Microbiological and hematological aspects of canine pyometra and associated risk factors.

Canine Pyometra, also known as cystic endometrial hyperplasia complex, is a common reproductive issue in bitches. This study aimed to identify associated risk factors, hematological variation, bacteria involved, and the most potent anti-bacterial against bacterial isolates of canine pyometra. Forty-five bitches of different habitats, breeds, and ages infected with pyometra were included in the study. The samples were cultured to isolate bacteria associated with the pyometra and antibiotic sensitivity was done for each bacterial isolates to get antibiogram. The study findings showed that potential risk factors such as age group, medroxyprogesterone acetate administration, and changes in the white blood cells parameters were significantly associated (P < 0.05) with the type of pyometra. Closed cervix pyometra in dogs showed significantly higher prevalence of clinical signs including depression, vomiting, abdominal enlargement, and fever compared to the open cervix pyometra. Low levels of red blood cells, pack cell volume, and hemoglobin indicated that the pyometra-infected dogs were more likely to have normocytic, normochromic, and non-regenerative anemia. Pyometra was attributed to an increase in AST (Aspertate aminotransferase), ALT (Alanine transaminase), ALP (Alkaline phosphatase), BUN (Blood Urea Nitrogen), and Creatinine while a decrease in serum albumin. Of the all bacterial isolates, E. coli (35.55%) was the most common pathogen isolated from canine pyometra, followed by Pseudomonas spp. (26.66%). E coli and Pseudomonas spp. were susceptible to Imipenem, Amikacin, and Gentamicin while highly resistant to Ampicillin and Erythromycin. Imipenem, Amikacin, and Gentamicin were the most sensitive antibiotics, while Ampicillin and Erythromycin were the most resistant antibiotics for the bacterial strain isolated from canine pyometra. Multidrug resistant was observed in 26 of the isolated bacteria, indicating acquired resistance due to improper and uncontrolled use. Hence early diagnosis and close monitoring of antimicrobial susceptibility before therapeutic intervention is indispensable in preventing the global threat of antimicrobial resistance.

Application of diagnostic network optimization in Kenya and Nepal to design integrated, sustainable and efficient bacteriology and antimicrobial resistance surveillance networks.

Antimicrobial resistance (AMR) is a major global public health concern, particularly in low- and middle-income countries, which experience the highest burden of AMR. Critical to combatting AMR is ensuring there are effective, accessible diagnostic networks in place to diagnose, monitor and prevent AMR, but many low- and middle-income countries lack such networks. Consequently, there is substantial need for approaches that can inform the design of efficient AMR laboratory networks and sample referral systems in lower-resource countries. Diagnostic network optimization (DNO) is a geospatial network analytics approach to plan diagnostic networks and ensure greatest access to and coverage of services, while maximizing the overall efficiency of the system. In this intervention, DNO was applied to strengthen bacteriology and AMR surveillance network design in Kenya and Nepal for human and animal health, by informing linkages between health facilities and bacteriology testing services and sample referral routes between farms, health facilities and laboratories. Data collected from the target settings in each country were entered into the open-access DNO tool OptiDx, to generate baseline scenarios, which depicted the current state of AMR laboratory networks and sample referral systems in the countries. Subsequently, baselines were adjusted to evaluate changing factors such as samples flows, transport frequency, transport costs, and service distances. Country stakeholders then compared resulting future scenarios to identify the most feasible solution for their context. The DNO analyses enabled a wealth of insights that will facilitate strengthening of AMR laboratory and surveillance networks in both countries. Overall, the project highlights the benefits of using a data-driven approach for designing efficient diagnostic networks, to ensure better health resource allocation while maximizing the impact and equity of health interventions. Given the critical need to strengthen AMR laboratory and surveillance capacity, DNO should be considered an integral part of diagnostic strategic planning in the future.

Situational Analysis and Knowledge, Attitudes, and Practices of Antimicrobial Use and Resistance among Broiler Poultry Farmers in Nepal.

