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基于死亡率数据估算高致病性禽流感(H7N7)病毒传入家禽群体的日期。

Estimating the day of highly pathogenic avian influenza (H7N7) virus introduction into a poultry flock based on mortality data.

作者信息

Bos Marian E H, Van Boven Michiel, Nielen Mirjam, Bouma Annemarie, Elbers Armin R W, Nodelijk Gonnie, Koch Guus, Stegeman Arjan, De Jong Mart C M

机构信息

Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.

出版信息

Vet Res. 2007 May-Jun;38(3):493-504. doi: 10.1051/vetres:2007008. Epub 2007 Apr 11.

Abstract

Despite continuing research efforts, knowledge of the transmission of the highly pathogenic avian influenza (HPAI) virus still has considerable gaps, which complicates epidemic control. The goal of this research was to develop a model to back-calculate the day HPAI virus is introduced into a flock, based on within-flock mortality data. The back-calculation method was based on a stochastic SEIR (susceptible (S) - latently infected (E) - infectious (I) - removed (= dead; R)) epidemic model. The latent and infectious period were assumed to be gamma distributed. Parameter values were based on experimental H7N7 within-flock transmission data. The model was used to estimate the day of virus introduction based on a defined within-flock mortality threshold (detection rule for determining AI). Our results indicate that approximately two weeks can elapse before a noticeable increase in mortality is observed after a single introduction into a flock. For example, it takes twelve (minimum 11 - maximum 15) days before AI is detected if the detection rule is fifty dead chickens on two consecutive days in a 10 000 chicken flock (current Dutch monitoring rule for notification). The results were robust for flock size and detection rule, but sensitive to the length of the latent and infectious periods. Furthermore, assuming multiple introductions on one day will result in a shorter estimated period between infection and detection. The implications of the model outcomes for detecting and tracing outbreaks of H7N7 HPAI virus are discussed.

摘要

尽管一直在进行研究,但对于高致病性禽流感(HPAI)病毒的传播,我们的了解仍存在相当大的差距,这使得疫情控制变得复杂。本研究的目的是开发一个模型,根据鸡群内的死亡率数据,反向推算高致病性禽流感病毒引入鸡群的日期。反向推算方法基于一个随机的SEIR(易感(S)-潜伏感染(E)-感染(I)-清除(=死亡;R))疫情模型。潜伏期和感染期假定呈伽马分布。参数值基于H7N7病毒在鸡群内传播的实验数据。该模型用于根据设定的鸡群内死亡率阈值(确定禽流感的检测规则)来估计病毒引入的日期。我们的结果表明,病毒单次引入鸡群后,大约需要两周时间死亡率才会显著上升。例如,如果检测规则是在一个10000只鸡的鸡群中连续两天有50只鸡死亡(荷兰目前的监测通报规则),那么在检测到禽流感之前需要12天(最短11天 - 最长15天)。结果对于鸡群规模和检测规则具有稳健性,但对潜伏期和感染期的长度敏感。此外,假设在某一天有多次引入会导致感染与检测之间的估计时间缩短。本文讨论了该模型结果对于检测和追踪H7N7高致病性禽流感病毒疫情的意义。

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