Condiciones de vulnerabilidad, sociodemográficas y clínicas de la población diagnosticada con COVID-19 incluida en la estrategia de atención primaria en salud del municipio de Mosquera 2020
Introducción: en diciembre de 2019 la Comisión Municipal de Salud y Sanidad de Wuhan, China, reportó 27 casos de neumonía de causa desconocida llegando a Colombia. Los municipios implementaron estrategias para minimizar contagios como lo hizo Mosquera, Cundinamarca, sin embargo no se conoció la caracterización de la población afectada por COVID-19. Objetivo: analizar las condiciones de vulnerabilidad, sociodemográficas y clínicas de la población con COVID-19 incluida en la estrategia de atención primaria en salud. Metodología: estudio cuantitativo, observacional, de corte transversal, retrospectivo, con análisis de condiciones de vulnerabilidad, características sociodemográficas y clínicas de la población diagnosticada con COVID-19 del muni... Ver más
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Condiciones de vulnerabilidad, sociodemográficas y clínicas de la población diagnosticada con COVID-19 incluida en la estrategia de atención primaria en salud del municipio de Mosquera 2020 Cieza Zevallos J, Uriol Lescano C. Letalidad y la mortalidad de Covid 19 en 60 países afectados y su impacto en los aspectos demográficos, económicos y de salud. Rev Medica Hered. 2021;31(4):214–21. http://dx.doi.org/10.20453/rmh.v31i4.3852 Ramírez IJ, Lee J. COVID-19 emergence and social and health determinants in Colorado: A rapid spatial analysis. Int J Environ Res Public Health. 2020;17(11):1–15. doi: 10.3390/ijerph1711385 Muscillo A, Pin P, Razzolini T. Spreading of an infectious disease between different locations. J Econ Behav Organ. 2021;183:508–32. https://doi.org/10.1016/j.jebo.2021.01.004 Mendolia S, Stavrunova O, Yerokhin O. Determinants of the community mobility during the COVID-19 epidemic: The role of government regulations and information. J Econ Behav Organ. 2021;184:199–231. https://doi.org/10.1016/j.jebo.2021.01.023 McCarthy CP, Murphy S, Jones-O’Connor M, Olshan DS, Khambhati JR, Rehman S, et al. Early clinical and sociodemographic experience with patients hospitalized with COVID-19 at a large American healthcare system. EClinicalMedicine. 2020;26:100504. https://doi.org/10.1016/j.eclinm.2020.100504 Harlem G. Descriptive analysis of social determinant factors in urban communities affected by COVID-19. J Public Heal (United Kingdom). 2020;42(3):466–9. https://doi.org/10.1093/pubmed/fdaa078 Witteveen D. Sociodemographic inequality in exposure to COVID-19-induced economic hardship in the United Kingdom. Res Soc Stratif Mobil. 2020;69:100551. https://doi.org/10.1016/j.rssm.2020.100551 Chan Yang EY, Huang Z, Kai Lo ES, Ching Hung KK, Wong ELY, Wong SYS. Sociodemographic predictors of health risk perception, attitude and behavior practices associated with health-emergency disaster risk management for biological hazards: The case of COVID-19 pandemic in Hong Kong, SAR China. Int J Environ Res Public Health. 2020;17(11): :3869. doi: 10.3390/ijerph17113869 Benatar S. The most powerful healt-promoting forces in COVID-19 are social. S Afr J Sci. 2020;116(7-8):148–62. https://hdl.handle.net/10520/EJC-1f60b9dc0c Becerra-García JA, Giménez Ballesta G, Sánchez-Gutiérrez T, Barbeito Resa S, Calvo Calvo A. [Psychopathological symptoms during Covid-19 quarantine in spanish general population: a preliminary analysis based on sociodemographic and occupational-contextual factors.]. Rev Esp Salud Publica. 2020;94:e202006059 Presidencia de la República. (2020, 25 de agosto) Decreto 1168. Por el cual se imparten instrucciones en virtud de la emergencia sanitaria generada por la pandemia del Coronavirus covid–19, y el mantenimiento del orden público y se decreta el aislamiento selective con distanciamiento individual responsable. (Diario Oficial 51362 de 2020). Ministerio de la protección Social. El Coronavirus en Colombia [Internet]. 2021 [cited 2021 Sep 16]. Available from: https://coronaviruscolombia.gov.co/Covid19/index.html Kahlout AM, ALhubidi K, AlMesaifri MA, AL Mansour T, Khudadad H. The prevalence of COVID 19 among PHCC workers and its relation to place of works and medical comorbidities. World Fam Med. 2021;19(4):84–104. Organización Mundial de la Salud, Organización Panamericana de Salud. Actualización Epidemiológica: Nuevo coronavirus (Covid-19). Organ Mund la Salud. 