Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark.
Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Sydney, NSW, Australia.
Transbound Emerg Dis. 2022 Nov;69(6):3238-3246. doi: 10.1111/tbed.14675. Epub 2022 Aug 19.
Avian influenza poses an increasing problem in Europe and around the world. Simulation models are a useful tool to predict the spatiotemporal risk of avian influenza spread and evaluate appropriate control actions. To develop realistic simulation models, valid transmission parameters are critical. Here, we reviewed published estimates of the basic reproduction number (R ), the latent period and the infectious period by virus type, pathogenicity, species, study type and poultry flock unit. We found a large variation in the parameter estimates, with highest R estimates for H5N1 and H7N3 compared with other types; for low pathogenic avian influenza compared with high pathogenic avian influenza types; for ducks compared with other species; for estimates from field studies compared with experimental studies; and for within-flock estimates compared with between-flock estimates. Simulation models should reflect this observed variation so as to produce more reliable outputs and support decision-making. How to incorporate this information into simulation models remains a challenge.
禽流感在欧洲和世界各地构成的问题日益严重。模拟模型是预测禽流感传播的时空风险和评估适当控制措施的有用工具。为了开发现实的模拟模型，有效的传播参数是至关重要的。在这里，我们回顾了已发表的关于基本繁殖数（R ）、潜伏期和感染期的估计值，这些估计值按病毒类型、致病性、物种、研究类型和家禽群单位进行了划分。我们发现参数估计值存在很大的差异，H5N1 和 H7N3 的 R 估计值最高，与其他类型相比；低致病性禽流感与高致病性禽流感类型相比；与其他物种相比，鸭类的 R 估计值更高；与实验研究相比，实地研究的 R 估计值更高；与群间估计值相比，群内估计值更高。模拟模型应反映这种观察到的差异，以产生更可靠的输出结果并支持决策制定。如何将这些信息纳入模拟模型仍然是一个挑战。
