• Korean Journal of Fisheries and Aquatic Sciences
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• v.45 no.6
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• pp.666-674
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• 2012

We examined the cause of a disease outbreak in adult olive flounder Paralichthys olivaceus, which occurred at a Korean aquaculture farm in Korea in 2011. The principal signs included an expanded abdomen and congested liver, with persistent mortality (a little over two months). At the beginning of the outbreak, farm administrators misjudged the disease as bacterial in origin, because of the aforementioned signs, persistent mortality, and the detection of bacterial species, including Vibrio spp. and Streptococcus spp. Moreover, the detection of viral hemorrhagic septicemia virus (VHSV) by reverse trasnscription-PCR analysis was complicated by use of the VHS-VN primer set, which has been in general use recently, because it produced weak bands in some samples. Therefore, we recommend the use of at least two different primer sets in the diagnosis of VHSV. Our histopathological findings indicate that necrotizing myocarditis could be considered a pathogenic sign of VHSV infection.

• Journal of Food Hygiene and Safety
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• v.12 no.2
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• pp.153-159
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• 1997

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2005.04a
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• pp.43.1-43.1
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• 2005

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.302-310
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• 2023

In this study, the extent of the impact of rainfall on the outbreak of fire blight during the blossom infection risk period was explored. In the Chungnam province, the outbreak of fire blight disease began in 2015, and changes in the outbreak's scale were most pronounced between 2020 and 2022, significantly escalating from 63 orchards in 2020 to 170 orchards in 2021, before decreasing to 46 orchards in 2022. In 2022, the number of incidence has decreased and the number of canker symptom in branches has also decreased. It was evaluated that the significant decrease of fire blight disease in 2022 was due to the dry weather during the flowering season. In other words, this yearly fluctuation in fire blight outbreaks was correlated with the presence or absence of rainfall and accumulated precipitation during the blossom infection risk period. This trend was observed across all surveyed regions where apples and pears were cultivated. Among the weather conditions influencing the blossom infection risk period, rainfall notably affected the activation of pathogens from over-wintering cankers and flower infections. In particular, precipitation during the initial 3 days of the blossom infection risk warning was confirmed as a decisive factor in determining the outbreak's scale.

• ALGAE
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• v.29 no.4
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• pp.249-265
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• 2014

As with land crops, cultivated algae are affected by various diseases ranging from large outbreaks of a disease to chronic epiphytes, which may downgrade the value of the final product. The recent development of intensive and dense mariculture practices has enabled some new diseases to spread much faster than before. A new disease is reported almost every year, and the impact of diseases is expected to increase with environmental change, such as global warming. We observed the incidence of diseases in two Pyropia sea farms in Korea from 2011 to 2014, and estimated the economic loss caused by each disease. Serious damage is caused by the oomycete pathogens, Pythium porphyrae and Olpidiopsis spp., which decreased the productivity of the Pyropia sea farms. In Seocheon sea farms, an outbreak of Olpidiopsis spp. disease resulted in approximately US $1.6 million in loss, representing approximately 24.5% of total sales during the 2012-2013 season. The damage caused by green-spot disease was almost as serious as oomycete diseases. An outbreak of green-spot disease in the Seocheon sea farms resulted in approximately US $1.1 million in loss, representing 10.7% of total sales in the 2013-2014 season in this area. However, the causative agent of green-spot disease is still not confirmed. "Diatom felt" is regarded as a minor nuisance that does not cause serious damage in Pyropia; however, our case study showed that the economic loss caused by "diatom felt" might be as serious as that of oomycete diseases. Bacteria and cyanobacteria are indigenous members of epiphytic microbial community on Pyropia blades, but can become opportunistic pathogens under suitable environmental conditions, especially when Pyropia suffers from other diseases. A regular acid wash of the Pyropia cultivation nets is the most common treatment for all of the above mentioned diseases, and represents approximately 30% of the total cost in Pyropia sea farming. However, the acid wash is ineffective for some diseases, especially for Olpidiopsis and bacterial diseases.

• Journal of Preventive Medicine and Public Health
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• v.49 no.1
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• pp.1-17
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• 2016

The Middle East respiratory syndrome coronavirus (MERS-CoV) outbreak in South Korea in 2015 has drawn public attention regarding the legal regulation of infectious disease control in Korea. This paper discusses the interpretive and legislative concerns regarding the Infectious Disease Prevention and Control Act, its ordinance and enforcement regulations, as well as public statements from the relevant administrative agency. Future improvements are also proposed.

