Continental synchronicity of human influenza virus epidemics despite climatic variation.
Continental synchronicity of human influenza virus epidemics despite climatic variation.
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DOI：
10.1371/journal.ppat.1006780
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发表时间：
2018-01
期刊：
影响因子：
6.7
通讯作者：
Holmes EC
中科院分区：
文献类型：
--
作者：
Geoghegan JL;Saavedra AF;Duchêne S;Sullivan S;Barr I;Holmes EC
决定流感病毒在大陆范围内传播模式和速度的因素尚不确定。虽然最近的研究表明，美国的流感流行表现出很强的地理相关性，但澳大利亚的流感时空动态尚不清楚，澳大利亚是一个面积和气候复杂性大致相似的国家和大陆，但人口要少得多。使用包括> 450，000个条目和基因组序列数据的大规模实验室确认的流感监测的独特组合，我们确定了这种重要的人类病原体在澳大利亚全国范围内的地方水平空间扩散。我们使用实验室确认的流感数据来描述2007-2016年期间流感病毒在澳大利亚的传播情况。已确立的流行病的爆发在不同季节有所不同，高度同步的流行病与抗原性不同的病毒的出现相吻合，特别是在2009年甲型H1N1流感大流行期间。流行病的爆发在人口最多的城市之间基本上是同步的，即使是那些相距3000公里以上的城市和那些经历了巨大差异的气候的城市。此外，通过分析全球流行病学的地理模式，我们发现，澳大利亚各城市流感的同步传播涉及来自全球流感人群的多次引入，加上强大的国内连接，而不是通过独特的辐射状的地理分布模式，由工作流传输驱动，在美国观察到。此外，通过比较甲型和B型流感的空间结构，我们发现这些病毒倾向于占据不同的地理区域，并在不同的季节达到高峰，这可能表明存在中度交叉保护性免疫或病毒干扰效应。本文揭示的流感病毒在大陆范围内高度同步爆发的情况突出表明，在出现新型人传人病毒的情况下，协调一致的公共卫生应对措施非常重要。我们使用大规模实验室确认的流感监测和基因组序列数据的独特组合，利用澳大利亚10年期间（2007-2016）收集的450，000个数据条目，确定流感在大陆范围内时空传播的模式和决定因素。我们的研究结果揭示了一个显着的流行病学的同步性在这个大的和地理上多样化的大陆，并在巨大的气候变化，从热带北部到温带南部。这种同步性在与抗原性不同菌株的出现相关的年份中尤其明显。这种大陆同步性模式突出了在出现新型人传人病毒时高度协调应对的重要性，因此具有广泛的公共卫生影响。
The factors that determine the pattern and rate of spread of influenza virus at a continental-scale are uncertain. Although recent work suggests that influenza epidemics in the United States exhibit a strong geographical correlation, the spatiotemporal dynamics of influenza in Australia, a country and continent of approximately similar size and climate complexity but with a far smaller population, are not known. Using a unique combination of large-scale laboratory-confirmed influenza surveillance comprising >450,000 entries and genomic sequence data we determined the local-level spatial diffusion of this important human pathogen nationwide in Australia. We used laboratory-confirmed influenza data to characterize the spread of influenza virus across Australia during 2007–2016. The onset of established epidemics varied across seasons, with highly synchronized epidemics coinciding with the emergence of antigenically distinct viruses, particularly during the 2009 A/H1N1 pandemic. The onset of epidemics was largely synchronized between the most populous cities, even those separated by distances of >3000 km and those that experience vastly diverse climates. In addition, by analyzing global phylogeographic patterns we show that the synchronized dissemination of influenza across Australian cities involved multiple introductions from the global influenza population, coupled with strong domestic connectivity, rather than through the distinct radial patterns of geographic dispersal that are driven by work-flow transmission as observed in the United States. In addition, by comparing the spatial structure of influenza A and B, we found that these viruses tended to occupy different geographic regions, and peak in different seasons, perhaps indicative of moderate cross-protective immunity or viral interference effects. The highly synchronized outbreaks of influenza virus at a continental-scale revealed here highlight the importance of coordinated public health responses in the event of the emergence of a novel, human-to-human transmissible, virus. We use a unique combination of large-scale laboratory-confirmed influenza surveillance and genomic sequence data to determine the pattern and determinants of influenza spread through time and space at a continental scale, utilizing 450,000 data entries gathered across Australia over a 10-year period (2007–2016). Our results reveal a remarkable epidemiological synchronicity across this large and geographically diverse continent, and in the face of enormous climatic variation, from the tropical north to the temperate south. Such synchronicity was especially marked during years associated with the emergence of antigenically distinct strains. This pattern of continental synchronicity highlights the importance of a highly coordinated responses in the event of the emergence of a novel, human-to-human transmissible, virus, and hence has broad-scale public health implications.
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影响因子：
64.8
作者：
Ferguson, NM;Galvani, AP;Bush, RM
通讯作者：
Bush, RM
影响因子：
56.9
作者：
Viboud, C;Bjornstad, ON;Grenfell, BT
通讯作者：
Grenfell, BT
影响因子：
10.7
作者：
Katoh K;Standley DM
通讯作者：
Standley DM
DOI：
10.1073/pnas.0308344101
发表时间：
2004-10-19
影响因子：
11.1
作者：
Hufnagel, L;Brockmann, D;Geisel, T
通讯作者：
Geisel, T
影响因子：
11.8
作者：
Viboud C;Boëlle PY;Pakdaman K;Carrat F;Valleron AJ;Flahault A
通讯作者：
Flahault A