Himalayan College of Agricultural Sciences & Technology
Recent publications
A technique to predict crucial clinical prostate cancer (PC) is desperately required to prevent diagnostic errors and overdiagnosis. To create a multimodal model that incorporates long-established messenger RNA (mRNA) indicators and conventional risk variables for identifying individuals with severe PC on prostatic biopsies. Urinary has gathered for mRNA analysis following a DRE and before a prostatic examination in two prospective multimodal investigations. A first group ( n = 489 ) generated the multimodal risk score, which was then medically verified in a second group ( n = 283 ). The reverse transcription qualitative polymerase chain reaction determined the mRNA phase. Logistic regression was applied to predict risk in patients and incorporate health risks. The area under the curve (AUC) was used to compare models, and clinical efficacy was assessed by using a DCA. The amounts of sixth homeobox clustering and first distal-less homeobox mRNA have been strongly predictive of high-grade PC detection. In the control subjects, the multimodal method achieved a total AUC of 0.90, with the most important aspects being the messenger riboneuclic acid features’ PSA densities and previous cancer-negative tests as a nonsignificant design ability to contribute to PSA, aging, and background. An AUC of 0.86 was observed for one more model that added DRE as an extra risk component. Two methods were satisfactorily verified without any significant changes within the area under the curve in the validation group. DCA showed a massive net advantage and the highest decrease in inappropriate costs.
Perception of hub genes engaged in metastatic gastric cancer (mGC) promotes novel ways to diagnose and treat the illness. The goal of this investigation is to recognize the hub genes and reveal its molecular mechanism. In order to explore the potential facts for gastric cancer, the expression profiles of two different datasets were used (GSE161533 and GSE54129). The genes were confirmed to be part of the PPI network for gastric cancer pathogenesis and prognosis. In Cytoscape, the CytoHubba module was used to discover the hub genes. Responsible hub genes were identified. Data from Kaplan–Meier plotter confirmed the predictive value of these distinct genes in various stages of gastric malignancy. Upregulated and downregulated genes were identified to utilize for further analysis. Positive regulation by a host of viral process, positive regulation of granulocyte differentiation, negative regulation of histone H3–K9 methylation were found in DEGs analysis. In addition, five KEGG pathways were identified as an essential enhancer that include nucleotide excision repair; base excision repair; DNA replication; homologous recombination; and complement and coagulation cascades. POLE, BUB1B, POLD4, C3, BLM, CCT7, PRPF31, APEX1, PSMA7, and CDC45 were chosen as hub genes after combining the PPI results. Our study recommends that BUB1B, CCT7, APEX1, PSMA7, and CDC45 might be potential biomarkers for gastric cancer. These biomarkers are upregulated genes. Therefore, suppression of these genes will increase the survival rate in gastric cancer patients.
Globally, billions of people and their livelihood are threatened by the onset of COVID-19. In Nepal, resource-poor people who lost their job were the hardest hit among millions of impacted populations. Further, the associated effects of pandemics are food supply chain interruption and people's inferior physical and mental wellbeing. The COVID-19 pandemic and associated impacts have questioned Nepal's ability to achieve the 17 United Nations sustainable development goals (SDGs) in the post-pandemic era. Yet no scientific studies available to see COVID-19 and SDGs relationships in Nepal, government reports, and macroeconomic updates indicated that COVID-19 is likely to deter significantly in achieving SDGs targets. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to quantify the impacts of the COVID-19 pandemic in Nepal's macro-economy from March 2020 to December 2021. Our study indicated that the COVID-19 exerted inevitable challenges in achieving SDGs targets in terms of food security and household poverty. Therefore, this paper recommended creating more employment opportunities in the domestic economy and establishing a resilient food system.
