Analyzing municipal patterns of suicide and depression in Mexico : a Multilayer Network Approach

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<title>Analyzing municipal patterns of suicide and depression in Mexico</title>
<subTitle>: a Multilayer Network Approach</subTitle>
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<namePart>IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial
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<abstract displayLabel="Summary">This article analyzes the spatial and temporal patterns of suicide and depression in municipalities in Mexico during the period 20152020 using a multilayer network approach. Based on a panel of indicators related to mental health, substance use, medical consultations, and healthcare infrastructure, the authors construct a multilayer graph using cosine similarity and apply the Infomap algorithm to detect communities with similar profiles. The study identifies five clusters with differentiated behaviors, revealing territories with higher rates of substance use and worse mental health outcomes. The findings show how network-based methods can detect municipal groupings at risk and provide useful information for guiding public health policies and interventions</abstract>
<note type="statement of responsibility">Jorge Manuel Pool Cen...[et al.]</note>
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<topic>Salud mental</topic>
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<topic>Depresión</topic>
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<topic>Suicidio</topic>
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<topic>Estadística matemática</topic>
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<topic>Estadística de muestreo</topic>
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<topic>Drogas</topic>
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<geographic>México</geographic>
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<url displayLabel="electronic resource" usage="primary display">https://journal.iberamia.org/index.php/intartif/article/view/2504</url>
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<title>Revista Iberoamericana de Inteligencia Artificial</title>
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<publisher> : IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial , 2018-</publisher>
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<identifier type="issn">1988-3064</identifier>
<identifier type="local">MAP20200034445</identifier>
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<text>08/12/2025 Volume 28 Number  76 - December 2025 , p. 1 - 12</text>
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