• Pediatric Infection and Vaccine
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• v.9 no.1
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• pp.67-73
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• 2002

Purpose : Despite of the appropriate measles vaccination programs, epidemics occur every 2~3 years and especially occurred in large group in late of 2000 and early of 2001. To evaluate the effect of the vaccination, needs for revaccination and to determine the optimal age for revaccination, we examined measles specific IgG and IgM in mealses patients and investigated different antibody appearance according to vaccination history. Methods : Anti-measles antibodies were checked in sera of 201 patients(male : 117, female : 84) that are responsible for Criteria for Disease Control among 298 patients that are suspicious of measles including inpatients and outpatients in Wonju Christian Hospital from June in 2000 to June in 2001. They were checked by immunofluorescent assay. Then we classified them according to sex, month, distribution of age due to vaccination and appearance of measles antibody. Results : The ratio of male and female was 1.4 : 1. The maximum incidence was 38 cases(18.9%) in May in 2001. Incidence was increased from November in 2000 to January in 2001 and decreased in February and March in 2001. Thereafter it was increased from April in 2001 again and decreased from June. There were 93 cases(46.3%) in vaccinated group and 108 cases(53.7%) in unvaccinated group. In the distribution according to age in vaccinated group, there were 54 cases(58.1%) in more than 10 years old, 15 cases(16.0%) between 7 and 10 years old, 12 cases(12.9%) between 15 months and 3 years old, 6 cases (6.5%) between 4 and 6 years old and 6 cases(6.5%) between 6 months and 14 months old. In the distribution according to age in unvaccinated group, there were 88 cases(81.5%) between 6 months and 14 months old, 9 cases(8.3%) between 15 months and 3 years old, 7 cases(6.5%) less than 6 months old, 3 cases(2.8%) more than 10 years old and 1 case(0.9%) between 7 and 10 years old. In the distribution of measles specific IgG and IgM, 78 cas (87.6%) were IgG(+), IgM(+) and 11 cases(12.4%) are IgG(+), IgM(-) in vaccinated group. In unvaccinated group, there were 69 cases(63.9%) of IgG(+), IgM(+) and 39 cases (36.1%) of IgG(-), IgM(+). Con c lu s i on s : We thought that measles incidence was peaked between 6 months and 14 months old in unvaccinated group because of maximum decrement of transplacental matenal antibody and was peaked in more than 10 years old in vaccinated group because of maximum decrement of measles specific IgG. We think that measles revaccination as well as vaccination and especially optimal age for revaccination is very important to prevent measles successfully.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.69-76
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• 2013

The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.