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Research article2023Peer reviewedOpen access

The prevalence and risk factors of subclinical mastitis in water buffalo (Bubalis bubalis) in Bangladesh

Singha, Shuvo; Koop, Gerrit; Ceciliani, Fabrizio; Derks, Marjolein; Hoque, Md. Ahasanul; Hossain, Mohammed Kawser; Rahman, Md. Mizanur; Khatun, Momena; Boqvist, Sofia; Persson, Ylva


Subclinical mastitis (SCM) in water buffalo is responsible for reduced milk yield and quality. This cross-sectional study was carried out to a) estimate the prevalence of SCM, b) identify risk factors associated with SCM, and c) identify farm-level risk factors associated with bulk milk somatic cell count (BMSCC). The buffalo farms included in this study represented five rearing systems: free-range, semi-free-range, household, semi-intensive, and intensive, providing a total of 3491 functional quarters of 880 lactating buffalo on 248 farms. The California mastitis test score was used to identify SCM. Bulk milk samples (n = 242) were used for farm-level BMSCC. Quarter and buffalo-level risk factors for SCM were measured using questionnaires and observations. The overall SCM prevalence was high at 27.9% at the quarter-level (25th and 75th percentiles: 8.3% and 41.7%) and 51.5% at buffalo-level (25th and 75th percentiles: 33.3% and 66.7%). The geometric mean BMSCC was 217,000 cells/mL of milk (ranging from 36,000-1,213,000 cells/mL), which is low on average, but some farms could improve substantially. The buffalo rearing system, udder location (left versus right), teat shape, udder asymmetry, number of milkers, and having a quarantine facility were associated with buffalo udder health. Our findings suggest that mainly using free-range rearing systems may help decrease the prevalence of SCM primarily by employing buffalo breeding and better farm biosecurity, and udder health control strategies can be designed based on our findings.


Bulk milk somatic cell count; California mastitis test; Teat and udder shape; Hand milking; Udder health; Survey; Bangladesh farms

Published in

Research in Veterinary Science
2023, Volume: 158, pages: 17-25

    UKÄ Subject classification

    Clinical Science

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