Evidence map›Paper›PMID 34620614›Full record

ArticleBMJ global health2021

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

Hyunwoo Cho, Youngmok Park, Jeongjoo Seok, Joon Sup Yeom, Jun Yong Choi, Hee Jin Kim, Young Ae Kang, Jeehyun Lee

Abstract read
In one paragraph

Article in BMJ global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Hyunwoo ChoSchool of Mathematics and Computing, Yonsei University, Seodaemun-gu, South Korea.
Youngmok ParkDepartment of Internal Medicine, Yonsei University College of Medicine, Seodaemun-gu, South Korea.
Jeongjoo SeokSchool of Mathematics and Computing, Yonsei University, Seodaemun-gu, South Korea.
Joon Sup YeomInternal Medicine, Yonsei University College of Medicine, Seoul, South Korea.ORCID 0000-0001-8940-7170
Jun Yong ChoiDepartment of Internal Medicine, Yonsei University College of Medicine, Seodaemun-gu, South Korea.
Hee Jin KimKorean National Tuberculosis Association, Seoul, South Korea.
Young Ae Kang *Department of Internal Medicine, Yonsei University College of Medicine, Seodaemun-gu, South Korea ezhyun@yonsei.ac.kr MDKANG@yuhs.ac.
Jeehyun Lee *School of Mathematics and Computing, Yonsei University, Seodaemun-gu, South Korea ezhyun@yonsei.ac.kr MDKANG@yuhs.ac.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAmong 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.

methodsWe 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.

resultsIn 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%.

conclusionThe 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.

Indexed as

TuberculosisTuberculosis, Multidrug-ResistantDemocratic People's Republic of KoreaHumansIncidenceModels, Theoreticalcontrol strategiesmathematical modellingtuberculosis

Identifiers

PMID34620614
PMCPMC8499335

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