The Correlation Between Poverty and Access to Essential Surgical Care in Ghana: A Geospatial Analysis
Bibliographic record
Abstract
BACKGROUND: Surgical disease burden falls disproportionately on individuals in low- and middle-income countries. These populations are also the least likely to have access to surgical care. Understanding the barriers to access in these populations is therefore necessary to meet the global surgical need. METHODS: Using geospatial methods, this study explores the district-level variation of two access barriers in Ghana: poverty and spatial access to care. National survey data were used to estimate the average total household expenditure (THE) in each district. Estimates of the spatial access to essential surgical care were generated from a cost-distance model based on a recent surgical capacity assessment. Correlations were analyzed using regression and displayed cartographically. RESULTS: Both THE and spatial access to surgical care were found to have statistically significant regional variation in Ghana (p < 0.001). An inverse relationship was identified between THE and spatial access to essential surgical care (β -5.15 USD, p < 0.001). Poverty and poor spatial access to surgical care were found to co-localize in the northwest of the country. CONCLUSIONS: Multiple barriers to accessing surgical care can coexist within populations. A careful understanding of all access barriers is necessary to identify and target strategies to address unmet surgical need within a given population.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".