Oxytetracycline (OTC) which is a broad-spectrum veterinary tetracycline antibiotic is extensively used in poultry farms as a prophylactic, therapeutic, and growth stimulator. Upon administration, unmetabolized OTC is excreted from the animal body through droppings and accumulated in litter in the poultry industry. This study aimed at investigating the OTC degradation potential of an-OTC tolerant bacterial strain, isolated from poultry manure. The isolated strain’s morphology, biochemical properties, and 16S ribosomal RNA (rRNA) gene sequence confirmed that it belonged to the Lysinibacillus genus. To measure the residual OTC concentration, a high-performance liquid chromatography method was used. OTC degradation rates were 2.579 mg L−1d−1 with Lysinibacillus strain 3+I and 1.149 mg L−1d−1 without Lysinibacillus strain 3+I. In the presence of strain 3+I, the half-life significantly reduced to 2.68 days, compared to 6.03 days without strain 3+I. The strain demonstrated 85% removal with the OTC concentration of 10 μg/ml. The influence of pH, temperature, carbon sources, and nitrogen source, which influence degradation, were also investigated. The optimum condition favouring degradation was pH 6 at a temperature of 30°C. In addition, Lysinibacillus sp. strain 3+I’s ability to degrade OTC in poultry litter offers a promising approach to treat poultry manure and effluent containing OTC, preventing its contamination in the environment.
Objective: In recent times, urinary tract infection (UTI) is one of the most widely recognized bacterial diseases all over the planet. UTI influences individuals of any age and gender. The target of this study is to concentrate on the recurrence of uropathogens, the antimicrobial susceptibility pattern of the isolates, and the plasmid profile of people from the government clinics of Karaikudi. Methods: From July 2017 to December 2017, 100 urine tests were gathered and handled for the isolation of pathogenic microbes. In total, 89 isolates were found from the samples collected. Results: Escherichia coli was discovered as the most common bacterial isolate screened from the UTI-infected people, accounting for 28.09 percent of all isolates. E. coli was seen to be the highest prevalent bacterium for UTI in all age groups and demonstrated resistance to routinely used medications, especially cefpodoxime and novobiocin, which have been 100 percent resistant. The E. coli isolates screened were positive for beta-lactamase and film generation, and they have strong antimicrobial resistance. As a result, the E. coli strains with the highest prevalence of virulence determinants have become more resistant to many medications because they support the microorganism in overcoming the host's defense and colonizing or entering the urinary system. The amplified 16S rRNA product was analyzed, and phylogenetic relationships were determined. The presence of TEM (56 percent), CTX-M (64 percent), SHV (40 percent), and OXA (60 percent) was discovered. Among E. coli isolates, CTX-M was the most common extended spectrum-beta lactamase (ESBL). Multiplex PCR was also used to identify the existence of CTX-M subgroups in E. coli isolates. Conclusion: Finally, we urge that antibiotic selection should be predicated on the awareness of the specific prevalence and that novel antimicrobial medicines for urinary infections be developed to combat the overuse of antibiotics.
A field experiment was carried out during the month of August – December 2020 at the Floriculture Development Center, Godawari, Lalitpur, Nepal. The experiment was conducted in randomized block design with seven treatments comprising of 3 levels each of MH (T2 : 200 ppm, T3: 300 ppm, T4 : 400 ppm) and GA3 (T5: 100 ppm, T6: 200 ppm, T7: 300 ppm) along with control (T1) replicated thrice with an objective to access the impact of maleic Hydrazide and gibberellic Acid on production and productivity of African marigold (Tagetes erecta L.) cv. Calcuttia Orange. The foliar spray of the growth regulators was applied at 30 DAT. The result revealed that vegetative growth viz. plant spread (2083 cm2), stem diameter (1.2 cm), number of primary (8.13) and secondary branches (28.27) was recorded significantly maximum with the treatment of MH at 400 ppm. The plant height (56.33 cm) was found to be maximum when treated with GA3 at 200 ppm whereas MH at 300 ppm resulted in highest number of leaves (139.26). First flowering (45 days), 50 % flowering (50 days), full bloom (54 days), maximum flower weight (11.33 g) and maximum flower diameter (8.10 cm) were achieved with GA3 at 200 ppm. However, the maximum number of flowers (29) was obtained by the foliar spray of MH at 400 ppm. MH at 400 ppm resulted the maximum yield of the flowers (23.528 t/ha) followed by GA3 at 200 ppm (23.079 t/ha). The experiment concluded that MH at 400 ppm and GA3 at 200 ppm contributed to increased growth, flowering and yield of the crop.
