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

BMJ Glob Health. 2021 Oct;6(10):e005953. doi: 10.1136/bmjgh-2021-005953.

Abstract

Background: 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.

Keywords: control strategies; mathematical modelling; tuberculosis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Democratic People's Republic of Korea / epidemiology
  • Humans
  • Incidence
  • Models, Theoretical
  • Tuberculosis* / diagnosis
  • Tuberculosis* / drug therapy
  • Tuberculosis* / epidemiology
  • Tuberculosis, Multidrug-Resistant* / diagnosis
  • Tuberculosis, Multidrug-Resistant* / drug therapy
  • Tuberculosis, Multidrug-Resistant* / epidemiology