Gonnerman Matthew, Mullinax Jennifer M, Fox Andrew, Patyk Kelly A, Fields Victoria L, McCool Mary-Jane, Torchetti Mia K, Lantz Kristina, Sullivan Jeffery D, Prosser Diann J
Department of Environmental Science and Technology, University of Maryland, College Park, MD 20742, USA.
Post-doctoral affiliate with the U.S. Geological Survey, Eastern Ecological Science Center, Laurel, MD 20708, USA.
One Health. 2025 Aug 19;21:101172. doi: 10.1016/j.onehlt.2025.101172. eCollection 2025 Dec.
With the continued spread of highly pathogenic avian influenza (HPAI), understanding the complex dynamics of virus transfer at the wild - agriculture interface is paramount. Spillover events (i.e., virus transfer from wild birds into poultry) are related to proximity to infected wild bird populations and environmental conditions. By accounting for such dynamics, we can take a combined approach to assess the impacts of biosecurity measures implemented at poultry farms while simultaneously accounting for their local risk levels. We implemented a Bayesian joint-likelihood logistic regression for the Continental U.S. comparing models of spatiotemporal risk according to land use, weather, and predicted waterfowl distributions followed by integrating a farm-level case-control questionnaire dataset focused on identifying trends in HPAI spillover risk associated with a farm's biosecurity practices. We found that estimates of waterfowl abundance, along with mean precipitation and temperature during winter, were most correlated with spatiotemporal HPAI risk. Additionally, we identified multiple biosecurity practices associated with reduced risk to HPAI, where the strongest relationships were related to litter decontamination treatments, vehicle wash stations, and avoiding shared dead-bird disposal sites with other farms. This model broadly guides surveillance of HPAI in wild and domestic populations, identifying when and where we are most likely to see increased instances of the virus while also providing insights into how poultry farms can better protect themselves from risk.
随着高致病性禽流感(HPAI)的持续传播,了解野生与农业界面病毒传播的复杂动态至关重要。溢出事件(即病毒从野生鸟类传播到家禽)与靠近受感染野生鸟类种群以及环境条件有关。通过考虑这些动态因素,我们可以采用综合方法来评估家禽养殖场实施的生物安全措施的影响,同时考虑其当地风险水平。我们对美国大陆实施了贝叶斯联合似然逻辑回归,根据土地利用、天气和预测的水禽分布比较时空风险模型,随后整合了一个农场层面的病例对照问卷调查数据集,重点是确定与农场生物安全措施相关的HPAI溢出风险趋势。我们发现,水禽数量估计值以及冬季的平均降水量和温度与HPAI时空风险的相关性最强。此外,我们确定了多种与降低HPAI风险相关的生物安全措施,其中最强的关系与垫料去污处理、车辆清洗站以及避免与其他农场共用死禽处理场有关。该模型广泛指导对野生和家养种群中HPAI的监测,确定我们最有可能在何时何地看到病毒感染增加的情况,同时也为家禽养殖场如何更好地保护自己免受风险提供见解。