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The webpage presents a case study on the use of artificial intelligence (AI) in global early warning systems as part of the United Nations’ “Early
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The UNDP webpage “Climate Information and Early Warning Systems” explains how climate information and early
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The text explains what early warning systems are and why they are important for climate action and disaster risk reduction. It describes how these systems collect and analyze data to detect hazards
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Front Public Health . 2025 Jun 23:13:1609615. doi: 10.3389/fpubh.2025.1609615. eCollection 2025.
Key findings reveal the prevalent use of machine learning (ML), deep learning (DL), and natural language processing (NLP), which often integrate diverse data sources (e.g., epidemiological, web, climat
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The WHO handbook “Epidemiological Data Analysis for the Early Warning Alert and Response Network (EWARN) in Humanitarian Emergencies” explains how to collect, analyse, interpret, and share healt
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No publication year indicated
In the context of the floods in August 2015 in Myanmar, the Disaster Risk Reduction Working Group (DRR WG) was requested to provide clear recommendations to the DMH (Department of Hydrology and Meteorology)to strengthen preparedness activities, in particular for t ...
In the context of the floods in August 2015 in Myanmar, the Disaster Risk Reduction Working Group (DRR WG) was requested to provide clear recommendations to the DMH (Department of Hydrology and Meteorology)to strengthen preparedness activities, in particular for t ...
- Build community resilience to coastal hazards by improving capacity of inclusive disaster management systems.
- Reduce the mortality rate of persons with disabilities in situations of risk.
- Raise awareness about inclusive policies, practices and disaster risk reduction strategies that address
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This study aims to analyze national and international stakeholders and their initiatives in Early Warning Systems in Myanmar, to identify priority gaps that need to be addressed by all stakeholders.
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In order to contribute especially to the achievement of Target (g) of the Sendai Framework, several international and regional organizations as well as national institutions with a key role in early warnin
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Consistent with previous editions of this Global Status Report, evidence continues to suggest that concrete progress has been made by countries to improve the coverage and comprehensiveness of MHEWS. Countries have also taken actions to reduce the negative impacts of disasters through investment and
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Health Informatics Journal 1–38. AI has shown promise in enhancing the speed and accuracy of epidemic detection. However, challenges related to data quality, bias, and model transparency need to be addressed to improve the reliability and generalizability of AI-based EWS. Continuous monitoring and
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The frequency of infectious disease epidemics is increasing, and the role of the health sector in the management of epidemics is crucial in terms of response. In the context of infectious disease epidemics, the use of climate-informed early
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Torrential rains and the onset of Cyclone Komen triggered severe and widespread floods and landslides in July and August 2015 across 12 out of 14 states and regions in Myanmar. An estimated 1.6 million individuals were recorded as having been temporarily displaced from their homes by the disaster, a
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