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Sifuentes-Osornio J, Angulo-Guerrero O, De Anda-Jáuregui G, Díaz-De-León-Santiago JL, Hernández-Lemus E, Benítez-Pérez H, Herrera LA, López-Arellano O, Revuelta-Herrera A, Rosales-Tapia AR, Suárez-Lastra M, Kershenobich D, Ruiz-Gutiérrez R. Probability of hospitalisation and death among COVID-19 patients with comorbidity during outbreaks occurring in Mexico City. J Glob Health 2022; 12:05038. [DOI: 10.7189/jogh.12.05038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Affiliation(s)
- José Sifuentes-Osornio
- Departamento de Medicina, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Ofelia Angulo-Guerrero
- Secretaría de Educación, Ciencia, Tecnología e Innovación, Gobierno de la Ciudad de México, Mexico City, Mexico
| | - Guillermo De Anda-Jáuregui
- Computational Genomics Division, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | | | - Enrique Hernández-Lemus
- Computational Genomics Division, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Héctor Benítez-Pérez
- Dirección General de Cómputo y de Tecnologías de Información y Comunicación, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Luis A Herrera
- Computational Genomics Division, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
- Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Oliva López-Arellano
- Secretaría de Educación, Ciencia, Tecnología e Innovación, Gobierno de la Ciudad de México, Mexico City, Mexico
| | - Arturo Revuelta-Herrera
- Dirección General de Cómputo y de Tecnologías de Información y Comunicación, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Ana R Rosales-Tapia
- Instituto de Geografía, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Manuel Suárez-Lastra
- Instituto de Geografía, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - David Kershenobich
- Departamento de Medicina, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Rosaura Ruiz-Gutiérrez
- Secretaría de Educación, Ciencia, Tecnología e Innovación, Gobierno de la Ciudad de México, Mexico City, Mexico
- Facultad de Ciencias, Universidad Nacional Autónoma de México, Mexico City, Mexico
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Covantes-Rosales CE, Barajas-Carrillo VW, Girón-Pérez DA, Toledo-Ibarra GA, Díaz-Reséndiz KJG, Navidad-Murrieta MS, Ventura-Ramón GH, Pulido-Muñoz ME, Mercado-Salgado U, Ojeda-Durán AJ, Argüero-Fonseca A, Girón-Pérez MI. Comparative Analysis of Age, Sex, and Viral Load in Outpatients during the Four Waves of SARS-CoV-2 in A Mexican Medium-Sized City. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:5719. [PMID: 35565114 PMCID: PMC9104031 DOI: 10.3390/ijerph19095719] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/02/2022] [Accepted: 05/06/2022] [Indexed: 12/20/2022]
Abstract
Governments have implemented measures to minimize SARS-CoV-2 spread. However, these measures were relaxed, and the appearance of new variants has prompted periods of high contagion known as waves. In Mexico, four waves distributed between July and August 2020, January and February 2021, August and September 2021, and January and February 2022 have appeared. Current health policies discourage mass sampling, preferring to focus on the corrective treatment of severe cases. Outpatients are only advised to undergo brief voluntary confinement and symptomatic treatment, with no follow-up. Therefore, the present study aimed to analyze sex, age, and viral load in outpatients during the four waves in a medium-sized city in Mexico. For each wave, the date of peak contagion was identified, and data were collected within ±15 days. In this regard, data from 916 patients (434 men and 482 women) were analyzed. The age range of positive patients (37-45 years) presented a higher frequency during the first and third waves, while 28-36 years was the most frequent age range during the second and fourth waves, while the viral load values were significantly higher, for both sexes, during the fourth wave. Obtained data of COVID-19 prevalence in population segments can be used for decision-making in the design of effective public health policies.
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Affiliation(s)
- Carlos Eduardo Covantes-Rosales
- Laboratorio Nacional de Investigación Para la Inocuidad Alimentaria (LANIIA) Unidad Nayarit, Universidad Autónoma de Nayarit, Tepic 63000, Nayarit, Mexico; (C.E.C.-R.); (V.W.B.-C.); (D.A.G.-P.); (G.A.T.-I.); (K.J.G.D.-R.); (M.S.N.-M.); (G.H.V.-R.); (M.E.P.-M.); (U.M.-S.); (A.J.O.-D.)
| | - Victor Wagner Barajas-Carrillo
- Laboratorio Nacional de Investigación Para la Inocuidad Alimentaria (LANIIA) Unidad Nayarit, Universidad Autónoma de Nayarit, Tepic 63000, Nayarit, Mexico; (C.E.C.-R.); (V.W.B.-C.); (D.A.G.-P.); (G.A.T.-I.); (K.J.G.D.-R.); (M.S.N.-M.); (G.H.V.-R.); (M.E.P.-M.); (U.M.-S.); (A.J.O.-D.)
| | - Daniel Alberto Girón-Pérez
- Laboratorio Nacional de Investigación Para la Inocuidad Alimentaria (LANIIA) Unidad Nayarit, Universidad Autónoma de Nayarit, Tepic 63000, Nayarit, Mexico; (C.E.C.-R.); (V.W.B.-C.); (D.A.G.-P.); (G.A.T.-I.); (K.J.G.D.-R.); (M.S.N.-M.); (G.H.V.-R.); (M.E.P.-M.); (U.M.-S.); (A.J.O.-D.)
| | - Gladys Alejandra Toledo-Ibarra
- Laboratorio Nacional de Investigación Para la Inocuidad Alimentaria (LANIIA) Unidad Nayarit, Universidad Autónoma de Nayarit, Tepic 63000, Nayarit, Mexico; (C.E.C.-R.); (V.W.B.-C.); (D.A.G.-P.); (G.A.T.-I.); (K.J.G.D.-R.); (M.S.N.-M.); (G.H.V.-R.); (M.E.P.-M.); (U.M.-S.); (A.J.O.-D.)
