As of 21 April 2020, 176 ASF outbreaks have occurred in China. For each outbreak, an investigation was conducted, including historical data retrieval and traceability of potential contacts. The purpose of this study is to conduct a preliminary analysis of the data obtained from the outbreak investigations, including an investigation of the possible contributing factors of the spread of ASF in China. Based on the epidemic situation and the policies issued, the entire epidemic can be divided into three phases. 71 outbreaks were reported between 3 August 2018 and 17 November 2018; 44 outbreaks between 19 November 2018 and 30 March 2019; and 61 outbreaks between 4 April 2019 and 12 April 2020. Based on the reported outbreaks, the proportional rate of outbreaks in small farms (livestock ≤ 500, 127/168) is significantly higher than that of medium (501 ≤ livestock < 2,000, 14/168; 2001 ≤ livestock ≤ 5,000, 9/168) and large farms (livestock ≥ 5,001, 18/168). The odds of infection related to swill feeding (OR = 2.5, 95% CI, 1.5–4.3) and the mechanical dissemination of vehicles and personnel (OR = 2.7, 95% CI, 1.6–4.5) are significantly higher than those of pigs and pig production transportation. Swill feeding is the major contributing factor for small farms while mechanical dissemination of vehicles and personnel is the major contributing factor for large farms. The average duration from the beginning of the infection to the official outbreak report is gradually decreasing, which means that response speed of industry entities and the animal husbandry and veterinary departments from the beginning of the infection to the outbreak report is gradually increasing. Based on the analysis for ASF outbreaks, some policies and suggestions were put forward, such as improving the biosecurity level of the farms, as well as strengthening the supervision of breeding, transportation and slaughter.

In this survey study, the networks among poultry farms and related poultry enterprises in two counties in China (Feixi County in Anhui Province and Beizhen city in Liaoning Province) were analysed and evaluated focusing on the connectivity of contacts, movements, and potential pathogen transmission. The Feixi County poultry production network exhibited greater connectivity, which incorporated approximately 94% of the farms interviewed in a major component (a set of connected farms not linked with each other), mainly due to linkages of backyard farms through local produce stores and individual agents, whilst the Beizhen City network was more fragmented owing to independent in-house operations (from breed, raise, to slaughter and process) of a few large companies, with multiple smaller components. A range of factors influencing the contacts/movements among farms (act as bridges) were identified in this study. Ability to predict the pathway with the network characteristics on the basis of the factors, such as entity type and geographic location, is useful for developing risk-based approaches for disease prevention, surveillance, early detection, and effective controlling.

The influenza A virus of the H7N9 subtype (FLUAV H7N9) emerged in Eastern China provinces in 2013 causing illness in both poultry and humans. Most reported FLUAV H7N9 human cases were related to those associated with the live poultry market chain. From 2013 to 2017, there were five epidemic waves of human infections, and from the end of 2016, the number of human cases increased sharply. To control FLUAV H7N9 in the market chain, the so‐called ‘1110’ policy at live poultry markets and a national vaccination programme were implemented. The relative efficacy of these two measures on the number of poultry and human infections has not been quantified and compared. To explore their efficacy, a cross‐sectional study was conducted in six provinces of China, and the vaccination and surveillance data of H7N9 were analysed. Our survey data showed that poultry vendors were not widely aware of and did not accept the ‘1110’ policy. For subjective and objective factors, some measures of the ‘1110’ policy were not implemented in live bird markets (LBMs). However, the national vaccination programme achieved good immune effects and sharply decreased poultry FLUAV H7N9 infections. The detection rates of FLUAV H7N9 in LBMs and farms gradually decreased since the vaccination programme was implemented. Our analysis also indicated that human infections were closely related to poultry virus carriage rates; therefore, controlling FLUAV H7N9 circulation in poultry was an effective measure to control FLUAV H7N9 infections in humans. Although LBMs play a significant role in human infections, the management measures may not be implemented efficiently; hence, we need to conduct more investigations before developing related policies.

In this study, we introduce a vulnerability index to measure the regional ASF epidemic and present the ASF severity ratings of the 31 provinces of mainland China.The index is defined based on the data from the investigation, national statistical yearbook and reports. The data to be used include pig breeding, financial resources, human resources, epidemic information of ASF and price fluctuation from the 31 provinces. Then, we use the data envelopment analysis (DEA) method to define the vulnerability index, the relative severity value for each region, which quantitatively reflects the damage degree caused by the epidemic of ASF. The method allows us to provide a systematic classification for the regional vulnerability level of ASF in China.Using this index, we find that the vulnerability of the whole country is at a high level, and there is no regional aggregation phenomenon. The vulnerability level of the 31 provinces is quite different and the provinces with high vulnerability level are dispersive geographically. For the five major prevention and control zones for ASF in China, the northern region has the highest vulnerability level, while the eastern zoon level is the lowest.

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