Background The threat of methicillin-resistant Staphylococcus aureus (MRSA) exists globally and has been listed as a priority pathogen by the World Health Organization. One of the sources of MRSA emergence is livestock and its products, often raised in poor husbandry conditions. There are limited studies in Nepal to understand the prevalence of MRSA in dairy animals and its antimicrobial resistance (AMR) profile. A cross-sectional study was conducted in Chitwan, one of the major milk-producing districts of Nepal, from February 2018 to September 2019 to estimate the prevalence of MRSA in milk samples and its AMR profile. The collected milk samples (n = 460) were screened using the California Mastitis Test (CMT) and positive samples were subjected to microbiological analysis to isolate and identify S. aureus. Polymerase Chain Reaction (PCR) was used to identify the presence of the mecA gene and screen for MRSA. Results In total, 41.5% (191/460) of milk samples were positive in the CMT test. Out of 191 CMT positive milk samples, the biochemical tests showed that the prevalence of S. aureus was 15.2% (29/191). Among the 29 S. aureus isolates, 6.9% (2/29) were identified as MRSA based on the detection of a mecA gene. This indicates that that 1.05% (2/191) of mastitis milk samples had MRSA. The antibiotic sensitivity test showed that 75.9% (22/29) and 48.3% (14/29) S. aureus isolates were found to be sensitive to Cefazolin and Tetracycline respectively (48.3%), whereas 100% of the isolates were resistant to Ampicillin. In total 96.6% (28/29) of S. aureus isolates were multidrug-resistant (MDR). Conclusions This study revealed a high prevalence of S. aureus-mediated subclinical mastitis in dairy herds in Chitwan, Nepal, with a small proportion of it being MRSA carrying a mecA gene. This S. aureus, CoNS, and MRSA contaminated milk poses a public health risk due to the presence of a phenotype that is resistant to very commonly used antibiotics. It is suggested that dairy herds be screened for subclinical mastitis and treatments for the animals be based on antibiotic susceptibility tests to reduce the prevalence of AMR. Furthermore, future studies should focus on the Staphylococcus spp. to explore the antibiotic resistance genes in addition to the mecA gene to ensure public health.
Background Since 1999, West Nile virus (WNV) has moved rapidly across the United States, resulting in tens of thousands of human cases. Both the number of human cases and the minimum infection rate (MIR) in vector mosquitoes vary across time and space and are driven by numerous abiotic and biotic forces, ranging from differences in microclimates to socio-demographic factors. Because the interactions among these multiple factors affect the locally variable risk of WNV illness, it has been especially difficult to model human disease risk across varying spatial and temporal scales. Cook and DuPage Counties, comprising the city of Chicago and surrounding suburbs, experience some of the highest numbers of human neuroinvasive cases of WNV in the United States. Despite active mosquito control efforts, there is consistent annual WNV presence, resulting in more than 285 confirmed WNV human cases and 20 deaths from the years 2014–2018 in Cook County alone. Methods A previous Chicago-area WNV model identified the fifty-five most high and low risk locations in the Northwest Mosquito Abatement District (NWMAD), an enclave ¼ the size of the combined Cook and DuPage county area. In these locations, human WNV risk was stratified by model performance, as indicated by differences in studentized residuals. Within these areas, an additional two-years of field collections and data processing was added to a 12-year WNV dataset that includes human cases, MIR, vector abundance, and land-use, historical climate, and socio-economic and demographic variables, and was assessed by an ultra-fine-scale (1 km spatial x 1 week temporal resolution) multivariate logistic regression model. Results Multivariate statistical methods applied to the ultra-fine-scale model identified fewer explanatory variables while improving upon the fit of the previous model. Beyond MIR and climatic factors, efforts to acquire additional covariates only slightly improved model predictive performance. Conclusions These results suggest human WNV illness in the Chicago area may be associated with fewer, but increasingly critical, key variables at finer scales. Given limited resources, these findings suggest large variations in model performance occur, depending on covariate availability, and provide guidance in variable selection for optimal WNV human illness modeling.
