante modelos matemáticos.  Métodos Se construyeron dos modelos matemáticos para estimar los casos confirmados importados y los casos confirmados relacionados de la infección por COVID-19 en Colombia, respectivamente. La fenomenología de los casos confirmados importados es modelada con una función sigmoidal, mientras que los casos confirmados relacionados son modelados mediante una combinación de funciones exponenciales y funciones algebraicas polinomiales. Se utilizan algoritmos de ajuste basados en métodos de mínimos cuadrados y métodos de búsqueda directa para la determinación de los parámetros de los modelos.  Resultados El modelo sigmodial realiza una estimación altamente convergente de los datos reportados, al 28 de mayo de 2020, de los casos confirmados importados de infección por COVID-19. El modelo muestra un error de predicción de 0,5%, que se mide usando la raíz del error cuadrático medio normalizado. El modelo para los casos confirmados reportados como relacionados muestra un error en la predicción del 3,5 % y un sesgo bajo del -0,01 asociado a la sobrestimación.  Conclusiones El presente trabajo evidencia que los modelos matemáticos permiten eficaz y efectivamente predecir el comportamiento de la infección por COVID-19 en Colombia cuando los casos importados y los casos relacionados de infección son consideradores de manera independiente.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT  Objective To estimate the COVID-19 infection behavior in Colombia using mathematical models.  Methods Two mathematical models were constructed to estimate imported confirmed cases and related confirmed cases of COVID-19 infection in Colombia, respectively. The phenomenology of imported confirmed cases is modeled with sigmoidal function, while related confirmed cases are modeled using a combination of exponential functions and polynomial algebraic functions. The fitting algorithms based on least squares methods and direct search methods are used to determine the parameters of the models.  Results The sigmodial model performs a highly convergent estimation of the reported confirmed cases of COVID-19 infection to May 28, 2020. This model achieved a prediction error of 0.5 % measured using the normalized root mean square error. The model of the confirmed cases reported as related shows a 3.5 % prediction error and a low bias of -0.01 associated with overestimation.  Conclusions This work shows that the mathematical models allow to predict the behavior of the infection efficiently and effectively by COVID 19 in Colombia when the imported cases and the related cases of infection are independently considered.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Infecciones por coronavirus]]></kwd>
<kwd lng="es"><![CDATA[COVID-19]]></kwd>
<kwd lng="es"><![CDATA[modelos predictivos (source: MeSH, NLM)]]></kwd>
<kwd lng="en"><![CDATA[Coronavirus infections]]></kwd>
<kwd lng="en"><![CDATA[COVID-19 pandemic]]></kwd>
<kwd lng="en"><![CDATA[forecasting (fuente: DeCS, BIREME)]]></kwd>
</kwd-group>
</article-meta>
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