Antimicrobial use patterns and resistance among peri-urban and
rural poultry farmers in Soroti and Wakiso districts, Uganda
Irene Mbatidde1, Dickson Ndoboli1, Dreck Ayebare1, Savino Biryomumaisho2,
Kristina Roesel1, Michel Dione1, Dishon Muloi1, Bernd-Alois Tenhagen3, Eddie Wampande2,
John Elmerdahl Olsen4 and Arshnee Moodley1
Objectives
Describe antimicrobial use (AMU) on semi-intensive and free-range poultry farms in Wakiso with good access to Vet
services and Soroti with poor access and to detect Salmonella spp. and quantify antimicrobial-resistant E. coli.
Methods
• Cross-sectional study on 400 broiler farms between Oct 21 – Feb 22
• Farm size = 500-2000 birds in Wakiso and >20 birds in Soroti
• Structured questionnaire to capture AMU data
• Regression analysis using Stata/SE 17.0
• Microbiology: two samples collected from one chicken house per farm
• Composite environmental and a boot sock.
• Salmonella spp. isolated using XLD and chromogenic agar
• Quantification of AMR E. coli was done by serial dilution and plating on
MacConkey agar with and without antimicrobials (cefotaxime and colistin)
Pictures
Conclusions
• Lack of access to Vet services was associated with less
frequent AMU but frequent use of human drugs
• The more intensive farms used antimicrobials more
frequently than the traditional farms
• >40% of farms had colistinR and cefotaximeR E.coli but
do not report the use of these antibiotics
Corresponding author Irene Mbatidde
I.Mbatidde@cgiar.org
ILRI c/o Bioversity International
P.O. Box 24384, Kampala Uganda
+256 392 081 154/155
This document is licensed for use under the Creative Commons
Attribution 4.0 International Licence. September 2022.
22 September 2022
ILRI thanks all donors and organizations which globally support its work through their contributions to the CGIAR Trust Fund.
Contribution to Uganda’s livestock development
agenda
• Highlight gaps in AMU practices and provides AMR data on
zoonotic pathogens in semi-intensive and free-range systems
for appropriate interventions
• Personnel capacity development in epidemiology, risk
assessment and antimicrobial resistance
1International Livestock Research Institute, Kenya/Uganda, 2Makerere University, Uganda, 3Germany Federal Institute for Risk assessment,
4University of Copenhagen, Denmark
0 20 40 60 80 100
Macrolides
Sulphonamides
Aminoglycosides
Penicilin
Fluoroquinolones
Tetracycline
Vitamins
Vaccines
Antihelmitics
AM USE BY DISTRICT
Percentage AM-Use Soroti Percentage AM-Use Wakiso
Findings
Microbiology
More farms in Soroti were positive for Salmonella compared to Wakiso
45-62% of farms were positive for presumptive colistinR E.coli and cefotaximeR E.coli
CFU counts
1 x 102 – 4.6 x 105 CFU/g (colistinR E.coli )
1 x 102 – 1.1 x 106 CFU/g (cefotaximeR E.coli )
Logistic regression model showed strong association between antimicrobial use and these variables
AM Use Odds Ratio Z Value P-Value confidence Interval
(95%)
Who Diagnosed (ref.Vet)
Farmer 0.24 -3.10 0.002 0.1-0.6
Drug store 1.8 0.75 0.5 0.4-7
Other Health worker 0.8 -0.23 0.8 0.2-3.3
Production
scale(ref.Traditinal)
Semi-intensive (51-2000) 2 1.37 0.172 0.7-5.5
Intensive (>2000) 7.2 2.69 0.007 1.7-30
Easy access to Vet services 0.5 -1.5 0.144 0.1-1.2