• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.135-137
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• 2009

Mathematical models for describing the Human Immunodeficiency Virus(HIV) infection can be devised to better understand how the HIV causes Acquired Immune Deficiency Syndrome(AIDS). The HIV models can then be used to find clues to curing AIDS from a control theoretical point of view. Some models take Cytotoxic T Lymphocytes(CTL) response to HIV infection into account, and others consider mutants against the drugs. However, to the best of our knowledge, there has been no model developed, which describes CTL response and mutant HIV together. Hence we propose a unified model to consider both of these. On the basis of the resulting model, we also present a Model Predictive Control(MPC) scheme to find an optimal treatment strategy. The optimization is performed under the assumption that the Structured Treatment Interruption(STI) policy is employed.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.1
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• pp.29-36
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• 2011

HPAI (High pathogenic avian influenza) which is a disease legally designated as an epidemic generally shows rapid spread of disease resulting in high mortality rate as well as severe economic damages. Because Korea is contiguous with China and southeast Asia where HPAI have occurred frequently, there is a high risk for HPAI outbreak. A prompt treatment against epidemics is most important for prevention of disease spread. The spread of HPAI should be considered by both direct and indirect contact as well as various spread factors including airborne spread. There are high risk of rapid propagation of HPAI flowing through the air because of collective farms mostly in Korea. Field experiments for the mechanism of disease spread have limitations such as unstable weather condition and difficulties in maintaining experimental conditions. In this study, therefore, computational fluid dynamics which has been actively used for mass transfer modeling were adapted. Korea has complex terrains and many livestock farms are located in the mountain regions. GIS numerical map was used to estimate spreads of virus attached aerosol by means of designing three dimensional complicated geometry including farm location, road network, related facilities. This can be used as back data in order to take preventive measures against HPAI occurrence and spread.

• Journal of Veterinary Clinics
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• v.29 no.1
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• pp.63-67
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• 2012

Mosquitoes are the vectors of a number of viral diseases in cattle, such as Akabane disease, bovine ephemeral fever, Ainovirus infection, Chuzan virus infection, and Ibaraki disease. These diseases are transmitted from an infected animal to a non-infected host via the blood feeding of the vector. In Korea, the National Veterinary Research and Quarantine Services, Ministry for Food, Agriculture, Forestry and Fisheries is responsible for planning, implementation, laboratory investigations and reporting the results of the national surveillance program for mosquito-borne bovine diseases (MBD). The surveillance program, which was started in 1993, focused to determine the seroprevalence of each disease in cattle herds in space and time. From the epidemiological point of view, more important component of the surveillance program is to monitor infection rates in vectors for specific pathogens because this information is essential for a more precise understanding the dynamics of these diseases in a given environment and for determining risk of transmission. The aim of this study was to describe and compare methods for estimation of vector infection rates using maximum likelihood (MLE) and minimum infection rate in pooled samples. Factors affecting MLE such as number of pools, pooling size and diagnostic test performance are also discussed, assuming some hypothetical sampling scenarios for MBD.

• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.1-9
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• 2024

Predicting the spread of COVID-19 remains a challenge due to the complexity of the disease and its evolving nature. This study presents an integrated approach using the classic SIR model for infectious diseases, enhanced by the chemical master equation (CME). We employ a Monte Carlo method (SSA) to solve the model, revealing unique aspects of the SARS-CoV-2 virus transmission. The study, a first of its kind in Korea, adopts a step-by-step and complementary approach to model prediction. It starts by analyzing the epidemic's trajectory at local government levels using both basic and stochastic SIR models. These models capture the impact of public health policies on the epidemic's dynamics. Further, the study extends its scope from a single-infected individual model to a more comprehensive model that accounts for multiple infections using the jump SIR prediction model. The practical application of this approach involves applying these layered and complementary SIR models to forecast the course of the COVID-19 epidemic in small to medium-sized local governments, particularly in Gangnam-gu, Seoul. The results from these models are then compared and analyzed.

