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PLoS One
. 2025 Feb 4;20(2):e0316248.
doi: 10.1371/journal.pone.0316248. eCollection 2025. Spatial risk modelling of highly pathogenic avian influenza in France: Fattening duck farm activity matters
Jean Artois 1 2 , Timothée Vergne 3 , Lisa Fourtune 3 , Simon Dellicour 1 4 , Axelle Scoizec 5 , Sophie Le Bouquin 5 , Jean-Luc Guérin 3 , Mathilde C Paul 3 , Claire Guinat 3
Affiliations
In this study, we present a comprehensive analysis of the key spatial risk factors and predictive risk maps for HPAI infection in France, with a focus on the 2016-17 and 2020-21 epidemic waves. Our findings indicate that the most explanatory spatial predictor variables were related to fattening duck movements prior to the epidemic, which should be considered as indicators of farm operational status, e.g., whether they are active or not. Moreover, we found that considering the operational status of duck houses in nearby municipalities is essential for accurately predicting the risk of future HPAI infection. Our results also show that the density of fattening duck houses could be used as a valuable alternative predictor of the spatial distribution of outbreaks per municipality, as this data is generally more readily available than data on movements between houses. Accurate data regarding poultry farm densities and movements is critical for developing accurate mathematical models of HPAI virus spread and for designing effective prevention and control strategies for HPAI. Finally, our study identifies the highest risk areas for HPAI infection in southwest and northwest France, which is valuable for informing national risk-based strategies and guiding increased surveillance efforts in these regions.
. 2025 Feb 4;20(2):e0316248.
doi: 10.1371/journal.pone.0316248. eCollection 2025. Spatial risk modelling of highly pathogenic avian influenza in France: Fattening duck farm activity matters
Jean Artois 1 2 , Timothée Vergne 3 , Lisa Fourtune 3 , Simon Dellicour 1 4 , Axelle Scoizec 5 , Sophie Le Bouquin 5 , Jean-Luc Guérin 3 , Mathilde C Paul 3 , Claire Guinat 3
Affiliations
- PMID: 39903711
- DOI: 10.1371/journal.pone.0316248
In this study, we present a comprehensive analysis of the key spatial risk factors and predictive risk maps for HPAI infection in France, with a focus on the 2016-17 and 2020-21 epidemic waves. Our findings indicate that the most explanatory spatial predictor variables were related to fattening duck movements prior to the epidemic, which should be considered as indicators of farm operational status, e.g., whether they are active or not. Moreover, we found that considering the operational status of duck houses in nearby municipalities is essential for accurately predicting the risk of future HPAI infection. Our results also show that the density of fattening duck houses could be used as a valuable alternative predictor of the spatial distribution of outbreaks per municipality, as this data is generally more readily available than data on movements between houses. Accurate data regarding poultry farm densities and movements is critical for developing accurate mathematical models of HPAI virus spread and for designing effective prevention and control strategies for HPAI. Finally, our study identifies the highest risk areas for HPAI infection in southwest and northwest France, which is valuable for informing national risk-based strategies and guiding increased surveillance efforts in these regions.