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The text explains the concept of disaster preparedness and outlines how societies can better prepare for and respond to emergencies. It describes key components such as risk assessment, planning, resource management, warning systems, and training, emphasizing that effective preparedness requires coo
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The World report on promoting the health of refugees and migrants: Monitoring progress on the WHO global action plan provides the first global baseline for assessing implementation of the 2019-2030 WHO Global Action Plan on Promoting the Health of Refugees and Migrants (GAP). Building on the 2022 Wo
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rld report on the health of refugees and migrants, it examines how countries are integrating refugee and migrant health into broader public health, migration governance, development, and universal health coverage (UHC) agendas.
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The document presents a strategic framework by the World Health Organization for managing risks related to emergencies and disasters in the health sector. It highlights that such events (such as epidemics, natural disasters, or conflicts) have major impacts on health, healthcare systems, and societa
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l development. The framework proposes a comprehensive and proactive approach based on prevention, preparedness, response, and recovery, while emphasizing the importance of collaboration across different sectors and stakeholders. Its main objective is to reduce health risks, strengthen the resilience of communities and health systems, and improve health security at the global level.
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Incorporating epidemics risk in the INFORM Global Risk Index
Poljanšek K., Marin-Ferrer M., Vernaccini L., Messina L.
European Commission – Joint Research Centre (JRC)
(2018)
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The document focuses on integrating epidemic risk into the INFORM Global Risk Index, a tool used to assess and compare crisis and disaster risks across countries. It explains how epidemics can significantly impact vulnerability and hazard exposure, and therefore should be systematically included in
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risk assessments. The report outlines methods, indicators, and data sources for incorporating epidemic risk into the index, improving its ability to capture health-related threats. Overall, the document aims to enhance risk analysis and support better preparedness, planning, and decision-making by providing a more comprehensive understanding of global risks.
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Artificial intelligence for tuberculosis control: a scoping review of applications in public health
Menon, S.; and K. Ghislein Kuro
(2025)
J Glob Health. 2025;15:04192. This scoping review highlights the potential of AI-driven predictions in national TB programmes to enhance diagnostics, track trends, and strengthen public health surveillance. While promising for reducing transmission and support-
ing TB care in low-resource settings,
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these models require large-scale validation to ensure real-world applicability, especially for high-risk groups
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BMC Public Health (2025) 25:3774 https://doi.org/10.1186/s12889-025-24555-6. The study results provide useful insights on how climate change influences malaria in African countries, and reiterates the need for a greater engagement of policymakers and social partners, in intensifying the action neede
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d to fight the transmission of malaria in Sub-Sahara Africa
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The GHEC framework is designed to provide guiding principles for standardizing health emergency workforce structures to strengthen the capacity of countries in responding to health emergencies, and to enhance collaboration between countries by better connecting regional and global surge response mec
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hanisms, facilitating information exchange, and improving access to expertise and human response capacity at times of need.
This is the first version of the GHEC framework and is intended to be updated as experience is gained with its implementation and adaptation.
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This report presents a WHO–PREZODE collaboration to develop and validate standardized indicators that assess the risk of zoonotic disease emergence by modeling pathogen circulation in animals and the risk of animal to human zoonotic spillover. The proposed indicators are intended to be actionable,
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i.e., to reflect the impact of the implementation of a prevention strategy along the process of zoonotic pathogen emergence and over time.
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This tool enables a rapid, systematic review of pharmacy curricula at the national or institutional level to evaluate their robustness in delivering the expected content and competencies. It can also assist institutions in designing strategies to strengthen AMR curricular content, and to facilitate
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structured, periodic dialogue on AMR and infection-related competencies among pharmacy faculty and other relevant stakeholders. A pharmacy curriculum that comprehensively integrates AMR content will help ensure that future pharmacists have the knowledge, skills, and attitudes needed to address AMR effectively in both clinical practice and public health.
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This guidance addresses one type of generative AI, large multi-modal models (LMMs), which can accept one or more type of data input and generate diverse outputs that are not limited to the type of data fed into the algorithm. It has been predicted that LMMs will have wide use and application in heal
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th care, scientific research, public health and drug development. LMMs are also known as “general-purpose foundation models”, although it is not yet proven whether LMMs can accomplish a wide range of tasks and purposes.
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TArtificial intelligence (AI) is transforming health systems, reshaping how care is planned, delivered and governed. This report presents the first assessment of AI integration into health systems across the whole of the WHO European Region, based on findings from the 2024–2025 survey on AI for he
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alth care. It examines national strategies, governance models, legal and ethical frameworks, workforce readiness, data governance, stakeholder engagement, private sector roles and the uptake of AI applications. Drawing on insights from 50 Member States, the report explores how countries are navigating opportunities and challenges, highlighting emerging trends, gaps and practices to guide policy-makers towards coherent, ethical and people-centred approaches to AI in health care.
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