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The paper “Artificial Intelligence for Public Health Surveillance in Africa: Applications and Opportunities” examines how artificial intelligence (AI) can improve public health systems across Africa, particularly in low-resource settings. It explores how machine learning and other AI techniques
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are being used for disease detection, outbreak prediction, real-time surveillance, and health resource management.
The authors focus on major public health challenges such as HIV, cholera, Ebola, measles, tuberculosis, malaria, COVID-19, and mental health. Through numerous case studies, the paper shows that AI can enhance the accuracy and speed of disease detection, predict outbreaks more effectively than traditional methods, support vaccination strategies, and optimize healthcare resource allocation. At the same time, it discusses important barriers to implementation, including limited data quality, infrastructure constraints, ethical concerns, and shortages of technical expertise.
Overall, the paper highlights AI’s strong potential to strengthen disease surveillance and health outcomes in Africa while emphasizing the need for careful integration, improved data systems, and supportive policy frameworks.
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This report examines how clinical trials contribute to environmental impacts and outlines key considerations for integrating environmental sustainability into trial design, conduct and oversight. It explores the carbon footprint and resource use associated with clinical research activities – inclu
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ding site operations, participant travel, supply chains, data management and waste – and highlights how these impacts intersect with climate change risks to health systems and research infrastructure.
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World Health Organization (2018). A practical guide for developing and conducting simulation exercises to test and validate pandemic influenza preparedness plans.
The document “Strengthening the global architecture for health emergency prevention, preparedness, response and resilience” presents a report by the Director-General of the World Health Organization (WHO) to the World Health Assembly on global efforts to improve preparedness and response to heal
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th emergencies. It reviews the implementation of the Health Emergency Prevention, Preparedness, Response and Resilience (HEPR) framework and highlights lessons learned from recent crises such as COVID-19. The report describes international initiatives to strengthen global health governance, surveillance systems, laboratory networks, community protection measures, healthcare capacity and access to medical countermeasures like vaccines and diagnostics. It also discusses coordination of emergency responses, support for countries facing outbreaks or humanitarian crises, and the importance of international cooperation. In addition, the report emphasizes the need for sustainable and coordinated financing to strengthen global health security and ensure that countries can better prevent, detect and respond to future health threats.
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The document provides guidance from the CDC on conducting an Operational Readiness Review (ORR) within the Public Health Emergency Preparedness (PHEP) cooperative agreement. It outlines the purpose, structure, and evaluation criteria used to assess whether public health systems are prepared to respo
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nd effectively to emergencies. The guidance describes required capabilities, review processes, and documentation expectations, helping jurisdictions demonstrate their readiness and identify areas for improvement in emergency preparedness and response.
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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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rdination between institutions, communities, and individuals. The text also highlights the importance of early warning systems, showing that not only technical accuracy but also clear communication and community response are crucial. Overall, it argues that disaster preparedness is an ongoing process that combines planning, capacity building, and practical measures to reduce risks and improve emergency response.
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The document provides practical guidelines for conducting a national disaster risk assessment, developed by the United Nations Office for Disaster Risk Reduction. It emphasizes the importance of understanding disaster risk as a foundation for effective disaster risk management and sustainable develo
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pment. The guidelines outline a structured process that includes preparing and scoping the assessment, conducting risk analysis, and using the results to inform policy and decision-making. They promote a comprehensive, multi-hazard approach that considers vulnerabilities, exposure, and capacities, while encouraging collaboration among governments, experts, and stakeholders. Overall, the document aims to help countries build stronger systems for assessing and managing risks, thereby enhancing resilience and reducing the impacts of disasters.
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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)
C2
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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A comprehensive guide to integrating drones into medical supply chains, taking into account cost and effectiveness
The 2025 Impact Report summarises Malaria Consortium's year in numbers and includes a message from the Chief Executive.
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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Были подготовлены "запросы" о принятии частными предприятиями конкретных мер в связи с пандемией КОВИД19 .
The 'asks' have been prepared for private businesses to take concrete actions in the COVID19 pandemic.
Recherche zur Umsetzbarkeit menschenrechtlicher Sorgfalt in deutschen und europäischen Unternehmen
