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Irregular water supply, household usage and dengue: a bio-social study in the Brazilian Northeast

2009· article· en· W2156646883 on OpenAlexfundno aff
Andréa Caprara, José Wellington de Oliveira Lima, Alice Correia Pequeno Marinho, Paola Gondim Calvasina, Lucyla Oliveira Paes Landim, Johannes Sommerfeld

Bibliographic record

VenueCadernos de Saúde Pública · 2009
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungInternational Development Research CentreUnited Nations Development Programme
KeywordsWater supplyUrbanizationGarbageVector (molecular biology)Dengue feverGeographySocioeconomicsAedes aegyptiSlumEcologyEnvironmental planningBiologyPopulationSociologyEnvironmental engineeringEnvironmental scienceEngineeringDemography

Abstract

fetched live from OpenAlex

Despite increased vector control efforts, dengue fever remains endemic in Fortaleza, Northeast Brazil, where sporadic epidemic outbreaks have occurred since 1986. Multiple factors affect vector ecology such as social policy, migration, urbanization, city water supply, garbage disposal and housing conditions, as well as community level understanding of the disease and related practices. This descriptive study used a multi-disciplinary approach that bridged anthropology and entomology. A multiple case study design was adopted to include research in six study areas, defined as blocks. The water supply is irregular in households from both under-privileged and privileged areas, however, clear differences exist. In the more privileged blocks, several homes are not connected to the public water system, but have a well and pump system and therefore irregularity of supply does not affect them. In households from under-privileged blocks, where the water supply is irregular, the frequent use of water containers such as water tanks, cisterns, barrels and pots, creates environmental conditions with a greater number of breeding areas. In under-privileged homes, there are more possible breeding areas and environmental conditions that may improve the chances of Aedes aegypti survival.

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)0.003
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 score0.122
Threshold uncertainty score0.243

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
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 head0.015
GPT teacher head0.266
Teacher spread0.251 · 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

Citations130
Published2009
Admission routes1
Has abstractyes

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