Chen Banghua, Sumi Ayako, Wang Lei, Zhou Wang, Kobayashi Nobumichi
Department of Infectious Diseases Control and Prevention, Wuhan Center for Disease Control and Prevention, Wuhan, Hubei, China.
Department of Hygiene, Sapporo Medical University School of Medicine, S-1, W-17, Chuo-ku, Sapporo, Hokkaido, 060-8556, Japan.
BMC Infect Dis. 2017 Aug 3;17(1):538. doi: 10.1186/s12879-017-2640-1.
Chickenpox is a common contagious disease that remains an important public health issue worldwide. Over 90% of unvaccinated individuals become infected, but infection occurs at different ages in different parts of the world. Many people have been infected by 20 to 30 years of age in China, and adults and pregnant women who become infected often develop severe infection. Furthermore, a mortality rate of 2-3 per 100,000 infected persons has been reported. In this study, we explore the temperature-dependent transition of patterns of reported chickenpox cases in two large subtropical climate cities, Wuhan and Hong Kong, China, to aid in the prediction of epidemics and preparation for the effects of climatic changes on epidemiology of chickenpox in China.
We used a time series analysis comprising a spectral analysis based on the maximum entropy method in the frequency domain and the nonlinear least squares method in the time domain. Specifically, the following time series data were analyzed: data of reported chickenpox cases and meteorological data, including the mean temperature, relative humidity and total rainfall in Wuhan and Hong Kong from January 2008 to June 2015.
The time series data of chickenpox for both Wuhan and Hong Kong have two peaks per year, one in winter and another in spring, indicating a bimodal cycle. To investigate the source of the bimodal cycle of the chickenpox data, we defined the contribution ratio of the 1-year cycle, Q , and the 6-month cycle, Q , as the contribution of the amplitude of a 1-year cycle and a 6-month cycle, respectively, to the entire amplitude of the time-series data. The Q values of Wuhan and Hong Kong were positively correlated with the annual mean temperature and rainfall of each city. Conversely, the Q values of Wuhan and Hong Kong were negatively correlated with the annual mean temperature and rainfall of Wuhan and Hong Kong.
Our results showed that the mean temperature and rainfall have a significant influence on the incidence of chickenpox, and might be important predictors of chickenpox incidence in Wuhan and Hong Kong.
水痘是一种常见的传染病，在全球范围内仍是一个重要的公共卫生问题。超过90%未接种疫苗的人会被感染，但在世界不同地区，感染发生在不同年龄段。在中国，许多人在20到30岁时已被感染，而感染的成年人和孕妇往往会发展为严重感染。此外，据报道，每10万名感染者中有2至3人的死亡率。在本研究中，我们探讨了中国两个亚热带气候大城市武汉和香港报告的水痘病例模式的温度依赖性转变，以帮助预测疫情，并为气候变化对中国水痘流行病学的影响做好准备。
我们采用了一种时间序列分析方法，包括频域中基于最大熵方法的谱分析和时域中的非线性最小二乘法。具体而言，分析了以下时间序列数据：2008年1月至2015年6月武汉和香港报告的水痘病例数据以及气象数据，包括平均温度、相对湿度和总降雨量。
武汉和香港的水痘时间序列数据每年有两个峰值，一个在冬季，另一个在春季，呈现双峰循环。为了研究水痘数据双峰循环的来源，我们将1年周期的贡献率Q₁和6个月周期的贡献率Q₂分别定义为1年周期和6个月周期的振幅对时间序列数据总振幅的贡献。武汉和香港的Q₁值与每个城市的年平均温度和降雨量呈正相关。相反，武汉和香港的Q₂值与武汉和香港的年平均温度和降雨量呈负相关。
我们的结果表明，平均温度和降雨量对水痘发病率有显著影响，可能是武汉和香港水痘发病率的重要预测指标。
