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Sunmi Lee 5 Articles
The Characteristics of Middle Eastern Respiratory Syndrome Coronavirus Transmission Dynamics in South Korea
Yunhwan Kim, Sunmi Lee, Chaeshin Chu, Seoyun Choe, Saeme Hong, Youngseo Shin
Osong Public Health Res Perspect. 2016;7(1):49-55.   Published online February 28, 2016
DOI: https://doi.org/10.1016/j.phrp.2016.01.001
  • 2,745 View
  • 24 Download
  • 59 Citations
AbstractAbstract PDF
Objectives
The outbreak of Middle Eastern respiratory syndrome coronavirus (MERS-CoV) was one of the major events in South Korea in 2015. In particular, this study pays attention to formulating a mathematical model for MERS transmission dynamics and estimating transmission rates.
Methods
Incidence data of MERS-CoV from the government authority was analyzed for the first aim and a mathematical model was built and analyzed for the second aim of the study. A mathematical model for MERS-CoV transmission dynamics is used to estimate the transmission rates in two periods due to the implementation of intensive interventions.
Results
Using the estimates of the transmission rates, the basic reproduction number was estimated in two periods. Due to the superspreader, the basic reproduction number was very large in the first period; however, the basic reproduction number of the second period has reduced significantly after intensive interventions.
Conclusion
It turned out to be the intensive isolation and quarantine interventions that were the most critical factors that prevented the spread of the MERS outbreak. The results are expected to be useful to devise more efficient intervention strategies in the future.

Citations

Citations to this article as recorded by  
  • On the analysis of Caputo fractional order dynamics of Middle East Lungs Coronavirus (MERS-CoV) model
    Qura Tul Ain, Naveed Anjum, Anwarud Din, Anwar Zeb, Salih Djilali, Zareen A. Khan
    Alexandria Engineering Journal.2022; 61(7): 5123.     CrossRef
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    AIP Advances.2022; 12(3): 035349.     CrossRef
  • MODELING FRACTIONAL-ORDER DYNAMICS OF MERS-COV VIA MITTAG-LEFFLER LAW
    HAIDONG QU, MATI UR RAHMAN, YE WANG, MUHAMMAD ARFAN, ADNAN
    Fractals.2022;[Epub]     CrossRef
  • Distinguishing viruses responsible for influenza-like illness
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    Journal of Theoretical Biology.2022; 545: 111145.     CrossRef
  • ON THE ANALYSIS OF FRACTAL-FRACTIONAL ORDER MODEL OF MIDDLE EAST RESPIRATION SYNDROME CORONAVIRUS (MERS-CoV) UNDER CAPUTO OPERATOR
    LEI ZHANG, TAREQ SAEED, MIAO-KUN WANG, NUDRAT AAMIR, MUHAMMAD IBRAHIM
    Fractals.2022;[Epub]     CrossRef
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    Tariq Mahmood, Fuad S. Al-Duais, Mei Sun
    Physica A: Statistical Mechanics and its Applicati.2022; 606: 128144.     CrossRef
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    Kahkashan Mahreen, Qura Tul Ain, Gauhar Rahman, Bahaaeldin Abdalla, Kamal Shah, Thabet Abdeljawad
    AIMS Mathematics.2022; 7(10): 19267.     CrossRef
  • Modeling and Dynamics of the Fractional Order SARS-CoV-2 Epidemiological Model
    Tahir Khan, Roman Ullah, Ali Yousef, Gul Zaman, Qasem M. Al-Mdallal, Yasser Alraey, M. De Aguiar
    Complexity.2022; 2022: 1.     CrossRef
