Salud digital y Covid-19 en los países BRICS: análisis bibliométrico
DOI:
https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1369Palabras clave:
Países en Desarrollo, Tecnología Biomédica, COVID-19Resumen
Objetivo: analizar el estado del arte en cuanto a las soluciones de salud digital para hacer frente a la Covid-19 desarrolladas e implementadas por los países del BRICS. Método: análisis bibliométrico basado en una revisión de alcance realizada en las bases de datos Medline/Pubmed, Lilacs, Scopus y Web of Science en agosto de 2022. Resultados: se incluyeron 430 registros que presentaban soluciones digitales en uno de los países del BRICS, centrándose en la vigilancia, prevención/control o manejo clínico de la Covid-19. China e India, junto con investigadores de estos países, destacaron en términos de número de publicaciones. Fue relevante el uso de inteligencia artificial para prever la evolución de la pandemia, orientar medidas gubernamentales y apoyar el diagnóstico. Conclusión: se confirma la tendencia de liderazgo chino e indio y se aboga por la colaboración para aprovechar la salud digital en los demás países del grupo.
Citas
Kalhori SRN, Bahaadinbeigy K, Deldar K, Gholamzadeh M, Hajesmaeel-Gohari S, Ayyoubzadeh S. Digital Health Solutions to Control the COVID-19 Pandemic in Countries With High Disease Prevalence: Literature Review. J Med Internet Res. 2021;23(3):e19473. DOI: https://doi.org/10.2196/19473
World Health Organization. WHO guideline: recommendations on digital interventions for health system strengthening. Recommendations and justification. Geneva: World Health Organization; 2019.
Topol EJ. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again (English Edition). New York: Basic Books; 2019.
Senanayake B, Tyagi N, Zhou X, Edirippulige S. Workforce readiness and digital health integration. In Sandhu K, editors. Opportunities and challenges in digital healthcare innovation. Hershey: IGI Global; 2020. DOI: https://doi.org/10.4018/978-1-7998-3274-4.ch010
Costa CA. Saúde Digital e a Revolução na Medicina. J. Health Inform. 2023;15(2):1. DOI: https://doi.org/10.59681/2175-4411.v15.i2.2023.1132
Lobato LVC. The social issue in the BRICS Project. Cien Saude Colet. 2018;23(7):2133-2146. DOI: https://doi.org/10.1590/1413-81232018237.09072018
Moore C. BRICS and Global Health Diplomacy in the Covid-19 Pandemic: Situating BRICS’ diplomacy within the prevailing global health governance context. Rev Bras Polít Int. 2022;65(2):e022. DOI: https://doi.org/10.1590/0034-7329202200222
Francombe J, Ali GC, Gloinson ER, Feijao C, Morley KI, Gunashekar S, et al. Assessing the Implementation of Digital Innovations in Response to the COVID-19 Pandemic to Address Key Public Health Functions: Scoping Review of Academic and Non academic Literature. JMIR Public Health Surveill. 2022;8(7):e34605. DOI: https://doi.org/10.2196/34605
Sust PP, Solans O, Fajardo JC, Peralta MM, Rodenas P, Gabalda J, et al. Turning the Crisis Into an Opportunity: Digital Health Strategies Deployed During the COVID-19 Outbreak. JMIR Public Health Surveill. 2020;6(2): e19106. DOI: https://doi.org/10.2196/19106
Labrique AB, Wadhwani C, Williams KA, Lamptey P, Hesp C, Luk R, et al. Best practices in scaling digital health in low and middle income countries. Globalization and Health. 2018; 14(103). DOI: https://doi.org/10.1186/s12992-018-0424-z
Mitgang EA, Blaya JA, Chopra M. Digital Health in Response to COVID-19 in Low- and Middle-income Countries: Opportunities. and Challenges. Global Policy. 2021;12(suppl.6):107-109. DOI: https://doi.org/10.1111/1758-5899.12880