The purpose of this study was twofold: first, to conduct a situational analysis, and second, to assess the knowledge, attitudes, and practices (KAP) of broiler poultry farmers (BPF) regarding antimicrobial use (AMU) and antimicrobial resistance (AMR). Data were collected from 500 BPF across 40 districts, representing 88.1% of Nepal's broiler poultry population. Among these farmers, 81.0% were male, 59.6% had up to 4 years of experience in poultry farming, and 50.8% had completed at least a high school education. The most used antimicrobials on the farms were doxycycline (23.5%), neomycin (17.1%), and colistin sulfate (9.6%) out of 27 reported antimicrobials. While the BPF exhibited limited knowledge (62.6%) and practice (55.5%) related to AMU and AMR, their overall attitude toward these issues was positive (91.6%). This study also identified significant factors influencing farmers' attitudes toward AMU and AMR. Farmers aged 31-40 showed a stronger inclination compared to other age groups (OR = 4.2, p = 0.02), and those using antimicrobials for preventive purposes had a more favorable attitude compared to those using them for other purposes (OR = 5.9, p = 0.02). In light of these findings, this study recommends the implementation of effective regulatory measures for drug usage, along with awareness programs addressing AMU and AMR to address the issue of AMR in poultry production.

Molecular Detection and Identification of Piroplasm in Cattle from Kathmandu Valley, Nepal.

BACKGROUND: Tick-borne protozoan parasites (TBPPs) cause significant problems for domestic animals' health in Nepal. TBPPs are routinely diagnosed by labor-intensive blood smear microscopy. In Nepal, there are some reports of Babesia and Theileria in cattle, although species identification is rarely performed. Therefore, we performed conventional nested PCR (nPCR) followed by sequence analysis to identify TBPP species infecting cattle in Nepal. METHODS: One hundred and six blood samples were collected from cattle in the Kathmandu Valley. Thin blood smears were prepared for microscopic examination. Parasite DNA was extracted from the blood, and nPCR and sequencing were performed to identify the TBPPs present. RESULTS: Among the 106 samples, 45 (42.5%) were positive for piroplasm (Babesia spp. and Theileria spp.) via microscope observation and 56 (52.8%) samples were positive via nPCR. The obtained PCR products were used for direct sequencing, and we identified the species as B. bigemina, B. bovis, T. annulate and T. orientalis. Phylogenetic analyses showed that the B. bovis, B. bigemina and T. orientalis sequences from this study belonged to each species clade. On the other hand, T. annulate was divided into two clades in the analysis, and our T. annulate sequences were also divided in these two clades. The piroplasm-positive cattle showed lower hemoglobin and red blood cells than healthy cattle. CONCLUSIONS: To the best of our knowledge, this study is the first to apply molecular detection and species determination of TBPPs in cattle in Nepal. The results of this study may be used as a starting point for the development of successful TBPP surveillance and prevention programs in Nepal.

Integrative Digital Tools to Strengthen Data Management for Antimicrobial Resistance Surveillance in the "One Health" Domain in Nepal.

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.

Sero-epidemiology and associated risk factors of brucellosis among sheep and goat population in the south western Nepal: a comparative study.

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.

Detection of Plasmid-Mediated Colistin Resistant mcr-1 Gene in Escherichia coli Isolated from Infected Chicken Livers in Nepal.

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.

Risk factors of tuberculosis in human and its association with cattle TB in Nepal: A one health approach.

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. The study consists of human and animal subjects. Firstly, a retrospective matched case-control study was conducted at the National Tuberculosis Center (NTC), Bhaktapur, Nepal. A total of 290 people (equal numbers of TB cases and control subjects) were interviewed to obtain information on socio-demographic, behavioral, and occupational risks, including the history of cattle related exposures. Secondly, a cross-sectional study was performed among the cattle owned by the TB-confirmed patients. Comparative tuberculin skin test, rapid antibody test, and ELISA were used in parallel to detect M. bovis infection in cattle. The risk factors for the development of TB in humans were smokers (OR = 4.6, 95% CI: 2.1-10.0, p < 0.001), previous history of TB (OR = 7.9, 95% CI: 3.0-20.6, p < 0.001) and history of cattle exposures (OR = 3.9, 95% CI: 2.1-7.4, p = 0.001). Out of 123 cattle sampled, 12 cattle (9.76%, 95% CI: 5.37-16.76, p < 0.0001) were positive by the tuberculin test, 46 (37.4%, 95% CI: 28.97-46.62, p = 0.007) were tested positive by the rapid test, and 7 (5.7%, 95% CI: 2.52-11.80, p < 0.0001) by ELISA test. The inter-test agreement between the tuberculin and ELISA was very strong (κ = 0.72, 95% CI: 0.48-0.95, p < 0.01). This study indicates that exposure to infected cattle and socio-demographic risk factors can contribute to the development of TB in human beings.

Risk factors associated with Avian Influenza subtype H9 outbreaks in poultry farms in Kathmandu valley, Nepal.

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.