Publications

 Selected Journal Article

  1. H. Lee, G. Lee, T. Kim, S. Kim, H. Kim and S. Lee Variability in the serial interval of COVID-19 in South Korea: a comprehensive analysis of age and regional influences Front. Public Health(2024)
  2. A. Azizi, C. Kazanci and S. Lee Adaptive Social Distancing Strategies for Controlling Infection Inequality in Emerging Infectious Diseases Letters in Biomathematics(2023)
  3. T. Kim, H. Lee, S. Kim, C. Kim, H. Son and S. Lee Improved time-varying reproduction numbers using the generation interval for COVID-19 Front. Public Health(2023)
  4. J. Jeon, S. Lee and C. Oh Age-specific risk factors for the prediction of obesity using a machine learning approach frontiers in Public Health(2023)
  5. S. Kim, A. Abdulalib, S. Lee Heterogeneity is a key factor describing the initial outbreak of COVID-19 Applied Mathematical Modeling(2023)
  6. S. Ryu, J. Chun, S. Lee, D. Yoo, Y. kim, S. T. Ali, B. Chun Epidemiology and Transmission Dynamics of Infectious Diseases and Control Measures viruses(2022)
  7. S. Ryu, C. Han, D. Kim, T. K, Tsang, B. J Cowling, S. Lee Association Between the Relaxation of Public Health and Social Measures and Transmission of the SARS-CoV-2 Omicron Variant in South Korea JAMA Network(2022)
  8. J. Kim, S. Lee, H. Kim Booster Vaccination Strategies for “Living With COVID-19” frontiers in Public Health (2022)
  9. Sunmi Lee, Chang Yong Han, Minseok Kim and Yun Kang “Optimal control of a discrete-time plant–herbivore/pest model with bistability in fluctuating environments” Mathematical Biosciences and Engineering (2022)
  10. J. Jeon, C. Han, T. Kim, S. Lee. “Evolution of responses to COVID-19 and epidemiological characteristics in South Korea”, International Journal of Environmental Research and Public Health (2022)
  11. Y. Kim, S. Lee “#ShoutYourAbortion on Instagram: Exploring the visual representation of hashtag movement and the public’s responses”, SAGE Open (2022)
  12. Kim, D.; Ali, S.T.; Kim, S.; Jo, J.; Lim, J.; Lee, S.; Ryu, S. “Estimation of Serial Interval and Reproduction Number to Quantify the Transmissibility of SARS-CoV-2 Omicron Variant in South Korea”, Viruses (2022)
  13. S. Kim, M. Kim, S. Lee, Y. Lee. “Discovering spatiotemporal patterns of COVID-19 pandemic in South Korea”, Scientific Reports (2021)
  14. H. Lee, C. Han, J. Jung, S. Lee. “Analysis of Superspreading Potential from Transmission Clusters of COVID-19 in South Korea”, International Journal of Environmental Research and Public Health (2021)
  15. H. Lee, Y. Kim, E. Kim, S. Lee. “Risk assessment of importation and local transmission of COVID-19 in South Korea: Statistical modeling approach”, JMIR Public Health and Surveillance (2021)
  16. Y. Kim, S. Lee, “Personality of public health organizations’ instagram accounts and according differences in photos at content and pixel levels”, International Journal of Environmental Research and Public Health (2021)
  17. S. Lee, et al. “Age-specific mathematical model for tuberculosis transmission dynamics in South Korea”, Mathematics (2021)
  18. Y. Kim, et al. “Effectiveness of intervention strategies on MERS-CoV transmission dynamics in South Korea, 2015: Simulations on the network based on the real-world contact data” International Journal of Environmental Research and Public Health (2021)
  19. A.M. Fernando, et al. “The seasonal reproduction number of p.vivax malaria dynamics in Korea”, Mathematics and Statistics (2021)
  20. H. Ryu, et al. “Assessing the Effectiveness of Isolation and Contact-Tracing Interventions for Early Transmission Dynamics of COVID-19 in South Korea”, IEEE ACCESS (2021)
  21. B. Kim, et al. “Mathematical Model of COVID-19 Transmission Dynamics in South Korea: The Impacts of Travel Restrictions, Social Distancing, and Early Detection”, Processes8.10 (2020).
  22. S. Choe, H. Kim, and S. Lee. “Exploration of Superspreading Events in 2015 MERS-CoV Outbreak in Korea by Branching Process Models”, International Journal of Environmental Research and Public Health 17.17 (2020).
