Desigualdades en salud y su relación con las tasas de letalidad del COVID-19 en una clínica de alto nivel de complejidad de Armenia – Quindío entre 2020 a 2021
The COVID-19 pandemic had a global impact, disproportionately affecting different populations based on socioeconomic, geographical, and healthcare access factors. The virus's lethality, the proportion of deaths among diagnosed cases, is a key indicator for assessing health inequalities and the...
- Autores:
-
Castillo Valencia, Ginna Marcela
Villazón Gutiérrez, Edgardo
- Tipo de recurso:
- Fecha de publicación:
- 2025
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/14335
- Acceso en línea:
- https://hdl.handle.net/11323/14335
https://repositorio.cuc.edu.co/
- Palabra clave:
- Cobertura de servicios de salud
COVID-19
Desigualdades en la salud
Factores socioeconómicos
Letalidad
Health Services Coverage
Health Status Disparities
Socioeconomic factors
Mortality
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
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Desigualdades en salud y su relación con las tasas de letalidad del COVID-19 en una clínica de alto nivel de complejidad de Armenia – Quindío entre 2020 a 2021 |
| title |
Desigualdades en salud y su relación con las tasas de letalidad del COVID-19 en una clínica de alto nivel de complejidad de Armenia – Quindío entre 2020 a 2021 |
| spellingShingle |
Desigualdades en salud y su relación con las tasas de letalidad del COVID-19 en una clínica de alto nivel de complejidad de Armenia – Quindío entre 2020 a 2021 Cobertura de servicios de salud COVID-19 Desigualdades en la salud Factores socioeconómicos Letalidad Health Services Coverage Health Status Disparities Socioeconomic factors Mortality |
| title_short |
Desigualdades en salud y su relación con las tasas de letalidad del COVID-19 en una clínica de alto nivel de complejidad de Armenia – Quindío entre 2020 a 2021 |
| title_full |
Desigualdades en salud y su relación con las tasas de letalidad del COVID-19 en una clínica de alto nivel de complejidad de Armenia – Quindío entre 2020 a 2021 |
| title_fullStr |
Desigualdades en salud y su relación con las tasas de letalidad del COVID-19 en una clínica de alto nivel de complejidad de Armenia – Quindío entre 2020 a 2021 |
| title_full_unstemmed |
Desigualdades en salud y su relación con las tasas de letalidad del COVID-19 en una clínica de alto nivel de complejidad de Armenia – Quindío entre 2020 a 2021 |
| title_sort |
Desigualdades en salud y su relación con las tasas de letalidad del COVID-19 en una clínica de alto nivel de complejidad de Armenia – Quindío entre 2020 a 2021 |
| dc.creator.fl_str_mv |
Castillo Valencia, Ginna Marcela Villazón Gutiérrez, Edgardo |
| dc.contributor.advisor.none.fl_str_mv |
Beltran Venegas, Tulia Jervis Jalabe, David |
| dc.contributor.author.none.fl_str_mv |
Castillo Valencia, Ginna Marcela Villazón Gutiérrez, Edgardo |
| dc.contributor.jury.none.fl_str_mv |
Lasprilla Fawcett, Silvana Garizabalo, Claudia Arrieta Reales, Nancy |
| dc.subject.proposal.spa.fl_str_mv |
Cobertura de servicios de salud COVID-19 Desigualdades en la salud Factores socioeconómicos Letalidad |
| topic |
Cobertura de servicios de salud COVID-19 Desigualdades en la salud Factores socioeconómicos Letalidad Health Services Coverage Health Status Disparities Socioeconomic factors Mortality |
| dc.subject.proposal.eng.fl_str_mv |
Health Services Coverage Health Status Disparities Socioeconomic factors Mortality |
| description |
The COVID-19 pandemic had a global impact, disproportionately affecting different populations based on socioeconomic, geographical, and healthcare access factors. The virus's lethality, the proportion of deaths among diagnosed cases, is a key indicator for assessing health inequalities and the effectiveness of health responses. Understanding how these inequalities manifest is essential for developing more equitable health policies. To determine the relationship between health inequalities and COVID-19 lethality in patients treated at the Sagrada Familia Clinic in Armenia, Quindío, between 2020 and 2021. A quantitative methodology with descriptive and correlational statistical analysis was used. The Relative Index of Inequality (RII), the Concentration Index (CI), and the Concentration Curve (CC) were used to measure inequalities in the case-fatality rate (CFR) of COVID-19. CFR was calculated discriminated by age groups, sex, socioeconomic status, area of occurrence, health insurance regime, and nationality. Data were obtained from the SIVIGILA database, completed during the pandemic for each suspected case. Significant differences in COVID-19 lethality were found. The highest rates were observed in socioeconomic stratum 1 (0.528) and in dispersed rural areas (0.143). A concentration of lethality was identified among patients under the subsidized regime (0.138) and in rural areas. The Concentration Index was -0.14, indicating an unequal distribution of lethality towards the most disadvantaged groups. Lethality was zero among foreign patients (0.000), while for Colombians it was 0.072. The findings indicate the need to implement health policies aimed at reducing the observed inequality gaps. It is a priority to focus efforts on improving access to healthcare for vulnerable groups and in rural areas. This quantitative analysis contributes to the design of more equitable strategies for managing future health emergencies. |
| publishDate |
2025 |
| dc.date.accessioned.none.fl_str_mv |
