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Record W2996310416 · doi:10.1186/s12963-019-0199-3

Social capital is associated with lower mosquito vector indices: secondary analysis from a cluster randomised controlled trial of community mobilisation for dengue prevention in Mexico

2019· article· en· W2996310416 on OpenAlexaff
Víctor Manuel Alvarado-Castro, Sergio Paredes‐Solís, Elizabeth Nava-Aguilera, Arcadio Morales-Pérez, Miguel Flores-Moreno, José Legorreta-Soberanis, Esmeralda Jaimes-Néstor, Anne Cockcroft, Neil Andersson

Bibliographic record

VenuePopulation Health Metrics · 2019
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsMcGill University
FundersUBS Optimus FoundationConsejo Nacional de Ciencia y Tecnología
KeywordsSocial capitalCluster randomised controlled trialPsychological interventionMedicineOdds ratioDemographyEnvironmental healthSocioeconomicsEconomicsSociologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Control of the Aedes aegypti mosquito is central to reducing the risk of dengue, zika, chikungunya, and yellow fever. Randomised controlled trials, including the Camino Verde trial in Mexico and Nicaragua, demonstrate the convincing impact of community mobilisation interventions on vector indices. These interventions might work through building social capital but little is known about the relationship between social capital and vector indices. METHODS: A secondary analysis used data collected from 45 intervention clusters and 45 control clusters in the impact survey of the Mexican arm of the Camino Verde cluster randomised controlled trial. Factor analysis combined responses to questions about aspects of social capital to create a social capital index with four constructs, their weighted averages then combined into a single scale. We categorised households as having high or low social capital based on their score on this scale. We examined associations between social capital and larval and pupal vector indices, taking account of the effects of other variables in a multivariate analysis. We report associations as odds ratios and 95% confidence intervals. RESULTS: The four social capital constructs were involvement, participation, investment, and communication. Among the 10,112 households, those in rural communities were much more likely to have a high social capital score (OR 4.51, 95% CIca 3.26-6.26). Households in intervention sites had higher social capital, although the association was not significant at the 5% level. Households with high social capital were more likely to be negative for larvae or pupae (OR 1.38, 95% CIca 1.12-1.69) and for pupae specifically (OR 1.37, 95% CIca 1.08-1.74). There was interaction between intervention status and social capital; in multivariate analysis, a combined variable of intervention/high social capital remained associated with larvae or pupae (ORa l.56, 95% CIca 1.19-2.04) and with pupae specifically (ORa 1.65, 95% CIca 1.20-2.28). CONCLUSION: This is the first report of an association of high social capital with low vector indices. Our findings support the idea that the Camino Verde community mobilisation intervention worked partly through an interaction with social capital. Understanding such interactions may help to maximise the impact of future community mobilisation interventions.

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)0.007
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.033
GPT teacher head0.345
Teacher spread0.312 · 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

Citations12
Published2019
Admission routes1
Has abstractyes

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