Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hatfield, Hertfordshire, AL9 7TA, UK.
Department of Medicine & Surgery, Faculty of Veterinary Medicine, Chattogram Veterinary and Animal Sciences University, Chattogram, 4225, Bangladesh.
Sci Rep. 2021 Oct 7;11(1):19962. doi: 10.1038/s41598-021-98989-4.
Live animal markets are known hotspots of zoonotic disease emergence. To mitigate those risks, we need to understand how networks shaped by trading practices influence disease spread. Yet, those practices are rarely recorded in high-risk settings. Through a large cross-sectional study, we assessed the potential impact of live poultry trading networks' structures on avian influenza transmission dynamics in Bangladesh. Networks promoted mixing between chickens sourced from different farming systems and geographical locations, fostering co-circulation of viral strains of diverse origins in markets. Viral transmission models suggested that the observed rise in viral prevalence from farms to markets was unlikely explained by intra-market transmission alone, but substantially influenced by transmission occurring in upstream network nodes. Disease control interventions should therefore alter the entire network structures. However, as networks differed between chicken types and city supplied, standardised interventions are unlikely to be effective, and should be tailored to local structural characteristics.
活禽市场是众所周知的人畜共患病出现的热点。为了降低这些风险，我们需要了解由交易行为塑造的网络如何影响疾病传播。然而，这些行为在高风险环境中很少被记录下来。通过一项大型的横断面研究，我们评估了孟加拉国活禽交易网络结构对禽流感传播动态的潜在影响。网络促进了来自不同养殖系统和地理位置的鸡之间的混合，促进了不同来源的病毒株在市场中的共同循环。病毒传播模型表明，从农场到市场观察到的病毒流行率上升不太可能仅由市场内传播来解释，而是受到上游网络节点传播的显著影响。因此，疾病控制干预措施应该改变整个网络结构。然而，由于不同类型的鸡和城市供应的鸡的网络不同，标准化的干预措施不太可能有效，应该根据当地的结构特征进行调整。
