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Epidemic intelligence activities among national public and animal health agencies: a European cross-sectional study

Dub Timothée, Mäkelä Henna, Van Kleef Esther, Leblond Agnès, Mercier Alizé, Hénaux Viviane, Bouyer Fanny, Binot Aurélie, Thiongane Oumy, Lancelot Renaud, Delconte Valentina, Zamuner Lea, Van Bortel Wim, Arsevska Elena. 2023. Epidemic intelligence activities among national public and animal health agencies: a European cross-sectional study. BMC Public Health, 23 (1):1488, 13 p.

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Résumé : Epidemic Intelligence (EI) encompasses all activities related to early identification, verification, analysis, assessment, and investigation of health threats. It integrates an indicator-based (IBS) component using systematically collected surveillance data, and an event-based component (EBS), using non-official, non-verified, non-structured data from multiple sources. We described current EI practices in Europe by conducting a survey of national Public Health (PH) and Animal Health (AH) agencies. We included generic questions on the structure, mandate and scope of the institute, on the existence and coordination of EI activities, followed by a section where respondents provided a description of EI activities for three diseases out of seven disease models. Out of 81 gatekeeper agencies from 41 countries contacted, 34 agencies (42%) from 26 (63%) different countries responded, out of which, 32 conducted EI activities. Less than half (15/32; 47%) had teams dedicated to EI activities and 56% (18/34) had Standard Operating Procedures (SOPs) in place. On a national level, a combination of IBS and EBS was the most common data source. Most respondents monitored the epidemiological situation in bordering countries, the rest of Europe and the world. EI systems were heterogeneous across countries and diseases. National IBS activities strongly relied on mandatory laboratory-based surveillance systems. The collection, analysis and interpretation of IBS information was performed manually for most disease models. Depending on the disease, some respondents did not have any EBS activity. Most respondents conducted signal assessment manually through expert review. Cross-sectoral collaboration was heterogeneous. More than half of the responding institutes collaborated on various levels (data sharing, communication, etc.) with neighbouring countries and/or international structures, across most disease models. Our findings emphasise a notable engagement in EI activities across PH and AH institutes of Europe, but opportunities exist for better integration, standardisation, and automatization of these efforts. A strong reliance on traditional IBS and laboratory-based surveillance systems, emphasises the key role of in-country laboratories networks. EI activities may benefit particularly from investments in cross-border collaboration, the development of methods that can automatise signal assessment in both IBS and EBS data, as well as further investments in the collection of EBS data beyond scientific literature and mainstream media.

Mots-clés Agrovoc : surveillance épidémiologique, santé publique, santé animale, Enquête pathologique, maladie infectieuse, transmission des maladies, épidémiologie, maladie des animaux, contrôle de maladies, coronavirus 2 du syndrome respiratoire aigu sévère, maladie transmise par vecteur, impact sur l'environnement, enquête

Mots-clés géographiques Agrovoc : Europe

Mots-clés libres : Epidemic intelligence, Indicator-based surveillance, Event-based surveillance, Outbreak detection

Classification Agris : S50 - Santé humaine
L73 - Maladies des animaux

Champ stratégique Cirad : CTS 4 (2019-) - Santé des plantes, des animaux et des écosystèmes

Agences de financement européennes : European Commission

Programme de financement européen : H2020

Projets sur financement : (EU) MOnitoring Outbreak events for Disease surveillance in a data science context

Auteurs et affiliations

  • Dub Timothée, THL (FIN) - auteur correspondant
  • Mäkelä Henna, THL (FIN)
  • Van Kleef Esther, ITM (BEL)
  • Leblond Agnès, INRAE (FRA)
  • Mercier Alizé, INRAE (FRA)
  • Hénaux Viviane, ANSES (FRA)
  • Bouyer Fanny, GERDAL (FRA)
  • Binot Aurélie, CIRAD-BIOS-UMR ASTRE (FRA) ORCID: 0000-0002-0295-4241
  • Thiongane Oumy, IRD (BFA)
  • Lancelot Renaud, CIRAD-BIOS-UMR ASTRE (REU)
  • Delconte Valentina, Agro Business Park (NLD)
  • Zamuner Lea, Agro Business Park (NLD)
  • Van Bortel Wim, ITM (BEL)
  • Arsevska Elena, CIRAD-BIOS-UMR ASTRE (FRA) ORCID: 0000-0002-6693-2316

Source : Cirad-Agritrop (https://agritrop.cirad.fr/608552/)

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