Hybrid Approach to Estimation of Underreporting of Tuberculosis Case Notification in High-Burden Settings With Weak Surveillance Infrastructure: Design and Implementation of an Inventory Study

Abstract

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: The greatest risk of infectious disease under-notification occurs in settings with limited capacity to reliably detect it. WHO guidance on measurement of mis-reporting is paradoxical, requiring robust, independent systems to assess surveillance completeness. Objective: Methods are needed to estimate under-notification in settings with weak surveillance systems that do not meet WHO preconditions. This study aims to design tuberculosis (TB) inventory study methods that balance rigor with feasibility for high need settings. Methods: We choose to census most health facilities (HF) and laboratories, restricted reliance upon probability proportional to size sampling to HF types with no capacity to notify. Applying distinct analytical approaches for bacteriologically confirmed versus clinical TB limited the need for extrapolation. At the request of public local health stakeholders, the scope of the TB inventory study methodologies was broadened to include the identification of factors responsible for under-notification and acceptability of potential solutions. Results: Retrospective data collection over longer time horizons minimizes bias due to seasonality and measures “natural” recording and reporting behaviors. Leveraging a priori knowledge, minimizing recourse to inference, manual entry, use of transparent probabilistic linkage methods, incentivizing private sector participation, and cross-border case verification help to generate valid estimates despite challenging conditions. Conclusions: Adaptive study designs permit rigorous, relevant, ethical inventory studies in the countries that need them even in the absence of WHO established preconditions. Use of triangulation techniques, minimizing recourse to extrapolation, and a strategic focus on the practical needs of local stakeholders, yielded reasonable misreporting estimates and, crucially, viable policy recommendations.