  23. S. Lee, et al. “Resource Allocation in Two-Patch Epidemic Model with State-Dependent Dispersal Behaviors Using Optimal Control”, Processes 8.9 (2020).
  24. Y. Kim, et al. “Joint Demosaicing and Denoising Based on Interchannel Nonlocal Mean Weighted Moving Least Squares Method”, Sensors 20.17 (2020).
  25. J. Kim, et al. “A Two-Patch Mathematical Model for Temperature-Dependent Dengue Transmission Dynamics”, Processes (2020): 8(7), 781; https://doi.org/10.3390/pr8070781.
  26. Y. Kim, A. Barber, S. Lee, “Modeling influenza transmission dynamics with media coverage data of the 2009 H1N1 outbreak in Korea” PloS one, v.15, no.6, pp.e0232580 (2020).
  27. Y. Kim, S. Lee, “Exploration of the Characteristics of Emotion Distribution in Korean TV Series: Common Pattern and Statistical Complexity”, IEEE Access, v.8, pp.69438-69447 (2020).
  28. A. V. Barber, S. Lee, “Integro-differential age-structured system for influenza transmission dynamics”, Mathematics and Statistics, v.7, no.1, pp.14-24 (2019).
  29. D. Murillo, A. Murillo, and S. Lee, “The Role of Vertical Transmission in the Control of Dengue Fever”, International Journal of Environmental Research and Public Health, v.16, no.5 (2019).
  30. Y. Kim, H. Ryu, S. Lee, “Agent-based modeling for supersupreading events: A case study of MERS-CoV transmission dynamics in the Republic of Korea.” International Journal of Environmental Research and Public Health 15, (2018): 2369, 1-17.
  31. H.D. Toro-Zapata, S. Lee et al. “The role of immune response in optimal HIV treatment interventions”, Processes (2018): 6, 102; 1-16.
  32. J. Kim, H. Lee, S. Lee, C. Lee, “Potential effects of climate change on dengue transmission dynamics in Korea”, PloS one (2018).
  33. S. Lee, “Dynamics of trapped solitary waves for the forced KdV equation,” SYMMETRY-BASEL (2018).
  34. E. Barrios, S. Lee, O. Vasilieva, “Assessing the effects of daily commuting in two-patch dengue dynamics: A case study of Cali, Colombia”, Journal of Theoretical Biology (2018).
  35. H. Kim, S. Lee et al. “Cost-Benefit Analysis of Malaria Chemoprophylaxis and Early Diagnosis for Korean Soldiers in Malaria Risk Regions”, JOURNAL OF KOREAN MEDICAL SCIENCE (2018).
  36. J. Kim, S. Lee et al. “Assessment of optimal strategies in a two-patch dengue transmission model with seasonality”, PLOS ONE (2017).
  37. K. Lee, S. Lee, H. Shin, “Extended phase-matching properties of periodically poled potassium niobate crystals for mid-infrared polarization-entangled photon-pair generation”, Applied optics (2016).
  38. H. Kim, S. Lee, “Explicit solutions of the fifth-order KdV type nonlinear evolution equation using the system technique”, Results in physics (2016).
  39. S. Lee, G. Chowell, “Exploring optimal control strategies in seasonally varying flu-like epidemics”, Journal of Theoretical Biology, (2016).
  40. S. Whang, S. Lee, “Fully localized solitary waves for the forced Kadomtsev-Petviashvili equation”, Computers and Mathematics with Applications, (2016).
  41. H. Lee H, S. Lee, C. Lee, “Stochastic Methods for Epidemic Models: An Application to the 2009 H1N1 Influenza outbreak in Korea”, Applied Mathematics and Computation, (2016): 7(1), 49-55.
  42. Y. Kim, S. Lee et al. “The Characteristics of Middle Eastern Respiratory Syndrome Coronavirus Transmission Dynamics in South Korea”, Osong Public Health and Research Perspectives. (2016): 7(1), 49-55.
  43. S. Choe, S. Lee, “Modeling optimal treatment strategies in a heterogeneous mixing model” Theoretical Biology and Medical Modelling (2015): 12:28.
  44. G. Chowell, S. Lee et al. “Transmission characteristics of MERS and SARS in the healthcare setting: a comparative study” BMC MEDICINE (2015): 13:210.
