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Application of structural equation modelling to inform best management strategies for Marek's disease in Amhara region, Ethiopia.

Mastewal BirhanNega BerhaneSaddam Mohammed IbrahimAbebe Tesfaye GesseseBereket DessalegnWubet Weledemedhin WoldemichaelEsayas GelayeBelayneh GetachewTakele AbaynehMolalegne Bitew
Published in: Scientific reports (2023)
Marek's disease, a highly contagious and an economically significant oncogenic and paralytic viral diseases of poultry, is becoming a serious problem in Ethiopia's poultry sector. The aim of the study was to examine the relationship between risk factors and their contribution to develop risk with the intentions to implement MD control measures in the different chicken production systems of Ethiopia using the SEM framework. A questionnaire was designed based on the framework and each model constructed was measured using a set of rating scale items. Thus, a sample size of 200 farmers from different production systems were chosen for the data collection. From the analysis, Cornbrash's Alpha (coefficient of reliability) based on the average inter-item correlations were evaluated for each parameter. The result showed that when litter management goes up by 1, the number of sick goes down by 37.575, the number of staff goes up by 1, the number of sick goes down by 7.63, litter management goes up by 1, the number of deaths goes down by 2.505, flock size goes up by 1, the number of deaths goes down by 0.007 than the rest of the activities. The result of this structural equation modeling finding indicates that the data fit the model well (χ 2  = 0.201, RMSEA = 0.000, CFI = 1.00, TLI = 1.496, Degrees of freedom = 2) and the model was appropriated. In conclusion, flock size, litter management and number of staff activities have more impact on the numbers of sick, drops in egg production and the number of deaths. Therefore, practicing regular awareness creation for producers regarding management techniques is recommended.
Keyphrases
  • risk factors
  • sars cov
  • machine learning
  • magnetic resonance
  • cross sectional
  • molecular dynamics
  • transcription factor
  • wastewater treatment
  • antimicrobial resistance