Antimicrobial resistance of avian pathogenic Escherichia coli isolated from broiler, layer, and breeder chickens.

Background and Aim: Antimicrobials are extensively used in poultry production for growth promotion as well as for the treatment and control of diseases, including avian pathogenic Escherichia coli (APEC). Poor selection, overuse, and misuse of antimicrobial agents may promote the emergence and dissemination of antimicrobial resistance (AMR) in APEC. This study aimed to assess antimicrobial susceptibility patterns and detect antibiotic resistance genes (ARGs) in APEC isolated from clinical cases of colibacillosis in commercial broiler, layer, and breeder chickens. Materials and Methods: A total of 487 APEC were isolated from 539 across 300 poultry farms in various regions of Nepal. Antimicrobial susceptibility patterns was determined using the Kirby-Bauer disk diffusion and broth microdilution methods. The index of AMR, such as multiple antibiotic resistance (MAR) index, resistance score (R-score), and multidrug resistance (MDR) profile, were determined. Polymerase chain reaction was employed to detect multiple ARGs and correlations between phenotypic and genotypic resistance were analyzed. Results: The prevalence of APEC was 91% (487/539). All of these isolates were found resistant to at least one antimicrobial agent, and 41.7% of the isolates were resistant against 8-9 different antimicrobials. The antibiogram of APEC isolates overall showed the highest resistance against ampicillin (99.4%), whereas the highest intermediate resistance was observed in enrofloxacin (92%). The MAR index and R-score showed significant differences between broiler and layers, as well as between broiler breeder and layers. The number of isolates that were resistant to at least one agent in three or more antimicrobial categories tested was 446 (91.6%) and were classified as MDR-positive isolates. The ARGs were identified in 439 (90.1%) APEC isolates, including the most detected mobilized colistin resistance (mcr1) which was detected in the highest (52.6%) isolates. Overall, resistance gene of beta-lactam (blaTEM), mcr1, resistance gene of sulphonamide (sul1) and resistance gene of tetracycline (tetB) (in broiler), were detected in significantly higher than other tested genes (p < 0.001). When examining the pair-wise correlations, a significant phenotype-phenotype correlation (p < 0.001) was observed between levofloxacin and ciprofloxacin, chloramphenicol and tetracycline with doxycycline. Similarly, a significant phenotype-genotype correlation (p < 0.001) was observed between chloramphenicol and the tetB, and colistin with blaTEM and resistance gene of quinolone (qnrA). Conclusion: In this study, the current state of APEC AMR in commercial chickens is revealed for the first time in Nepal. We deciphered the complex nature of AMR in APEC populations. This information of molecular surveillance is useful to combat AMR in APEC and to contribute to manage APEC associated diseases and develop policies and guidelines to enhance the commercial chicken production.

Policy implications for awareness gaps in antimicrobial resistance (AMR) and antimicrobial use among commercial Nepalese poultry producers.

BACKGROUND: Nepal's poultry industry has increased with a growing middle class, which has translated to an increase in antimicrobial consumption and thus a rise in antimicrobial resistance (AMR). Describing and understanding antimicrobial use practices among commercial poultry producers in Nepal may help minimize the risks of AMR development in both humans and animals and determine the effectiveness of relevant policies. METHODS: From July to August 2018, poultry farmers were randomly recruited from Nepal's Chitwan District to participate in a cross-sectional study. The lead producer in each poultry operation was administered a quantitative structured-survey via a 30-min interview. Participants were asked to provide demographics, production practices, and knowledge about their antimicrobial use practices. Descriptive data analysis was performed to obtain frequencies and compare practices. RESULTS: In total, 150 commercial poultry producers of whom raised between 300 and 40,000 birds completed the interviews. Only 33% (n = 49) of producers reported knowing what AMR was, and among them only 50% (n = 25) consulted a veterinarian for treatment options. Antimicrobial administration for growth promotion was still employed by 13% of poultry producers. Similarly, critically important antimicrobial drugs, specifically colistin, were identified at 35% of participating operations. Producers reported low overall understanding and compliance of withdrawal periods (n = 41; 27%), which may result in both AMR development and adverse health reactions among consumers who ingest antimicrobial residues. Although Nepal has publicized antimicrobial use policies and awareness campaigns to instill healthy production practices, most producers (82%) were unaware of them. CONCLUSION: Many Nepalese poultry producers lack overall antimicrobial use and AMR awareness, which is evidenced by low antimicrobial withdrawal period compliance, use of antimicrobials for growth promotion, and the sustained use of critically important antimicrobials. Improved outreach and educational capacities, paired with increased veterinary resources and extensive monitoring in operations and retail meat products, may increase AMR awareness and policy enforcement.

Informing influenza pandemic preparedness using commercial poultry farmer knowledge, attitudes, and practices (KAP) surrounding biosecurity and self-reported avian influenza outbreaks in Nepal.

Avian influenza (AI) is a global health obstacle of critical concern as novel viruses are capable of initiating a pandemic. Recent spillover events of AI into human populations have occurred at human-poultry food system interfaces. As Nepal's poultry sector transitions to more intensified commercial production systems, it is important to examine the epidemiology of AI and the knowledge, attitudes and practices (KAP) of poultry sector workers. We conducted a cross-sectional KAP study utilizing a structured survey to interview 150 commercial poultry farmers in Chitwan District, Nepal. All commercial poultry farmers had knowledge of AI previous to the study and the majority farmers were able to identify farm-farm and poultry-human transmission mechanisms of AI. Farmers had more knowledge surrounding poultry AI symptoms as compared to human AI symptoms. Most farmers believe that AI is serious, contagious and a threat to everyone, yet only half believe it can be prevented. Individual-level personal protective equipment (PPE) uptake, such as facemask, glove and boot usage, on the enrolled farms was low and farm-level biosecurity practices varied greatly. Nine commercial poultry farms (6%) self-reported having an HPAI outbreak and 60 farms (40%) self-reported having an LPAI outbreak in the past 5 years. Layer farms had higher odds (OR: 5.4, 95% CI: 2.3-12.8) of self-reported LPAI as compared broiler farms. Poultry sector farmers face multiple obstacles when attempting to report AI to government authorities such as the fear of flock culling and the perceived lack of monetary compensation for culling. Our study provides updated KAP surrounding AI of farmers and self-reported AI farm-level epidemiology in Nepal's highest density commercial poultry production district. Commercial poultry farmers are fairly knowledgeable on AI, but do not take further protective practice efforts to implement their knowledge and prevent AI. Due to the potential role that human-poultry interfaces may play in AI emergence, it is critical to collaborate with the commercial poultry industry when planning and conducting AI pandemic preparedness mechanisms.