Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5546018 | Veterinary Parasitology: Regional Studies and Reports | 2017 | 26 Pages |
Abstract
A hospital-based case-control study was undertaken to identify risk factors for - and space-time clusters of - bovine fascioliasis in Mymensingh, Bangladesh. Fascioliasis cases diagnosed using fecal sample test between January 2006 and December 2015 (n = 593) at the Bangladesh Agricultural University Veterinary Teaching Hospital (BAUVTH) and three controls per case (n = 1563) were selected. Data on date of report, location, age, breed, sex and body weight were extracted from the hospital records. A mixed multivariable logistic regression model with location as a random effect was built to identify risk factors for fascioliasis. The scan statistic (Bernoulli model) was used to identify space-time clusters. Compared to cattle â¤Â 1 year of age, the odds of fascioliasis were 5.2- (95% confidence interval [CI]: 3.6-7.4), 6.1- (95% CI: 4.2-8.7) and 10.7-times (95% CI: 6.9-16.6) greater in cattle aged > 1-3, > 3-8 and > 8 years, respectively. The odds of fascioliasis were 1.4- (95% CI: 1.03-1.99) and 1.5-times (95% CI: 1.13-2.11) greater in post-monsoon and monsoon seasons, respectively, compared to winter. Five significant (P < 0.05) clusters (7-13 locations each) were identified, lasting from six months to 5 years. Six locations - Bhangnamari, Deuhakhola, Gauripur, Ishwarganj, Nandail and Rasulpur - appeared to be at more risk for fascioliasis: these locations were part of at least 3 significant clusters. Anthelmintic treatment should focus on high risk age groups (> 1 year, especially those > 8 years). Importantly, we have demonstrated high-risk periods (monsoon and post-monsoon) and disease hotspots of bovine fascioliasis. Focusing disease control efforts in time and space offers an opportunity to more effectively control bovine fascioliasis in Bangladesh and in other similar geo-climatic zones throughout the world.
Keywords
Related Topics
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Veterinary Science and Veterinary Medicine
Veterinary Science
Authors
Mamun Khan, A.K.M. Anisur Rahman, Shamir Ahsan, Amimul Ehsan, Navneet Dhand, Michael P. Ward,