• Korean journal of applied entomology
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• v.58 no.4
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• pp.347-354
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• 2019

Temperature-dependent traits of Laodelphax striatellus, rice stripe virus vector, were investigated at 10 constant temperatures (12.5, 15.0, 17.5, 20.0, 22.5, 25.0, 27.5, 30.0, 32.5, and 35.0 ± 1℃) under a fixed photoperiod (14/10-hr light/dark cycle). Unit functions for the oviposition model were estimated and implemented into a population dynamics model using DYMEX. The longevity of L. striatellus adults decreased with increasing temperature (56.0 days at 15.0℃ and 17.7 days at 35.0℃). The highest total fecundity (515.9 eggs/female) was observed at 22.5℃, while the lowest (18.6 eggs/female) was observed at 35.0℃. Adult developmental rates, temperature-dependent fecundity, age-specific mortality rates, and age-specific cumulative oviposition rates were estimated. All unit equations described adult performances of L. striatellus accurately (r² =0.94~0.97). After inoculating adults, the constructed model was tested under pot and field conditions using the rice-plant hopper system. The model output and observed data were similar up to 30 days after inoculation; however, there were large discrepancies between observed and estimated population density after 30 days, especially for 1^st and 2^nd instar nymph densities. Model estimates were one or two nymphal stages faster than was observed. Further refinement of the model created in this study could provide realistic forecasting of this important rice pest.

• Korean Journal of Veterinary Research
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• v.48 no.1
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• pp.67-73
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• 2008

Porcine reproductive and respiratory syndrome (PRRS) is the most economically important viral infectious disease in pig populations worldwide. This study was conducted to better understand the epidemic and dynamics of PRRS virus (PRRSV) on each farm and to evaluate the risk of PRRSV infection in Korea. Interviews with pig farmers were carried out to obtain PRRS vaccination programmes in 60 pig farms throughout Korea. Blood samples were also collected from the 59 pig farms to investigate outbreak patterns of each farm. Vaccination against PRRS was performed in 16.7% farms for breeding pigs and 8.3% of farms for nursery pigs. According to the seroepidemiological analysis, 56 (94.9%) out of 59 farms were considered to be affected by PRRSV infection. The results revealed that 68.9% of sows tested were seroconverted and interestingly, gilt herds had the highest seropositive rate (73%), suggesting that gilts may play a key role in PRRSV transmission in sow herds. Among the PRRS-affected piglet herds, 33 (55.9%), 14 (23.7%) and 6 (10.2%) farms were initially infected with PRRSV during the weaning, suckling and nursery period, respectively. It seems likely, therefore, that PRRSV infection predominantly occurs around the weaning period in piglet herds. Based on antibody seroprevalence levels in both sow and piglet groups, we were able to classify patterns of PRRSV infection per farm unit into 4 categories; category 1 (stable sow groups and non-infected piglet groups), category 2 (unstable sow groups and non-infected piglet groups), category 3 (stable sow groups and infected piglet groups), and category 4 (unstable sow groups and infected piglet groups). Our data suggested that 43 (72.9%) farms were analysed to belong to category 4, which is considered to be at high-risk for PRRS outbreak. Taken together, our information from this study will provide insight into the establishment of an effective control strategy for PRRS on the field.

• Journal of Life Science
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• v.27 no.3
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• pp.283-288
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• 2017

Porcine circovirus type 2 (PCV2) is a notorious and ubiquitous virus in the swine industry. The susceptibility of the host to PCV2 infection is considered to be one factor associated with the dynamics of PCV2. The objective of this study was to verify the criteria for host susceptibility to PCV2, using blood parameters of post-weaned pigs naturally infected with the virus. The PCV2 DNA viral load, antibody titer, and leukopenia characteristics were measured in the serum extracted from the pigs at the 10th week. We classified the pigs into high (>5.0), intermediate (3.0 to 5.0), and low (<3.0) groups on the basis of the PCV2 viral load (log copies/ml), or as positive (${\leq}0.50$) and negative (>0.50) groups on the basis of antibody titer (sample-to-negative corrected ratio). Moreover, using these two categorized parameters, we suggested the criteria for classification into the susceptible and resistant groups. Statistical analyses revealed that pigs in the susceptible group had a significantly higher viral load (p<0.001) and negative antibody titer (p<0.001), as well as significantly lower leukocyte counts (p=0.018) and lower amounts of several leukocyte components (p<0.05), than pigs in the resistant group. We concluded that the susceptible group could be considered to have PCV2-induced leukopenia. Therefore, we suggest that the combined classifications of viral loads and anti-PCV2 antibodies can be used to determine PCV2-induced leukopenia in the subclinical PCV2 infection of post-weaned pig populations.

