TB Related Costs, Social Protection, Coping Strategies, and Social Consequences – A Survey among TB Patients Attending District Chest Clinics in Sri Lanka
Bibliographic record
Abstract
Introduction: Drivers of TB epidemic are closely linked with the social determinants of health. One of the End TB targets is to reach “Zero” catastrophic cost due to TB by 2035. The current study was planned to describe the TB related costs, the social protection, coping strategies and the social consequences experienced by TB patients. Methodology: A longitudinal study was conducted among 736 drug sensitive TB patients in nine districts from September 2021 to February 2022 using a multistage cluster sampling with probability proportional to size of the patients detected in the previous year. Data were collected using an interviewer administered questionnaire and the results were presented as proportions, median and inter quartile range (IQR). Results: Out of 750, 634 responded (84.5%). The median age (IQR) was 50 (23-27) years and one quarter (n=162, 25.6%) was in the age group of 55-64 years, majority (n=372, 58%) were males. Direct medical cost was the highest during pre-treatment period, whereas indirect costs increased over the TB episode contributing to 75% of per patient cost which was 127 USD. Around 16.8% of the patients experienced catastrophic cost due to TB. Around 30% of the participants who employed previously lost their jobs after diagnosis. Less than a quarter of patients had social protection by means of financial support and adopted coping strategies such as use of savings (46%) and loans from relatives (29%). Conclusion: Pre-treatment Direct medical costs and indirect costs after diagnosis are considerable while social protection is sub optimal for TB patients which need policy reforms.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".