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This document aims to provide public health authorities in European Union and European Economic Area (EU/EEA) countries with guidance for improved preparedness planning taking the lessons that have been identified through various activities in the context of recent public health crises (e.g. COVID-1
...
9 pandemic, mpox multi-country outbreak 2022–23) and translating them to concrete advice. This document, together with the ECDC recommendations on the implementation of public health and social measures (PHSMs) for health emergencies and pandemics published in 2024, form a package of concrete recommendations for preparedness planning for the EU/EEA countries. Lessons learned primarily from the response to the COVID-19 pandemic, but also from the response to the multicountry mpox outbreak in 2022–23, were collected through various activities from Member States, the European Commission, the World Health Organization (WHO) and the WHO Regional Office from Europe. We have then presented these in the form of specific recommendations for planners within each phase of the continuous cycle of preparedness (Anticipation, Response and Recovery), following a prototype structure of a preparedness and response plan. In each section, we have presented a relevant example from a Member State or international organisation to illustrate their practice or attempt to implement lessons after COVID-19 or the mpox outbreak. These examples were identified either through literature review or communication with representatives of the countries within ECDC’s network for Preparedness and Response.
more
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,
...
these models require large-scale validation to ensure real-world applicability, especially for high-risk groups
more
