<?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>2444-054X</journal-id>
<journal-title><![CDATA[Cirugía y cirujanos]]></journal-title>
<abbrev-journal-title><![CDATA[Cir. cir.]]></abbrev-journal-title>
<issn>2444-054X</issn>
<publisher>
<publisher-name><![CDATA[Academia Mexicana de Cirugía A.C.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2444-054X2021000400503</article-id>
<article-id pub-id-type="doi">10.24875/ciru.20000725</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Surveillance system for acute severe infections with epidemic potential based on a deterministic-stochastic model, the StochCum Method]]></article-title>
<article-title xml:lang="es"><![CDATA[Sistema de vigilancia de infecciones graves con potencial epidémico basado en un modelo determinístico-estocástico, el StochCum Method]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Castañón-González]]></surname>
<given-names><![CDATA[Jorge A.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
<xref ref-type="aff" rid="Aaf"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Polanco-González]]></surname>
<given-names><![CDATA[Carlos]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
<xref ref-type="aff" rid="Aaf"/>
<xref ref-type="aff" rid="A a"/>
<xref ref-type="aff" rid="A4"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[González-González]]></surname>
<given-names><![CDATA[Ricardo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Carrillo-Ruiz]]></surname>
<given-names><![CDATA[José D.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
<xref ref-type="aff" rid="Aaf"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Anahuac Faculty of Health Sciences Health Sciences Research Center]]></institution>
<addr-line><![CDATA[Huixquilucan Estado de Mexico]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Hospital Juarez de Mexico Department of Critical Care Medicine ]]></institution>
<addr-line><![CDATA[Mexico City ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Nacional Autónoma de Mexico Faculty of Sciences ]]></institution>
<addr-line><![CDATA[Mexico City ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Instituto Nacional de Cardiología "Ignacio Chávez" Department of Electromechanical Instrumentation ]]></institution>
<addr-line><![CDATA[Mexico City ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af5">
<institution><![CDATA[,Instituto Nacional de Ciencias Médicas y Nutrición Department of Epidemiology ]]></institution>
<addr-line><![CDATA[Mexico City ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af6">
<institution><![CDATA[,Hospital General de México Research Direction ]]></institution>
<addr-line><![CDATA[Mexico City ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>08</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>08</month>
<year>2021</year>
</pub-date>
<volume>89</volume>
<numero>4</numero>
<fpage>503</fpage>
<lpage>519</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2444-054X2021000400503&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2444-054X2021000400503&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2444-054X2021000400503&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract  Background: The dynamic interactions of severe infectious diseases with epidemic potential and their hosts are complex. Therefore, it remains uncertain if a sporadic zoonosis restricted to a certain area will become a global pandemic or something in between.  Objective: The objective of the study was to present a surveillance system for acute severe infections with epidemic potential based on a deterministic-stochastic model, the StochCum Method.  Design: The StochCum Method is founded on clinical, administrative, and sociodemographic variables that provide a space/time map as a preventive warning of possible outbreaks of severe infections that can be complemented based on the sum of all the first accumulated cases. If the outbreak is happening in high-risk areas, an early warning can be elicited to activate the health response system and save time while waiting for the confirmation of symptomatic cases.  Results: The surveillance system was tested virtually for 1 month on admissions to the Emergency Room of a public hospital located in Mexico City, Mexico. It promptly identified simulated cases of acute respiratory infections with epidemic potential.  Conclusions: The StochCum method proved to be a practical and useful system for conducting epidemic surveillance on a hospital network.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen  Antecedentes: Las interacciones dinámicas de enfermedades infecciosas graves con potencial epidémico y sus hospederos son complejas. Por lo tanto, sigue siendo incierto si una zoonosis esporádica restringida a una determinada región se convertirá en una pandemia o algo intermedio.  Objectivo: Presentar un sistema computacional de vigilancia de las infecciones graves agudas con potencial epidémico basado en un modelo estocástico determinista, el StochCum Method.  Diseño: El StochCum method se basa en variables clínicas, administrativas y sociodemográficas que proporcionan un mapa espacio-temporal de posibles brotes de infecciones graves, que se ponderan con los casos de contagios confirmados. El sistema es especialmente útil para obtener una alerta temprana mientras se confirman los casos sintomáticos.  Resultados: El sistema de vigilancia fue probado en forma virtual durante un mes con los ingresos al Servicio de Urgencias de un hospital público ubicado en la Ciudad de México. En todos identificó los casos de sujetos con infecciones respiratorias agudas con potencial epidémico.  Conclusiones: El StochCum method mostró ser un sistema práctico y útil para efectuar vigilancia epidemiológica sobre una red hospitalaria.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Epidemic potential]]></kwd>
<kwd lng="en"><![CDATA[Severe infections]]></kwd>
<kwd lng="en"><![CDATA[Deterministic-stochastic epidemiological warning systems]]></kwd>
<kwd lng="es"><![CDATA[Potencial pandémico]]></kwd>
<kwd lng="es"><![CDATA[Infecciones graves]]></kwd>
<kwd lng="es"><![CDATA[Sistemas determinísticos-estocásticos de alerta epidemiológica]]></kwd>
</kwd-group>
</article-meta>
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