| | - Karina Janice Guadalupe Díaz-Reséndiz
- Laboratorio Nacional de Investigación Para la Inocuidad Alimentaria (LANIIA) Unidad Nayarit, Universidad Autónoma de Nayarit, Tepic 63000, Nayarit, Mexico; (C.E.C.-R.); (V.W.B.-C.); (D.A.G.-P.); (G.A.T.-I.); (K.J.G.D.-R.); (M.S.N.-M.); (G.H.V.-R.); (M.E.P.-M.); (U.M.-S.); (A.J.O.-D.)
| | - Migdalia Sarahy Navidad-Murrieta
- Laboratorio Nacional de Investigación Para la Inocuidad Alimentaria (LANIIA) Unidad Nayarit, Universidad Autónoma de Nayarit, Tepic 63000, Nayarit, Mexico; (C.E.C.-R.); (V.W.B.-C.); (D.A.G.-P.); (G.A.T.-I.); (K.J.G.D.-R.); (M.S.N.-M.); (G.H.V.-R.); (M.E.P.-M.); (U.M.-S.); (A.J.O.-D.)
| | - Guadalupe Herminia Ventura-Ramón
- Laboratorio Nacional de Investigación Para la Inocuidad Alimentaria (LANIIA) Unidad Nayarit, Universidad Autónoma de Nayarit, Tepic 63000, Nayarit, Mexico; (C.E.C.-R.); (V.W.B.-C.); (D.A.G.-P.); (G.A.T.-I.); (K.J.G.D.-R.); (M.S.N.-M.); (G.H.V.-R.); (M.E.P.-M.); (U.M.-S.); (A.J.O.-D.)
| | - Mirtha Elena Pulido-Muñoz
- Laboratorio Nacional de Investigación Para la Inocuidad Alimentaria (LANIIA) Unidad Nayarit, Universidad Autónoma de Nayarit, Tepic 63000, Nayarit, Mexico; (C.E.C.-R.); (V.W.B.-C.); (D.A.G.-P.); (G.A.T.-I.); (K.J.G.D.-R.); (M.S.N.-M.); (G.H.V.-R.); (M.E.P.-M.); (U.M.-S.); (A.J.O.-D.)
| | - Ulises Mercado-Salgado
- Laboratorio Nacional de Investigación Para la Inocuidad Alimentaria (LANIIA) Unidad Nayarit, Universidad Autónoma de Nayarit, Tepic 63000, Nayarit, Mexico; (C.E.C.-R.); (V.W.B.-C.); (D.A.G.-P.); (G.A.T.-I.); (K.J.G.D.-R.); (M.S.N.-M.); (G.H.V.-R.); (M.E.P.-M.); (U.M.-S.); (A.J.O.-D.)
| | - Ansonny Jhovanny Ojeda-Durán
- Laboratorio Nacional de Investigación Para la Inocuidad Alimentaria (LANIIA) Unidad Nayarit, Universidad Autónoma de Nayarit, Tepic 63000, Nayarit, Mexico; (C.E.C.-R.); (V.W.B.-C.); (D.A.G.-P.); (G.A.T.-I.); (K.J.G.D.-R.); (M.S.N.-M.); (G.H.V.-R.); (M.E.P.-M.); (U.M.-S.); (A.J.O.-D.)
| | - Aimée Argüero-Fonseca
- Laboratorio de Psicofisiología y Conducta, Unidad Académica de Ciencias Sociales, Universidad Autónoma de Nayarit, Tepic 63000, Nayarit, Mexico;
| | - Manuel Iván Girón-Pérez
- Laboratorio Nacional de Investigación Para la Inocuidad Alimentaria (LANIIA) Unidad Nayarit, Universidad Autónoma de Nayarit, Tepic 63000, Nayarit, Mexico; (C.E.C.-R.); (V.W.B.-C.); (D.A.G.-P.); (G.A.T.-I.); (K.J.G.D.-R.); (M.S.N.-M.); (G.H.V.-R.); (M.E.P.-M.); (U.M.-S.); (A.J.O.-D.)
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Fowler Davis S, Choppin S, Kelly S. Towards an Understanding of Population Health Data in a Single NHS Trust during COVID-19. Healthcare (Basel) 2022; 10:healthcare10030447. [PMID: 35326925 PMCID: PMC8953481 DOI: 10.3390/healthcare10030447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 02/20/2022] [Accepted: 02/24/2022] [Indexed: 11/30/2022] Open
Abstract
The objective of this study was to determine the further care needs of people discharged from the hospital following a COVID-19 illness from April–September 2020. Methods: In partnership with an NHS trust in the UK, data analysis was undertaken by linking data from the Trust, to facilitated a triage process. The intention was to provide information in a format that enabled an examination of the population data and highlight any inequality in provision. Data were mapped onto the indices of multiple deprivation, and a range of text and graphical methods were used to represent the population data to the hospital leadership. The visual representation of the demographics and deprivation of people discharged during a critical period of the pandemic was intended to support planning for community services. The results demonstrated that just under half of those discharged were from the poorest fifth of the English population and that just under half were aged 75 or older. This reflected the disproportional effect of COVID-19 on those who were poorer, older or had pre-existing multiple morbidities. Referral to community or outpatient services was informed by the analysis, and further understanding of the diversity of the population health was established in the Trust. Conclusion: By identifying the population and mapping to the IMD, it was possible to show that over half of discharged patients were from deprived communities, and there was significant organisational learning bout using data to identify inequalities.. The challenge of planning services that target underserved communities remains an important issue following the pandemic, and lessons learnt from one health system are being shared.
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