2020. Arora P, Mittal H, Gupta N, Jimmy JK, Jain K, Sharma A. Sociodemographic Factors and Clinical Profile of Covid-19 Patients Admitted in a Tertiary Care Centre of Central Rajasthan, India. J Evid Based Med Healthc. 2021;8(13):773–7. doi: 10.18410/jebmh/2021/152 Li L, Hang D, Dong H, Yuan-Yuan C, Bo-Heng L, Ze-Lin Y, et al. Temporal dynamic in the impact of COVID− 19 outbreak on cause-specific mortality in Guangzhou, China. BMC Public Health. 2021;21(1):1–11. https://doi.org/10.1186/s12889-021-10771-3 Hawkins D. Social determinants of covid-19 in massachusetts, United States: An ecological study. J Prev Med Public Heal. 2020;53(4):220–7. doi: 10.3961/jpmph.20.256 Revista Repertorio de Medicina y Cirugía - 2022 http://purl.org/coar/resource_type/c_2df8fbb1 Text http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess http://purl.org/coar/version/c_970fb48d4fbd8a85 info:eu-repo/semantics/publishedVersion http://purl.org/redcol/resource_type/ART http://purl.org/coar/resource_type/c_6501 Al-Rasheed M. Protective Behavior against COVID-19 among the Public in Kuwait: An Examination of the Protection Motivation Theory, Trust in Government, and Sociodemographic Factors. Soc Work Public Health [Internet]. 2020;35(7):546–56. https://doi.org/10.1080/19371918.2020.1806171 info:eu-repo/semantics/article McNeely CL, Schintler LA, Stabile B. Social Determinants and COVID-19 Disparities: Differential Pandemic Effects and Dynamics. World Med Heal Policy. 2020;12(3):206–17. https://doi.org/10.1002/wmh3.370 Owens MR, Brito-silva F, Kirkland T, Moore CE, Davis KE, Patterson MA, et al. Prevalence and Social Determinants of Food Insecurity among College Students during the COVID-19 Pandemic. Nutrients. 2020;12(9):2515. doi: 10.3390/nu12092515 Rivera-Izquierdo M, Valero-Ubierna del MC, R-delamo JL, Fernández-García MA, Martínez-Diz S, Tahery-Mahmoud A, Rodríguez-Camacho M, et al. Sociodemographic, clinical and laboratory factors on admission associated with COVID-19 mortality in hospitalized patients: A retrospective observational study. PLoS One. 2020;15(6): e0235107. https://doi.org/10.1371/journal.pone.0235107 Hassan MM, Kalam MA, Shano S, Nayem MRK, Rahman MK, Khan SA, et al. Assessment of Epidemiological Determinants of COVID-19 Pandemic Related to Social and Economic Factors Globally. J Risk Financ Manag. 2020;13(9):194. https://doi.org/10.3390/jrfm13090194 Brouard S, Vasilopoulos P, Becher M. Sociodemographic and psychological correlates of compliance with the Covid-19 public health measures in France. Can J Polit Sci. 2020;53(2):253–8. doi: 10.1017/S0008423920000335 Zhu Z, Xu S, Wang H, Liu Z, Wu J, Li G, et al. COVID-19 in Wuhan: Sociodemographic characteristics and hospital support measures associated with the immediate psychological impact on healthcare workers. EClinicalMedicine. 2020;24:100443. doi: 10.1016/j.eclinm.2020.100443 World Health Organization (WHO). Novel Coronavirus situation report 7 ( 2019-nCoV ). World Health Organization; 2020. https://creativecommons.org/licenses/by-nc-sa/4.0/ text/html Introducción: en diciembre de 2019 la Comisión Municipal de Salud y Sanidad de Wuhan, China, reportó 27 casos de neumonía de causa desconocida llegando a Colombia. Los municipios implementaron estrategias para minimizar contagios como lo hizo Mosquera, Cundinamarca, sin embargo no se conoció la caracterización de la población afectada por COVID-19. Objetivo: analizar las condiciones de vulnerabilidad, sociodemográficas y clínicas de la población con COVID-19 incluida en la estrategia de atención primaria en salud. Metodología: estudio cuantitativo, observacional, de corte transversal, retrospectivo, con análisis de condiciones de vulnerabilidad, características sociodemográficas y clínicas de la población diagnosticada con COVID-19 del municipio de Mosquera en la época de la pandemia durante el año 2020. Resultados: 4.610 casos positivos para COVID-19, 99% en la zona urbana, edad 5% entre 0-11 años, 4% entre 12-17 años, 21% entre 18-28 años, 59% entre 29-59 años y 12% más de 60 años. La población más afectada fueron adultos 58%, régimen contributivo 82% y mujeres 56%. Del total 73% fue sintomático, 92% no requirió hospitalización y la mayoría de los positivos tuvieron entre 2 a 3 contactos estrechos (29%), de los cuales 82% fue asintomático. Conclusiones: la pandemia