Interventions for vector-borne diseases focused on housing and hygiene in urban areas: a scoping review
Bibliographic record
Abstract
BACKGROUND: Over half the world's human populations are currently at risk from vector-borne diseases (VBDs), and the heaviest burden is borne by the world's poorest people, communities, and countries. The aim of this study was to conduct a review on VBD interventions relevant to housing and hygiene (including sanitation and waste management) in urban areas. MAIN BODY: We conducted a scoping review, which involved systematically searching peer-reviewed and grey literature published between 2000 and 2016 using five scientific databases and one database for grey literature. Different data extraction tools were used for data coding and extraction. We assessed the quality of each study using the Mixed Methods Appraisal Tool and extracted descriptive characteristics and data about implementation process and transferability from all studies using the Template for Intervention Description and Replication and ASTAIRE (a tool for analyzing the transferability of health promotion interventions) tools. We reviewed 44 studies. Overall, the studies were judged to be of high risk for bias. Our results suggest multifaceted interventions, particularly community-based interventions, have the potential to achieve wider and more sustained effects than do standard vertical single-component programs. The evaluations of multifaceted interventions tend to include integrated evaluations, using not only entomological indicators but also acceptability and sustainability indicators. CONCLUSIONS: This review highlighted the important need for higher quality research in VBDs and improved and standardized reporting of interventions. Significant research gaps were found regarding qualitative research and implementation research, and results highlighted the need for more interventions focus on sanitation and hygiene practices.
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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 | 0.020 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".