Biosecurity and water, sanitation, and hygiene (WASH) interventions in animal agricultural settings for reducing infection burden, antibiotic use, and antibiotic resistance: a One Health systematic review
Bibliographic record
Abstract
Prevention and control of infections across the One Health spectrum is essential for improving antibiotic use and addressing the emergence and spread of antibiotic resistance. Evidence for how best to manage these risks in agricultural communities-45% of households globally-has not been systematically assembled. This systematic review identifies and summarises evidence from on-farm biosecurity and water, sanitation, and hygiene (WASH) interventions with the potential to directly or indirectly reduce infections and antibiotic resistance in animal agricultural settings. We searched 17 scientific databases (including Web of Science, PubMed, and regional databases) and grey literature from database inception to Dec 31, 2019 for articles that assessed biosecurity or WASH interventions measuring our outcomes of interest; namely, infection burden, microbial loads, antibiotic use, and antibiotic resistance in animals, humans, or the environment. Risk of bias was assessed with the Systematic Review Centre for Laboratory Animal Experimentation tool, Risk of Bias in Non-Randomized Studies of Interventions, and the Appraisal tool for Cross-Sectional Studies, although no studies were excluded as a result. Due to the heterogeneity of interventions found, we conducted a narrative synthesis. The protocol was pre-registered with PROSPERO (CRD42020162345). Of the 20 672 publications screened, 104 were included in this systematic review. 64 studies were conducted in high-income countries, 24 studies in upper-middle-income countries, 13 studies in lower-middle-income countries, two in low-income countries, and one included both upper-middle-income countries and lower-middle-income countries. 48 interventions focused on livestock (mainly pigs), 43 poultry (mainly chickens), one on livestock and poultry, and 12 on aquaculture farms. 68 of 104 interventions took place on intensive farms, 22 in experimental settings, and ten in smallholder or subsistence farms. Positive outcomes were reported for ten of 23 water studies, 17 of 35 hygiene studies, 15 of 24 sanitation studies, all three air-quality studies, and 11 of 17 other biosecurity-related interventions. In total, 18 of 26 studies reported reduced infection or diseases, 37 of 71 studies reported reduced microbial loads, four of five studies reported reduced antibiotic use, and seven of 20 studies reported reduced antibiotic resistance. Overall, risk of bias was high in 28 of 57 studies with positive interventions and 17 of 30 studies with negative or neutral interventions. Farm-management interventions successfully reduced antibiotic use by up to 57%. Manure-oriented interventions reduced antibiotic resistance genes or antibiotic-resistant bacteria in animal waste by up to 99%. This systematic review highlights the challenges of preventing and controlling infections and antimicrobial resistance, even in well resourced agricultural settings. Most of the evidence emerges from studies that focus on the farm itself, rather than targeting agricultural communities or the broader social, economic, and policy environment that could affect their outcomes. WASH and biosecurity interventions could complement each other when addressing antimicrobial resistance in the human, animal, and environmental interface.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.012 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".