About
Jaewoon Jeong
D.V.M., M.S., Ph.D.
Veterinary epidemiolgist & Disease ecologist
Science advisor, Fisheries and Oceans Canada
After studying veterinary medicine in South Korea, I studied epidemiology at the University of California, Davis, with an emphasis on biostatistics and epidemiological methods. I was particularly fascinated with infectious disease modelling and risk analysis, and used mathematical modelling to investigate swine infections in my thesis. I continued to study modelling during my PhD but from a different perspective. In my PhD, I studied wildlife infection in terms of ecology. Through the modelling of wild bat infections, I learned the concepts of one health, emerging infectious diseases, and zoonoses. Intent on expanding my knowledge in quantitative studies of infectious diseases, I moved to PEI, Canada to investigate sea lice modelling in salmon populations. Currently, I am expanding my research of marine parasites both with farmed salmon and with wild salmon at DFO. This pathway has enabled me to cover a wide range of disciplines, from veterinary medicine to ecology, from livestock to wildlife, and from biology to statistics.
Education
Ph.D. in Disease Ecology 2017
Griffith University, Brisbane, QLD, Australia
M.S. in Epidemiology 2012
University of California, Davis, USA
D.V.M. (Doctor of Veterinary Medicine) 2010
Konkuk University, Seoul, South Korea
Research Interests
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Modelling of infectious diseases
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Quantitative disease ecology
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Veterinary epidemiology
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One health
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Risk assessment
Research
Sea lice infestation on salmon
Salmon sampling for sea lice abundance estimation
Effective sampling is essential to monitoring and controlling sea lice infestations on salmon farms, and the decision of sea lice treatment depends on the sampling result. However, the reliability and efficiency of sampling are poorly understood. We explored the advantages of using prevalence instead of abundance, and the impact of incorrectly estimated sea lice abundance on lice management.
I developed an open web-based application, FISHSAMPLING, to guide the determination of sampling approaches on salmon farms to accurately estimate sea louse abundance. It can be used for three different sampling objectives, to estimate: i) the probability that an estimated abundance will fall within a given range, ii) the probability that the abundance will be incorrectly estimated relative to some lice limit, and, iii) the probability of correctly detecting a different between two abundance levels. The web-based application is freely available here.
Population dynamics of sea lice
Sea lice go through multiple life stages and the development period and mortality in each stage depend on environmental factors such as temperature and salinity. By quantifying the life stages of sea lice, we simulated population dynamis of sea lice on salmon farms and suggested efficient control strategies of sea lice. Also, the quantification of sea lice life cycle can help further modelling studies.
Zoonotic viral infections in Australian bats
Understanding viral transmission dynamics within populations of reservoir hosts can facilitate greater knowledge of the spillover of emerging infectious diseases. I used ordinary differential equations, Gillespie algorithm, and Bayesian method to simulate the infectiuos status of bats with zoonotic viruses. These studies focused on exploring how the virus can be permanently maintained in the reservoir populations of bats without extinction, unlike in other species.
Quantitative microbial risk assessment for food safety
Salmonellosis caused by chicken consumption has been a critical issue in food safety worldwide. I used @RISK to build a model of salmonellosis caused by chicken consumption in a South Korean setting. By quantifying the all processes from slaughtering to consumption, the concentration of salmonella in chicken was assessed and finally the probability of salmonellosis due to chicken consumption was estimated. Also, these studies indicate the critical points in the processes, and thereby suggest the points to focus our effort to reduce the probability of salmonellosis.
Porcine reproductive and respiratory syndrome in a farm of piglets
Infection with porcine reproductive and respiratory syndrome (PRRS) virus causes reproductive disorders in sows and pneumonia and growth reduction in growing pigs. In this study, my first modelling study, stochastic simulation was used to compare several different control measures of PRRS in a swine farm. We found that repeated mass immunization with a PRRS modified-live virus vaccine with herd closure or gilt acclimitization was the scenario most likely to achieve a stabilized status. Estimation of the cost of various PRRS control strategies is necessary.
