• Journal of Preventive Medicine and Public Health
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• v.38 no.4
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• pp.379-385
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• 2005

The impact of the next influenza pandemic is difficult to predict. It is dependent on how virulent the virus is, how rapidly it spreads from population to population, and the effectiveness of prevention and response efforts. Despite the uncertainty about the magnitude of the next pandemic, estimates of the health and economic impact remain important to aid public health policy decisions and guide pandemic planning for health and emergency sectors. Planning ahead in preparation for an influenza pandemic, with its potentially very high morbidity and mortality rates, is essential for hospital administrators and public health officials. The estimat ion of pandemic impact is based on the previous pandemics- we had experienced at least 3 pandemics in 20th century. But the epidemiologi cal characteristics - ie, start season, the impact of 1st wave, pathogenicity and virulence of the viruses and the primary victims of population were quite different from one another. I reviewed methodology for estimation and modelling of pandemic impact and described some nations's results using them in their national preparedness plans. And then I showed the estimates of pandemic influenza impact in Korea with FluSurge and FluAid. And, I described the results of pandemic modelling with parameters of 1918 pandemic for the shake of education and training of the first-line responder health officials to the epidemics. In preparing influenza pandemics, the simulation and modelling are the keys to reduce the uncertainty of the future and to make proper policies to manage and control the pandemics.

• Communications of Mathematical Education
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• v.24 no.4
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• pp.877-889
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• 2010

Mathematical modelling is a useful method for reinterpreting the real world and for solving real problems. In this paper, we introduced a theory on mathematical modelling. Further, we developed a mathematical model of the H1N1 influenza with Excel. Then, we analyzed the model which tells us what role it can play in an appropriate prediction of the future and in the decision of accompanied policies.

• Nonlinear Functional Analysis and Applications
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• v.28 no.2
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• pp.473-495
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• 2023

The use of mathematical modelling in the study of epidemiological disorders continues to grow substantially. In order to better support global policy initiatives and explain the possible consequence of an outbreak, mathematical models were constructed to forecast how epidemic illnesses spread. In this paper, fractional derivatives and (${\varpi}$ - F_𝓒)-contractions are used to explore the existence and uniqueness solutions of the novel coronavirus-19 model.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.89-95
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• 1999

This study investigates the population model of the spread of HIV/AIDS which the infection is generated by an infectious individual in a population of susceptible. A mathematical model is presented for the transmission dynamics of HIV infection within the communities of homosexual males. The pattern on the epidemic character of HIV, the causative agent of AIDS, was analysed by the mathematical model of AIDS system which is derived according to the ecological relationship between five epidemilogic states of individuals. The computer simulation was performed using real data and the following conclusions are drawn on the basis of the simulations. 1. The model structure and the algorithm described n the thesis is good. 2. In proportion to increase Ro, the population of AIDS patient increases and the time of its widespread reaches earlier. 3. The AIDS patients will be maximum between 7 and 21 years after an attack of AIDS and widespread between 10 and 20 years. 4. Considering the properties of the incubation periods, the maximum number of infected person is increased, and the attack rate is decreased.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.699-702
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• 1998

This study investigates the population model of the spread of HIV/AIDS which the infection is generated by an infectious in dividual in a population of susceptibles. A mathematical model is presented for the transmission dynamics of HIV infection within the communities of homosexual males. The pattern on the epidemic character of HIV, the causative agent of AIDS, was analysed by the mathematical model of AIDS system which is derived according to the ecological relationship between five epidemilogic states of individuals. The computer simulation was performed using real data.

• Journal of Veterinary Science
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• v.24 no.2
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• pp.21.1-21.5
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• 2023

Under the current African swine fever (ASF) epidemic situation, a science-based ASF-control strategy is required. An ASF transmission mechanistic model can be used to understand the disease transmission dynamics among susceptible epidemiological units and evaluate the effectiveness of an ASF-control strategy by simulating disease spread results with different control options. The force of infection, which is the probability that a susceptible epidemiological unit becomes infected, could be estimated by applying an ASF transmission mechanistic model. The government needs to plan an ASF-control strategy based on an ASF transmission mechanistic model.

• Journal of Preventive Veterinary Medicine
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• v.42 no.4
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• pp.163-170
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• 2018

The cost-effectiveness of foot-and-mouth disease (FMD) control strategies was evaluated using a simulation model fitted to the 2010/11 FMD epidemic in the city of Andong, Republic of Korea. Seven FMD-control strategies were evaluated with respect to the direct cost of a FMD-control strategy, such as slaughtering, movement restriction, and vaccination. All the strategies included pre-emptive slaughtering, movement restriction, and vaccination, but the levels of each control option were different. The simulated median cost of the baseline FMD-control strategy (three kilometers of pre-emptive slaughtering area, 100 days of movement restriction and vaccination of all FMD-susceptible animals in the study area) was estimated to be USD 99.7 million. When a five kilometer vaccination area was applied (with the other control measures being the same as the baseline strategy), the simulated median cost was reduced to USD 81.1 million from USD 99.7. The simulated median costs were USD 107.6 million for a five kilometer radius slaughtering area and USD 168.8 million for 60 days of movement restriction. The FMD-control strategy cost decreased with increasing number of farms depopulated per day. The probability of passive surveillance being effective or the probability of the successful implementation of movement restrictions were increased. Cost-effectiveness analysis is a suitable tool for evaluating the financial consequences of FMD-control strategies by comparing the cost of control strategies for a specific area.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.774-777
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• 2005

Dengue Fever(DF) and Dengue haemorrhagic fever(DHF) has become a major international public health concern. Dengue Fever(DF) and Dengue haemorrhagic Fever (DHF) is also still the major health problem of Thailand, although many campaigns against it have been conducted throughout the country. GIS and Remotely Sensed data are used to evaluate the relationships between socio-spatial, environmental factors/indicators and the incidences of viral diseases. The aim of the study is to identify the spatial risk factors in Dengue and Dengue Haemorrhagic Fever in Sukhothai province, Thailand using statistical, spatial and GIS Modelling. Preliminary results demonstrated that physical factors derived from remotely sensed data could indicate variation in physical risk factors affecting DF and DHF. The present study emphasizes the potential of remotely sensed data and GIS in spatial factors affecting Dengue Risk Zone analysis. The relationship between land cover and the cases of incidence of DF and DHF by information value method revaluated that highest information value is obtained for Built-up area. A negative relationship was observed for the forest area. The relations between climate data and cases of incidence have shown high correlation with rainfall factors in rainy season but poor correlation with temperature and relative humidity. The present study explores the potential of remotely sensed data and GIS in spatial analysis of factors affecting Dengue epidemic, strong spatial analysis tools of GIS. The capabilities of GIS for analyst spatial factors influencing risk zone has made it possible to apply spatial statistical analysis in Disease risk zone.