Assessing the risk of ASFV entry into Japan through pork products illegally brought in by air passengers from China and fed to pigs in Japan

Abstract

A risk assessment was conducted to assess the risk of ASFV entry into Japan through pork products illegally brought in by air passengers from China and fed to pigs in Japan. Scenario tree modelling was used with the following entry and exposure pathway considered to be the most likely route of ASF entry: an ASFV infected pork product is illegally brought into Japan by air travellers from China; this pork product is then used in a restaurant where scrap waste is recycled for animal feed and subsequently fed to pigs without being heattreated. Input parameter values were based on surveys conducted by the authors, scientific data gathered from the literature and official data published by government agencies. The annual probability of ASFV entry into Japan via this pathway was predicted to be 0.20 (90% prediction interval: 0.00-0.90). The wide prediction interval was mainly caused by the uncertainty regarding the dose response relation of ASFV, followed by the probability of an ASF infected pig dying on affected farms, the loading of ASFV in an infected pig and the probability of an illegally imported pork product being heat-treated in China and used in restaurants. The results of scenario analysis revealed that the annual probability of ASFV entry into Japan will increase with an increase in the number of ASF affected farms in China. The probability of ASFV entry will increase substantially even if only a small proportion of Ecofeed is not heat-treated during the production process. The probability will decrease if an increased proportion of farms that feed swill apply heat-treatment before feeding swill to their pigs. These findings indicate that stringent application of heat-treatment of Ecofeed and swill is key to protecting the Japanese pig industry from the introduction of ASFV.

Change in the ASF entry risk into Japan as a result of the COVID‐19 pandemic

“…Prob_restaurant c , 2020). Monthly number was used in this study instead of using annual number in the previous study (Sugiura et al, 2020). c Probability that the illegally imported pork product is used in restaurants.…”

“…The wide prediction intervals were caused by the uncertainty of parameters used in the model, in particular the dose-response relationship of ASF virus, the probability of an ASF-infected animal die on an affected farm in China, and the infectious load of an infected pig. Collecting data on these parameters through further research will contribute to reducing the uncertainty of prediction (Sugiura et al, 2020).…”

Change in the ASF entry risk into Japan as a result of the COVID-19 pandemic

“…We used the risk assessment model that we previously developed (Sugiura et al, 2020), reparametrizing the variables that are deemed to be affected under the coronavirus pandemic, namely the number of air travelers from China and the amount of food waste from restaurants. We assumed that variables other than these two do not change even under the coronavirus pandemic.…”

“…Japanese pig population is petentially at risk of getting infected with ASFV as a result of being fed illegally imported pork products from ASF-affected countries (Sugiura et al, 2018). Based on this assumption, we have previously assessed the risk of ASF introduction into Japan through pork products illegally imported from China and fed to pigs as swill, using a stochastic model and the latest data available up to 2019 (Sugiura et al, 2020). As a result, the annual probability of ASFV entry into Japan via this pathway was predicted to be 20% (90% prediction interval: 0-90%) (Sugiura et al, 2020).…”

“…Based on this assumption, we have previously assessed the risk of ASF introduction into Japan through pork products illegally imported from China and fed to pigs as swill, using a stochastic model and the latest data available up to 2019 (Sugiura et al, 2020). As a result, the annual probability of ASFV entry into Japan via this pathway was predicted to be 20% (90% prediction interval: 0-90%) (Sugiura et al, 2020). However, under the various interventions taken to manage the human coronavirus outbreak that started in late 2019, there have been substantial changes in the value of some of the variables used in the model.…”