Coxiella burnetii, a Gram-negative bacterium is a zoonotic agent causing coxiellosis in animals. Small ruminants and cattle are the primary reservoirs for human infection. This study was aimed to estimate the sero-prevalence of C. burnetii in the ruminants of the selected region in Nepal. Field visits were carried out at four sites in different geographical regions of Nepal. A total of 522 sera samples were collected from 118 sheep, 242 goats and 162 cattle with the history of abortion, anoestrus and infertility. Sera were tested for the presence of antibodies against C. burnetii using a commercially available ready-to-use ELISA test kit. The overall true sero-prevalence was 1.89% (95% CI: 0.33-3.45), the prevalence ranged between 4.35% and 23.21% in goats. Sero-prevalence in goat was higher than that of cattle and sheep which ascertained that total freedom from coxiellosis cannot be confirmed in Nepal. This could complement the impacts of other infectious causes of the infertility in the farm animals as well as the public health of the farming households.
Background: The emergence of the novel coronavirus in December 2019, now named SARS-CoV-2, has reached the pandemic level. The ongoing pandemic has already infected more than twenty-nine million people with a global death tally of over nine hundred thousand as of Mid-September 2020. The knowledge, attitude, and practice (KAP) of people towards this disease is important to understand to limit its transmission. Methods: This cross-sectional study was conducted among 101 secondary level students in Bharatpur, Chitwan, Nepal to assess their KAP. Results: The majority of the students were found to be knowledgeable of the timeline of the first outbreak (92.08%), and nearly three-fourth participants were aware of the hand-washing duration of 20 seconds (73.27%). The knowledge of the presence of disease in Nepal (50.50%), the causative agent of disease (65.53%), and symptoms (57.43%) showed that there is significant knowledge gap among participants. The good proportion of participants were found to have a positive attitude towards the prevention and control of the disease. The majority of the respondents reported using face mask (77.23%), adopting hand-washing measures (79.21%) as preventive measures for COVID-19. The majority of the students were highly concerned about the disease. Conclusion: In summary, secondary level students of Chitwan, Nepal were found to have fair knowledge and understanding of the disease, showed a moderately positive attitude towards preventive measure and reported appropriate preventive practices against COVID-19. It is recommended that a similar study with a wider population be conducted to assess KAP of Nepalese people towards COVID-19.
Modeling vector-borne diseases is best conducted when heterogeneity among interacting biotic and abiotic processes is captured. However, the successful integration of these complex processes is difficult, hindered by a lack of understanding of how these relationships influence disease transmission across varying scales. West Nile virus (WNV) is the most important mosquito-borne disease in the United States. Vectored by Culex mosquitoes and maintained in the environment by avian hosts, the virus can spill over into humans and horses, sometimes causing severe neuroinvasive illness. Several modeling studies have evaluated drivers of WNV disease risk, but nearly all have done so at broad scales and have reported mixed results of the effects of common explanatory variables. As a result, fine-scale relationships with common explanatory variables, particularly climatic, socioeconomic, and human demographic, remain uncertain across varying spatial extents. Using an interdisciplinary approach and an ongoing 12-year study of the Chicago region, this study evaluated the factors explaining WNV disease risk at high spatiotemporal resolution, comparing the human WNV model and covariate performance across three increasing spatial extents: ultrafine, local, and county scales. Our results demonstrate that as spatial extent increased, model performance increased. In addition, only six of the 23 assessed covariates were included in best-fit models of at least two scales. These results suggest that the mechanisms driving WNV ecology are scale-dependent and covariate importance increases as extent decreases. These tools may be particularly helpful for public health, mosquito, and disease control personnel in predicting and preventing disease within local and fine-scale jurisdictions, before spillover occurs.