  • Product of natural evolution (SARS, MERS, and SARS-CoV-2); deadly diseases, from SARS to SARS-CoV-2
    Mohamad Hesam Shahrajabian, Wenli Sun, Qi Cheng
    Human Vaccines & Immunotherapeutics.2021; 17(1): 62.     CrossRef
  • Analysis of the fractional corona virus pandemic via deterministic modeling
    Nguyen Huy Tuan, Vo Viet Tri, Dumitru Baleanu
    Mathematical Methods in the Applied Sciences.2021; 44(1): 1086.     CrossRef
  • Mathematical analysis of SIRD model of COVID-19 with Caputo fractional derivative based on real data
    Kottakkaran Sooppy Nisar, Shabir Ahmad, Aman Ullah, Kamal Shah, Hussam Alrabaiah, Muhammad Arfan
    Results in Physics.2021; 21: 103772.     CrossRef
  • COVID-19 outbreak, social distancing and mass testing in Kenya-insights from a mathematical model
    Rachel Waema Mbogo, John W. Odhiambo
    Afrika Matematika.2021; 32(5-6): 757.     CrossRef
  • Fractal-fractional mathematical modeling and forecasting of new cases and deaths of COVID-19 epidemic outbreaks in India
    Mansour A. Abdulwasaa, Mohammed S. Abdo, Kamal Shah, Taher A. Nofal, Satish K. Panchal, Sunil V. Kawale, Abdel-Haleem Abdel-Aty
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  • Mathematical analysis of COVID-19 via new mathematical model
    Abdullah, Saeed Ahmad, Saud Owyed, Abdel-Haleem Abdel-Aty, Emad E. Mahmoud, Kamal Shah, Hussam Alrabaiah
    Chaos, Solitons & Fractals.2021; 143: 110585.     CrossRef
  • Modeling the transmission dynamics of middle eastern respiratory syndrome coronavirus with the impact of media coverage
    BiBi Fatima, Manar A. Alqudah, Gul Zaman, Fahd Jarad, Thabet Abdeljawad
    Results in Physics.2021; 24: 104053.     CrossRef
  • Theoretical and numerical analysis for transmission dynamics of COVID-19 mathematical model involving Caputo–Fabrizio derivative
    Sabri T. M. Thabet, Mohammed S. Abdo, Kamal Shah
    Advances in Difference Equations.2021;[Epub]     CrossRef
  • A computational tool for trend analysis and forecast of the COVID-19 pandemic
    Henrique Mohallem Paiva, Rubens Junqueira Magalhães Afonso, Fabiana Mara Scarpelli de Lima Alvarenga Caldeira, Ester de Andrade Velasquez
    Applied Soft Computing.2021; 105: 107289.     CrossRef
  • Assessment of Prediction Models of Confirmed, Recovered and Deceased cases due to COVID-19
    P Rakshit, S Debnath, J Mistri, S Kumar
    Journal of Physics: Conference Series.2021; 1797(1): 012004.     CrossRef
  • Modeling the dynamics of novel coronavirus (COVID-19) via stochastic epidemic model
    Tahir Khan, Gul Zaman, Youssef El-Khatib
    Results in Physics.2021; 24: 104004.     CrossRef
  • Middle East respiratory syndrome coronavirus – The need for global proactive surveillance, sequencing and modeling
    Jaffar A. Al-Tawfiq, Eskild Petersen, Ziad A. Memish, Stanley Perlman, Alimuddin Zumla
    Travel Medicine and Infectious Disease.2021; 43: 102118.     CrossRef
  • Mathematical model of COVID-19 in Nigeria with optimal control
    Adesoye Idowu Abioye, Olumuyiwa James Peter, Hammed Abiodun Ogunseye, Festus Abiodun Oguntolu, Kayode Oshinubi, Abdullahi Adinoyi Ibrahim, Ilyas Khan
    Results in Physics.2021; 28: 104598.     CrossRef
  • The Effect of Feedback Controls on Stability in a Fractional-Order SI Epidemic Model
    Saad Z. Rida, Ahmed A. Farghaly, Fatma Hussien
    International Journal of Applied and Computational.2021;[Epub]     CrossRef
