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Record W3201648964

Mapping Global Vulnerability to Dengue using the Water Associated Disease Index

2014· article· en· W3201648964 on OpenAlex
Laura Fullerton, Sarah Dickin, Corinne J. Schuster‐Wallace

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2014
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
FundersGovernment of CanadaMcMaster University
KeywordsDengue feverIndex (typography)Vulnerability (computing)Disease surveillanceGeographyDiseaseVirologyComputer scienceMedicineComputer security
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.190
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it