Economic Evaluation of Public Health Interventions: An Application to Interventions for the Prevention of Violence Against Women and Girls Implemented by the “What Works to Prevent Violence Against Women and Girls?” Global Program
Bibliographic record
Abstract
Violence against women and girls (VAWG) has important social, economic, and public health impacts. Governments and international donors are increasing their investment in VAWG prevention programs, yet clear guidelines to assess the "value for money" of these interventions are lacking. Improved costing and economic evaluation of VAWG prevention can support programming through supporting priority setting, justifying investment, and planning the financing of VAWG prevention services. This article sets out a standardized methodology for the economic evaluation of complex, that is, multicomponent and/or multiplatform, programs designed to prevent VAWG in low- and middle-income countries (LMICs). It outlines an approach that can be used alongside the most recent guidance for the economic evaluation of public health interventions in LMICs. It defines standardized methods of data collection and analysis, outcomes, and unit costs (i.e., average costs per person reached, output or service delivered), and provides guidance to investigate the uncertainty in cost-effectiveness estimates and report results. The costing approach has been developed and piloted as part of the "What Works to Prevent Violence Against Women and Girls?" (What Works?) program in five countries. This article and its supplementary material can be used by both economists and non-economists to contribute to the generation of new cost-effectiveness data on VAWG prevention, and ultimately improve the allocative efficiency and financing across VAWG programs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".