Infectious laryngotracheitis (ILT) is a disease of high economic consequence to the poultry sector. Gallid herpesvirus 1 (GaHV-1), a.k.a infectious laryngotracheitis virus (ILTV), under the genus Iltovirus, and the family Herpesviridae, is the agent responsible for the disease. Despite the clinical signs on the field suggestive of ILT, it has long been considered nonexistent and a disease of no concern in Ethiopia. A cross-sectional study was conducted from November 2020 to June 2021 in three selected zones of the Amhara region (Central Gondar, South Gondar, and West Gojjam zones), Ethiopia, with the objective of estimating the seroprevalence of ILTV in chickens and identifying and quantifying associated risk factors. A total of 768 serum samples were collected using multistage cluster sampling and assayed for anti-ILTV antibodies using indirect ELISA. A questionnaire survey was used to identify the potential risk factors. Of the 768 samples, 454 (59.1%, 95% CI: 0.56–0.63) tested positive for anti-ILTV antibodies. Mixed-effect logistic regression analysis of potential risk factors showed that local breeds of chicken were less likely to be seropositive than exotic breeds (OR: 0.38, 95% CI: 0.24–0.61). In addition, factors such as using local feed source (OR: 6.53, 95% CI: 1.77–24.04), rearing chickens extensively (OR: 1.97, 95% CI: 0.78–5.02), mixing of different batches of chicken (OR: 14.51, 95% CI: 3.35–62.77), careless disposal of litter (OR: 1.62, 95% CI: 0.49–4.37), lack of house disinfection (OR: 11.05, 95% CI: 4.09–47.95), lack of farm protective footwear and clothing (OR: 20.85, 95% CI: 5.40–80.45), and careless disposal of dead chicken bodies had all been associated with increased seropositivity to ILTV. Therefore, implementation of biosecurity measures is highly recommended to control and prevent the spread of ILTV. Furthermore, molecular confirmation and characterization of the virus from ILT suggestive cases should be considered to justify the use of ILT vaccines.
Background Models have been presented to evaluate the link between dairy farm production factors and their degree of association with production determinants. Studies have found causal relationships between production parameters (dairy farm facility, farm hygiene and waste management, feed and nutrition, reproduction performance, health and extension services, mode of transportation, education level and gross revenue) as well as farm efficiency parameters. Furthermore, structural equation modelling (SEM) allows for the estimation of parameters that are not directly quantifiable, known as latent variables. Objective The research was designed to identify the dairy management determinants and evaluate farm production performance using an SEM approach in the selected areas of the Amhara region, Ethiopia. Methodology In‐person survey using a semi‐structured pre‐tested questionnaire was employed in 2021 to collect primary data on 117 randomly selected commercial dairy producers keeping cross‐breed Holstein Frisian cows in the Amhara region. SEM was used to study the complexity of influences on efficiency measures in milk production utilizing the combined data. Results The model result revealed that the relationship between construct reliabilities and farm facilities was significantly varied (p < 0.01). The model analysis showed that the level of education has also a positive and statistically significant correlation with the reproduction performance of the dairy farms, (ρ = 0.337) and the gross revenue of the farm showed as (p = 0.849). Farm gross revenue articulated a positive, strong statistically significant association with feed and nutrition values (ρ = 0.906), dairy farm facilities (ρ = 0.934), and hygiene and waste management (ρ = 0.921). Consequently, the predictors of dairy farm facility's feed and nutrition and hygiene and waste management explained 93.40%, 84.0%, 80.20%, and 88.50% of the variance. Conclusion The proposed model was scientifically valid, and training and education have an effect on management practices, subsequently affecting the production performance of the dairy farms.
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