Evaluating Biosecurity Measures and Farmer Behavioural Change Strategy to Mitigate Antimicrobial Resistance and Climate Impacts in Poultry Farms in Nepal: A Cluster-Based Intervention Study

Last registered on September 03, 2025

Pre-Trial

Trial Information

General Information

Title
Evaluating Biosecurity Measures and Farmer Behavioural Change Strategy to Mitigate Antimicrobial Resistance and Climate Impacts in Poultry Farms in Nepal: A Cluster-Based Intervention Study
RCT ID
AEARCTR-0016636
Initial registration date
August 28, 2025

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
September 03, 2025, 8:50 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Affiliation
Group for Technical Assistance

Other Primary Investigator(s)

PI Affiliation
Group for Technical Assistance
PI Affiliation
Group for Technical Assistance
PI Affiliation
Group for Technical Assistance
PI Affiliation
Group for Technical Assistance
PI Affiliation
Group for Technical Assistance

Additional Trial Information

Status
In development
Start date
2025-09-01
End date
2026-06-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Climate change poses a significant threat to human health, food systems, and ecosystems globally. Poultry farming is particularly vulnerable. Simultaneously, antimicrobial resistance (AMR) has emerged as a leading global health challenge, driven by the irrational use of antimicrobials in livestock. These issues are further exacerbated in LMICs. Evidences suggest that climate change acts as a driver of AMR, compounding risks to poultry production. In Nepal, poultry is the largest livestock subsector, contributing significantly to national GDP and food security. Cheaper and technically viable interventions that mitigate both climate and AMR threats are urgently required to tackle these compounded risks. Spreading disinfectant represents a promising strategy by inhibiting pathogen growth. These measures can improve poultry health, reduce illnesses, and ultimately lower antimicrobial use (AMU) while lowering hazardous ammonia and greenhouse gas (GHG) emissions. This project will assess the independent and combined effects of a technical intervention (disinfectant spraying) and a behavioural intervention (farmer education and guidance) on AMU, AMR, GHG emissions, ammonia concentration, and poultry health outcomes in broiler farms in Nepal. In the first phase, we will concurrently do mapping and a baseline KAP survey among 400 broiler farms in Bagmati Province of Nepal. In the second phase, as informed by the baseline farm mapping and stakeholder consultation, we will design and implement the intervention trial to evaluate the effects of disinfectant application and farmer training across two study arms (each arm comprising 144 farms). The findings will inform the development of scalable, climate-smart, and behaviourally grounded mitigation for AMR and sustainable poultry production in Nepal.
External Link(s)

Registration Citation

Citation
Bajracharya, Deepak C. et al. 2025. "Evaluating Biosecurity Measures and Farmer Behavioural Change Strategy to Mitigate Antimicrobial Resistance and Climate Impacts in Poultry Farms in Nepal: A Cluster-Based Intervention Study." AEA RCT Registry. September 03. https://doi.org/10.1257/rct.16636-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
The farms in this arm will receive both technical and behavioural interventions. As a part of behavioural intervention, the farmers will receive weekly training and guidance sessions covering rational AMU practices, waste management, hygiene, and biosecurity practices. Delivery will be via. verbal communication, supplemented with IEC materials. Tailored ad hoc guidance will also be offered to improve existing practices. As a part of technical intervention, farmers will be oriented and encouraged to manually spray disinfectant (Virkon®-S at 10 gm/L) twice a week at 6 am on the bedding. Given that the application will occur during shed uptime, poultry flocks will be directly exposed to disinfectant agents, so disinfectants should minimize adverse health effects and minimize AMR selective pressure. Thus, Virkon®-S, a peroxygen compound, would be the ideal.
Intervention Start Date
2026-02-01
Intervention End Date
2026-04-30

Primary Outcomes

Primary Outcomes (end points)
Effectiveness of disinfectant and farmer training in poultry farms in mitigating AMR and climate change
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
● Changes in knowledge, attitudes, and practices (KAP) of improving poultry health.
● Effect of the intervention of biosecurity measures and farmer training on AMU, AMR, CO2, ammonia levels, and poultry health.
●Understanding implementation process of the biosecurity measures and farmer training interventions using the RE-AIM framework.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
A mixed-methods, randomized control trial approach combining quantitative and qualitative data collection will be employed. The farm observation tool will be utilized to monitor and evaluate the intervention's effectiveness. Additionally, process monitoring will be conducted to document fidelity, the quality of implementation, and identify challenges and success factors through observations, note-taking, and verbal communication.
Experimental Design Details
Not available
Randomization Method
Randomization will be done by random number method using computer (MS Excel).
Randomization Unit
Farm
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
The calculated sample size is 288, split equally into two arms.
Sample size: planned number of observations
288
Sample size (or number of clusters) by treatment arms
Using stratified randomization, the farms from the clusters will be allocated equally across two intervention arms (144 arms per arms: control and intervention).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Assumptions for sample size calculation for Randomized Controlled Trials (RCT): Two-sided significance level (1-alpha): 95 Power (1-beta, % chance of detecting): 80 Ratio of sample size, control/intervention: 1 Odds Ratio: 2
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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