2025-07-25T21:29:40Z |
| dc.date.available.none.fl_str_mv |
2025-07-25T21:29:40Z |
| dc.date.issued.none.fl_str_mv |
2025-04-26 |
| dc.type.none.fl_str_mv |
Trabajo de grado - Maestría |
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Text |
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info:eu-repo/semantics/masterThesis |
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http://purl.org/redcol/resource_type/TM |
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info:eu-repo/semantics/acceptedVersion |
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acceptedVersion |
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https://hdl.handle.net/11323/14335 |
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Corporación Universidad de la Costa |
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REDICUC - Repositorio CUC |
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https://repositorio.cuc.edu.co/ |
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https://hdl.handle.net/11323/14335 https://repositorio.cuc.edu.co/ |
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Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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spa |
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spa |
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Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Beltran Venegas, TuliaJervis Jalabe, DavidCastillo Valencia, Ginna MarcelaVillazón Gutiérrez, EdgardoLasprilla Fawcett, SilvanaGarizabalo, ClaudiaArrieta Reales, Nancy2025-07-25T21:29:40Z2025-07-25T21:29:40Z2025-04-26https://hdl.handle.net/11323/14335Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/The COVID-19 pandemic had a global impact, disproportionately affecting different populations based on socioeconomic, geographical, and healthcare access factors. The virus's lethality, the proportion of deaths among diagnosed cases, is a key indicator for assessing health inequalities and the effectiveness of health responses. Understanding how these inequalities manifest is essential for developing more equitable health policies. To determine the relationship between health inequalities and COVID-19 lethality in patients treated at the Sagrada Familia Clinic in Armenia, Quindío, between 2020 and 2021. A quantitative methodology with descriptive and correlational statistical analysis was used. The Relative Index of Inequality (RII), the Concentration Index (CI), and the Concentration Curve (CC) were used to measure inequalities in the case-fatality rate (CFR) of COVID-19. CFR was calculated discriminated by age groups, sex, socioeconomic status, area of occurrence, health insurance regime, and nationality. Data were obtained from the SIVIGILA database, completed during the pandemic for each suspected case. Significant differences in COVID-19 lethality were found. The highest rates were observed in socioeconomic stratum 1 (0.528) and in dispersed rural areas (0.143). A concentration of lethality was identified among patients under the subsidized regime (0.138) and in rural areas. The Concentration Index was -0.14, indicating an unequal distribution of lethality towards the most disadvantaged groups. Lethality was zero among foreign patients (0.000), while for Colombians it was 0.072. The findings indicate the need to implement health policies aimed at reducing the observed inequality gaps. It is a priority to focus efforts on improving access to healthcare for vulnerable groups and in rural areas. This quantitative analysis contributes to the design of more equitable strategies for managing future health emergencies.La pandemia de COVID-19 impactó globalmente, afectando de manera desproporcionada a distintas poblaciones según factores socioeconómicos, geográficos y de acceso a salud. La letalidad del virus, proporción de muertes entre casos diagnosticados, es un indicador clave para evaluar las desigualdades en salud y la efectividad de las respuestas sanitarias. Comprender cómo estas desigualdades se manifiestan es esencial para desarrollar políticas de salud más equitativas, determinar la relación de las desigualdades en salud con la letalidad por COVID-19 en pacientes atendidos en la Clínica La Sagrada Familia de Armenia, Quindío, entre los años 2020 y 2021. Se empleó una metodología cuantitativa con análisis estadístico descriptivo y correlacional. Se utilizaron el Índice Relativo de Desigualdad (IRD), el Índice de Concentración (IC) y la Curva de Concentración (CC) para medir las desigualdades en la tasa de letalidad (TL) por COVID-19. Se calculó la TL discriminada por grupos etarios, sexo, estrato socioeconómico, área de ocurrencia, régimen de aseguramiento en salud y nacionalidad. Los datos se obtuvieron de la base de datos de SIVIGILA, diligenciada durante la pandemia para cada caso sospechoso. Se encontraron diferencias significativas en la letalidad por COVID-19. Las tasas más altas se observaron en el estrato socioeconómico 1 (0.528) y en áreas rurales dispersas (0.143). Se identificó una concentración de la letalidad en pacientes del régimen subsidiado (0.138) y en áreas rurales. El Índice de Concentración fue de -0.14, indicando una distribución desigual de la letalidad hacia los grupos más desfavorecidos. La letalidad fue nula en pacientes extranjeros (0.000), mientras que para los colombianos fue de 0.072.Los hallazgos señalan la necesidad de implementar políticas de salud orientadas a reducir las brechas de