Dairy animals are an important source of income, food, and nutritional security, and improvements in the productivity of dairy animals substantially improve the wellbeing of smallholder dairy farmers. As in other developing countries, dairy animals are key for rural livelihoods in Nepal but often suffer from mastitis—a production disease causing economic losses to farmers, challenges to the dairy processing industry, and possible health hazards to consumers. Studies show that the prevalence of subclinical mastitis in Africa and Asia typically exceeds 50%, threatening animal wellbeing, farmers, dairy processors, and consumers. We conducted a study in Nepal to develop a technology training package to control mastitis in dairy animals. Following identification of knowledge gaps, a technology package consisting of (1) developing good husbandry practices, implementing mastitis detection and control technologies; and (2) training technicians and farmers was implemented. A strategy was subsequently established to provide feedback to farmers in dairy cooperatives on the subclinical mastitis status of their cows. The package was applied in the mid-western region of Nepal. Six months after implementation, we observed a reduction in subclinical mastitis prevalence: from 55% (baseline) to 28% (endline; n = 432) in dairy cows and from 78% to 18% (n = 216) in buffalo. These positive study outcomes strongly suggest that the mastitis technology training package should be scaled across smallholder farmers within and beyond Nepal to control mastitis in dairy animals.
Coronavirus disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), was first reported in late 2019 from Wuhan, China. Considering COVID-19's alarming levels of spread and severity, the World Health Organization (WHO) declared a global pandemic on March 11, 2020. The first case of COVID-19 in Nepal was reported on January 23, 2020. The Government of Nepal implemented different public health measures to contain COVID-19, including border closures and a countrywide lockdown. We collected the daily data provided by the Ministry of Health and Population (MoHP) of the Government of Nepal and illustrated the early epidemiological characteristics of COVID-19 in Nepal. By May 31, 2020, 1,572 cases and eight deaths were reported in Nepal associated with COVID-19. The estimate of prevalence for COVID-19 among tested populations was 2.25% (95% CI: 2.15–2.37%) and case-fatality rate was 0.5%. The majority of the cases were young males (n = 1,454, 92%), with overall average age being 30.5 years (ranging from 2 months to 81 years) and were mostly asymptomatic. There were only five cases from three districts until the end of March, but cases surged from April and spread to 57 out of 77 districts of Nepal by the end of May 2020 despite the continuous lockdown. Most of these cases are from the southern plains of Nepal, bordering India. As the effect of COVID-19 is expected to persist longer, the Government of Nepal should make appropriate strategies for loosening lockdowns in a phase-wise manner while maintaining social distancing and personal hygiene and increasing its testing, tracking, and medical capacity.
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.
Bagmati River has been a terrific boon in different aspects like natural, cultural, ecological, etc. However, the river has been in a critical situation with the shift in its quality and quantity during these years. Since the changes are slow-growing, actual shifts are barely noticed. While the in-situ analysis and experimentation become costly, the analysis of Landsat images acquired with the application of Remote Sensing (RS) and Geographic Information System (GIS) provides an inexpensive technique in estimating and mapping such temporal shift in the river. Concerning the case, this study modelled the temporal changes of the Bagmati River within 25 years (1991–2016) using the multi-temporal Landsat images. We adopted the Normalized Difference Water Index (NDWI for the unsupervised extraction of the water feature and monitoring the changes. A model was developed in Arc-GIS by discerning the river, and the difference was determined for 25 years. The result indicated a major temporal shift in the river channel with a decreasing trend from 1991 to 2016. Over 25 years, the river loss almost one-third of its original water-flow channel with a severe sweep in the south-western portion of the study area. With this precise information, a field-based study can be undertaken either to analyse the damage caused by the river in those particular portions or to assess the factors affecting the river shift. Hence, we strongly recommend employing the cost-effective methods, RS and GIS, for detecting, analysing and monitoring the shifts and changes in the rivers and lakes over a while.
Current information on the domestic yak (Poephagus grunniens or Bos grunniens) in the Himalayan agroecological zone in Nepal is limited. Despite their isolation, yak may contact other domestic livestock particularly during the winter when they are at lower altitudes and as such they may be exposed to infectious disease. Faeces from 50 adult yak from a herd of 123 adults and 27 calves in the Kaski region of the Nepali Himalaya were analysed for the presence of gastrointestinal parasites using standard flotation and sedimentation methods. In this herd, 18 per cent (95% CI 9% to 31%) of the samples showed evidence of nematode infection, with trichostrongyle and Nematodirus/Marshallagia species eggs being detected. No trematode eggs were detected in any samples, and no Galba species or other snails were found in the environment. The herd appeared healthy with low intestinal parasitic burdens. Our findings may indicate Nematodirus/Marshallagia species infection to be exclusive to yak in this region.
