微生物所流感病毒与气候因子模型构建研究获进展
人类感染H7N9和H5N1高致病性流感病毒的病例呈散发性分布，目前针对环境因子与上述两种病毒发病率的相关性研究较少。鉴于此，中国科学院微生物研究所科研人员分析该类病毒的环境影响因素，并分别对H7N9和H5N1的感染病例进行了比较分析。结果表明，流感病毒爆发和传播与温度、湿度等气候因子相关。时空分析发现，H5N1感染病例主要集中在华南、中部以及西北地区，而H7N9的感染病例主要集中在东部和南部沿海地区。H5N1流感病毒感染主要集中在12月、1月和2月三个月份，而H7N9无明显月份分布差异。除了时空特性的差异，两种病毒的适宜气候因子也不相同。H5N1感染的适宜温度为5-10℃，风速1-2 km/h；而H7N9的适宜温度为10-15℃；风速2-3 km/h；另外两株病毒对应的适宜湿度均为60-80%。
通过整合气候因子对人类感染两株高致病禽流感病毒的分析，对于预测可能爆发的疫情和制定预防措施提供了有利依据。该研究拓展了对气候变化与人类疾病关联规律的基本认识，明确气候因子影响人类疾病的阈值，揭示气候变化影响传染性疾病的动态时空传播和进化机制。该研究将进一步探索气候变化直接、间接影响典型传染性疾病的突发性，并揭示气候变化影响传染性疾病的传播机制。
这些结果已于2015年12月11日在Scientific Reports 发表，题为Identification of climate factors related to human infection with avian influenza A H7N9 and H5N1 viruses in China。
该研究得到了刘起勇主持的全球变化国家重大科学研究计划（“973”计划）（项目名称：气候变化对人类健康的影响与适应机制研究、项目编号：2012CB955500）、国家自然科学基金项目及“十二五”传染病专项能力建设项目的资助。
http://www.bio360.net/attachments/2016/01/14530879766c585cddc62c9436.pngH5N1和H7N9通过PCA分析的预测结果
来源：微生物研究所
Identification of climate factors related to human infection with avian influenza A H7N9 and H5N1 viruses in China
Jing Li, Yuhan Rao, Qinglan Sun, Xiaoxu Wu, Jiao Jin, Yuhai Bi, Jin Chen, Fumin Lei, Qiyong Liu, Ziyuan Duan, Juncai Ma, George F. Gao, Di Liu & Wenjun Liu
Human influenza infections display a strongly seasonal pattern. However, whether H7N9 and H5N1 infections correlate with climate factors has not been examined. Here, we analyzed 350 cases of H7N9 infection and 47 cases of H5N1 infection. The spatial characteristics of these cases revealed that H5N1 infections mainly occurred in the South, Middle, and Northwest of China, while the occurrence of H7N9 was concentrated in coastal areas of East and South of China. Aside from spatial-temporal characteristics, the most adaptive meteorological conditions for the occurrence of human infections by these two viral subtypes were different. We found that H7N9 infections correlate with climate factors, especially temperature (TEM) and relative humidity (RHU), while H5N1 infections correlate with TEM and atmospheric pressure (PRS). Hence, we propose a risky window (TEM 4–14 °C and RHU 65–95%) for H7N9 infection and (TEM 2–22 °C and PRS 980-1025 kPa) for H5N1 infection. Our results represent the first step in determining the effects of climate factors on two different virus infections in China and provide warning guidelines for the future when provinces fall into the risky windows. These findings revealed integrated predictive meteorological factors rooted in statistic data that enable the establishment of preventive actions and precautionary measures against future outbreaks.
http://www.nature.com/articles/srep18094
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