por COVID-19 ha tenido impactos negativos desproporcionados en poblaciones desfavorecidas y desatendidas en todo el mundo. La desigualdad y los determinantes sociales relacionados que afectan a ciertos grupos, están en relación directamente con los resultados de salud adversos de las poblaciones vulnerables durante la pandemia. López Guzmán, Yudy Carolina Barros Castillo, Sabrina María Leal Betancourt, Michell Ignacio Restrepo Guerrero, Héctor Fabio Tellez Romero, Martha Patricia determinantes sociales COVID-19 estrategia de atención primaria en salud 31 , Año 2022 : Suplemento COVID-19 application/pdf Artículo de revista application/epub+zip Sociedad de Cirugía de Bogotá, Hospital de San José y Fundación Universitaria de Ciencias de la Salud Español https://revistas.fucsalud.edu.co/index.php/repertorio/article/view/1335 text/xml Revista Repertorio de Medicina y Cirugía Publication audio/mpeg primary health care strategy COVID-19 social determinants Journal article Introduction: as of December 2019, the Municipal Health Commission of Wuhan, China, reported 27 cases of pneumonia of unknown etiology coming to Colombia. The municipalities implemented strategies to minimize contagions as did Mosquera, Cundinamarca. However, information describing the characteristics of the COVID-19 affected population was limited. Objective: to analyze the vulnerability, sociodemographic and clinical conditions of the population with COVID-19 included in the primary health care strategy. Methodology: quantitative, observational, cross-sectional, retrospective study, analyzing the vulnerability, sociodemographic and clinical conditions of COVID-19 confirmed cases reported in the municipality of Mosquera during the 2020 phase of the pandemic. Results: 4,610 COVID-19 positive cases were included, of which 99% lived in the urban area. Five percent were between 0 -11 years old, 4% between 12 -17, 21% between 18-28, 59% between 29-59 and 12% over 60. The most affected populations were adults (58%), people covered by the contributory health regime (82%) and women (56%). Of the total number of participants, 73% were symptomatic, 92% did not require hospital admission and most of the positive cases reported 2 to 3 close contacts (29%), of which 82% were asymptomatic. Conclusions: the COVID-19 pandemic has had disproportionate negative impacts on disadvantaged and underserved populations worldwide. Inequality and social determinants affecting certain groups are directly related to adverse health outcomes among vulnerable populations during the pandemic. Vulnerability, socio-demographic and clinical conditions of the Covid 19 affected population included in the 2020 primary health care strategy of the municipality of Mosquera 2022-04-05T00:00:00Z 51 2022-04-05 https://doi.org/10.31260/RepertMedCir.01217372.1335 10.31260/RepertMedCir.01217372.1335 https://revistas.fucsalud.edu.co/index.php/repertorio/article/download/1335/2082 2462-991X 0121-7372 40 https://revistas.fucsalud.edu.co/index.php/repertorio/article/download/1335/2095 https://revistas.fucsalud.edu.co/index.php/repertorio/article/download/1335/2080 2022-04-05T00:00:00Z https://revistas.fucsalud.edu.co/index.php/repertorio/article/download/1335/2078 https://revistas.fucsalud.edu.co/index.php/repertorio/article/download/1335/2079 |
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FUNDACIÓN UNIVERSITARIA DE CIENCIA DE LA SALUD |
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Colombia |
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Revista Repertorio de Medicina y Cirugía |
| title |
Condiciones de vulnerabilidad, sociodemográficas y clínicas de la población diagnosticada con COVID-19 incluida en la estrategia de atención primaria en salud del municipio de Mosquera 2020 |
| spellingShingle |
Condiciones de vulnerabilidad, sociodemográficas y clínicas de la población diagnosticada con COVID-19 incluida en la estrategia de atención primaria en salud del municipio de Mosquera 2020 López Guzmán, Yudy Carolina Barros Castillo, Sabrina María Leal Betancourt, Michell Ignacio Restrepo Guerrero, Héctor Fabio Tellez Romero, Martha Patricia determinantes sociales COVID-19 estrategia de atención primaria en salud primary health care strategy COVID-19 social determinants |
| title_short |
