Prediction of different interventions on the burden of drug-resistant tuberculosis in China: a dynamic modelling study

Abstract

Tuberculosis (TB) is one of the top 10 causes of death worldwide. The World Health Organization adopted the 'End TB Strategy' to end the global TB epidemic by 2035. However, achieving this goal will be difficult using current measures. A Susceptible-Exposed-Infectious-Recovered (SEIR) model that distinguishes drug-sensitive (DS) and drug-resistant (DR) TB in the entire Chinese population was established. Goodness-of-fit tests and sensitivity analyses were used to assess model performance. Predictive analysis was performed to assess the effect of different prevention and control strategies on DR-TB. We used parameter fitting to determine the basic reproduction number of the model as R0 = 0.6993. The predictive analysis led to two major projections that can achieve the goal by 2035. First, if the progression rate of latently infected people reaches 10%, then there will be 92.2% fewer cases than in 2015. Second, if the cure rate of DR-TB increases to 40%, then there will be 91.5% fewer cases than in 2015. A combination of five interventions could lead to earlier achievement of the 2035 target. We found that reducing the probability of transmission and the rate of disease progression in patients with DR-TB and improving treatment compliance and the cure rate of patients with DR-TB can contribute to attaining the goal of the End TB Strategy.