Publications
Jeong, J., McEwan, G. F., Arriagada, G., Gallardo, C., Revie, C. W. (2022) Quantifying key parameters related to the life cycle of Caligus rogercresseyi. Journal of Fish Diseases. 00, 1–6. https://doi.org/10.1111/jfd.13535
Jeong, J., Stormoen, M., Thakur, K. K., Revie, C. W. (2021) Imperfect estimation of Lepeophtheirus salmonis abundance and its impact on salmon lice treatment on Atlantic salmon farms. Frontiers in Marine Science. 1514. https://doi.org/10.3389/fmars.2021.763206
Jeong, J., Stormoen, M., McEwan, G. F., Thakur, K. K., Revie, C. W. (2021) Salmon lice should be managed before they attach to salmon: Exploring epidemiological factors affecting Lepeophtheirus salmonis abundance on salmon farms. Aquaculture. 541, 736792. https://doi.org/10.1016/j.aquaculture.2021.736792
Jeong, J., McCallum, H. (2021). Effects of Waning Maternal Immunity on Infection Dynamics in Seasonally Breeding Wildlife. EcoHealth. https://doi.org/10.1007/s10393-021-01541-z
Jeong, J., McCallum, H. (2021) The persistence of a SIR disease in a metapopulation: Hendra virus epidemics in Australian black flying foxes (Pteropus alecto). Australian Journal of Zoology. https://doi.org/10.1071/ZO20094
Jeong, J., McCallum, H. (2021) Using Stochastic Modelling to Predict the effect of Culling and Colony Dispersal of Bats to Zoonotic Viral Epidemics. Vector-borne and zoonotic diseases. https://doi.org/10.1089/vbz.2020.2700
Seo, K. H., Jeong, J., & Kim, H. (2020). Synergistic Effects of Heat-Killed Kefir Paraprobiotics and Flavonoid-Rich Prebiotics on Western Diet-Induced Obesity. Nutrients, 12(8), 2465.
Jeong, J., & Revie, C. W. (2020). Appropriate sampling strategies to estimate sea lice prevalence on salmon farms with low infestation levels. Aquaculture, 734858. https://doi.org/10.1016/j.aquaculture.2019.734858
Lee, M.J., Song, K.Y., Lee, W.C., Chon, J.W., Kim, H., Jeong, J., Bae, D. and Seo, K.H., (2019). Epidemiological aspects of pathogenic microbial foodborne disease outbreaks in Korea and Japan from 2011 to 2015. Journal of Preventive Veterinary Medicine, 43(2), pp.62-67.
Jeong, J., Kim, H. and Seo, K.H., (2019). Quantitative Risk Assessment Model for Salmonellosis in Chicken Skewers from Street Food Vendors in South Korea. Journal of food protection, 82(6), pp.955-962. https://doi: 10.4315/0362-028X.JFP-18-113.
Jeong, J., Chon, J. W., Kim, H., Song, K. Y., & Seo, K. H. (2018). Risk Assessment for Salmonellosis in Chicken in South Korea: The Effect of Salmonella Concentration in Chicken at Retail. Korean journal for food science of animal resources, 38(5), 1043.
Solberg, Ingrid, Bengt Finstad, Henrik Hårdensson Berntsen, Ola H. Diserud, Kevin Frank, Kari Olli Helgesen, Jeong J., et al. (2018). "Kartlegging og testing av metodikk for telling av lakselus og beregning av luseforekomst.".
Jeong, J., Smith, C.S., Peel, A.J., Plowright, R.K., Kerlin, D.H., McBroom, J., McCallum, H. (2017) Persistent infections support maintenance of a coronavirus in a population of Australian bats (Myotis macropus). Epidemiology & Infection. 2017 Jul;145(10):2053-2061. https://doi.org/10.1017/S0950268817000991
Jeong, J., Aly, S. S., Cano, J. P., Polson, D., Kass, P. H., & Perez, A. M. (2014). Stochastic model of porcine reproductive and respiratory syndrome virus control strategies on a swine farm in the United States. American journal of veterinary research, 75(3), 260-267.
Yoon, H., Jeong, W., Jeong, J., Kim, Y. J., Jeon, W. J., & Moon, O. K. (2013). Estimation of prevalence and sampling to estimate prevalence of Bovine Tuberculosis. Journal of the Preventive Veterinary Medicine Vol, 37(1), 19-23.