• Mycobiology
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• v.39 no.1
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• pp.26-32
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• 2011

Powdery mildew is one of the most devastating diseases in cucurbits. Crop yield can decline as the disease severity increases. In this study, we evaluated the effect of silver nanoparticles against powdery mildew under different cultivation conditions in vitro and in vivo. Silver nanoparticles (WA-CV-WA13B) at various concentrations were applied before and after disease outbreak in plants to determine antifungal activities. In the field tests, the application of 100 ppm silver nanoparticles showed the highest inhibition rate for both before and after the outbreak of disease on cucumbers and pumpkins. Also, the application of 100 ppm silver nanoparticles showed maximum inhibition for the growth of fungal hyphae and conidial germination in in vivo tests. Scanning electron microscope results indicated that the silver nanoparticles caused detrimental effects on both mycelial growth and conidial germination.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.161-168
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• 2015

The epidemic is seemed to be extremely difficult for accurate predictions. The new models have been suggested that show quite different results. The basic reproductive number of epidemic for consequent time intervals are estimated based on stochastic processes. In this paper, we proposed a transmission distribution estimation for Ebola virus disease epidemic model. This estimation can be easier to obtain in real time which is useful for informing an appropriate public health response to the outbreak. Finally, we implement our proposed method with data from Guinea Ebola disease outbreak.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.60-74
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• 2017

To facilitate prevention of highly pathogenic avian influenza (HPAI), a GIS is widely used for monitoring, investigating epidemics, managing HPAI-infected farms, and eradicating the disease. After the outbreak of foot-and-mouth disease in 2010 and 2011, the government of the Republic of Korea (ROK) established the GIS-based Korean Animal Health Integrated System (KAHIS) to avert livestock epidemics, including HPAI. However, the KAHIS is not sufficient for controlling HPAI outbreaks due to lack of responsibility in fieldwork, such as sterilization of HPAI-infected poultry farms and regions, control of infected animal movement, and implementation of an eradication strategy. An outbreak prediction model to support efficient HPAI control in the ROK is proposed here, constructed via analysis of HPAI outbreak patterns in the ROK. The results show that 82% of HPAI outbreaks occurred in Jeolla and Chungcheong Provinces. The density of poultry farms in these regions were $2.2{\pm}1.1/km^2$ and $4.2{\pm}5.6/km^2$, respectively. In addition, reared animal numbers ranged between 6,537 and 24,250 individuals in poultry farms located in HPAI outbreak regions. Following identification of poultry farms in HPAI outbreak regions, an HPAI outbreak prediction model was designed using factors such as the habitat range for migratory birds(HMB), freshwater system characteristics, and local road networks. Using these factors, poultry farms which reared 6,500-25,000 individuals were filtered and compared with number of farms actually affected by HPAI outbreaks in the ROK. The HPAI prediction model shows that 90.0% of the number of poultry farms and 54.8% of the locations of poultry farms overlapped between an actual HPAI outbreak poultry farms reported in 2014 and poultry farms estimated by HPAI outbreak prediction model in the present study. These results clearly show that the HPAI outbreak prediction model is applicable for estimating HPAI outbreak regions in ROK.

• Journal of Environmental Health Sciences
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• v.47 no.6
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• pp.521-529
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• 2021

Background: The coronavirus disease (COVID-19) has caused changes in human activity, and these changes may possibly increase or decrease exposure to fine dust (PM_2.5). Therefore, it is necessary to evaluate the exposure to PM_2.5 in relation to the outbreak of COVID-19. Objectives: The purpose of this study was to compare and evaluate the exposure to PM_2.5 concentrations by the variation of dynamic populations before and after the outbreak of COVID-19. Methods: This study evaluated exposure to PM_2.5 concentrations by changes in the dynamic population distribution in Guro-gu, Seoul, before and after the outbreak of COVID-19 between Jan and Feb, 2020. Gurogu was divided into 2,204 scale standard grids of 100 m×100 m. Hourly PM_2.5 concentrations were modeled by the inverse distance weight method using 24 sensor-based air monitoring instruments. Hourly dynamic population distribution was evaluated according to gender and age using mobile phone network data and time-activity patterns. Results: Compared to before, the population exposure to PM_2.5 decreased after the outbreak of COVID-19. The concentration of PM_2.5 after the outbreak of COVID-19 decreased by about 41% on average. The variation of dynamic population before and after the outbreak of COVID-19 decreased by about 18% on average. Conclusions: Comparing before and after the outbreak of COVID-19, the population exposures to PM_2.5 decreased by about 40%. This can be explained to suggest that changes in people's activity patterns due to the outbreak of COVID-19 resulted in a decrease in exposure to PM_2.5.