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Setting research priorities for global pandemic preparedness: An international consensus and comparison with ChatGPT's output
P. Song, D. Adeloye, Y. Acharya, DA. Bojude, S. Ali, R. Alibudbud, S. Bastien, F. Becerra-Posada, M. Berecki, A. Bodomo, F. Borrescio-Higa, M. Buchtova, H. Campbell, KY. Chan, S. Cheema, M. Chopra, DA. Cipta, LD. Castro, K. Ganasegeran, T. Gebre,...
Jazyk angličtina
Typ dokumentu časopisecké články
NLK
Directory of Open Access Journals
od 2011
Free Medical Journals
od 2011
PubMed Central
od 2011
Europe PubMed Central
od 2011
ProQuest Central
od 2015-01-01
Open Access Digital Library
od 2011-01-01
Open Access Digital Library
od 2011-01-01
CINAHL Plus with Full Text (EBSCOhost)
od 2013-06-01
Health & Medicine (ProQuest)
od 2015-01-01
ROAD: Directory of Open Access Scholarly Resources
od 2011
PubMed
38386716
DOI
10.7189/jogh.14.04054
Knihovny.cz E-zdroje
- MeSH
- COVID-19 * epidemiologie prevence a kontrola MeSH
- dítě MeSH
- konsensus MeSH
- lidé MeSH
- připravenost na pandemii * MeSH
- výzkumný projekt MeSH
- zdraví dítěte MeSH
- Check Tag
- dítě MeSH
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: In this priority-setting exercise, we sought to identify leading research priorities needed for strengthening future pandemic preparedness and response across countries. METHODS: The International Society of Global Health (ISoGH) used the Child Health and Nutrition Research Initiative (CHNRI) method to identify research priorities for future pandemic preparedness. Eighty experts in global health, translational and clinical research identified 163 research ideas, of which 42 experts then scored based on five pre-defined criteria. We calculated intermediate criterion-specific scores and overall research priority scores from the mean of individual scores for each research idea. We used a bootstrap (n = 1000) to compute the 95% confidence intervals. RESULTS: Key priorities included strengthening health systems, rapid vaccine and treatment production, improving international cooperation, and enhancing surveillance efficiency. Other priorities included learning from the coronavirus disease 2019 (COVID-19) pandemic, managing supply chains, identifying planning gaps, and promoting equitable interventions. We compared this CHNRI-based outcome with the 14 research priorities generated and ranked by ChatGPT, encountering both striking similarities and clear differences. CONCLUSIONS: Priority setting processes based on human crowdsourcing - such as the CHNRI method - and the output provided by ChatGPT are both valuable, as they complement and strengthen each other. The priorities identified by ChatGPT were more grounded in theory, while those identified by CHNRI were guided by recent practical experiences. Addressing these priorities, along with improvements in health planning, equitable community-based interventions, and the capacity of primary health care, is vital for better pandemic preparedness and response in many settings.
African Studies University of Vienna Austria
Algebra University College Zagreb Croatia
Capital Institute of Pediatrics Beijing China
Centre for Global Health Usher Institute University of Edinburgh UK
Children and Mother Health Movement Action Yogyakarta Indonesia
Children's Investment Fund Foundation London UK
Croatian Institute for Brain Research Zagreb University School of Medicine Zagreb Croatia
Croatian Science Foundation Zagreb Croatia
Department of Health Policy and Administration The Pennsylvania State University USA
Department of Hematology Dubrava University Hospital Zagreb Croatia
Department of Medicine Ziauddin Medical University Karachi Pakistan
Department of Nutrition University of Oslo Norway
Department of Public Health and Recreation San José State University San Jose California USA
Department of Public Health Policy and Systems The University of Liverpool UK
Department of Sociology and Behavioral Sciences De La Salle University Manila Philippines
Editor Journal of Global Health Reports Washington USA
Faculty of Biology Medicine and Health The University of Manchester Manchester UK
Gombe State University Gombe Nigeria
Guangdong Provincial People's Hospital Guangzhou China
Johns Hopkins Bloomberg School of Public Health Baltimore USA
Jos University Teaching Hospital Nigeria
Koltzov Institute of Developmental Biology of Russian Academy of Sciences Moscow Russia
Lagos State University Ojo Lagos Nigeria
Massachusetts General Hospital Boston USA
National Institute of Psychiatry Ramón de la Fuente Muñiz Mexico City Mexico
Norwegian University of Life Sciences Ås Norway
Oasi Research Institute IRCCS Troina Italy
Olomouc University Social Health Institute Palacký University Olomouc Czechia
Pasteur Institute Novi Sad Novi Sad Serbia
Public Health Development Organization El Paso USA
Royal Infirmary of Edinburgh University of Edinburgh UK
School of Health and Life Sciences Teesside University UK
School of Health Humanities Peking University Beijing China
School of Information Science and Technology Hangzhou Normal University Hangzhou China
School of Medicine University of Zagreb Croatia
School of Public Health and Women's Hospital Zhejiang University School of Medicine China
School of Social Sciences Monash University Australia
Seberang Jaya Hospital Ministry of Health Malaysia
Stellenbosch University Cape Town South Africa
The Task force for Global Health Addis Ababa Ethiopia
Universidad Adolfo Ibañez Santiago Chile
Universidad San Sebastián Santiago Chile
Universitas Pelita Harapan Jakarta Indonesia
Universiti Kebangsaan Malaysia Medical Centre Kuala Lumpur Malaysia
University of Dhaka Bangladesh
University of Nigeria Enugu Campus Nigeria
University of Puthisastra Phnom Penh Cambodia
Usher Institute University of Edinburgh UK
Citace poskytuje Crossref.org
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