Visualizing the Geography of HIV Observational Cohorts With Density-Adjusted Cartograms
Bibliographic record
Abstract
BACKGROUND: Maps are potent tools for describing the spatial distribution of population and disease characteristics and, thereby, for appropriately targeting public health interventions. People with HIV (PWH) tend to live in densely populated and spatially compact areas that may be difficult to visualize on maps using unadjusted geographic or political borders. SETTING: To illustrate these challenges, we used geographic data from adult PWH at the Vanderbilt Comprehensive Care Clinic (VCCC) in Nashville, Tennessee, and aggregated data from the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) from 1998 to 2015. METHODS: We compared choropleth maps that use differential shading of political/geographic boundaries with density-adjusted cartograms that allow for shading and deformed boundaries according to a variable of interest, such as PWH. RESULTS: Cartograms enlarged high-burden areas and shrank low-burden areas of PWH, improving visual interpretation of where to focus HIV prevention and mitigation efforts, when compared with choropleth maps. Cartograms may also demonstrate cohort representativeness of underlying populations (eg, Tennessee for VCCC or the United States for NA-ACCORD), which can guide efforts to assess external validity and improve generalizability. CONCLUSION: Choropleth maps and cartograms offer powerful visual evidence of the geographic distribution of HIV disease and cohort representation and should be used to guide targeted public health interventions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".