Prevalence and Associated Risk Factors of Infection with Tick-borne Pathogens in Sheep from Baghdad Governorate, Iraq: with a Special Reference to Babesia Ovis.
Published In: Alexandria Journal of Veterinary Sciences, 2025, v. 87. P. 40 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Al-Qudsi, Anhar S.; Saleh, Somaya; Faraj, Azhar A.; Abu-Elwafa, Salah A. 3 of 3
Abstract
A cross-sectional study was performed from November 2023 to October 2024 to investigate the prevalence and molecular characterization of tick-borne pathogens (TBPs) in sheep from four districts of Baghdad governorate, Iraq. A total of 505 blood samples were collected and examined microscopically and molecularly. Thin blood smears were stained with Giemsa and examined under oil immersion, revealing an overall TBPs prevalence of 27.52% (139/505). Three pathogens were identified: Babesia spp. (46.76%), Anaplasma spp. (41.72%), and Theileria spp. (40.28). Epidemiological analysis revealed significant associations with season, age, and locality. Higher infection rates were recorded in Summer (64.07%) and in sheep aged 2–3 years (43.35%), where females showed higher but non-significant prevalence compared to males. PCR confirmed the presence of TBPs in all microscopically positive samples, amplifying the 18S rRNA gene (piroplasms) and 16S rRNA gene (Anaplasma spp.). Sequencing identified Babesia ovis, Theileria ovis, and Anaplasma ovis, which were deposited in GenBank under accession numbers PP964812.1–PP961318.1. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Alexandria Journal of Veterinary Sciences. 2025/10, Vol. 87, p40
- Document Type:Article
- Subject Area:Geography and Cartography
- Publication Date:2025
- ISSN:1110-2047
- DOI:10.5455/ajvs.282823
- Accession Number:191144561
- Copyright Statement:Copyright of Alexandria Journal of Veterinary Sciences is the property of Faculty of Veterinary Medicine, Alexandria University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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