Tapera R, Singh YA. A bibliometric analysis of medical informatics and telemedicine in sub-Saharan Africa and BRICS nations. J Public Health Res. 2021;10(3):1903. DOI: https://doi.org/10.4081/jphr.2021.1903
Dong J, Wu H, Zhou D, Li K, Zhang Y, Ji H, et al. Application of Big Data and Artificial Intelligence in COVID-19 Prevention, Diagnosis, Treatment and Management Decisions in China. J Med Syst. 2021;45(9):84. DOI: https://doi.org/10.1007/s10916-021-01757-0
Bassi A, Arfin S, John O, Jha V. An overview of mobile applications (apps) to support the coronavirus disease 2019 response in India. Indian J Med Res. 2020;151(5):468-473. DOI: https://doi.org/10.4103/ijmr.IJMR_1200_20
Caetano R, Silva AB, Guedes ACCM, Paiva CCN, Ribeiro GR, Santos DL, et al. Challenges and opportunities for telehealth during the COVID-19 pandemic: ideas on spaces and initiatives in the Brazilian context. Cad Saude Publica. 2020; 36(5):e00088920 DOI: https://doi.org/10.1590/0102-311x00088920
The Joanna Briggs Institute. Joanna Briggs Institute Reviewers’ Manual: Methodology for JBI Scoping Reviews. Australia: The Joanna Briggs Institute, 2015.
Tricco AC, Lillie E, Zarin W, O'Brien KK, Colquhoun H, Levac D, et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med. 2018;169(7):467–73. DOI: https://doi.org/10.7326/M18-0850
World Health Organization. Classification of digital interventions, services and applications in health: a shared language to describe the uses of digital technology for health, second edition. Geneva: World Health Organization; 2023.
Shastri S, Singh K, Deswal M, Kumar S, Mansotra V. CoBiD-net: a tailored deep learning ensemble model for time series forecasting of covid-19. Spat Inf Res. 2022;30:9-22. DOI: https://doi.org/10.1007/s41324-021-00408-3
Kumar S, Shastri S, Mahajan S, Singh K, Gupta S, Rani R, et al. LiteCovidNet: A lightweight deep neural network model for detection of COVID-19 using X-ray images. Int J Imaging Syst Technol. 2022;32(5):1464-1480. DOI: https://doi.org/10.1002/ima.22770
Yang Q, Xu H, Tang X, Hu C, Wang P, Xiáng Y, et al. Medical Imaging Engineering and Technology Branch of the Chinese Society of Biomedical Engineering expert consensus on the application of Emergency Mobile Cabin CT. Quant Imaging Med Surg. 2020;10(11):2191-2207. DOI: https://doi.org/10.21037/qims-20-980
Yang Z, Zeng Z, Wang K, Wong SS, Liang W, Zanin M, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions. J Thorac Dis. 2020;12(3):165-174. DOI: https://doi.org/10.21037/jtd.2020.02.64
Yang Z, Zeng Z, Wang K, Zhong N, He J. Scientific guidance to fight the pandemic: the Coronavirus Disease 2019 (COVID-19). J Thorac Dis. 2021;13(2):505-510. DOI: https://doi.org/10.21037/jtd-2021-02
Li SQ, Guo WL, Liu H, Wang T, Zhou YY, Yu T, et al. Clinical application of an intelligent oropharyngeal swab robot: implication for the COVID-19 pandemic. Eur Respir J. 2020;56(2):2001912. DOI: https://doi.org/10.1183/13993003.01912-2020
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
La sumisión de un artículo a el Journal of Health Informatics es entendida como exclusiva y que no esta siendo considerado para publicación en otro periódico. La permisión de los autores para la publicación de su artículo en lo JHI implica en la exclusiva autorización concedida a los editores para su inclusión en la revista. Al someter un artículo, a lo autor será solicitada la permisión electrónica de una Nota de Copyright. Una mensaje electrónica será enviada a lo autor correspondiente confirmando el recibo del manuscrito y lo aceite de la Nota de Copyright.