  • Superspreading and heterogeneity in transmission of SARS, MERS, and COVID-19: A systematic review
    Jingxuan Wang, Xiao Chen, Zihao Guo, Shi Zhao, Ziyue Huang, Zian Zhuang, Eliza Lai-yi Wong, Benny Chung-Ying Zee, Marc Ka Chun Chong, Maggie Haitian Wang, Eng Kiong Yeoh
    Computational and Structural Biotechnology Journal.2021; 19: 5039.     CrossRef
  • Middle East Respiratory Syndrome Coronavirus
    Jaffar A. Al-Tawfiq, Esam I. Azhar, Ziad A. Memish, Alimuddin Zumla
    Seminars in Respiratory and Critical Care Medicine.2021; 42(06): 828.     CrossRef
  • Early warning signal reliability varies with COVID-19 waves
    Duncan A. O'Brien, Christopher F. Clements
    Biology Letters.2021;[Epub]     CrossRef
  • Epidemiology of Coronavirus COVID-19: Forecasting the Future Incidence in Different Countries
    Johannes Stübinger, Lucas Schneider
    Healthcare.2020; 8(2): 99.     CrossRef
  • Super-spreading events and contribution to transmission of MERS, SARS, and SARS-CoV-2 (COVID-19)
    J.A. Al-Tawfiq, A.J. Rodriguez-Morales
    Journal of Hospital Infection.2020; 105(2): 111.     CrossRef
  • Mathematical modeling of COVID-19 transmission dynamics with a case study of Wuhan
    Faïçal Ndaïrou, Iván Area, Juan J. Nieto, Delfim F.M. Torres
    Chaos, Solitons & Fractals.2020; 135: 109846.     CrossRef
  • A Generalized Overview of SARS-CoV-2: Where Does the Current Knowledge Stand?
    Hiya Islam, Ahsab Rahman, Jaasia Masud, Dipita Saha Shweta, Yusha Araf, Md. Asad Ullah, Syed Muktadir Al Sium, Bishajit Sarkar
    Electronic Journal of General Medicine.2020; 17(6): em251.     CrossRef
  • Optimal control strategies for the transmission risk of COVID-19
    Legesse Lemecha Obsu, Shiferaw Feyissa Balcha
    Journal of Biological Dynamics.2020; 14(1): 590.     CrossRef
  • A data-driven model to describe and forecast the dynamics of COVID-19 transmission
    Henrique Mohallem Paiva, Rubens Junqueira Magalhães Afonso, Igor Luppi de Oliveira, Gabriele Fernandes Garcia, Martin Chtolongo Simuunza
    PLOS ONE.2020; 15(7): e0236386.     CrossRef
  • SEIR model for COVID-19 dynamics incorporating the environment and social distancing
    Samuel Mwalili, Mark Kimathi, Viona Ojiambo, Duncan Gathungu, Rachel Mbogo
    BMC Research Notes.2020;[Epub]     CrossRef
  • Controlling the Spread of COVID-19: Optimal Control Analysis
    Chinwendu E. Madubueze, Sambo Dachollom, Isaac Obiajulu Onwubuya
    Computational and Mathematical Methods in Medicine.2020; 2020: 1.     CrossRef
  • Fractional order mathematical modeling of COVID-19 transmission
    Shabir Ahmad, Aman Ullah, Qasem M. Al-Mdallal, Hasib Khan, Kamal Shah, Aziz Khan
    Chaos, Solitons & Fractals.2020; 139: 110256.     CrossRef
  • Exploration of Superspreading Events in 2015 MERS-CoV Outbreak in Korea by Branching Process Models
    Seoyun Choe, Hee-Sung Kim, Sunmi Lee
    International Journal of Environmental Research an.2020; 17(17): 6137.     CrossRef
  • Study of transmission dynamics of COVID-19 mathematical model under ABC fractional order derivative
    Sabri T.M. Thabet, Mohammed S. Abdo, Kamal Shah, Thabet Abdeljawad
    Results in Physics.2020; 19: 103507.     CrossRef
  • A New Compartmental Epidemiological Model for COVID-19 with a Case Study of Portugal
    Ana P. Lemos-Paião, Cristiana J. Silva, Delfim F.M. Torres
