Disease burden of tuberculosis under different diagnostic scenarios in China: a dynamic modeling study

Abstract

Objective: Under different diagnostic scenarios, we tried to establish a tuberculosis dynamic model, to predict the incidence burden and to provide evidence for developing the prevention and control programs of tuberculosis. Methods: A systematic dynamic model was established to fit the annual incidence rates of tuberculosis data from the China CDC, between 2005 and 2018. Basic reproductive number (R(0)) was calculated. Impact of different diagnostic scenarios on tuberculosis burden was explored by numerical changes in diagnosis-related parameters. Results: Results from the Chi-square test indicated that the model accuracy appeared as: χ(2)=1.102 (P=1.000). Also, the computed result showed that R(0)=0.063<1, indicating that tuberculosis would gradually be disappearing in China. Approaches that including 'reducing the delayed diagnosis time'or 'improving the timely medical treatment'would end the fluctuations of the number of infectious and hospitalized patients and thus leading to continuous reduction in the number of these patients, in a long run. Conclusions: This model fitted well for the trend of tuberculosis incidence rates between 2005 and 2018. Reducing the delay time in diagnosis and improving the rate of timely medical treatment could effectively reduce the long-term burden of tuberculosis. Improvement of this model would be further explored.