SUMMARY
BackgroundSeveral meta-analyses assessing the efficacy of anti-Helicobacter pylori treatment in adults have been published but a comparable meta-analysis in children is lacking.
SUMMARYThe dominant approach to decision-making in public health policy for infectious diseases relies heavily on expert opinion, which often applies empirical evidence to policy questions in a manner that is neither systematic nor transparent. Although systematic reviews are frequently commissioned to inform specific components of policy (such as efficacy), the same process is rarely applied to the full decision-making process. Mathematical models provide a mechanism through which empirical evidence can be methodically and transparently integrated to address such questions. However, such models are often considered difficult to interpret. In addition, models provide estimates that need to be iteratively reevaluated as new data or considerations arise. Using the case study of a novel diagnostic for tuberculosis, a framework for improved collaboration between public health decision-makers and mathematical modellers that could lead to more transparent and evidence-driven policy decisions for infectious diseases in the future is proposed. The framework proposes that policymakers should establish long-term collaborations with modellers to address key questions, and that modellers should strive to provide clear explanations of the uncertainty of model structure and outputs. Doing so will improve the applicability of models and clarify their limitations when used to inform real-world public health policy decisions.
This ET system included an effective patient routing process that provided an efficient way to increase access to STD testing among persons at lower risk, at a reduced cost per patient, while maintaining high treatment coverage.
OBJECTIVES:The tuberculin skin test (TST) has been preferred for screening young children for latent tuberculosis infection (LTBI) because of concerns that interferon-g release assays (IGRAs) may be less sensitive in this high-risk population. In this study, we compared the predictive value of IGRAs to the TST for progression to tuberculosis disease in children, including those ,5 years old.METHODS: Children ,15 years old at risk for LTBI or progression to disease were tested with TST, QuantiFERON-TB Gold In-Tube test (QFT-GIT), and T-SPOT.TB test (T-SPOT) and followed actively for 2 years, then with registry matches, to identify incident disease.RESULTS: Of 3593 children enrolled September 2012 to April 2016, 92% were born outside the United States; 25% were ,5 years old. Four children developed tuberculosis over a median 4.3 years of follow-up. Sensitivities for progression to disease for TST and IGRAs were low (50%-75%), with wide confidence intervals (CIs).
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