Methods to detect avian influenza virus for food safety surveillance

• Published in: Journal of Integrative Agriculture Vol. 14; no. 11; pp. 2296 - 2308
• Main Author: SHI Ping, Shu Geng, LI Ting-ting, LI Yu-shui, FENG Ting, WU Hua-nan (1International Food Policy Research Institute (IFPRI) 2Center for Chinese Agricultural Policy Institute of Geographical Sciences and Natural 3College of Food Science and Nutritional Engineering china Agricultural University Beijing, P.R.China 4Member of JIA Editorial Board Northwest AF University Yangling, P.R.China)
• Format: Journal Article
• Language: English
• Published: Science Press 01.11.2015; Elsevier
• Subjects: avian influenza; avian influenza food safety detection methods poultry supply chain surveillance system; detection methods; food safety; poultry supply chain; surveillance system; 世界动物卫生组织; 安全监测; 家禽产品; 病毒检测; 禽流感疫情; 禽流感病毒; 食品供应链; 食品安全
• ISSN: 2095-3119; 2352-3425
• DOI: 10.1016/S2095-3119(15)61122-4

Avian influenza （AI）, caused by the influenza A virus, has been a global concern for public health. AI outbreaks not only impact the poultry production, but also give rise to a risk in food safety caused by viral contamination of poultry products in the food supply chain. Distinctions in AI outbreak between strains H5N1 and H7N9 indicate that early detection of the AI virus in poultry is crucial for the effective warning and control of AI to ensure food safety. Therefore, the establishment of a poultry surveillance system for food safety by early detection is urgent and critical. In this article, methods to detect AI virus, including current methods recommended by the World Health Organization （WHO） and the World Organisation for Animal Health （Office International des Epizooties, OIE） and novel techniques not commonly used or commercialized are reviewed and evaluated for feasibility of use in the poultry surveillance system. Conventional methods usually applied for the purpose of AI diagnosis face some practical challenges to establishing a comprehensive poultry surveillance program in the poultry supply chain. Diverse development of new technologies can meet the specific requirements of AI virus detection in various stages or scenarios throughout the poultry supply chain where onsite, rapid and ultrasensitive methods are emphasized. Systematic approaches or integrated methods ought to be employed according to the application scenarios at every stage of the poultry supply chain to prevent AI outbreaks.