Out-of-Pocket expenditures associated with Congenital Zika Syndrome in Brazil: an analysis of household health spending
Bibliographic record
Abstract
Abstract Introduction The study aims to estimate out-of-pocket household expenditures associated with the diagnosis and follow-up treatment of Congenital Zika Syndrome (CZS) in children affected during the 2015-2016 epidemic in Brazil. Methods Ninety-six interviews were held in the cities of Fortaleza and Rio de Janeiro in a convenience sample, using a questionnaire on sociodemographic characteristics and private household expenditures associated with the syndrome, which also allowed estimating catastrophic expenditures resulting from care for CZS. Results Most of the mothers interviewed in the study were brown, under 34 years of age, unemployed, and reported a monthly family income of two minimum wages or less. Spending on medicines accounted for 77.6% of the out-of-pocket medical expenditures, while transportation and food were the main components of nonmedical expenditures, accounting for 79% of this total. The mean annual out-of-pocket expenditures by households was equivalent to almost a quarter of the annual minimum wage. Conclusions The affected households were largely low-income and suffered catastrophic expenditures due to the disease. Public policies should consider the financial and healthcare needs of these families to ensure adequate support for individuals affected by CZS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".