Background: Plasmid-mediated resistance to the colistin in poultry is considered as an emerging problem worldwide. While poultry constitutes the major industry in Nepal, there is a paucity of evidence on colistin resistance in Escherichia coli isolates causing natural infections in poultry. This study aimed to explore the prevalence of plasmid-mediated colistin resistance gene, mcr-1 in E. coli isolated from liver samples of dead poultry suspected of E. coli infections. Methods: A total of two hundred and seventy liver samples (227 broilers and 43 layers) from dead poultry suspected of colibacillosis were collected from post-mortem in the Central Veterinary Laboratory (CVL), Kathmandu, between 1 February and 31 July 2019. The specimens were processed to isolate and identify E. coli; an antimicrobial susceptibility test (AST) using disk diffusion method was performed with 12 different antibiotics: Amikacin (30 µg), ampicillin (10 µg), ciprofloxacin (5 µg), chloramphenicol (30 µg), cefoxitin (30 µg), ceftazidime (30 µg), ceftriaxone (30 µg), cotrimoxazole (25 µg), gentamicin (10 µg), imipenem (10 µg), levofloxacin (5 µg) and tetracycline (30 µg). Colistin resistance was determined by agar dilution method and colistin-resistant strains were further screened for plasmid-mediated mcr-1 gene, using conventional polymerase chain reaction (PCR). Results: Out of 270 liver samples, 53.3% (144/270) showed growth of E. coli. The highest number (54%; 109/202) of E. coli isolates was obtained in the liver samples from poultry birds (of both types) aged less than forty days. In AST, 95.1% (137/144) and 82.6% (119/144) of E. coli isolates were resistant against tetracycline and ciprofloxacin, respectively, while 13.2% (19/144) and 25.7% (37/144) isolates were resistant to cefoxitin and imipenem, respectively. In the same assay, 76.4% (110/144) E. coli isolates were multi-drug resistant (MDR). The phenotypic prevalence of colistin resistance was 28.5% (41/144). In the PCR assay, 43.9% (18/41) of colistin-resistant isolates were screened positive for plasmid-mediated mcr-1. Conclusion: The high prevalence of mcr-1 in colistin-resistant E. coli isolates in our study is a cause of concern for the probable coming emergence of colistin resistance in human pathogens, due to horizontal transfer of resistant genes from poultry to human isolates.

Tuberculosis (TB) in humans is primarily caused by Mycobacterium tuberculosis (M. tuberculosis), with millions of infections and hundreds of thousands of deaths worldwide. It creates a substantial economic burden on the community. Unlike M. tuberculosis, Mycobacterium bovis infects cattle and causes bovine TB, also known as zoonotic TB. People can contract zoonotic TB after consumption of unpasteurized dairy products, handling the sick animals, and via occupational exposures. The association between the zoonotic TB in humans and cattle is not well known in Nepal. The study examined the associated risk factors, including exposure to infected cattle, that contribute to TB's development in human beings in Nepal.

Background: Brucellosis is a zoonotic disease caused by Brucella spp. In Nepal, the presence of brucellosis in small ruminants, namely sheep and goats, has impacted farmers’ livelihood and the food safety of consumers. A cross-sectional study was conducted in Rupandehi district of Nepal during January to March 2020 to investigate the seroepidemiology and associated risk factors of brucellosis in the sheep and goat population. Altogether, 19 sheep and 60 goat farms in the district were visited. Owners were interviewed to get information on animals, including their management and movement patterns. Three hundred fifty-seven samples (80 sheep and 277 goat samples) were collected proportionately based on farm sizes. Each serum sample was tested with Rose Bengal Test and ELISA to estimate the seropositivity of brucellosis. Logistic regression was carried out to calculate corresponding odds ratios of each variable associated with detection of brucellosis. Results: At the farm level, 31.6% (6/19; 95% CI: 12, 54%) of sheep farms and 3.3% (2/60, 95% CI: 0.9, 11.4%) of goat farms were seropositive to brucellosis. Out of 80 sheep serum samples, 12 (15%; 95% CI: 8.79–24.41%) and out of 277 goat serum samples, three (1.1%; 95% CI: 0.37–3.14%) were seropositive to brucellosis. Age greater than 1.5 years (OR = 5.56, 95% CI: 1.39, 29.38; p = 0.02) and herd size of greater than 100 (OR = 4.74, 95% CI: 1.23, 20.32, p = 0.03) were identified as significant risk factors for seropositivity of brucellosis in the sheep population. While in the goat population, none of the variables was identified as a significant risk factor. Conclusion: The study provides evidence that the older sheep and the sheep from the large herds were at higher risk of brucellosis. A control program should be put in place immediately in the sheep population because they may transmit infections to other livestock as they were regularly moved for grazing and selling purposes. Also, strict biosecurity measures should be implemented among pastoralists to prevent brucellosis transmission in them. We suggest further one health-based study to reveal the transmission dynamics of brucellosis between animals and humans.