Condiciones de vulnerabilidad, sociodemográficas y clínicas de la población diagnosticada con COVID-19 incluida en la estrategia de atención primaria en salud del municipio de Mosquera 2020 |
| title_full |
Condiciones de vulnerabilidad, sociodemográficas y clínicas de la población diagnosticada con COVID-19 incluida en la estrategia de atención primaria en salud del municipio de Mosquera 2020 |
| title_fullStr |
Condiciones de vulnerabilidad, sociodemográficas y clínicas de la población diagnosticada con COVID-19 incluida en la estrategia de atención primaria en salud del municipio de Mosquera 2020 |
| title_full_unstemmed |
Condiciones de vulnerabilidad, sociodemográficas y clínicas de la población diagnosticada con COVID-19 incluida en la estrategia de atención primaria en salud del municipio de Mosquera 2020 |
| title_sort |
condiciones de vulnerabilidad, sociodemográficas y clínicas de la población diagnosticada con covid-19 incluida en la estrategia de atención primaria en salud del municipio de mosquera 2020 |
| title_eng |
Vulnerability, socio-demographic and clinical conditions of the Covid 19 affected population included in the 2020 primary health care strategy of the municipality of Mosquera |
| description |
Introducción: en diciembre de 2019 la Comisión Municipal de Salud y Sanidad de Wuhan, China, reportó 27 casos de neumonía de causa desconocida llegando a Colombia. Los municipios implementaron estrategias para minimizar contagios como lo hizo Mosquera, Cundinamarca, sin embargo no se conoció la caracterización de la población afectada por COVID-19. Objetivo: analizar las condiciones de vulnerabilidad, sociodemográficas y clínicas de la población con COVID-19 incluida en la estrategia de atención primaria en salud. Metodología: estudio cuantitativo, observacional, de corte transversal, retrospectivo, con análisis de condiciones de vulnerabilidad, características sociodemográficas y clínicas de la población diagnosticada con COVID-19 del municipio de Mosquera en la época de la pandemia durante el año 2020. Resultados: 4.610 casos positivos para COVID-19, 99% en la zona urbana, edad 5% entre 0-11 años, 4% entre 12-17 años, 21% entre 18-28 años, 59% entre 29-59 años y 12% más de 60 años. La población más afectada fueron adultos 58%, régimen contributivo 82% y mujeres 56%. Del total 73% fue sintomático, 92% no requirió hospitalización y la mayoría de los positivos tuvieron entre 2 a 3 contactos estrechos (29%), de los cuales 82% fue asintomático. Conclusiones: la pandemia por COVID-19 ha tenido impactos negativos desproporcionados en poblaciones desfavorecidas y desatendidas en todo el mundo. La desigualdad y los determinantes sociales relacionados que afectan a ciertos grupos, están en relación directamente con los resultados de salud adversos de las poblaciones vulnerables durante la pandemia.
|
| description_eng |
Introduction: as of December 2019, the Municipal Health Commission of Wuhan, China, reported 27 cases of pneumonia of unknown etiology coming to Colombia. The municipalities implemented strategies to minimize contagions as did Mosquera, Cundinamarca. However, information describing the characteristics of the COVID-19 affected population was limited. Objective: to analyze the vulnerability, sociodemographic and clinical conditions of the population with COVID-19 included in the primary health care strategy. Methodology: quantitative, observational, cross-sectional, retrospective study, analyzing the vulnerability, sociodemographic and clinical conditions of COVID-19 confirmed cases reported in the municipality of Mosquera during the 2020 phase of the pandemic. Results: 4,610 COVID-19 positive cases were included, of which 99% lived in the urban area. Five percent were between 0 -11 years old, 4% between 12 -17, 21% between 18-28, 59% between 29-59 and 12% over 60. The most affected populations were adults (58%), people covered by the contributory health regime (82%) and women (56%). Of the total number of participants, 73% were symptomatic, 92% did not require hospital admission and most of the positive cases reported 2 to 3 close contacts (29%), of which 82% were asymptomatic. Conclusions: the COVID-19 pandemic has had disproportionate negative impacts on disadvantaged and underserved populations worldwide. Inequality and social determinants affecting certain groups are directly related to adverse health outcomes among vulnerable populations during the pandemic.
