中国上海的天气变化与甲型H7N9流感传播：贝叶斯空间分析
Weather variability and influenza A (H7N9) transmission in Shanghai, China: a Bayesian spatial analysis.
作者信息
Hu Wenbiao, Zhang Wenyi, Huang Xiaodong, Clements Archie, Mengersen Kerrie, Tong Shilu
机构信息
School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia; Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia.
Institute of Disease Control and Prevention, Academy of Military Medical Science, Beijing, People's Republic of China.
出版信息
Environ Res. 2015 Jan;136:405-12. doi: 10.1016/j.envres.2014.07.033. Epub 2014 Nov 25.
BACKGROUND
A novel avian influenza A (H7N9) virus was first found in humans in Shanghai, and infected over 433 patients in China. To date, very little is known about the spatiotemporal variability or environmental drivers of the risk of H7N9 infection. This study explored the spatial and temporal variation of H7N9 infection and assessed the effects of temperature and rainfall on H7N9 incidence.
METHODS
A Bayesian spatial conditional autoregressive (CAR) model was used to assess the spatiotemporal distribution of the risk of H7N9 infection in Shanghai, by district and fortnight for the period 19th February-14th April 2013. Data on daily laboratory-confirmed H7N9 cases, and weather variability including temperature (°C) and rainfall (mm) were obtained from the Chinese Information System for Diseases Control and Prevention and Chinese Meteorological Data Sharing Service System, respectively, and aggregated by fortnight.
RESULTS
High spatial variations in the H7N9 risk were mainly observed in the east and centre of Shanghai municipality. H7N9 incidence rate was significantly associated with fortnightly mean temperature (Relative Risk (RR): 1.54; 95% credible interval (CI): 1.22-1.94) and fortnightly mean rainfall (RR: 2.86; 95% CI: 1.47-5.56).
CONCLUSION
There was a substantial variation in the spatiotemporal distribution of H7N9 infection across different districts in Shanghai. Optimal temperature and rainfall may be one of the driving forces for H7N9.
背景
一种新型甲型禽流感（H7N9）病毒首次在上海的人类中被发现，并在中国感染了433多名患者。迄今为止，关于H7N9感染风险的时空变异性或环境驱动因素知之甚少。本研究探讨了H7N9感染的时空变化，并评估了温度和降雨对H7N9发病率的影响。
方法
采用贝叶斯空间条件自回归（CAR）模型，按区和两周时间评估2013年2月19日至4月14日期间上海H7N9感染风险的时空分布。每日实验室确诊的H7N9病例数据以及包括温度（℃）和降雨量（毫米）在内的天气变化数据，分别从中国疾病预防控制信息系统和中国气象数据共享服务系统获取，并按两周进行汇总。
结果
H7N9风险的高空间变异性主要出现在上海市的东部和中部。H7N9发病率与两周平均温度（相对风险（RR）：1.54；95%可信区间（CI）：1.22 - 1.94）和两周平均降雨量（RR：2.86；95%CI：1.47 - 5.56）显著相关。
结论
上海不同区的H7N9感染时空分布存在显著差异。适宜的温度和降雨可能是H7N9的驱动因素之一。
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