<?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>1012-2966</journal-id>
<journal-title><![CDATA[Gaceta Médica Boliviana]]></journal-title>
<abbrev-journal-title><![CDATA[Gac Med Bol]]></abbrev-journal-title>
<issn>1012-2966</issn>
<publisher>
<publisher-name><![CDATA[Facultad de Medicina de la Universidad Mayor de San Simón]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1012-29662025000200115</article-id>
<article-id pub-id-type="doi">10.47993/gmb.v48i2.1143</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Spatio-temporal analysis of dengue fever in Bolivia: climatic, environmental and sociodemographic factors]]></article-title>
<article-title xml:lang="es"><![CDATA[Análisis espacio-temporal del dengue en Bolivia: factores climáticos, ambientales y sociodemográficos]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cabrera]]></surname>
<given-names><![CDATA[Maritza]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Naranjo-Torres]]></surname>
<given-names><![CDATA[José]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[San-Martín-Órdenes]]></surname>
<given-names><![CDATA[Julio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Segovia]]></surname>
<given-names><![CDATA[Christian]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Fernández]]></surname>
<given-names><![CDATA[Gerardo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Estudios Avanzados del Maule (CIEAM) Centro de Investigaciones ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
</aff>
<aff id="Af2">
<institution><![CDATA[,Academic and ML Consulting Dpt. Global Consulting H &amp;G ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>U.S.A.</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Católica del Maule (UCM) Centro de Investigación de Estudios Avanzados del Maule (CIEAM) Programa de Doctorado en Salud Ecosistémica]]></institution>
<addr-line><![CDATA[Talca ]]></addr-line>
<country>Chile</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Universidad Católica del Maule (UCM) Departamento de Ciencias Preclínicas, Facultad de Medicina Laboratorio de Microbiología y Parasitología]]></institution>
<addr-line><![CDATA[Talca ]]></addr-line>
<country>Chile</country>
</aff>
<aff id="Af5">
<institution><![CDATA[,Universidad Técnica de Ambato (UTA) Facultad de Ciencias de la Salud ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Ecuador</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2025</year>
</pub-date>
<volume>48</volume>
<numero>2</numero>
<fpage>115</fpage>
<lpage>122</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.bo/scielo.php?script=sci_arttext&amp;pid=S1012-29662025000200115&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.bo/scielo.php?script=sci_abstract&amp;pid=S1012-29662025000200115&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.bo/scielo.php?script=sci_pdf&amp;pid=S1012-29662025000200115&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Dengue is a prevalent arbovirus globally, with incidence rising sharply in the Americas due to climate change and increased human mobility. Bolivia recorded its highest cumulative incidence in early 2023, signaling a severe public health crisis.  Objective:  To analyze dengue cases in Bolivia (2014-2023) from a spatio-temporal perspective, identifying the climatic, environmental, and sociodemographic factors associated with transmission and the expansion of Aedes aegypti vector.  Methods:  A longitudinal observational study was conducted using departmental data. Annual Standardized Incidence (ASI) was calculated. calculated. Climatic and environmental variables included NDVI, maximum temperature, and precipitation. Generalized Additive Models (GAM) were applied to interpret spatio-temporal structures.  Results:  The highest ASI values were concentrated in the eastern departments: Pando, Beni, Tarija, and Santa Cruz. Major outbreaks (2015, 2016, 2020, and 2023) coincided with the rainy season. NDVI showed the strongest correlation with incidence. The optimal GAM explained 67.8% of the variance. Incidence stabilized after 20 mm of rain and decreased below 20 °C.  Conclusion:  Dengue transmission in Bolivia is driven by climatic and environmental factors, primarily affecting the eastern regions. Foreign mobility and rainwater collection tanks are emerging risks. The study supports integrating eco-epidemiological models under a One Health approach for effective cross-border control.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El dengue es un arbovirus global. En América, su incidencia ha aumentado de manera significativa en los últimos años, impulsada por el cambio climático y la movilidad humana. Bolivia registró su mayor incidencia acumulada a principios de 2023, lo que representa un importante problema de salud pública.  Objetivo:  Analizar la incidencia del dengue en Bolivia (2014-2023) desde una perspectiva espacio-temporal, identificando los factores climáticos, ambientales y sociodemográficos asociados a la transmisión y a la expansión del vector Aedes aegypti.  Métodos:  Se realizó un estudio observacional longitudinal con datos departamentales. Se calculó la Incidencia Estándar Anual (ISA). Las variables climáticas y ambientales incluyeron NDVI, temperatura máxima y precipitación. Se aplicaron Modelos Aditivos Generalizados (GAM) para capturar asociaciones no lineales y para interpretar las estructuras espacio-temporales.  Resultados:  Las ISA más altas se concentraron en los departamentos orientales: Pando, Beni, Tarija y Santa Cruz. Los brotes críticos (2015, 2016, 2020 y 2023) coincidieron con la temporada de lluvias. El NDVI mostró la correlación más fuerte con la incidencia. El modelo GAM óptimo explicó el 67,8% de la varianza. La incidencia se estabilizó a los 20 mm de lluvia y descendió con temperaturas inferiores 20 °C.  Conclusión:  La transmisión del dengue en Bolivia está impulsada principalmente por factores climáticos y ambientales, con riesgos emergentes asociados a la movilidad de población extranjera y al almacenamiento de agua de lluvia. Los hallazgos respaldan la integración de modelos eco-epidemiológicos bajo un enfoque enfoque One Health para un control transfronterizo más efectivo.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Aedes aegypti]]></kwd>
<kwd lng="en"><![CDATA[Arbovirus]]></kwd>
<kwd lng="en"><![CDATA[climate change]]></kwd>
<kwd lng="en"><![CDATA[Dengue epidemiology]]></kwd>
<kwd lng="es"><![CDATA[Aedes aegypti]]></kwd>
<kwd lng="es"><![CDATA[Arbovirus]]></kwd>
<kwd lng="es"><![CDATA[Cambio climático]]></kwd>
<kwd lng="es"><![CDATA[Epidemiología del dengue]]></kwd>
</kwd-group>
</article-meta>
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