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An ecosystemic approach to evaluating ecological, socioeconomic and group dynamics affecting the prevalence of Aedes aegypti in two Colombian towns

2009· article· en· W2160155668 on OpenAlexfundno aff
Juliana Quintero, Gabriel Carrasquilla, Roberto Suárez, Catalina González-Uribe, Víctor Alberto Olano

Bibliographic record

VenueCadernos de Saúde Pública · 2009
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
FundersInternational Development Research CentreUnited Nations Development ProgrammeWorld Health Organization
KeywordsSocioeconomic statusAedes aegyptiPublic healthGeographyDengue feverEnvironmental healthStratumAedesSocioeconomicsEcologySocial determinants of healthQualitative researchDemographyBiologyPopulationSociologyMedicineSocial science

Abstract

fetched live from OpenAlex

This article focuses on the epidemiological methods and results of a global Ecohealth study that explored the complexity of the relationship between ecological, biological, economical, social and political factors and vector presence. The study was carried out in two dengue endemic areas of Colombia. A transdisciplinary team gathered quantitative and qualitative data. A survey in randomly sampled households was applied and, simultaneously, direct observation of potential breeding sites was carried out. Logistic regressions and qualitative techniques were used. Qualitative and quantitative data were compared using triangulation. The presence of low water containers increases seven-fold the risk of finding immature forms of Aedes aegypti in the household (OR = 7.5; 95%CI: 1.7-32.2). An inverse association between socioeconomic stratum and presence of the vector was identified (Low stratum OR = 0.9; 95%CI: 0.6-1.4; High stratum OR =0.4; 95%CI: 0.07-1.7). Water management is a complex social dynamic associated with the presence of Ae. aegypti. Dengue control is a challenge for public health authorities and researchers as they should address promotion and prevention strategies that take into account cultural, behavioral, socioeconomic and health factors.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.020
GPT teacher head0.330
Teacher spread0.311 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations71
Published2009
Admission routes1
Has abstractyes

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