Yield of systematic household contact investigation for tuberculosis in a high-burden metropolitan district of South Africa
Bibliographic record
Abstract
BACKGROUND: Systematic household contact investigation (SHCI) is recommended as an active-case-finding (ACF) strategy to identify individuals at high risk of tuberculosis (TB) infection, in order to enable early detection and treatment. Reluctance to implement SHCI in sub-Saharan African and South African high-burden contexts may stem from uncertainty about the potential yield of this strategy when targeting specific categories of TB index cases. In order to inform and motivate scale-up, this pilot study investigated the effectiveness of SHCI when targeting the World Health Organization's (WHO) recommended categories of infectious index cases. METHOD: Data were gathered in September and October 2016. Household contacts of infectious TB cases who attended 40 primary health care facilities in Mangaung Metropolitan District were recruited. The categories of TB index cases included 1) children <5 years, 2) HIV co-infected pulmonary TB (PTB) cases (≥5 years), 3) HIV-negative PTB cases (≥5 years), and 4) multidrug-resistant (MDR) TB cases. Contacts were screened for TB symptoms and symptomatic individuals and all children <5 years were referred for clinical evaluation. Data were analysed to establish the yield and factors associated with new TB diagnosis. RESULTS: Of 259 contacts screened, just under half (47.1%) underwent TB clinical investigation, during which 17 (6.6%) new TB cases were diagnosed, which represents a prevalence rate of 6564 per 100,000 population. Fifteen contacts needed to be screened to detect one new TB case. The proportion of new TB cases was the highest among contacts of HIV-negative PTB index cases (47.9%). The likelihood of TB diagnosis was higher among male contacts (odds ratio [OR]: 4.8; 95% confidence interval [CI]: 1.54-14.97) and those reporting coughing (OR: 4.3; 95% CI: 1.11-16.43). CONCLUSION: The high yield of new TB observed in this pilot study demonstrates that targeted SHCI may be an effective ACF strategy in Mangaung and similar high-burden settings in South Africa. Targeting different index case categories produced variable yield - the highest among contacts of HIV-negative TB index cases. SHCI among household contacts of all four the WHO-recommended categories of infectious TB index cases - and male and coughing contacts, in particular - should be maximised.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".