Fasina F O, Njage P M K, Ali A M M, Yilma J M, Bwala D G, Rivas A L, Stegeman A J
Department of Production Animal Studies, Faculty of Veterinary Science, University of Pretoria, Onderstepoort, South Africa.
Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalenaan, the Netherlands.
Zoonoses Public Health. 2016 Feb;63(1):20-33. doi: 10.1111/zph.12200. Epub 2015 Apr 29.
Avian influenza virus (H5N1) is a rapidly disseminating infection that affects poultry and, potentially, humans. Because the avian virus has already adapted to several mammalian species, decreasing the rate of avian-mammalian contacts is critical to diminish the chances of a total adaptation of H5N1 to humans. To prevent the pandemic such adaptation could facilitate, a biology-specific disease surveillance model is needed, which should also consider geographical and socio-cultural factors. Here, we conceptualized a surveillance model meant to capture H5N1-related biological and cultural aspects, which included food processing, trade and cooking-related practices, as well as incentives (or disincentives) for desirable behaviours. This proof of concept was tested with data collected from 378 Egyptian and Nigerian sites (local [backyard] producers/live bird markets/village abattoirs/commercial abattoirs and veterinary agencies). Findings revealed numerous opportunities for pathogens to disseminate, as well as lack of incentives to adopt preventive measures, and factors that promoted epidemic dissemination. Supporting such observations, the estimated risk for H5N1-related human mortality was higher than previously reported. The need for multidimensional disease surveillance models, which may detect risks at higher levels than models that only measure one factor or outcome, was supported. To develop efficient surveillance systems, interactions should be captured, which include but exceed biological factors. This low-cost and easily implementable model, if conducted over time, may identify focal instances where tailored policies may diminish both endemicity and the total adaptation of H5N1 to the human species.
禽流感病毒（H5N1）是一种迅速传播的传染病，可感染家禽，也可能感染人类。由于这种禽流感病毒已经适应了几种哺乳动物物种，因此降低禽畜与人类的接触率对于减少H5N1完全适应人类的可能性至关重要。为了预防这种适应可能引发的大流行，需要一种针对生物学特性的疾病监测模型，该模型还应考虑地理和社会文化因素。在此，我们构思了一种监测模型，旨在捕捉与H5N1相关的生物学和文化方面的信息，包括食品加工、贸易以及与烹饪相关的做法，还有对期望行为的激励措施（或抑制措施）。我们利用从埃及和尼日利亚的378个地点（当地[后院]养殖户/活禽市场/乡村屠宰场/商业屠宰场和兽医机构）收集的数据对这一概念验证进行了测试。研究结果揭示了病原体传播的诸多机会、缺乏采取预防措施的激励因素以及促进疫情传播的因素。支持这些观察结果的是，与H5N1相关的人类死亡估计风险高于此前报告的水平。这支持了对多维疾病监测模型的需求，这种模型可能比仅衡量一个因素或结果的模型能在更高层面检测风险。为了开发高效的监测系统，应捕捉各种相互作用，这些相互作用包括但不限于生物学因素。这种低成本且易于实施的模型，如果长期实施，可能会识别出一些关键情况，在这些情况下，量身定制的政策可能会减少H5N1的地方性流行以及它对人类的完全适应。
