<?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>2663-3981</journal-id>
<journal-title><![CDATA[Revista cartográfica]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. cartogr.]]></abbrev-journal-title>
<issn>2663-3981</issn>
<publisher>
<publisher-name><![CDATA[Instituto Panamericano de Geografía e Historia]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2663-39812024000100099</article-id>
<article-id pub-id-type="doi">10.35424/rcarto.i108.5732</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Examinando la relación de la profundidad óptica de aerosoles derivada de imágenes MODIS con contagios por COVID-19 en Santiago, Chile]]></article-title>
<article-title xml:lang="en"><![CDATA[Examining the relationship of the MODIS-derived optical aerosol thickness with COVID-19 infections in Santiago, Chile]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Peña]]></surname>
<given-names><![CDATA[Marco A.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Fuenzalida]]></surname>
<given-names><![CDATA[Manuel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Alberto Hurtado Departamento de Geografía ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Chile</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Alberto Hurtado Departamento de Geografía ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Chile</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2024</year>
</pub-date>
<numero>108</numero>
<fpage>99</fpage>
<lpage>116</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2663-39812024000100099&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2663-39812024000100099&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2663-39812024000100099&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen Aquí es examinada la relación que presenta el producto de grosor óptico de aerosoles (aerosol optical depth, AOD) MAIAC (Multi-Angle Implementation of Atmospheric Correction), derivado de imágenes satelitales MODIS (Moderate Resolution Imaging Spectroradiometer), con contagios COVID-19, un campo de investigación que aún permanece inexplorado en el estado del arte internacional, cuyo abordaje contribuiría a comprender la incidencia de la contaminación atmosférica en la ocurrencia de casos de esa enfermedad sobre grandes urbes. Para esto, datos diarios de AOD, adquiridos a las ~18:00 hora local, y tasas de contagio (R0s) por COVID-19 del Área Metropolitana de Santiago, Chile, fueron agregados y correlacionados a nivel de semanas epidemiológicas (SEs) en un periodo comprendido entre marzo y diciembre de 2020, dentro de cuatro zonas en que fue dividida el área de estudio. Las correlaciones más altas fueron obtenidas cuando AOD fue retardado en una semana respecto de R0s inferiores a 120 por cada 100 mil habitantes, rango que da cuenta del período de incubación del virus, así como del rezago con que actúa sobre la salud humana la exposición a la contaminación atmosférica cuando la transmisión aún no se torna comunitaria. Las zonas nororiente y suroriente arrojaron correlaciones más claras entre ambas fuentes de datos (r= 0,57 y 0,47, respectivamente), que aquellas norponiente y surponiente (r= 0,3), aspecto que guarda estrecha relación con la dinámica atmosférica que caracteriza al valle en que se asienta la ciudad de Santiago, y que determina la movilización de contaminantes hacia su sector más alto (oriente) durante el atardecer. Se espera que este trabajo constituya una primera aproximación a la construcción de modelos causales y predictivos sobre el comportamiento espaciotemporal de la enfermedad en cuestión a partir de productos de AOD.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Here, the relationship between the MAIAC (Multi-Angle Implementation of At-mospheric Correction) aerosol optical depth (AOD) product, derived from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite images, and COVID-19 infections is examined. This research field still remains unexplored in the international state-of-the-art, whose approach will contribute to understand the incidence of air pollution on the occurrence of the disease cases over large cities. For this, daily AOD data, acquired at ~18:00 local time, and COVID-19 reproduction number (R0) from the Metropolitan Area of Santiago, Chile, were aggregated and correlated on a weekly epidemiological basis (SE) in a period embracing from March to December 2020, within four zones that divided the study area. The highest correlations were obtained when AOD was lagged by one week regarding R0s lower than 120 per 100 thousand inhabitants. This temporal range accounts for the virus incubation period, as well as the delay at which air pollution exposure affects human health when transmission has not yet become community-acquired. The northeast and southeast areas showed clearer correlations between both data sources (r= 0.57 and 0.47, respectively), than those north-west and south-west (r= 0.3). This finding is closely related to the atmospheric dynamics characterizing the valley where Santiago city is located, determining the movement of pollutants towards its highest sector (east) at afternoon. It is expected that this work will constitute a first approach to the construction of causal and predictive AOD-based models on the spatiotemporal behavior of the disease at issue.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[grosor óptico de aerosoles]]></kwd>
<kwd lng="es"><![CDATA[material particulado]]></kwd>
<kwd lng="es"><![CDATA[COVID-19]]></kwd>
<kwd lng="es"><![CDATA[MODIS-MAIAC]]></kwd>
<kwd lng="en"><![CDATA[aerosol optical depth]]></kwd>
<kwd lng="en"><![CDATA[particulate matter]]></kwd>
<kwd lng="en"><![CDATA[COVID-19]]></kwd>
<kwd lng="en"><![CDATA[MODIS-MAIAC]]></kwd>
</kwd-group>
</article-meta>
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