Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Jul 9, 2020
Open Peer Review Period: Jul 9, 2020 - Jul 23, 2020
Date Accepted: Dec 8, 2020
(closed for review but you can still tweet)
Methods for estimating under-reporting of TB case notification in high burden settings with weak surveillance infrastructure
ABSTRACT
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.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.