  45. S. Lee, C. Castillo-Chavez, “The role of residence times in two-patch dengue transmission dynamics and optimal strategies”  Journal of Theoretical Biology 7;374 (2015): 152-164.
  46. C. Chu, S. Lee et al, “Assessment of intensive vaccination and antiviral treatment in 2009 influenza Pandemic in Korea” Osong Public Health and Research Perspectives. (2015): 6(1), 47-51.
  47. S. Lee, S. Whang, “Trapped supercritical waves of the forced KdV equation with two bumps”, Applied Mathematical Modelling. (2015): 39 2649-2660.
  48. J. Choi, S. Lee et al. “Assessment of the intensive countermeasures in the 2009 pandemic influenza in Korea”, Osong Public Health and Research Perspectives (2014).
  49. H.D. Toro-Zapata, A. Caicedo-Casso, B. Derdei, S. Lee, “The role of active and inactive cytotoxic immune response in the HIV dynamics within a host”, Osong Public Health and Research Perspectives. (2014).
  50. S. Kim, S. Lee et al, “What does a mathematical model tell about the impact of reinfection in Korean tuberculosis infection?” Osong Public Health and Research Perspectives. (2014).
  51. S. Yi, S. Lee, “A Locally Conservative Eulerian–Lagrangian Finite Difference Method for the forced KdV equation”. Applied Mathematics and Computation, Volume 230, 1 March p.276-289 (2014).
  52. P. Gonzalez–Parra, M. Ceberio, S. Lee, C. Castillo–Chavez, “Optimal Control for a Discrete Time Influenza Model” Advances in Computational Biology. Advances in Intelligent Systems and Computing. Volume 232, p.231-237 (2014).
  53. C. Castillo-Chavez, S. Lee, “Epidemiology Modeling” Chapter in Encyclopedia of Applied and Computational Mathematics (Björn Chan T. Engquist, W. J. Cook, E. Hairer, J. Hastad, A. Iserles, H.P. Langtangen, C. Le Bris, P.L. Lions, C. Lubich, A.J. Majda, J. McLaughlin, R. M. Nieminen, J. ODEN, P. Souganidis, A. Tveito, eds.), Springer-Verlag Berlin and Heidelberg GmbH & Co. K, (2013).
  54. S. Lee, M. Golinski, G. Chowell. “Modeling optimal age-specific vaccination strategies against pandemic”, Bulletin of Mathematical Biology, v.74, no.4, pp.958-980 (2012).
  55. S. Lee, R. Morales-Rosado, C. Castillo-Chavez, A note on the use of influenza vaccination strategies when supply is limited. Mathematical Biosciences and Engineering. Vol.8, No.1 p.171-182 (2011).
  56. P. Gonzalez-Parra, S. Lee, C. Castillo-Chavez, L. Velazquez, A note on the use of optimal control on a discrete time model of influenza. Mathematical Biosciences and Engineering. Vol.8, No.1 p.183-197 (2011).
  57. S. Lee, E. Jung, C. Castillo-Chavez, Optimal control intervention strategies in low and high-risk problem drinking populations. Socio-Economic Planning Science. Vol.44, Issue 4 p.258-265 (2010).
  58. S. Lee, G. Chowell, C. Castillo-Chavez, Optimal control of influenza pandemics: The role of antiviral treatment and isolation. Journal of Theoretical Biology. 265, p.136-150 (2010).
  59. W. Lee, E. Jung, S. Lee, Simulations of valveless pumping in an open elastic tube. SIAM J. Sci. Comput. Vol. 31, Issue 3 p.1901-1925 (2009).
  60. S. Lee, E. Jung, A two-chamber model of valveless pumping using the Immersed Boundary Method. Appl. Math.Compt. 206 p.876-884 (2008).
  61. E. Jung, S. Lim, W. Lee, S. Lee, Computational models of valveless pumping using the Immersed Boundary Method.  Compt. Methods Appl. Mech. Engrg. 197 p.2329-2339 (2008).
  62. S. Whang, S. Lee, Absorbing boundary conditions for the stationary forced KdV equation. Applied Mathematics and Computation. 202 p.511-519 (2008).
  63. S. Lee, R. Caflisch, Y. Lee, Exact artificial boundary conditions for continuum and discrete elasticity.  SIAM J. Applied Math.  Vol. 66, No. 5 p.1749-1775 (2006).
  64. S. Lee, Artificial boundary conditions for linear elasticity and atomistic strain models. Ph. D thesis (2005) UCLA.