The poultry sector contributes four percent to the national GDP of Nepal. However, this sector is under threat with periodic outbreaks of Avian Influenza (AI) subtypes H5 and H9 since 2009. This has been both a public health threat and an economic issue. Since the past few years, outbreaks of AI subtype H9 have caused huge economic losses in major poultry producing areas of Nepal. However, the risk factors associated with these outbreaks have not been assessed. A retrospective case-control study was conducted from April 2018 to May 2019 to understand the risk factors associated with AI subtype H9 outbreaks in Kathmandu valley. Out of 100 farms selected, 50 were “case” farms, confirmed positive to H9 at Central Veterinary Laboratory, Kathmandu, and another 50 farms were “control” farms, matched for farm size and locality within a radius of three km from the case farm. Each farm was visited to collect information using a semi-structured questionnaire. Twelve potential risk factors were included in the questionnaire under the broad categories: birds and farm characteristics, and management and biosecurity status of the farms. Univariable and multivariable logistic regression analysis was conducted and corresponding odds ratios were calculated. Risk factors, associated with AI subtype H9 outbreaks in Kathmandu valley, identified in the final multivariable model were: “farms that have flock size greater than median flock size of study farms (>1500)” (OR = 4.41, 95% CI: 1.53–12.71, p = 0.006), “farms that did not apply rules to wear boots for visitors inside the farms” (OR = 4.32, 95% CI: 1.52–12.29, p = 0.006) and “other commercial farms located within one km periphery” (OR = 10, 95% CI: 1.8–50, p = 0.007). This study showed that outbreaks of AI subtype H9 in Kathmandu valley were associated with a higher population of birds in the farm, poor management practices, and weak biosecurity measures in poultry farms. We suggest improving management practices and increase biosecurity in the farms to reduce incidences of AI subtype H9 outbreaks in Kathmandu valley.

The poultry industry has transformed into one of the vibrant economic activities in Nepal, contributing to almost 4% of the national GDP. We conducted a cross-sectional survey among the poultry farmers of Kathmandu valley and Chitwan district to assess their knowledge of antimicrobial resistance (AMR); their practice of antimicrobial usage and the biosecurity status of their poultry farms. The survey was done to understand the level of knowledge gap among the farmers regarding successful poultry farming with strict biosecurity protocol and minimal use of antibiotics. A semi-structured questionnaire was prepared to interview a total of 112 farmers, with 56 respondents from each study sites. Only nineteen percent (11/56) of the farmers from the Kathmandu valley and 16% (9/56) of that of Chitwan district knew about the antimicrobial resistance (AMR). Doxycycline (25.9%, 29/112) was the most used antibiotic followed by Tylosin (21.5%, 24/112), Colistin (18.75%, 21/112), Ciprofloxacin (13.4%, 15/112) and Neomycin (12.5%, 14/112) in both districts. Majority of the surveyed respondents lacked the proper awareness regarding the importance of considerate use of antimicrobial drugs, effectiveness of implementing proper biosecurity protocols in the farms, and the increasing challenge of AMR in the present world scenario. The findings and results of this survey identify the critical gaps in the knowledge of the farmers concerning the day-to-day operations in their poultry business. Immediate strategic actions and road-maps are required to solve the burgeoning problem of AMR considering the imprudent use of antibiotics in the poultry sector. Int. J. Appl. Sci. Biotechnol. Vol 10(1): 50-59.

Antimicrobial resistance (AMR) is increasing and represents one of the greatest public health challenges of our time, accounting for considerable morbidity and mortality globally. A “One Health” surveillance strategy, which integrates data concerning the resistant organisms circulating in humans, animals, and the environment, is required to monitor this issue and enable effective interventions. The timely collection, processing, analysis, and reporting of AMR surveillance data are necessary for the effective delivery of the information generated from such surveillance. Nepal has greatly improved its surveillance activities through a network of human and animal health laboratories; however, the data reported by sentinel laboratories are often inconsistent, incomplete, and delayed, causing challenges in terms of data cleaning, standardization, and visualization on a national level. To overcome these issues, innovative methods and procedures have been adopted in Nepal, with the development and customization of digital tools that reduce the human time and effort spent on data cleaning and standardization, with concomitant improvements in the accuracy of data. These standardized data can be uploaded to the district health information system 2 (DHIS2) One Health AMR surveillance portal, enabling the generation of reports that will help decision-makers and policy planners to combat the global problem of AMR.