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Prevalence of Bovine Tuberculosis in Yaks Between 1982 and 2020 in Mainland China: A Systematic Review and
Yu-Hao Song1, Dong Li1, Ying Zhou1
1College of Animal Science and Technology, Jilin Agricultural University, Changchun, China.
Abstract:
Bovine tuberculosis (bTB) is a major chronic bacterial disease in cattle and is the major economic and animal welfare issue in the world. Although the economic costs and public health safety risks associated with the disease are considerable, the overall epidemiology of the Chinese yak (Bos grunniens) bTB is unclear. To fully reveal the basic prevalence of yak bTB in different regions of China, we searched five databases including PubMed, Science Direct, CNKI (China National Knowledge Infrastructure), Wanfang and Chongqing VIP. Based on the incidence and prevalence of yak tuberculosis in China from 1982 to 2020, a meta-analysis of yak bTB in China was established for the first time. By formulating the search formula, 97 studies were searched in five databases. According to the established exclusion criteria and excluded comments and repeated and irrelevance research, we finally selected 19 cross-sectional studies, which showed the prevalence of bTB in Chinese yaks. Random-effect meta-regression model analysis showed that the estimated prevalence of 122,729 yaks in China was 1.0 (95% confidence interval [CI]: 0.0-1.0). The regional prevalence varies greatly, northwest China prevalence rate 0. 39% (95% CI: 0.2-0. 64) and southwest China prevalence rate 2.59% (95% CI: 1.94-3.34); in terms of province level, the prevalence was highest in Tibet 2.59% (95% CI: 1.94-3.34), followed by Xinjiang 2.36% (95% CI: 0.86-4.58), and Shanxi has the lowest 0.00% (95% CI: 0.00-0.98). This systematic review and meta-analysis identified the estimated prevalence of bTB in Chinese yaks and estimated the underlying factors associated with bTB, including geographic location, sampling year, age, and TB detection method. Provide evidence to plan corresponding disease control strategies for policymakers and to assess future economic risks accurately.
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