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目的分析互联网搜索数据与高致病性禽流感病毒H5N1的关系,探讨利用网络搜索工具对其监测和预警的可能性。方法基于联合国粮食及农业组织(Food and Agriculture Organization of the United Nations,FAO)和世界动物卫生组织(World Organization for Animal Health,OIE)收集整合了2004-2009年全球高致病性禽流感病毒H5N1在家禽中的暴发数据,从Google Trends获取同时期的相关关键词数据。在对二者的数据进行描述分析与对比的基础上,计算Spearman等级相关系数评价其相关程度,并通过平移技术以相关系数为指标分析互联网数据预测H5N1暴发的时间提前期。结果以2004-2009年为整体,互联网数据与H5N1的相关性并不高(r=0.276,t=3.57,P<0.001),但年度数据则均表现出了较强的相关性,2004-2009年相关性系数分别为r2004=0.718(t=3.64,P<0.001),r2005=0.576(t=3.58,P<0.001),r2006=0.760(t=3.62,P<0.001),r2007=0.474(t=3.45,P<0.001),r2008=0.750(t=3.47,P<0.001),r2009=-0.442(t=3.32,P=0.001)。且在各个年份中,将OIE/FAO流感监测数据提前1~4周后出现与Google Trends监测数据的相关系数最大值,可认为Google Trends数据可提前1~4周预测H5N1暴发的趋势。结论利用互联网搜索数据预测高致病性禽流感病毒H5N1的暴发可作为传统方法的补充手段,但由于搜索技术等的限制该方法仍需进行进一步的改进以提高准确性,其思路可推广至其他传染性疾病暴发的监测与预警。
Objective To analyze the relationship between Internet search data and H5N1 and to explore the possibility of using Web search tools to monitor and early warning. Methods Based on the collection and integration of the global HPAI virus H5N1 from 2004-2009 based on the Food and Agriculture Organization of the United Nations (FAO) and the World Organization for Animal Health (OIE) Get outbreak data in poultry to get relevant keyword data for the same period from Google Trends. Based on the descriptive analysis and comparison of the two data, Spearman rank correlation coefficient was calculated to evaluate the correlation degree, and the correlation coefficient was used as the index to analyze the Internet data to predict the H5N1 outbreak lead time. The results were from 2004 to 2009 as a whole. The correlation between Internet data and H5N1 was not high (r = 0.276, t = 3.57, P <0.001), but the annual data showed a strong correlation. 2004-2009 The annual correlation coefficients were r2004 = 0.718 (t = 3.64, P <0.001), r2005 = 0.576 (t = 3.58, P <0.001) = 3.45, P <0.001), r2008 = 0.750 (t = 3.47, P <0.001), r2009 = -0.442 (t = 3.32, P = 0.001). In each year, the trend of H5N1 outbreak was predicted 1 to 4 weeks ahead of schedule with the maximum correlation coefficient of OIE / FAO influenza surveillance data with Google Trends monitored 1 to 4 weeks in advance. Conclusion Prediction of the outbreak of HPAI H5N1 using Internet search data can be used as a supplement to traditional methods. However, this method needs to be further improved to improve the accuracy due to the limitation of search techniques, etc., and its concept can be extended to other Monitoring and early warning of outbreaks of infectious diseases.