School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, No. 11, Bei San Huan East Road, Chaoyang District, Beijing, 100029, China.
Hong Kong Chinese Medicine Clinical Study Centre, Chinese Clinical Trial Registry (Hong Kong Center), School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China.
BMC Infect Dis. 2019 May 17;19(1):435. doi: 10.1186/s12879-019-4011-6.
Over the past decades there have been outbreaks of mumps in many countries, even in populations that were vaccinated. Some studies suggest that the incidence of mumps is related to meteorological changes, but the results of these studies vary in different regions. To date there is no reported study on correlations between mumps incidence and meteorological parameters in Beijing, China.
A time series analysis incorporating selected weather factors and the number of mumps cases from 1990 to 2012 in Beijing was performed. First, correlations between meteorological variables and the number of mumps cases were assessed. A seasonal autoregressive integrated moving average model with explanatory variables (SARIMAX) was then constructed to predict mumps cases.
Mean temperature, rainfall, relative humidity, vapor pressure, and wind speed were significantly associated with mumps incidence. After constructing the SARIMAX model, mean temperature at lag 0 (β = 0.016, p < 0.05, 95% confidence interval 0.001 to 0.032) was positively associated with mumps incidence, while vapor pressure at lag 2 (β = -0.018, p < 0.05, 95% confidence interval -0.038 to -0.002) was negatively associated. SARIMAX (1, 1, 1) (0, 1, 1) with temperature at lag 0 was the best predictive construct.
The incidence of mumps in Beijing from 1990 to 2012 was significantly correlated with meteorological variables. Combining meteorological variables, a predictive SARIMAX model that could be used to preemptively estimate the incidence of mumps in Beijing was established.
在过去几十年中,许多国家都爆发了腮腺炎,甚至在已经接种疫苗的人群中也是如此。一些研究表明腮腺炎的发病率与气象变化有关,但这些研究的结果在不同地区有所不同。截至目前,尚未有报道称在中国北京,腮腺炎发病率与气象参数之间存在相关性。
对 1990 年至 2012 年北京的时间序列分析,结合选定的气象因素和腮腺炎病例数进行了分析。首先,评估了气象变量与腮腺炎病例数之间的相关性。然后,构建了具有解释变量的季节性自回归综合移动平均模型(SARIMAX)来预测腮腺炎病例。
平均温度、降雨量、相对湿度、蒸汽压和风速与腮腺炎发病率显著相关。在构建 SARIMAX 模型后,滞后 0 时的平均温度(β=0.016,p<0.05,95%置信区间 0.001 至 0.032)与腮腺炎发病率呈正相关,而滞后 2 时的蒸汽压(β=-0.018,p<0.05,95%置信区间 -0.038 至 -0.002)与腮腺炎发病率呈负相关。SARIMAX(1,1,1)(0,1,1)与滞后 0 时的温度是最佳预测结构。
1990 年至 2012 年北京腮腺炎的发病率与气象变量显著相关。结合气象变量,建立了一个可用于预测北京腮腺炎发病率的预测 SARIMAX 模型。