LAUSR

Introduction In the past three decades, China has made great strides in the prevention and treatment of tuberculosis (TB). However, the TB burden remains high. In 2019, China accounted for 8.4% of global incident cases of TB, the third highest in the world, with a higher prevalence in rural areas. The Healthy China 2030 highlights the gate-keeping role of primary healthcare (PHC). However, the impact of PHC reforms on the future TB burden is unclear. We propose to use mathematical models to project and evaluate the impacts of different gate-keeping policies. Methods and analysis We will develop a deterministic, population-level, compartmental model to capture the dynamics of TB transmission within adult rural population. The model will incorporate seven main TB statuses, and each compartment will be subdivided by service providers. The parameters involving preference for healthcare seeking will be collected using discrete choice experiment (DCE) method. We will solve the deterministic model numerically over a 20-year (2021–2040) timeframe and predict the TB prevalence, incidence and cumulative new infections under the status quo or various policy scenarios. We will also conduct an analysis following standard protocols to calculate the average cost-effectiveness for each policy scenario relative to the status quo. A numerical calibration analysis against the available published TB prevalence data will be performed using a Bayesian approach. Ethics and dissemination Most of the data or parameters in the model will be obtained based on secondary data (eg, published literature and an open-access data set). The DCE survey has been reviewed and approved by the Ethics Committee of the School of Public Health, Sun Yat-sen University. The approval number is SYSU [2019]140. Results of the study will be disseminated through peer-reviewed journals, media and conference presentations.