JMIR Publications

ABSTRACT

Background:

Tuberculosis (TB) remains a major public health concern. Despite improved diagnostic tools, delays in TB diagnosis persist and hinder control efforts.

Objective:

To investigate the spatiotemporal patterns of TB diagnostic delay and identify individual and spatial risk factors in Jiangsu province, China, from 2011 to 2021.

Methods:

This study used data from the Jiangsu Tuberculosis Information Management System from 2011 to 2021, and we decided a TB patient had diagnostic delay if he/she had more than 28 days between symptom onset and diagnosis. A Bayesian spatiotemporal model assessed county-level delay rates and spatial correlation. Logistic regression identified individual-level risk factors.

Results:

Spatial clustering in TB diagnostic delay rates was significant from 2015 onward (Moran’s I = 0.110 to 0.193, p < 0.05). The Bayesian spatiotemporal model, with a 34 % spatial dependency, identified a higher proportion of cross-county patients as a significant spatial driver of delays (posterior mean = -0.379, 95 % CI: -0.657 to -0.010). Males, education workers, and patients diagnosed at local CDCs had lower odds of delay, while elderly individuals, agricultural workers, migrants, clinically diagnosed patients, and those diagnosed at community health centers had higher odds.

Conclusions:

TB diagnostic delays in Jiangsu were influenced by individual and spatial factors. Urban-rural disparities and cross-county mobility contributed to significant spatiotemporal heterogeneity. Tailored interventions targeting high-risk groups and healthcare settings are needed.