Eurosurveillance - Volume 31, Issue 26, 02 July 2026

West Nile virus (WNV) is an orthoflavivirus maintained in an enzootic cycle between birds and ornithophilic Culex mosquitoes. Human infections are usually asymptomatic or paucisymptomatic, while severe neurological disease occurs mainly in children, elderly and immunocompromised individuals. Despite evidence of WNV circulation in France since the 1960s, nationwide seroprevalence data are unavailable.

We wanted to determine the seroprevalence of WNV among blood donors in mainland France to characterise the epidemiology of WNV and assess risk factors and potential implications for transfusion safety and public health.

Sera from 44,490 volunteer blood donors collected in 2021–2022 in France were screened for anti-WNV IgG by ELISA on pools of up to four samples, with samples from non-negative pools tested individually. ELISAs for various flaviviruses and virus neutralisation tests were used to assess non-negative results.

Seroprevalence was low overall, similar in pools and individual samples (0.87% and 0.97%, respectively). Prevalence was 1.13% in Nouvelle-Aquitaine and 1.81% in Ile-de-France, preceding the first local human cases reported in 2023 and 2025 in these regions, respectively. The risk factors identified as being associated with WNV seropositivity were geographic (living in the south of France: Occitanie, Provence-Alpes-Côte d'Azur and Corsica) and related to ABO blood group.

Seroprevalence of West Nile virus in France is low but variable, suggesting that WNV may have circulated undetected in some areas. Monitoring flavivirus prevalence in blood donors can serve as an early warning system for human infections and provide valuable data for public health preparedness.

Technologies available for applied public health practice are rapidly evolving. Artificial intelligence (AI) tools have become more accessible, however, their utilisation by field epidemiologists has not been described.

We explored AI use among Canadian, European, and United States (US) Field Epidemiology Training Program (FETP) fellows.

Fellows in the three programmes (n = 220) were invited to an online survey available from 25 November 2024 to 5 December 2024. Quantitative and qualitative data were collected concerning the AI platforms fellows used, AI applications, comfort level when applying AI, use frequency, impact on work, barriers, ethical concerns, AI policy/guideline availability, and AI training.

There were 105 (48%) survey respondents: 13, 56 and 36 in the Canadian, US and European FETPs respectively. The proportion of respondents who reported applying AI for work was 66% (69/105) overall, and highest among respondents of the European programme (32/36). The most adopted platform was ChatGPT (60/69; 87%), and the most common application was analytical coding assistance (63/69; 91%). Among AI users, most felt somewhat comfortable (34/69; 49%) or comfortable (24/69; 35%) with AI and reported weekly (29/69; 42%) or daily (21/69; 30%) use. Generally, AI’s reported impact was positive. Challenges included technical difficulties, accuracy concerns, bias introduction, uncertainty regarding permissible uses, and data privacy issues. Among respondents, 47% (49/105) affirmed having AI policies/guidelines in their institutions and 20% (21/105) had received AI training.

To further incorporate AI use among its fellows, FETPs should monitor AI’s evolving role, and provide guidance and adapt curricula accordingly.