desigualdad observadas. Es prioritario enfocar esfuerzos en mejorar el acceso a la atención sanitaria para grupos vulnerables y en zonas rurales. Este análisis cuantitativo contribuye al diseño de estrategias más equitativas para la gestión de futuras emergencias sanitarias.Lista de tablas y figuras 10--Tablas 10--Figuras 12--Planteamiento del problema 17--Descripción del área problemática o tema de investigación 22--Formulación del problema/pregunta de investigación 23--Sistematización del problema 23--Hipótesis General de Investigación 24--Hipótesis Específicas de Investigación 24--Justificación 26--Delimitación de la investigación 30--Objetivos 31--Objetivo general 31--Objetivos específicos 31--Marco teórico 32--Desigualdad en salud 32--Teoría de los Determinantes Sociales de la Salud 39--Modelo de Dahlgren y Whitehead 40--Modelo de Marmot 43--Modelo de Braveman y Gruskin 45--Enfermedades infecciosas 48--Estado del arte 50--Diseño metodológico 63--Tipo de estudio 67--Población y muestra 67--Técnicas e instrumentos de recolección de información 68--Procedimiento 68--Análisis estadísticos 68--Validación de datos 69--Limitaciones y consideraciones éticas 69--Resultados 70--Objetivo 1 70--Índice Relativo de Desigualdad 70--Análisis de varianza (TL) 76--Parámetros del modelo 78--Curva de concentración e índice de concentración 81--Objetivo 2 86--Índice Relativo de Desigualdad 86--Curva de concentración e índice de concentración 90--Objetivo 3 95--Índice Relativo de Desigualdad 96--Análisis de varianza (TL) 102--Parámetros del modelo 104--Curva de concentración e índice de concentración 107--Objetivo 4 112--Índice Relativo de Desigualdad 112--Curva de concentración e índice de concentración 115--Discusión 120--Conclusiones 122--Recomendaciones 124--Referencias 126--Magíster en Gestión de Servicios de SaludMaestría135 páginasapplication/pdfspaCorporacion Universidad de la CostaCiencias de la SaludBarranquilla, ColombiaMaestría en Gestión de Servicios de SaludCorporación Universidad de la CostaDesigualdades en salud y su relación con las tasas de letalidad del COVID-19 en una clínica de alto nivel de complejidad de Armenia – Quindío entre 2020 a 2021Trabajo de grado - MaestríaTextinfo:eu-repo/semantics/masterThesishttp://purl.org/redcol/resource_type/TMinfo:eu-repo/semantics/acceptedVersionArmeniaKjellsson G, Gerdtham UG. 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Available from: https://datos.bancomundial.org/pais/colombiaCobertura de servicios de saludCOVID-19Desigualdades en la saludFactores socioeconómicosLetalidadHealth Services CoverageHealth Status DisparitiesSocioeconomic factorsMortalityPublicationORIGINALDesigualdades en salud y su relación con las tasas de letalidad del COVID-19 en una clínica de alto nivel de complejidad de Armenia – Quindío entre 2020 a 2021.pdfDesigualdades en salud y su relación con las tasas de letalidad del COVID-19 en una clínica de alto nivel de complejidad de Armenia – Quindío entre 2020 a 2021.pdfapplication/pdf1130102https://repositorio.cuc.edu.co/bitstreams/125b70fc-d665-46cb-a93f-80880e37c5c1/download7f2d4f7bf7037c72f5d408cf67811311MD53LICENSElicense.txtlicense.txttext/plain; charset=utf-815543https://repositorio.cuc.edu.co/bitstreams/c4f84db3-ca63-43bf-8690-94322b99b067/download73a5432e0b76442b22b026844140d683MD52TEXTDesigualdades en salud y su relación con las tasas de letalidad del COVID-19 en una 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ara ejercer estos derechos sobre la Obra tal y como se indica a continuación:</p>
    <ol type="a">
      <li>Reproducir la Obra, incorporar la Obra en una o más Obras Colectivas, y reproducir la Obra incorporada en las Obras Colectivas.</li>
      <li>Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.</li>
      <li>Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.</li>
    </ol>
    <p>Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).</p>
  </li>
  <br/>
  <li>
    Restricciones.
    <p>La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:</p>
    <ol type="a">
      <li>Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).</li>
      <li>Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.</li>
      <li>Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.</li>
      <li>
        Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:
        <ol type="i">
          <li>Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.</li>
          <li>Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.</li>
        </ol>
      </li>
      <li>Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.</li>
    </ol>
  </li>
  <br/>
  <li>
    Representaciones, Garantías y Limitaciones de Responsabilidad.
    <p>A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.</p>
  </li>
  <br/>
  <li>
    Limitación de responsabilidad.
    <p>A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.</p>
  </li>
  <br/>
  <li>
    Término.
    <ol type="a">
      <li>Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.</li>
      <li>Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.</li>
    </ol>
  </li>
  <br/>
  <li>
    Varios.
    <ol type="a">
      <li>Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.</li>
      <li>Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.</li>
      <li>Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.</li>
      <li>Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.</li>
    </ol>
  </li>
  <br/>
</ol>
 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