基于动态网络生物标志物的甲流疫情早期预警算法研究

Detecting Early Warning Signal for Influenza A Epidemic in Each Country by Dynamical Network Biomarker

为了让各个国家在甲型流感病毒暴发前做好预防措施有效应对甲流疫情,选取了中国、埃及和印度三个发展中国家,以及美国、英国、澳大利亚、加拿大、意大利、荷兰和韩国7个发达国家的甲型流感病毒蛋白质数据,利用特征向量构建十个蛋白质相互作用的动态网络,找出动态网络生物标志物,构造早期预警指标,从而有效识别甲流疫情暴发的早期预警信号。通过模型分析与各国报道的实际暴发年比较,发现该模型可以较准确、可靠地识别出各国甲流暴发前的临界点。

In order to make each country to adopt effective measures before the outbreak of influenza A virus and to deal with the epidemic effectively,the influenza A virus protein data from three developing countries,including China,Egypt and India,as well as seven developed countries,including the United States,England,Australia,Canada,Italy,Netherlands and Korea was selected.The dynamical network of interactions between ten proteins by using feature vector and the dynamical network biomarker was built,thus the early warning index and the early warning signal of influenza A epidemic was constructed effectively.Comparing model analysis with the actual outbreak reported by each country,it is found that this model can identify the critical point before the outbreak of influenza A in each country.