|
| author |
López Guzmán, Yudy Carolina Barros Castillo, Sabrina María Leal Betancourt, Michell Ignacio Restrepo Guerrero, Héctor Fabio Tellez Romero, Martha Patricia |
| author_facet |
López Guzmán, Yudy Carolina Barros Castillo, Sabrina María Leal Betancourt, Michell Ignacio Restrepo Guerrero, Héctor Fabio Tellez Romero, Martha Patricia |
| topicspa_str_mv |
determinantes sociales COVID-19 estrategia de atención primaria en salud |
| topic |
determinantes sociales COVID-19 estrategia de atención primaria en salud primary health care strategy COVID-19 social determinants |
| topic_facet |
determinantes sociales COVID-19 estrategia de atención primaria en salud primary health care strategy COVID-19 social determinants |
| citationvolume |
31 |
| citationedition |
, Año 2022 : Suplemento COVID-19 |
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Sociedad de Cirugía de Bogotá, Hospital de San José y Fundación Universitaria de Ciencias de la Salud |
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Revista Repertorio de Medicina y Cirugía |
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https://revistas.fucsalud.edu.co/index.php/repertorio/article/view/1335 |
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Español |
| format |
Article |
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Revista Repertorio de Medicina y Cirugía - 2022 http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/4.0/ |
| references |
Cieza Zevallos J, Uriol Lescano C. Letalidad y la mortalidad de Covid 19 en 60 países afectados y su impacto en los aspectos demográficos, económicos y de salud. Rev Medica Hered. 2021;31(4):214–21. http://dx.doi.org/10.20453/rmh.v31i4.3852 Ramírez IJ, Lee J. COVID-19 emergence and social and health determinants in Colorado: A rapid spatial analysis. Int J Environ Res Public Health. 2020;17(11):1–15. doi: 10.3390/ijerph1711385 Muscillo A, Pin P, Razzolini T. Spreading of an infectious disease between different locations. J Econ Behav Organ. 2021;183:508–32. https://doi.org/10.1016/j.jebo.2021.01.004 Mendolia S, Stavrunova O, Yerokhin O. Determinants of the community mobility during the COVID-19 epidemic: The role of government regulations and information. J Econ Behav Organ. 2021;184:199–231. https://doi.org/10.1016/j.jebo.2021.01.023 McCarthy CP, Murphy S, Jones-O’Connor M, Olshan DS, Khambhati JR, Rehman S, et al. Early clinical and sociodemographic experience with patients hospitalized with COVID-19 at a large American healthcare system. EClinicalMedicine. 2020;26:100504. https://doi.org/10.1016/j.eclinm.2020.100504 Harlem G. Descriptive analysis of social determinant factors in urban communities affected by COVID-19. J Public Heal (United Kingdom). 2020;42(3):466–9. https://doi.org/10.1093/pubmed/fdaa078 Witteveen D. Sociodemographic inequality in exposure to COVID-19-induced economic hardship in the United Kingdom. Res Soc Stratif Mobil. 2020;69:100551. https://doi.org/10.1016/j.rssm.2020.100551 Chan Yang EY, Huang Z, Kai Lo ES, Ching Hung KK, Wong ELY, Wong SYS. Sociodemographic predictors of health risk perception, attitude and behavior practices associated with health-emergency disaster risk management for biological hazards: The case of COVID-19 pandemic in Hong Kong, SAR China. Int J Environ Res Public Health. 2020;17(11): :3869. doi: 10.3390/ijerph17113869 Benatar S. The most powerful healt-promoting forces in COVID-19 are social. S Afr J Sci. 2020;116(7-8):148–62. https://hdl.handle.net/10520/EJC-1f60b9dc0c Becerra-García JA, Giménez Ballesta G, Sánchez-Gutiérrez T, Barbeito Resa S, Calvo Calvo A. [Psychopathological symptoms during Covid-19 quarantine in spanish general population: a preliminary analysis based on sociodemographic and occupational-contextual factors.]