Factors associated with strongylida infections in sheep on farms in peri-urban Nairobi, Kenya.

Autor: Tangus CJ; Department of Veterinary Pathology, Microbiology and Parasitology, University of Nairobi, 00625 Nairobi, Kenya. Electronic address: ctangus@uonbi.ac.ke., Nga'nga CJ; Department of Veterinary Pathology, Microbiology and Parasitology, University of Nairobi, 00625 Nairobi, Kenya., Njuguna KD; Department of Veterinary Pathology, Microbiology and Parasitology, University of Nairobi, 00625 Nairobi, Kenya., Gachuiri CK; Department of Clinical Studies, University of Nairobi, 00625 Nairobi, Kenya., Kimeli P; Department of Animal Production, University of Nairobi, 00625 Nairobi, Kenya.
Jazyk: angličtina
Zdroj: Veterinary parasitology, regional studies and reports [Vet Parasitol Reg Stud Reports] 2024 Jan; Vol. 47, pp. 100955. Date of Electronic Publication: 2023 Nov 16.
DOI: 10.1016/j.vprsr.2023.100955
Abstrakt: Gastrointestinal parasite infections are among the major limitations to production in sheep in many parts of the world. It is important to continually assess their levels of infection in order to institute control measures and reduce the impact. This study determined the factors associated with the strongylida egg counts in sheep on selected farms in peri-urban Nairobi, Kenya. This was a cross-sectional study in which farm and animal-level data, including faecal samples, were collected from 1640 sheep from 30 purposively selected farms in Ruai, and Kamulu wards in Kasarani sub-county and Utawala and Mihango wards in Embakasi East Sub-County, in Nairobi County Kenya. The faecal samples were subjected to coprological examination using a modified McMaster technique to determine counts of strongylida eggs and coccidia oocysts with a detection level of 100 egg or oocyst per gram (EPG or OPG) of faeces. The positive faecal samples for strongylida eggs were pooled per farm and cultured for morphological identification of larval stage three. Descriptive statistics and multilevel mixed-effect logistic regression analyses were used to determine factors associated with strongylida egg count ≥600 EPG (p < 0.05). The receiver operating characteristics curve was used to assess the overall diagnostic performance in the final model. Strongylida eggs were detected in 45.5% (746/1640) of the sheep, and the mean EPG was 486.0± 858.9 with a median of 200 and a range of 0-16,700. The coccidia oocysts were detected in 49.4% (810/1640) of the sheep with a mean OPG was 341.7± 1782.4, a median of 0 and a range of 0-60,000. In the coprocultures, the nematode genera identified (% differential count of L3) were Haemonchus (90%), Trichostrongylus (5%) and Oesophagostomum (5%). In the final multivariable regression model, the odds of detecting EPG ≥ 600 was 1.44 times higher for sheep shedding coccidia oocysts than those that did not. The odds for detecting EPG ≥ 600 was 4.01 times for sheep in Ruai ward compared with those in the combined Kamulu, Utawala and Mihango wards. The receiver operating characteristic curve area was 73.1%, suggestive of good model performance. The results suggest that gastrointestinal strongylida and coccidia infections are common in sheep and farmers should be educated on the importance of appropriate control measures.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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