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Predicting the impact of control strategies on the tuberculosis burden in South and North Korea using a mathematical model

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dc.contributor.author강영애-
dc.contributor.author박영목-
dc.contributor.author염준섭-
dc.contributor.author최준용-
dc.date.accessioned2021-11-19T01:38:35Z-
dc.date.available2021-11-19T01:38:35Z-
dc.date.issued2021-10-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/185959-
dc.description.abstractBackground: Among high-income countries, South Korea has a considerable tuberculosis (TB) burden; North Korea has one of the highest TB burdens in the world. Predicting the impact of control strategies on the TB burden can help to efficiently implement TB control programmes. Methods: We designed a deterministic compartmental model of TB in Korea. After calibration with notification of incidence data from South Korea, the TB burden for 2040 was predicted according to four different intervention strategies: latent TB infection (LTBI) treatment, rapid diagnosis, active case-finding and improvement of the treatment success rate. North Korea's burden in 2040 was similarly estimated by adjusting the model parameters. Results: In South Korea, the number of patients with drug-susceptible TB (DS-TB) and multidrug-resistant TB (MDR-TB) were predicted to be 27 581 and 625, respectively, in 2025. Active case-finding would lower DS-TB by 6.2% and MDR-TB by 26.7%, respectively, in 2040. The improvement in the success rate of DS-TB treatment would reduce the MDR-TB burden by 34.5%. In North Korea, the number of patients with DS-TB and MDR-TB are, respectively, predicted to be 77 629 and 5409 in 2025. Active case-finding would reduce DS-TB by 22.2% and MDR-TB by 69.7%. LTBI treatment would reduce DS-TB by 20.6% and MDR-TB by 38.6%. Conclusion: The impact of control strategies on the TB burden in South and North Korea was investigated using a mathematical model. The combined intervention strategies would reduce the burden and active case-finding is expected to result in considerable reduction in both South and North Korea.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherBMJ Publishing Group Ltd.-
dc.relation.isPartOfBMJ GLOBAL HEALTH-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHDemocratic People's Republic of Korea / epidemiology-
dc.subject.MESHHumans-
dc.subject.MESHIncidence-
dc.subject.MESHModels, Theoretical-
dc.subject.MESHTuberculosis* / diagnosis-
dc.subject.MESHTuberculosis* / drug therapy-
dc.subject.MESHTuberculosis* / epidemiology-
dc.subject.MESHTuberculosis, Multidrug-Resistant* / diagnosis-
dc.subject.MESHTuberculosis, Multidrug-Resistant* / drug therapy-
dc.subject.MESHTuberculosis, Multidrug-Resistant* / epidemiology-
dc.titlePredicting the impact of control strategies on the tuberculosis burden in South and North Korea using a mathematical model-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Internal Medicine (내과학교실)-
dc.contributor.googleauthorHyunwoo Cho-
dc.contributor.googleauthorYoungmok Park-
dc.contributor.googleauthorJeongjoo Seok-
dc.contributor.googleauthorJoon Sup Yeom-
dc.contributor.googleauthorJun Yong Choi-
dc.contributor.googleauthorHee Jin Kim-
dc.contributor.googleauthorYoung Ae Kang-
dc.contributor.googleauthorJeehyun Lee-
dc.identifier.doi10.1136/bmjgh-2021-005953-
dc.contributor.localIdA00057-
dc.contributor.localIdA05828-
dc.contributor.localIdA02353-
dc.contributor.localIdA04191-
dc.relation.journalcodeJ03647-
dc.identifier.eissn2059-7908-
dc.identifier.pmid34620614-
dc.subject.keywordcontrol strategies-
dc.subject.keywordmathematical modelling-
dc.subject.keywordtuberculosis-
dc.contributor.alternativeNameKang, Young Ae-
dc.contributor.affiliatedAuthor강영애-
dc.contributor.affiliatedAuthor박영목-
dc.contributor.affiliatedAuthor염준섭-
dc.contributor.affiliatedAuthor최준용-
dc.citation.volume6-
dc.citation.number10-
dc.citation.startPagee005953-
dc.identifier.bibliographicCitationBMJ GLOBAL HEALTH, Vol.6(10) : e005953, 2021-10-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers

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