. Rev Esp Salud Publica. 2020;94:e202006059 Presidencia de la República. (2020, 25 de agosto) Decreto 1168. Por el cual se imparten instrucciones en virtud de la emergencia sanitaria generada por la pandemia del Coronavirus covid–19, y el mantenimiento del orden público y se decreta el aislamiento selective con distanciamiento individual responsable. (Diario Oficial 51362 de 2020). Ministerio de la protección Social. El Coronavirus en Colombia [Internet]. 2021 [cited 2021 Sep 16]. Available from: https://coronaviruscolombia.gov.co/Covid19/index.html Kahlout AM, ALhubidi K, AlMesaifri MA, AL Mansour T, Khudadad H. The prevalence of COVID 19 among PHCC workers and its relation to place of works and medical comorbidities. World Fam Med. 2021;19(4):84–104. Organización Mundial de la Salud, Organización Panamericana de Salud. Actualización Epidemiológica: Nuevo coronavirus (Covid-19). Organ Mund la Salud. 2020. Arora P, Mittal H, Gupta N, Jimmy JK, Jain K, Sharma A. Sociodemographic Factors and Clinical Profile of Covid-19 Patients Admitted in a Tertiary Care Centre of Central Rajasthan, India. J Evid Based Med Healthc. 2021;8(13):773–7. doi: 10.18410/jebmh/2021/152 Li L, Hang D, Dong H, Yuan-Yuan C, Bo-Heng L, Ze-Lin Y, et al. Temporal dynamic in the impact of COVID− 19 outbreak on cause-specific mortality in Guangzhou, China. BMC Public Health. 2021;21(1):1–11. https://doi.org/10.1186/s12889-021-10771-3 Hawkins D. Social determinants of covid-19 in massachusetts, United States: An ecological study. J Prev Med Public Heal. 2020;53(4):220–7. doi: 10.3961/jpmph.20.256 Al-Rasheed M. Protective Behavior against COVID-19 among the Public in Kuwait: An Examination of the Protection Motivation Theory, Trust in Government, and Sociodemographic Factors. Soc Work Public Health [Internet]. 2020;35(7):546–56. https://doi.org/10.1080/19371918.2020.1806171 McNeely CL, Schintler LA, Stabile B. Social Determinants and COVID-19 Disparities: Differential Pandemic Effects and Dynamics. World Med Heal Policy. 2020;12(3):206–17. https://doi.org/10.1002/wmh3.370 Owens MR, Brito-silva F, Kirkland T, Moore CE, Davis KE, Patterson MA, et al. Prevalence and Social Determinants of Food Insecurity among College Students during the COVID-19 Pandemic. Nutrients. 2020;12(9):2515. doi: 10.3390/nu12092515 Rivera-Izquierdo M, Valero-Ubierna del MC, R-delamo JL, Fernández-García MA, Martínez-Diz S, Tahery-Mahmoud A, Rodríguez-Camacho M, et al. Sociodemographic, clinical and laboratory factors on admission associated with COVID-19 mortality in hospitalized patients: A retrospective observational study. PLoS One. 2020;15(6): e0235107. https://doi.org/10.1371/journal.pone.0235107 Hassan MM, Kalam MA, Shano S, Nayem MRK, Rahman MK, Khan SA, et al. Assessment of Epidemiological Determinants of COVID-19 Pandemic Related to Social and Economic Factors Globally. J Risk Financ Manag. 2020;13(9):194. https://doi.org/10.3390/jrfm13090194 Brouard S, Vasilopoulos P, Becher M. Sociodemographic and psychological correlates of compliance with the Covid-19 public health measures in France. Can J Polit Sci. 2020;53(2):253–8. doi: 10.1017/S0008423920000335 Zhu Z, Xu S, Wang H, Liu Z, Wu J, Li G, et al. COVID-19 in Wuhan: Sociodemographic characteristics and hospital support measures associated with the immediate psychological impact on healthcare workers. EClinicalMedicine. 2020;24:100443. doi: 10.1016/j.eclinm.2020.100443 World Health Organization (WHO). Novel Coronavirus situation report 7 ( 2019-nCoV ). World Health Organization; 2020. |
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