<?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>0188-4611</journal-id>
<journal-title><![CDATA[Investigaciones geográficas]]></journal-title>
<abbrev-journal-title><![CDATA[Invest. Geog]]></abbrev-journal-title>
<issn>0188-4611</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Instituto de Geografía]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0188-46112022000100110</article-id>
<article-id pub-id-type="doi">10.14350/rig.60457</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[COVID-19 in Hidalgo, Mexico. A study of territorial inequalities]]></article-title>
<article-title xml:lang="es"><![CDATA[COVID-19 en Hidalgo, México. Un estudio de las desigualdades territoriales]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Medina Pérez]]></surname>
<given-names><![CDATA[Patricia Catalina]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Tapia Fernández]]></surname>
<given-names><![CDATA[Héctor Jesús]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Intercultural del Estado de Hidalgo Sciences and Environment Department ]]></institution>
<addr-line><![CDATA[Tenango de Doria Hidalgo]]></addr-line>
<country>México</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Colegio del Estado de Hidalgo Geomatics Laboratory ]]></institution>
<addr-line><![CDATA[Exhacienda La Concepción Hidalgo]]></addr-line>
<country>México</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2022</year>
</pub-date>
<numero>107</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0188-46112022000100110&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0188-46112022000100110&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0188-46112022000100110&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract  Introduction  The ongoing global pandemic due to the COVID-19 virus has had varying impacts on the quality of life in different regions. This article aims to identify areas of high social vulnerability in the municipalities in Hidalgo with information gathered in 2015.  Methodology  The social vulnerability index was calculated by using the principal component analysis technique along with geographic information systems to evaluate its relationship with COVID-19 fatality ratio. Variables were constructed based on information taken from the 2015 Intercensal Survey for municipalities.  Results  Two regions, one in the northeast and the other in the southwest of the state of Hidalgo, showed a strong relationship between social vulnerability and the fatality ratio.  Conclusions  The variables that best explain social vulnerability in the Municipalities in Hidalgo are those that contemplate population characteristics. The findings could be used in planning social actions so that they not only focus on health care services in order to reduce the impacts of the current pandemic and reduce mortality due to COVID-19 in the most vulnerable sectors in Municipalities in Hidalgo.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen  Introducción  La pandemia mundial en curso, debido al virus COVID-19, ha tenido diversos impactos en la calidad de vida en diferentes regiones. Este artículo tiene como objetivo identificar áreas de alta vulnerabilidad social en los municipios hidalguenses con información recopilada en 2015.  Metodología  Se calculó el índice de vulnerabilidad social utilizando la técnica de análisis de componentes principales junto con sistemas de información geográfica para evaluar su relación con la tasa de letalidad por COVID-19. Las variables fueron construidas a partir de información extraída de la Encuesta Intercensal 2015 para municipios.  Resultados  Dos regiones, una en el noreste y otra en el suroeste del estado de Hidalgo, México, mostraron una fuerte relación entre la vulnerabilidad social y la tasa de letalidad.  Conclusiones  Las variables que mejor explican la vulnerabilidad social en los municipios hidalguenses son aquellas que contemplan las características de la población. Los hallazgos podrían ser utilizados en la planificación de acciones sociales para que no solo se enfoquen en los servicios de salud para reducir los impactos de la actual pandemia y reducir la mortalidad por COVID-19 en los sectores más vulnerables de dichos municipios.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[COVID]]></kwd>
<kwd lng="en"><![CDATA[inequalities]]></kwd>
<kwd lng="en"><![CDATA[territory]]></kwd>
<kwd lng="en"><![CDATA[mortality]]></kwd>
<kwd lng="en"><![CDATA[social vulnerability]]></kwd>
<kwd lng="es"><![CDATA[COVID]]></kwd>
<kwd lng="es"><![CDATA[desigualdades]]></kwd>
<kwd lng="es"><![CDATA[territorio]]></kwd>
<kwd lng="es"><![CDATA[mortalidad]]></kwd>
<kwd lng="es"><![CDATA[vulnerabilidad social]]></kwd>
</kwd-group>
</article-meta>
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