Modifications of facilities and/or practises to lower disease risk offers cost-effective options for disease prevention programmes at animal gathering points along the value chains, such as markets, abattoirs, and border points. Such interventions can be strengthened through the use of profiling/characterization in order to focus resources more effectively. Understanding the risks of avian influenzas (AI) in market settings and targeting disease prevention and control to reduce the risk of spillover to humans has been instrumental in determining the role live bird markets (LBM) play in promoting the emergence of the disease and acting as a reservoir for the virus in both developed and developing countries. However, as has been shown recently with influenza A (H7N9), even with strict prevention and control measures in place, LBM are prone to incursions of AI. It is therefore fundamental that along with prevention capabilities through facility upgrades, national veterinary services are equipped with greater proficiency in surveillance so that they are able to detect animal diseases at epidemiologically linked locations earlier, more efficiently, and with the potential to forecast disease events at connected nodes along the value chain through enhanced knowledge of animal movement flows and patterns. Furthermore, preventative surveillance of transmissible animal diseases at these locations through risk-based interventions is an efficient method of disease detection that presents economic benefits in comparison to the cost of control or eradication efforts.
The Food and Agriculture Organization’s online Epidemiology Value Chain (EVC) Platform provides visualisation tools and analysis that support capacity development through a series of online applications. Its aim is to improve both prevention and detection of disease events through the reduction of biosecurity risk and the improvement of risk-based surveillance capabilities.
FAO’s Epi-Value Chain (EVC) Platform enables users to maintain live, online, and dynamic databases that can store, analyse, and display a magnitude of different data. Furthermore, due to the constantly changing nature of disease risk, data analysis can be continuously updated as it is made available to maintain cost efficiency and the effectiveness of interventions. The EVC is programmed to utilise Google or other electronic collection systems such as Epicollect5 to gather data on specific locations and animal movement with the help of veterinary services personnel. It then allows for the creation of a variety of outputs to visualise data via maps, statistics, or graphs through the use of various ‘plug-in’ applications. These visualisations can be created in conjunction with national epidemiology units in order to ensure their outputs are relevant to planned interventions efforts. Lastly, the applications allow for dissemination of data, incorporating those stakeholders identified by the national epidemiology units into the prevention and detection efforts.
In 2016 FAO began initial piloting of the EVC in Viet Nam with the aim to not only categorising LBM based on risk factors such as infrastructure, facilities, and slaughtering, but also mapping the catchment areas of LBMs to further study the market networks of a country. As of 2020 all known LBM markets in the country had been profiled. However, the data has yet to be shared with the national veterinary services and all findings remain internal to FAO. The application requires validation from Vietnamese authorities in terms of the support required to carry out disease prevention, detection, and control efforts at LBM before it will be able to support intervention activities. In 2019 the MPA was first piloted across five countries in East and Southern Africa utilising the same risk factors generated for Viet Nam. The pilot covered only 73 total LBMs, however the project is considered a success as the profiling required minimal training, time, or monetary efforts. The results were presented to members of veterinary services from the five countries at the final project meeting, and significant interest in the potential of the application for Africa was expressed.