    Ecological Complexity.2020; 44: 100885.     CrossRef
  • Mathematical modeling, analysis, and simulation of the COVID-19 pandemic with explicit and implicit behavioral changes
    Comfort Ohajunwa, Kirthi Kumar, Padmanabhan Seshaiyer
    Computational and Mathematical Biophysics.2020; 8(1): 216.     CrossRef
  • Comparative Analysis of Eleven Healthcare-Associated Outbreaks of Middle East Respiratory Syndrome Coronavirus (Mers-Cov) from 2015 to 2017
    Sibylle Bernard-Stoecklin, Birgit Nikolay, Abdullah Assiri, Abdul Aziz Bin Saeed, Peter Karim Ben Embarek, Hassan El Bushra, Moran Ki, Mamunur Rahman Malik, Arnaud Fontanet, Simon Cauchemez, Maria D. Van Kerkhove
    Scientific Reports.2019;[Epub]     CrossRef
  • Development of a recombinant replication-deficient rabies virus-based bivalent-vaccine against MERS-CoV and rabies virus and its humoral immunogenicity in mice
    Hirofumi Kato, Mutsuyo Takayama-Ito, Itoe Iizuka-Shiota, Shuetsu Fukushi, Guillermo Posadas-Herrera, Madoka Horiya, Masaaki Satoh, Tomoki Yoshikawa, Souichi Yamada, Shizuko Harada, Hikaru Fujii, Miho Shibamura, Takuya Inagaki, Kinjiro Morimoto, Masayuki S
    PLOS ONE.2019; 14(10): e0223684.     CrossRef
  • Healthcare-associated infections: the hallmark of Middle East respiratory syndrome coronavirus with review of the literature
    J.A. Al-Tawfiq, P.G. Auwaerter
    Journal of Hospital Infection.2019; 101(1): 20.     CrossRef
  • Middle East respiratory syndrome coronavirus in pediatrics: a report of seven cases from Saudi Arabia
    Sarah H. Alfaraj, Jaffar A. Al-Tawfiq, Talal A. Altuwaijri, Ziad A. Memish
    Frontiers of Medicine.2019; 13(1): 126.     CrossRef
  • Asymptomatic Middle East Respiratory Syndrome Coronavirus (MERS-CoV) infection: Extent and implications for infection control: A systematic review
    Jaffar A. Al-Tawfiq, Philippe Gautret
    Travel Medicine and Infectious Disease.2019; 27: 27.     CrossRef
  • Clinical predictors of mortality of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) infection: A cohort study
    Sarah H. Alfaraj, Jaffar A. Al-Tawfiq, Ayed Y. Assiri, Nojoom A. Alzahrani, Amal A. Alanazi, Ziad A. Memish
    Travel Medicine and Infectious Disease.2019; 29: 48.     CrossRef
  • Practical Guidance for Clinical Microbiology Laboratories: Viruses Causing Acute Respiratory Tract Infections
    Carmen L. Charlton, Esther Babady, Christine C. Ginocchio, Todd F. Hatchette, Robert C. Jerris, Yan Li, Mike Loeffelholz, Yvette S. McCarter, Melissa B. Miller, Susan Novak-Weekley, Audrey N. Schuetz, Yi-Wei Tang, Ray Widen, Steven J. Drews
    Clinical Microbiology Reviews.2018;[Epub]     CrossRef
  • Agent-Based Modeling for Super-Spreading Events: A Case Study of MERS-CoV Transmission Dynamics in the Republic of Korea
    Yunhwan Kim, Hohyung Ryu, Sunmi Lee
    International Journal of Environmental Research an.2018; 15(11): 2369.     CrossRef
  • Evaluation of visual triage for screening of Middle East respiratory syndrome coronavirus patients
    S.H. Alfaraj, J.A. Al-Tawfiq, P. Gautret, M.G. Alenazi, A.Y. Asiri, Z.A. Memish
    New Microbes and New Infections.2018; 26: 49.     CrossRef
  • A multi-faceted approach of a nursing led education in response to MERS-CoV infection
    Jaffar A. Al-Tawfiq, Siobhan Rothwell, Heather A. Mcgregor, Zeina A. Khouri
