OUT OF POCKET EXPENDITURES FOR MANAGING CHILDHOOD ACUTE RESPIRATORY INFECTION IN CHILDREN UNDER 5 IN DISTRICT KASUR PUNJAB
Bibliographic record
Abstract
Background: Acute respiratory infections are major public health threats in children aged less than 5 years. Acute respiratory infections caused 20%of the childhood deaths worldwide in which 99% deaths in children under 5 are reported in developing countries like Pakistan. Globally, about 150 million people were affected with financial loss after out of pocket expenditure on health. Out of pocket costs accounts for 61% of the health care financing in Pakistan The mortality rates in rural areas in children under 5 are about a quarter to a third higher in comparison to urban areas. Methodology: Simple random sampling technique was used. Data was collected only on those children under 5 who met the case definition for acute respiratory infection. The main objective of the study was to estimate the cost per episode of acute respiratory infection in children under 5 years. A structured questionnaire was used for data collection. The calculated sample size was 229 Main findings: The median cost per episode of ARI on child treatment was approximately US$3 (300 PKR). The median of direct medical cost of ARI US$ 1.5(150PKR) was higher as compared to non-medical costs US$1.0(100 PKR).Almost every outpatient visit either in private or public hospital resulted in costs for prescribed medication but no laboratory tests were recommended.. Conclusion Study participants spend more on their male child as compared to female child. Families with higher income have more health expenditures on their child treatment than those having less income. The majority of the parents (75%) preferred to visit private health care providers for the treatment of their children. Estimated indirect cost was higher in public facilities as compared to private facilities because of waiting time to consult the doctor was longer. Keywords: Out of pocket expenditure, acute respiratory infections, costs, Direct, Indirect, Public, and Private.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".