Rising challenge of multidrug-resistant tuberculosis in China: a predictive study using Markov modeling.

Abstract

BACKGROUND:

Multidrug-resistant tuberculosis (MDR-TB) is on the rise in China. This study used a dynamic Markov model to predict the longitudinal trends of MDR-TB in China by 2050 and to assess the effects of alternative control measures.

METHODS:

Eight states of tuberculosis transmission were set up in the Markov model using a hypothetical cohort of 100 000 people. The prevalence of MDR-TB and bacteriologically confirmed drug-susceptible tuberculosis (DS-TB+) were simulated and MDR-TB was stratified into whether the disease was treated with the recommended regimen or not.

RESULTS:

Without any intervention changes to current conditions, the prevalence of DS-TB+ was projected to decline 67.7% by 2050, decreasing to 20 per 100 000 people, whereas that of MDR-TB was expected to triple to 58/100 000. Furthermore, 86.2% of the MDR-TB cases would be left untreated by the year of 2050. In the case where MDR-TB detection rate reaches 50% or 70% at 5% per year, the decline in prevalence of MDR-TB would be 25.9 and 36.2% respectively. In the case where treatment coverage was improved to 70% or 100% at 5% per year, MDR-TB prevalence in 2050 would decrease by 13.8 and 24.1%, respectively. If both detection rate and treatment coverage reach 70%, the prevalence of MDR-TB by 2050 would be reduced to 28/100 000 by a 51.7% reduction.

CONCLUSIONS:

MDR-TB, especially untreated MDR-TB, would rise rapidly under China's current MDR-TB control strategies. Interventions designed to promote effective detection and treatment of MDR-TB are imperative in the fights against MDR-TB epidemics.

• Authors: Bing-Ying Li, Wen-Pei Shi, Chang-Ming Zhou, Qi Zhao, Vinod K Diwan, Xu-Bin Zheng, Yang Li, Sven Hoffner, Biao Xu
• Journal: Infectious diseases of poverty (Infect Dis Poverty) Vol. 9 Issue 1 Pg. 65 (Jun 08 2020) ISSN: 2049-9957 [Electronic] England
• PMID: 32513262 (Publication Type: Journal Article)

Topics

• China (epidemiology)
• Cohort Studies
• Humans
• Markov Chains
• Prevalence
• Tuberculosis, Multidrug-Resistant (epidemiology, microbiology, prevention & control)