Predicting Tuberculosis Risk in Cattle, Buffaloes, Sheep, and Goats in China Based on Air Pollutants and Meteorological Factors
2024

Predicting Tuberculosis Risk in Cattle, Buffaloes, Sheep, and Goats in China

Sample size: 264 publication 10 minutes Evidence: high

Author Information

Author(s): Xu Le, Li Suya, Li Hong, Pan Haoju, Li Shiyuan, Yang Yingxue, Jiao Yuqing, Lan Feng, Chen Si, Chen Qiaoling, Du Li, Man Churiga, Wang Fengyang, Gao Hongyan, Rao Sangeeta

Primary Institution: Hainan Key Laboratory of Tropical Animal Reproduction & Breeding and Epidemic Disease Research, Hainan University

Hypothesis

The study investigates the effects of air pollutants and meteorological factors on tuberculosis in domestic ruminants.

Conclusion

The study identifies key risk factors for tuberculosis in domestic ruminants and highlights high-risk regions in China.

Supporting Evidence

  • The study identified nitrogen dioxide (NO2) as a significant risk factor for tuberculosis.
  • The average area under the curve (AUC) of the model was 0.873, indicating strong predictive performance.
  • High-risk regions for tuberculosis were primarily located in South, North, East, and Northwest China.
  • Environmental factors such as mean temperature of the coldest quarter and precipitation of the driest month significantly influenced tuberculosis prevalence.
  • Improved surveillance is recommended in identified high-risk areas.

Takeaway

This study looks at how air pollution and weather can make cows, sheep, and goats sick with tuberculosis, helping to find areas where they are most at risk.

Methodology

The study used a maximum entropy ecological niche model to simulate tuberculosis risk based on environmental factors.

Potential Biases

Potential biases may arise from missing information and the use of pseudo-absence data.

Limitations

The study could not determine specific pathogens involved in tuberculosis cases due to immediate culling of infected livestock.

Participant Demographics

The study focused on cattle, buffaloes, sheep, and goats in China.

Statistical Information

P-Value

0.873

Confidence Interval

0.851–0.895

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.3390/ani14243704

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