Risk factors for active tuberculosis in 938 QuantiFERON-positive schoolchildren in Mongolia: a community-based cross-sectional study.

BACKGROUND: There is controversy regarding the relative influence of 'exogenous' versus 'endogenous' factors on the risk of progression from latent tuberculosis infection to active tuberculosis (TB) disease in children. METHODS: We conducted a cross-sectional analysis to identify risk factors for active tuberculosis in QuantiFERON®-TB Gold (QFT-G)-positive children aged 6-13 years attending 18 schools in Ulaanbaatar, Mongolia. Children underwent clinical and radiological screening for active tuberculosis, and data relating to potential risk factors for disease progression were collected by questionnaire and determination of serum 25-hydroxyvitamin D (25[OH]D) concentrations. Risk ratios were calculated using generalized estimating equations with adjustment for potential confounders. RESULTS: 129/938 (13.8%) QFT-positive children were diagnosed with active tuberculosis. Risk of active tuberculosis was independently associated with household exposure to pulmonary TB (adjusted risk ratio [aRR] 2.40, 95% CI 1.74 to 3.30, P < 0.001), month of sampling (adjusted risk ratio [aRR] for March-May vs. June-November 3.31, 95% CI 1.63 to 6.74, P < 0.001; aRR for December-February vs. June-November 2.53, 95% CI 1.23 to 5.19, P = 0.01) and active smoking by the child (aRR 5.23, 95% CI 2.70 to 10.12, P < 0.001). No statistically significant independent association was seen for age, sex, socio-economic factors, presence of a Bacillus Calmette-Guérin (BCG) scar, tobacco exposure or vitamin D status. CONCLUSIONS: Household exposure to active TB, winter or spring season and active smoking were independently associated with risk of active tuberculosis in QFT-positive children. Our findings highlight the potentially high yield of screening child household contacts of infectious index cases for active tuberculosis in low- and middle-income countries.

Assessing the quality of tuberculosis care using routine surveillance data: a process evaluation employing the Zero TB Indicator Framework in Mongolia.

OBJECTIVES: To evaluate the feasibility of the Zero TB Indicator Framework as a tool for assessing the quality of tuberculosis (TB) case-finding, treatment and prevention services in Mongolia. SETTING: Primary health centres, TB dispensaries, and surrounding communities in four districts of Mongolia. DESIGN: Three retrospective cross-sectional cohort studies, and two longitudinal studies each individually nested in one of the cohort studies. PARTICIPANTS: 15 947 community members from high TB-risk populations; 8518 patients screened for TB in primary health centres and referred to dispensaries; 857 patients with index TB and 2352 household contacts. PRIMARY AND SECONDARY OUTCOME MEASURES: 14 indicators of the quality of TB care defined by the Zero TB Indicator Framework and organised into three care cascades, evaluating community-based active case-finding, passive case-finding in health facilities and TB screening and prevention among close contacts; individual and health-system predictors of these indicators. RESULTS: The cumulative proportions of participants receiving guideline-adherent care varied widely, from 96% for community-based active case-finding, to 79% for TB preventive therapy among household contacts, to only 67% for passive case-finding in primary health centres and TB dispensaries (range: 29%-80% across districts). The odds of patients completing active TB treatment decreased substantially with increasing age (aOR: 0.76 per decade, 95% CI: 0.71 to 0.83, p<0.001) and among men (aOR: 0.56, 95% CI: 0.36 to 0.88, p=0.013). Contacts of older index patients also had lower odds of initiating and completing of TB preventive therapy (aOR: 0.60 per decade, 95% CI: 0.38 to 0.93, p=0.022). CONCLUSIONS: The Zero TB Framework provided a feasible and adaptable approach for using routine surveillance data to evaluate the quality of TB care and identify associated individual and health system factors. Future research should evaluate strategies for collecting process indicators more efficiently; gather qualitative data on explanations for low-quality care; and deploy quality improvement interventions.