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.

BACKGROUND: The greatest risk of infectious disease undernotification occurs in settings with limited capacity to detect it reliably. World Health Organization guidance on the measurement of misreporting is paradoxical, requiring robust, independent systems to assess surveillance rigor. Methods are needed to estimate undernotification in settings with incomplete, flawed, or weak surveillance systems. This study attempted to design a tuberculosis (TB) inventory study that balanced rigor with feasibility for high-need settings. OBJECTIVE: This study aims to design a hybrid TB inventory study for contexts without World Health Organization preconditions. We estimated the proportion of TB cases that were not reported to the Ministry of Health in 2015. The study sought to describe TB surveillance coverage and quality at different levels of TB care provision. Finally, we aimed to identify structural-, facility-, and provider-level barriers to notification and reasons for underreporting, nonreporting, and overreporting. METHODS: Retrospective partial digitalization of paper-based surveillance and facility records preceded deterministic and probabilistic record linkage; a hybrid of health facilities and laboratory census with a stratified sampling of HFs with no capacity to notify leveraged a priori knowledge. Distinct extrapolation methods were applied to the sampled health facilities to estimate bacteriologically confirmed versus clinical TB. In-depth interviews and focus groups were used to identify causal factors responsible for undernotification and test the acceptability of remedies. RESULTS: The hybrid approach proved viable and instructive. High-specificity verification of paper-based records in the field was efficient and had minimal errors. Limiting extrapolation to clinical cases improved precision. Probabilistic record linkage is computationally intensive, and the choice of software influences estimates. Record absence, decay, and overestimation of the private sector TB treatment behavior threaten validity, meriting mitigation. Data management demands were underestimated. Treatment success was modest in all sectors (R=37.9%-72.0%) and did not align with treatment success reported by the state (6665/8770, 75.99%). One-fifth of TB providers (36/178, 20%) were doubtful that the low volume of patients with TB treated in their facility merited mastery of the extensive TB notification forms and procedures. CONCLUSIONS: Subnational inventory studies can be rigorous, relevant, and efficient in countries that need them even in the absence of World Health Organization preconditions, if precautions are taken. The use of triangulation techniques, with minimal recourse to sampling and extrapolation, and the privileging of practical information needs of local decision makers yield reasonable misreporting estimates and viable policy recommendations.

Childhood Tuberculosis in Nigeria: Disease Presentation and Treatment Outcomes.

OBJECTIVES: Understanding the factors that influence tuberculosis (TB) treatment outcomes in children is key to designing interventions to address them. This study aimed to determine the case category distribution of childhood TB in Nigeria and assess which clinical and demographic factors are associated with different treatment outcomes in childhood TB. MATERIALS AND METHODS: This was a retrospective cohort study involving a review of medical records of children (0-14 years) with TB in 3 states in Nigeria in 2015. RESULTS: Of 724 childhood TB cases registered during the review period, 220 (30.4%) were aged 0-4 years. A high proportion of patients had pulmonary TB 420/724 (58.0%), new TB infection 713/724 (98.5%), and human immunodeficiency virus (HIV) coinfection 108/724 (14.7%). About 28% (n = 201) were bacteriologically diagnosed. The proportion of TB treatment success was 601/724 (83.0%). Treatment success was significantly higher in children aged 5-14 years than those 0-4 years (85.3% vs 77.7%, P = .01). Factors associated with unsuccessful outcomes in patients aged 0-4 years are male sex (adjusted odds ratio [aOR]: 1.2), HIV-positive status (aOR: 1.2), and clinical method of diagnosis (aOR: 5.6). CONCLUSIONS: Efforts should be made to improve TB treatment outcomes in children by ensuring early and accurate diagnosis, focused training of health workers on childhood TB-HIV care, and effective adherence counseling of caregivers.

Tuberculosis case detection in Nigeria, the unfinished agenda.

OBJECTIVE: Underdetection of TB is a major problem in sub-Saharan Africa. WHO recommends countries should have at least 1 laboratory per 100,000 population. However, this recommendation is not evidence based. METHODS: We analysed surveillance data of the Nigerian National TB Control Programme (2008-2012) to describe TB case detection rates, their geographical distribution and their association with the density of diagnostic laboratories and HIV prevalence. RESULTS: The median CDR was 17.7 (range 4.7-75.8%) in 2008, increasing to 28.6% (range 10.6-72.4%) in 2012 (P < 0.01). The CDR2012 was associated with the 2008 baseline; however, states with CDR2008 < 30% had larger increases than states with CDR2008 > 30. There were 990 laboratories in 2008 and 1453 in 2012 (46.7% increase, range by state -3% to +118). The state CDR2012 could be predicted by the laboratory density (P < 0.001), but was not associated with HIV prevalence or the proportion of smear-positive cases. CDR2012 and laboratory density were correlated among states having < and > than 1 laboratory per 100,000 population. CONCLUSION: There are large variations in laboratory density and CDR across the Nigerian states. The CDR is associated with the laboratory density. A much larger number of diagnostic centres are needed. It is likely that a laboratory density above the recommended WHO guideline would result in even higher case detection, and this ratio should be considered a minimum threshold.