Background: Avian pathogenic Escherichia coli (APEC) are causative agent of extraintestinal infections, collectively known as colibacillosis, which results significant losses in poultry industries. The extraintestinal survival of E. coli is facilitated by numerous virulence factors which are coded by virulence genes. This study was conducted to find out the pattern of antibiotic resistance and virulence genes content in the APEC strains isolated from broiler chickens at National Avian Disease Investigation Laboratory and Veterinary Teaching Hospital, Rampur, Chitwan, Nepal. Results: A total of 50 E. coli strains were isolated from 50 colibacillosis suspected broiler chickens. Out of 50 isolates of E. coli, 47 (94%) showed resistant to three or more antimicrobials. The highest levels (22%) of multidrug-resistant E. coli were observed for five different types of antimicrobials. Antibiogram profiles of 50 E. coli strains showed the maximum resistance to ampicillin (98%), followed by co-trimoxazole (90%), and doxycycline (62%). The highest intermediate resistance was shown by colistin (50%) and the highest sensitivity was against amikacin (84%), followed by nitrofurantoin (55%). Based on the genetic criteria, 45 (90%) E. coli isolates were considered as pathogenic (APEC) which contained more than five virulence genes. Out of total APEC genes detected, we found the combination of iss, iucD, hlyF, ompT, iroN, and iutA genes were mostly associated with the APEC and additionally, to some lesser extent irp2, papC, Cva/cvi, and tsh genes showed the critical role for virulent traits of APEC strains. Conclusion: In this study, high prevalent of antimicrobial resistant pattern was found with avian pathogenic E. coli strains isolated from broiler chickens. To our knowledge, this is the first molecular analysis which confirmed the prevalence of APEC strains in poultry sector in Nepal. These finding suggest the need of surveillance and intervention system to control misuse of antibiotics and APEC outbreak in the poultry farm.
Background: The Bovine Viral Diarrhea Virus (BVDV) infection causes reproductive and respiratory disease in cattle and buffaloes and is an economically important livestock disease across the world. In Nepal, cattle and buffalo farming is an important source of income for a majority of farmers. Infectious reproductive and respiratory diseases are common in Nepalese dairy herds and a large proportion of these cases remains undiagnosed. The burden of BVDV in Nepal is unknown. The objective of this pilot study was to determine the prevalence of persistent BVDV infection in dairy cattle in two commercially important livestock districts of Nepal. Materials and Methods: In total, 240 ear notch samples (153 samples from Chitwan and 87 samples from Kavrepalanchowk) from 60 dairy herds (30 herds in each district) were collected from cattle and buffaloes from December, 2014 through April, 2015. Questionnaire surveys were conducted to collect information on demographics and farm characteristics. Results: The farm-wise prevalence was 3.3% (95% CI: 0.1-17.2%) in Chitwan and 10.0% (95% CI: 2.1-26.5%) in Kavrepalanchowk, whereas individual animal prevalence was 0.7% (95% CI: 0.0-3.6%) in Chitwan and 3.4% (95% CI: 1.2-9.7%) in Kavrepalanchowk. Questionnaire survey indicated overall poor biosecurity in dairy farms and use of natural insemination for breeding with bulls of unknown origin, which may contribute to the spread of BVDV infection. Conclusion: This pilot study indicates circulation of BVDV and the presence of persistent infections in dairy herds in Nepal. It is suggested that the Nepal government and commercial dairy farmers include BVDV in regular surveillance and diagnostic activities.
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62 members
Binayak Rajbhandari
  • Faculty of Agriculture
Aakash Adhikari
  • Faculty of Agriculture
Binayak P Rajbhandari
  • Crop and Soil Sciences
Injila Tiwari
  • Faculty of Agriculture
Bhaktapur, Nepal