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In recent years, Guangxi has become one of the most severely affected provinces by epidemics of avian cholera in China. To date, the major determinant climatic factors of the disease in the region have remained largely unknown, making it difficult to effectively target countermeasures for avian cholera surveillance and control. This study aimed to quantify the relationship between climatic variables and cases of avian cholera in subtropical areas of China. Data relating to local meteorological variables and notified cases of avian cholera were supplied by the relevant authorities between January 2006 and December 2015. Spearman correlation, co-linearity statistics and crosscorrelation analysis were applied to the data, controlling for co-linearity and lag effects. A time-series Poisson regression analysis was conducted to examine the degree of correlation between the climate variables and avian cholera transmission. The results indicated that monthly mean temperature, relative humidity, rainfall and the multivariate El Niño Southern Oscillation Index, with 2-3 months lag, were correlated with avian cholera incidence. The final model had good predictive ability for the occurrence of avian cholera. Overall, the findings indicate that climate variability plays an important role in avian cholera transmission in Guangxi province. Adoption of the model presented in this study could usefully inform avian cholera surveillance strategies, making them significantly simpler and more effective. The model could also serve as a decision support tool for veterinary professionals and health authorities.

Our findings indicate that a specific enhancement pattern of lymphadenopathy seen on MDCT was useful in differentiating between untreated TB and lymphomas of the cervical lymph nodes.

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