    Journal of Infection and Public Health.2018; 11(2): 260.     CrossRef
  • MERS transmission and risk factors: a systematic review
    Ji-Eun Park, Soyoung Jung, Aeran Kim, Ji-Eun Park
    BMC Public Health.2018;[Epub]     CrossRef
  • Working experiences of nurses during the Middle East respiratory syndrome outbreak
    Hee Sun Kang, Ye Dong Son, Sun-Mi Chae, Colleen Corte
    International Journal of Nursing Practice.2018; 24(5): e12664.     CrossRef
  • Disaster medicine: current status and future directions of emergency medical team for overseas disaster crisis
    Minhong Choa, Jiyoung Noh, Hyun Soo Chung
    Journal of the Korean Medical Association.2017; 60(2): 149.     CrossRef
  • Estimating and modelling the transmissibility of Middle East Respiratory Syndrome CoronaVirus during the 2015 outbreak in the Republic of Korea
    Xu-Sheng Zhang, Richard Pebody, Andre Charlett, Daniela de Angelis, Paul Birrell, Hunseok Kang, Marc Baguelin, Yoon Hong Choi
    Influenza and Other Respiratory Viruses.2017; 11(5): 434.     CrossRef
  • Influenza is more common than Middle East Respiratory Syndrome Coronavirus (MERS-CoV) among hospitalized adult Saudi patients
    Jaffar A. Al-Tawfiq, Ali A. Rabaan, Kareem Hinedi
    Travel Medicine and Infectious Disease.2017; 20: 56.     CrossRef
  • Dynamics of scientific publications on the MERS-CoV outbreaks in Saudi Arabia
    Ali A. Rabaan, Shamsah H. Al-Ahmed, Ali M. Bazzi, Jaffar A. Al-Tawfiq
    Journal of Infection and Public Health.2017; 10(6): 702.     CrossRef
  • Effects of Timely Control Intervention on the Spread of Middle East Respiratory Syndrome Coronavirus Infection
    Ilsu Choi, Dong Ho Lee, Yongkuk Kim
    Osong Public Health and Research Perspectives.2017; 8(6): 373.     CrossRef
  • Serologic responses of 42 MERS-coronavirus-infected patients according to the disease severity
    Jae-Hoon Ko, Marcel A. Müller, Hyeri Seok, Ga Eun Park, Ji Yeon Lee, Sun Young Cho, Young Eun Ha, Jin Yang Baek, So Hyun Kim, Ji-Man Kang, Yae-Jean Kim, Ik Joon Jo, Chi Ryang Chung, Myong-Joon Hahn, Christian Drosten, Cheol-In Kang, Doo Ryeon Chung, Jae-H
    Diagnostic Microbiology and Infectious Disease.2017; 89(2): 106.     CrossRef
  • Predictive factors for pneumonia development and progression to respiratory failure in MERS-CoV infected patients
    Jae-Hoon Ko, Ga Eun Park, Ji Yeon Lee, Ji Yong Lee, Sun Young Cho, Young Eun Ha, Cheol-In Kang, Ji-Man Kang, Yae-Jean Kim, Hee Jae Huh, Chang-Seok Ki, Byeong-Ho Jeong, Jinkyeong Park, Chi Ryang Chung, Doo Ryeon Chung, Jae-Hoon Song, Kyong Ran Peck
    Journal of Infection.2016; 73(5): 468.     CrossRef
  • Middle East respiratory syndrome coronavirus disease is rare in children: An update from Saudi Arabia
    Jaffar A Al-Tawfiq, Rana F Kattan, Ziad A Memish
    World Journal of Clinical Pediatrics.2016; 5(4): 391.     CrossRef
Assessment of Intensive Vaccination and Antiviral Treatment in 2009 Influenza Pandemic in Korea
Chaeshin Chu, Sunmi Lee
Osong Public Health Res Perspect. 2015;6(1):47-51.   Published online February 28, 2015
DOI: https://doi.org/10.1016/j.phrp.2014.11.007
  • 1,798 View
  • 16 Download
  • 2 Citations
AbstractAbstract PDF
Objectives
We characterized and assessed public health measures, including intensive vaccination and antiviral treatment, implemented during the 2009 influenza pandemic in the Republic of Korea.
