ArticleJournal of global health2024
Setting research priorities for global pandemic preparedness: An international consensus and comparison with ChatGPT's output.
Article in Journal of global health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The trial behind it
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Who cites it
12 citing papers in PubMed.
- Research priorities for improved pandemic and epidemic intelligence.The Lancet. Global health · 2026Review
- Editor's view: What makes a scientist successful?Journal of global health · 2026Article
- Exploring variation in research priorities generated by AI tools.Journal of global health · 2026Article
- The health diplomacy spiral: a conceptual framework linking health system integration and public health diplomacy.Public health reviews · 2026Review
- Ideometrics: a scientific approach to generating, evaluating, and prioritising ideas.Journal of global health · 2025Article
- Research priorities on physical-mental comorbidity in children and adolescents: an international consensus.EClinicalMedicine · 2025Review
- Two decades of the CHNRI method (2006-2025): Tracking its evolution and contribution to the emerging field of ideometrics.Journal of global health · 2025Article
- The potential role of AI in research priority setting exercises.Journal of global health · 2025Review
- Editor's view: Is the brain's perception of ideas an underappreciated human sense?Journal of global health · 2024Article
- COVID-19 and Mental Health: A "Pandemic Within a Pandemic".Advances in experimental medicine and biology · 2024Review
- COVID-19 vaccine coverage effectiveness among elderly with geographical information system mapping: what about Indonesia?Therapeutic advances in vaccines and immunotherapy · 2024Article
- Trust Building in Public Health Approaches: The Importance of a "People-Centered" Concept in Crisis Response.Risk management and healthcare policy · 2024Article
Corrections and comments
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Authors and funding
61 authors.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.