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Hachung Yoon 3 Articles
Risk Assessment Program of Highly Pathogenic Avian Influenza with Deep Learning Algorithm
Hachung Yoon, Ah-Reum Jang, Chungsik Jung, Hunseok Ko, Kwang-Nyeong Lee, Eunesub Lee
Osong Public Health Res Perspect. 2020;11(4):239-244.   Published online August 31, 2020
DOI: https://doi.org/10.24171/j.phrp.2020.11.4.13
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  • 45 Download
AbstractAbstract PDFSupplementary Material
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.

H5N8 Highly Pathogenic Avian Influenza in the Republic of Korea: Epidemiology During the First Wave, from January Through July 2014
Hachung Yoon, Oun-Kyong Moon, Wooseog Jeong, Jida Choi, Young-Myong Kang, Hyo-Young Ahn, Jee-Hye Kim, Dae-Sung Yoo, Young-Jin Kwon, Woo-Seok Chang, Myeong-Soo Kim, Do-Soon Kim, Yong-Sang Kim, Yi-Seok Joo
Osong Public Health Res Perspect. 2015;6(2):106-111.   Published online April 30, 2015
DOI: https://doi.org/10.1016/j.phrp.2015.01.005
  • 1,362 View
  • 24 Download
  • 11 Citations
AbstractAbstract PDF
Objectives
This study describes the outbreaks of H5N8 highly pathogenic avian influenza (HPAI) in Korea during the first wave, from January 16, 2014 through July 25, 2014. Its purpose is to provide a better understanding of the epidemiology of H5N8 HPAI.
Methods
Information on the outbreak farms and HPAI positive wild birds was provided by the Animal and Plant Quarantine Agency. The epidemiological investigation sheets for the outbreak farms were examined.
Results
During the 7-month outbreak period (January–July 2014), H5N8 HPAI was confirmed in 212 poultry farms, 38 specimens from wild birds (stools, birds found dead or captured). Ducks were the most frequently infected poultry species (159 outbreak farms, 75.0%), and poultry in 67 (31.6%) outbreak farms was asymptomatic.
Conclusion
As in the previous four H5N1 epidemics of HPAI that occurred in Korea, this epidemic of H5N8 proved to be associated with migratory birds. Poultry farms in Korea can hardly be free from the risk of HPAI introduced via migratory birds. The best way to overcome this geographical factor is to reinforce biosecurity to prevent exposure of farms, related people, and poultry to the pathogen.
Estimation of the Infection Window for the 2010/2011 Korean Foot-and-Mouth Disease Outbreak
Hachung Yoon, Soon-Seek Yoon, Han Kim, Youn-Ju Kim, Byounghan Kim, Sung-Hwan Wee
Osong Public Health Res Perspect. 2013;4(3):127-132.   Published online June 30, 2013
DOI: https://doi.org/10.1016/j.phrp.2013.04.010
  • 1,266 View
  • 14 Download
  • 10 Citations
AbstractAbstract PDF
Objectives
This study aims to develop a method for calculating infection time lines for disease outbreaks on farms was developed using the 2010/2011 foot-and-mouth disease (FMD) epidemic in the Republic of Korea.
Methods
Data on farm demography, the detection date of FMD, the clinical history for the manifestation of lesions, the presence of antibodies against FMD virus (including antibodies against the structural and nonstructural proteins of serotype O), vaccination status (O1 Manisa strain), the number of reactors and information on the slaughter of infected animals were utilized in this method.
Results
Based on estimates of the most likely infection date, a cumulative detection probability that an infected farm would be identified on a specific day was determined. Peak infection was observed between late December and early January, but peak detection occurred in mid-January. The early detection probability was highest for pigs, followed by cattle (dairy, then beef) and small ruminants. Nearly 90% of the infected pig farms were detected by Day 11 post-infection while 13 days were required for detection for both dairy and beef cattle farms, and 21 days were necessary for small ruminant (goat and deer) farms. On average, 8.1 ± 3.1 days passed prior to detecting the presence of FMD virus on a farm. The interval between infection and detection of FMD was inversely associated with the intensity of farming.
Conclusion
The results of our study emphasize the importance of intensive clinical inspection, which is the quickest method of detecting FMD infection and minimizing the damage caused by an epidemic.

PHRP : Osong Public Health and Research Perspectives