Methods
A mathematical model for the 2009 influenza pandemic is formulated. The transmission rate, the vaccination rate, the antiviral treatment rate, and the hospitalized rate are estimated using the least-squares method for the 2009 data of the incidence curves of the infected, vaccinated, treated, and hospitalized.
Results
The cumulative number of infected cases has reduced significantly following the implementation of the intensive vaccination and antiviral treatment. In particular, the intensive vaccination was the most critical factor that prevented severe outbreak.
Conclusion
We have found that the total infected proportion would increase by approximately six times under the half of vaccination rates.

Citations

Citations to this article as recorded by  
  • Modeling influenza transmission dynamics with media coverage data of the 2009 H1N1 outbreak in Korea
    Yunhwan Kim, Ana Vivas Barber, Sunmi Lee, Roberto Barrio
    PLOS ONE.2020; 15(6): e0232580.     CrossRef
  • Doing Mathematics with Aftermath of Pandemic Influenza 2009
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2015; 6(1): 1.     CrossRef
Assessment of the Intensive Countermeasures in the 2009 Pandemic Influenza in Korea
Jin Hyuk Choi, Yunhwan Kim, Seoyun Choe, Sunmi Lee
Osong Public Health Res Perspect. 2014;5(2):101-107.   Published online April 30, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.03.003
  • 1,768 View
  • 17 Download
AbstractAbstract PDF
Objectives
It is critical to implement effective multiple countermeasures to mitigate or retain the spread of pandemic influenza. We propose a mathematical pandemic influenza model to assess the effectiveness of multiple countermeasures implemented in 2009.
Methods
Age-specific parameters, including the transmission rate, the proportion of asymptomatic individuals, the vaccination rate, the social distancing rate, and the antiviral treatment rate are estimated using the least-square method calibrated to the incidence data.
Results
The multiple interventions (intensive vaccination, social distancing, antivrial treatment) were successfully implemented resulting in the dramatic reduction in the total number of incidence.
Conclusion
The model output is sensitive to age-specific parameters and this leads to the fact that a more elaborate age group model should be developed and extensive further studies must be followed.
What Does a Mathematical Model Tell About the Impact of Reinfection in Korean Tuberculosis Infection?
Sara Kim, Seoyun Choe, Junseong Kim, Sanga Nam, Yeon Shin, Sunmi Lee
Osong Public Health Res Perspect. 2014;5(1):40-45.   Published online February 28, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.01.002
  • 1,885 View
  • 14 Download
  • 7 Citations
AbstractAbstract PDF
Objectives
According to the Korea Centers for Disease Control and Prevention, new active tuberculosis (TB) cases have increased since 2001. Some key factors explain and characterize the transmission dynamics of Korean TB infection, such as a higher ratio of latent individuals and a new reporting system implemented in 2001, among others.
Methods
We propose a mathematical TB model that includes exogenous reinfection to gain a better understanding of the recent trend for TB incidence. We divide the simulation time window into two periods, 1970–2000 and 2001–2012, according to the implementation date of a new TB detection system.
Results
Two sets of parameters, including the transmission rate, the latent period, the recovery rate, and the proportion of exogenous reinfection, are estimated using the least-squares method and calibrated to data on the incidence of active TB.
Conclusion
Among some key parameters in the model, the case finding effort turned out to be the most significant impacting component on the reduction in the active TB cases.

