Prevalence, Risk Factors, and Molecular Detection of Campylobacter in Farmed Cattle of Selected Districts in Bangladesh.
Nazmul HoqueS K Shaheenur IslamMd Nasir UddinMohammad ArifA K M Ziaul HaqueSucharit Basu NeogiMd Mehedi HossainShinji YamasakiS M Lutful KabirPublished in: Pathogens (Basel, Switzerland) (2021)
A cross-sectional survey was conducted in selected districts of Bangladesh to estimate prevalence, risk factors, and molecular detection of Campylobacter isolates from 540 farmed cattle of 90 herds. As an individual sample, 540 feces, and as a pooled sample, 180 milk samples, 90 feed samples, 90 water samples, 90 manure samples, and 90 animal attendants' hand-rinse water were collected and tested via culture, biochemical, and molecular assays. A pretested semi-structured questionnaire was used to collect herd-level data on risk factors with the herd owners. The herd-level data on risk factors were analyzed through univariate and multivariate analyses, and a p-value <0.05 was considered statistically significant for all analyses. Overall, farm-level prevalence of bovine Campylobacter was enumerated to be 53.3% (95% confidence interval [CI]: 42.5-63.9%). The feces sample was found to be a high level of contamination of 30.9% (95% CI: 27-35%) followed by the manure swab (pooled) at 15.6% (95% CI: 8.8-24.7%). Campylobacter jejuni was documented as an abundant species (12.6%), followed by Campylobacter coli (5.1%), and Campylobacter fetus (0.3%). Older farms (>5 years of age), no/minimum cleaning and disinfection practices, along with animal roaming outside of the farm, were documented as significant risk factors for farm-level Campylobacter occurrence. Evidence-based control measures need to be taken through stringent biosecurity and hygienic measurement to lessen the load of the Campylobacter pathogen in the farm environment and prevent further transmission to animals and humans.
Keyphrases
- risk factors
- biofilm formation
- antimicrobial resistance
- escherichia coli
- pseudomonas aeruginosa
- risk assessment
- staphylococcus aureus
- candida albicans
- healthcare
- electronic health record
- drinking water
- physical activity
- big data
- cystic fibrosis
- deep learning
- wastewater treatment
- data analysis
- sewage sludge
- antibiotic resistance genes
- study protocol