每年流感流行都會導(dǎo)致全球幾十萬甚至百萬人的死亡,，是全球公共衛(wèi)生防控的重要對象。流感病毒在流行過程中會快速變異,，產(chǎn)生了不同危害程度的流感病毒變異株,，因而會導(dǎo)致流感病毒在不同的流感季節(jié)中死亡人數(shù)不一樣。但目前對流感導(dǎo)致人死亡的危害程度的估計主要依賴于監(jiān)控,，往往只能在流感流行了一段時間后才能相對準(zhǔn)確地估計,，不利于各國的衛(wèi)生部門快速有效地制訂流感防治的策略。如果能在病毒出現(xiàn)的早期就估算出其潛在的危害性,，將為科學(xué)有效地制訂流感防控政策提供重要依據(jù),。
中國科學(xué)院生物物理研究所蔣太交課題組提出了一個新的宿主-病毒相互作用模型，首次建立了病毒導(dǎo)致的超額死亡和其抗原變異程度之間的定量關(guān)系,，并進一步發(fā)展了直接從病毒序列出發(fā)快速準(zhǔn)確估算流感潛在危害性的計算方法,。該研究成果已經(jīng)在線發(fā)表在8月12日的PLoS Computational Biology上。該計算模型被同行專家認(rèn)為是一個概念上的創(chuàng)新,，研究成果將有助于各國衛(wèi)生部門制訂快速有效的流感防控策略,。論文的共同第一作者是生物物理研究所助理研究員吳愛平和博士研究生彭友松，國家流感中心舒躍龍教授參與指導(dǎo)了該項研究,。該研究得到了國家傳染病重大專項和“973”項目的大力支持,。（生物谷Bioon.com）
生物谷推薦原文出處：
PLoS Comput Biol doi:10.1371/journal.pcbi.1000882
Correlation of Influenza Virus Excess Mortality with Antigenic Variation: Application to Rapid Estimation of Influenza Mortality Burden
Aiping Wu1#, Yousong Peng1,2#, Xiangjun Du1,2, Yuelong Shu3, Taijiao Jiang1*
1 National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China, 2 Graduate School of the Chinese Academy of Sciences, Beijing, China, 3 State Key Laboratory for Molecular Virology and Genetic Engineering, National Institute for Viral Infectious Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
The variants of human influenza virus have caused, and continue to cause, substantial morbidity and mortality. Timely and accurate assessment of their impact on human death is invaluable for influenza planning but presents a substantial challenge, as current approaches rely mostly on intensive and unbiased influenza surveillance. In this study, by proposing a novel host-virus interaction model, we have established a positive correlation between the excess mortalities caused by viral strains of distinct antigenicity and their antigenic distances to their previous strains for each (sub)type of seasonal influenza viruses. Based on this relationship, we further develop a method to rapidly assess the mortality burden of influenza A(H1N1) virus by accurately predicting the antigenic distance between A(H1N1) strains. Rapid estimation of influenza mortality burden for new seasonal strains should help formulate a cost-effective response for influenza control and prevention.