Citations

Citations to this article as recorded by  
  • Mathematical analysis of a two-strain tuberculosis model in Bangladesh
    Md Abdul Kuddus, Emma S. McBryde, Adeshina I. Adekunle, Lisa J. White, Michael T. Meehan
    Scientific Reports.2022;[Epub]     CrossRef
  • Age-Specific Mathematical Model for Tuberculosis Transmission Dynamics in South Korea
    Sunmi Lee, Hae-Young Park, Hohyung Ryu, Jin-Won Kwon
    Mathematics.2021; 9(8): 804.     CrossRef
  • Scenario analysis for programmatic tuberculosis control in Bangladesh: a mathematical modelling study
    Md Abdul Kuddus, Michael T. Meehan, Md. Abu Sayem, Emma S. McBryde
    Scientific Reports.2021;[Epub]     CrossRef
  • Modeling drug-resistant tuberculosis amplification rates and intervention strategies in Bangladesh
    Md Abdul Kuddus, Michael T. Meehan, Lisa J. White, Emma S. McBryde, Adeshina I. Adekunle, Hasnain Seyed Ehtesham
    PLOS ONE.2020; 15(7): e0236112.     CrossRef
  • Predictors of job satisfaction and burnout among tuberculosis management nurses and physicians
    Hae-Suk Seo, Hyunjoong Kim, Se-Min Hwang, Soo Hyun Hong, In-Young Lee
    Epidemiology and Health.2016; 38: e2016008.     CrossRef
  • Is Tuberculosis Still the Number One Infectious Disease in Korea?
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5: S1.     CrossRef
  • Journal Publishing: Never Ending Saga
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5(1): 1.     CrossRef
Role of Active and Inactive Cytotoxic Immune Response in Human Immunodeficiency Virus Dynamics
Hernan Dario Toro Zapata, Angelica Graciela Caicedo Casso, Derdei Bichara, Sunmi Lee
Osong Public Health Res Perspect. 2014;5(1):3-8.   Published online February 28, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.01.001
  • 1,950 View
  • 25 Download
  • 8 Citations
AbstractAbstract PDF
Objectives
Mathematical models can be helpful to understand the complex dynamics of human immunodeficiency virus infection within a host. Most of work has studied the interactions of host responses and virus in the presence of active cytotoxic immune cells, which decay to zero when there is no virus. However, recent research highlights that cytotoxic immune cells can be inactive but never be depleted.
Methods
We propose a mathematical model to investigate the human immunodeficiency virus dynamics in the presence of both active and inactive cytotoxic immune cells within a host. We explore the impact of the immune responses on the dynamics of human immunodeficiency virus infection under different disease stages.
Results
Standard mathematical and numerical analyses are presented for this new model. Specifically, the basic reproduction number is computed and local and global stability analyses are discussed.
Conclusion
Our results can give helpful insights when designing more effective drug schedules in the presence of active and inactive immune responses.

Citations

Citations to this article as recorded by  
  • A Multi-Scale Model for the Spread of HIV in a Population Considering the Immune Status of People
    Sol de Amor Vásquez-Quintero, Hernán Darío Toro-Zapata, Dennis Alexánder Prieto-Medellín
    Processes.2021; 9(11): 1924.     CrossRef
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    John G. Alford, Stephen A. McCoy
    Involve, a Journal of Mathematics.2020; 13(3): 455.     CrossRef
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    Hernán Darío Toro-Zapata, Carlos Andrés Trujillo-Salazar, Edwin Mauricio Carranza-Mayorga
    Processes.2020; 8(7): 782.     CrossRef
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    Hernán Toro-Zapata, Angélica Caicedo-Casso, Sunmi Lee
    Processes.2018; 6(8): 102.     CrossRef
  • Evaluación teórica de estrategias óptimas y sub-óptimas de terapia antirretroviral para el control de la infección por VIH
    Hernán Darío Toro-Zapata, Carlos Andrés Trujillo-Salazar, Dennis Alexánder Prieto-Medellín
    Revista de Salud Pública.2018; 20(1): 117.     CrossRef
  • Summing Up Again
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5(4): 177.     CrossRef
  • Roll the Dice
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5(5): 243.     CrossRef
  • Journal Publishing: Never Ending Saga
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5(1): 1.     CrossRef

PHRP : Osong Public Health and Research Perspectives