Big data-based risk assessment of poultry farms during the 2020/2021 highly pathogenic avian influenza epidemic in Korea.

Outbreaks of H5-type highly pathogenic avian influenza (HPAI) in poultry have been reported in various parts of the world. To respond to these continuous threats, numerous surveillance programs have been applied to poultry raising facilities as well as wild birds. In Korea, a surveillance program was developed aimed at providing a preemptive response to possible outbreaks at poultry farms. The purpose of this study is to comprehensively present the risks of HPAI evaluated by this program in relation to actual outbreak farms during the epidemic of 2020/2021. A deep learning-based risk assessment program was trained based on the pattern of livestock vehicles visiting poultry farms and HPAI outbreaks to calculate the risk of HPAI for farms linked by the movement of livestock vehicles (such farms are termed "epidemiologically linked farms"). A total of 7,984 risk assessments were conducted, and the results were categorized into four groups. The proportion of the highest risk level was greater in duck farms (13.6%) than in chicken farms (8.8%). Among the duck farms, the proportion of the highest risk level was much greater in farms where breeder ducks were raised (accounting for 26.4% of the risk) than in farms where ducks were raised to obtain meat (12.8% of the risk). A higher risk level was also found in cases where the species of the outbreak farm and epidemiologically linked farms were the same (proportion of the highest risk level = 13.2%) compared to that when the species between the two farms were different (7.9%). The overall proportion of farms with HPAI outbreaks among epidemiologically linked farms (attack rate, AR) was 1.7% as HPAI was confirmed on 67 of the 3,883 epidemiologically linked farms. The AR was highest for breeder ducks (15.3%) among duck farms and laying hens (4.8%) among chicken farms. The AR of the pairs where livestock vehicles entered the inner farm area was 1.3 times (95% confidence interval: 1.4-2.9) higher than that of all pairs. With the risk information provided, customized preventive measures can be implemented for each epidemiologically linked farm. The use of this risk assessment program would be a good example of information-based surveillance and support decision-making for controlling animal diseases.

Risk Assessment Program of Highly Pathogenic Avian Influenza with Deep Learning Algorithm.

OBJECTIVES: This study presents the development and validation of a risk assessment program of highly pathogenic avian influenza (HPAI). This program was developed by the Korean government (Animal and Plant Quarantine Agency) and a private corporation (Korea Telecom, KT), using a national database (Korean animal health integrated system, KAHIS). METHODS: Our risk assessment program was developed using the multilayer perceptron method using R Language. HPAI outbreaks on 544 poultry farms (307 with H5N6, and 237 with H5N8) that had available visit records of livestock-related vehicles amongst the 812 HPAI outbreaks that were confirmed between January 2014 and June 2017 were involved in this study. RESULTS: After 140,000 iterations without drop-out, a model with 3 hidden layers and 10 nodes per layer, were selected. The activation function of the model was hyperbolic tangent. Precision and recall of the test gave F1 measures of 0.41, 0.68 and 0.51, respectively, at validation. The predicted risk values were higher for the "outbreak" (average ± SD, 0.20 ± 0.31) than "non-outbreak" (0.18 ± 0.30) farms (p < 0.001). CONCLUSION: The risk assessment model developed was employed during the epidemics of 2016/2017 (pilot version) and 2017/2018 (complementary version). This risk assessment model enhanced risk management activities by enabling preemptive control measures to prevent the spread of diseases.