• Journal of Veterinary Clinics
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• v.33 no.5
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• pp.278-285
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• 2016

Epidemiological studies have shown the association between transportation of live animals and the potential transmission of infectious disease between premises. This finding was also observed in the 2014-2015 foot-and-mouth disease (FMD) outbreak in Korea. Furthermore, slaughterhouses played a key role in the global spread of the FMD virus during the epidemic. In this context, in-depth knowledge of the structure of direct and indirect contact between slaughterhouses is paramount for understanding the dynamics of FMD transmission. But the social network structure of vehicle movements to slaughterhouses in Korea remains unclear. Hence, the aim of this study was to configure a social network topology of vehicle movements between slaughterhouses for a better understanding of how they are potentially connected, and to explore whether FMD outbreaks can be explained by the network properties constructed in the study. We created five monthly directed networks based on the frequency and chronology of on- and off-slaughterhouse vehicle movements. For the monthly network, a node represented a slaughterhouse, and an edge (or link) denoted vehicle movement between two slaughterhouses. Movement data were retrieved from the national Korean Animal Health Integrated System (KAHIS) database, which tracks the routes of individual vehicle movements using a global positioning system (GPS). Electronic registration of livestock movements has been a mandatory requirement since 2013 to ensure traceability of such movements. For each of the five studied networks, the network structures were characterized by small-world properties, with a short mean distance, a high clustering coefficient, and a short diameter. In addition, a strongly connected component was observed in each of the created networks, and this giant component included 94.4% to 100% of all network nodes. The characteristic hub-and-spoke type of structure was not identified. Such a structural vulnerability in the network suggests that once an infectious disease (such as FMD) is introduced in a random slaughterhouse within the cohesive component, it can spread to every other slaughterhouse in the component. From an epidemiological perspective, for disease management, empirically derived small-world networks could inform decision-makers on the higher potential for a large FMD epidemic within the livestock industry, and could provide insights into the rapid-transmission dynamics of the disease across long distances, despite a standstill of animal movements during the epidemic, given a single incursion of infection in any slaughterhouse in the country.

• Journal of Internet of Things and Convergence
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• v.7 no.2
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• pp.13-19
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• 2021

It is analyzed that the energy pattern is affected by the social matters of the disease trend where the energy consumption has been reduced following the depression of the national economy. The campaign of social distance for the people has been done by voluntary or legally due to the epidemic of the Coronavirus Disease 2019 (COVID-19). Some economic stimulus policies have been done in some countries including the United States, South Korea, and some others. It is shown the susceptible, infectious, and recovered (SIR) modeling applied by system dynamics (SD) where the logical modeling is constructed with S, I, and R. Especially, the I is connected with Society including Population, Race, and Maturity. In addition, Economy and Politics are connected to Income, GDP, Resources, President, Popularity, Ruling Government, and Leadership. The graph shows the big jump on 2020 April when is the starting month of the S value multiplication. This shows the effect of the COVID-19 and its related post-pandemic trend. The trends of OECD and non-OECD are very similar and the effect of the virus hazards causes significantly to the economic depressions.

• Journal of Veterinary Science
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• v.22 no.1
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• pp.5.1-5.16
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• 2021

Background: Arctic-like (AL) lineages of rabies viruses (RABVs) remains endemic in some Arctic and Asia countries. However, their evolutionary dynamics are largely unappreciated. Objectives: We attempted to estimate the evolutionary history, geographic origin and spread of the Arctic-related RABVs. Methods: Full length or partial sequences of the N and G genes were used to infer the evolutionary aspects of AL RABVs by Bayesian evolutionary analysis. Results: The most recent common ancestor (tMRCA) of the current Arctic and AL RABVs emerged in the 1830s and evolved independently after diversification. Population demographic analysis indicated that the viruses experienced gradual growth followed by a sudden decrease in its population size from the mid-1980s to approximately 2000. Genetic flow patterns among the regions reveal a high geographic correlation in AL RABVs transmission. Discrete phylogeography suggests that the geographic origin of the AL RABVs was in east Russia in approximately the 1830s. The ancestral AL RABV then diversified and immigrated to the countries in Northeast Asia, while the viruses in South Asia were dispersed to the neighboring regions from India. The N and G genes of RABVs in both clades sustained high levels of purifying selection, and the positive selection sites were mainly found on the C-terminus of the G gene. Conclusions: The current AL RABVs circulating in South and North Asia evolved and dispersed independently.