Mapping Global Vulnerability to Dengue using the Water Associated Disease Index
Bibliographic record
Abstract
Water-associated diseases, such as cholera, dengue, and schistosomiasis, threaten the health and wellbeing of billions worldwide. They are most prevalent in tropical and sub-tropical regions, and are spread through contact with contaminated water or exposure to disease-carrying vectors (such as mosquitoes) that depend upon water to survive. Exacerbated by poor water and waste management, rapid urbanization, high population density, and changing climate conditions, water associated diseases are of increasing concern in a rapidly changing and increasingly globalized world. With limited resources to treat or combat the spread of water-associated disease in many endemic regions, preventative interventions must be appropriately targeted and timed to maximize their efficacy. This requires accurate identification of regions most vulnerable to disease, and the timely delivery of interventions to prevent, mitigate, and manage disease in these regions. In this report, we apply the Water Associated Disease Index (WADI) to calculate and visually communicate vulnerability to dengue on a global scale. While a number of tools exist to measure vulnerability to disease, most focus on when and where environmental conditions are optimal for an outbreak to occur, with little or no consideration of the role social determinants play in shaping vulnerability. As with any disease, we believe that vulnerability is shaped by a diverse range of environmental and social conditions. With this in mind, the WADI was developed to assess vulnerability by integrating disease specific measures of environmental exposure (i.e., temperature, precipitation, land cover etc.) with disease-specific measures of social susceptibility (i.e., life expectancy, educational attainment, access to healthcare etc.) to provide a holistic picture of vulnerability to disease. The WADI is a practical disease-specific tool for assessing vulnerability at a range of different spatial and temporal scales using publicly available data. It provides a new way of conceptualizing and communicating vulnerability to disease and, in this instance, demonstrates clear patterns of dengue vulnerability and how these may change over time. It is our hope that the WADI will be used to inform mid- to long-term allocation of resources to reduce or eradicate the burden of water associated disease.
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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 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".