Interactions between timing and transmissibility explain diverse flavivirus dynamics in Fiji.
Interactions between timing and transmissibility explain diverse flavivirus dynamics in Fiji.
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DOI：
10.1038/s41467-021-21788-y
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发表时间：
2021-03-15
影响因子：
16.6
通讯作者：
Kucharski AJ
中科院分区：
文献类型：
--
作者：
Henderson AD;Kama M;Aubry M;Hue S;Teissier A;Naivalu T;Bechu VD;Kailawadoko J;Rabukawaqa I;Sahukhan A;Hibberd ML;Nilles EJ;Funk S;Whitworth J;Watson CH;Lau CL;Edmunds WJ;Cao-Lormeau VM;Kucharski AJ
寨卡病毒（ZIKV）在孤立人群中造成了大规模、短暂的疫情，但寨卡病毒也可以在多年内保持在低水平。这些不同的传播动态的原因仍然知之甚少。斐济经历了多次单季节登革热大流行，有证据表明2013年至2017年期间寨卡病毒发生了多年传播。为了确定可以解释密切相关的蚊媒黄病毒之间这些动力学差异的因素，我们联合监测、血清学和分子数据拟合了传播动力学模型。我们估计，观察到的ZIKV动态是两个关键因素的结果：强烈的季节效应，这为疫情的爆发创造了生态上的最佳时间；并在这个最佳时间之后引入了ZIKV，这使得ZIKV传播持续了多个季节。联合适应多个数据源的能力有助于确定其他环境中类似范围的可能爆发动态。登革热和寨卡病毒是密切相关的黄病毒，但在同一人群中可能具有截然不同的传播动态。在这里，作者使用了一个结合血清学、监测和病毒序列数据的模型来解释斐济传播动态的差异。
Zika virus (ZIKV) has caused large, brief outbreaks in isolated populations, however ZIKV can also persist at low levels over multiple years. The reasons for these diverse transmission dynamics remain poorly understood. In Fiji, which has experienced multiple large single-season dengue epidemics, there was evidence of multi-year transmission of ZIKV between 2013 and 2017. To identify factors that could explain these differences in dynamics between closely related mosquito-borne flaviviruses, we jointly fit a transmission dynamic model to surveillance, serological and molecular data. We estimate that the observed dynamics of ZIKV were the result of two key factors: strong seasonal effects, which created an ecologically optimal time of year for outbreaks; and introduction of ZIKV after this optimal time, which allowed ZIKV transmission to persist over multiple seasons. The ability to jointly fit to multiple data sources could help identify a similar range of possible outbreak dynamics in other settings. Dengue and Zika virus are closely related flaviviruses but can have contrasting transmission dynamics in the same populations. Here, the authors use a model combining serological, surveillance and viral sequence data to explain differences in transmission dynamics in Fiji.
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影响因子：
3.8
作者：
Funk S;Kucharski AJ;Camacho A;Eggo RM;Yakob L;Murray LM;Edmunds WJ
通讯作者：
Edmunds WJ
影响因子：
3.7
作者：
Craig AT;Joshua CA;Sio AR;Teobasi B;Dofai A;Dalipanda T;Hardie K;Kaldor J;Kolbe A
通讯作者：
Kolbe A
影响因子：
7.7
作者：
Henderson, Alasdair D.;Aubry, Maite;Kucharski, Adam J.
通讯作者：
Kucharski, Adam J.
影响因子：
11.8
作者：
Cao-Lormeau VM;Roche C;Musso D;Mallet HP;Dalipanda T;Dofai A;Nogareda F;Nilles EJ;Aaskov J
通讯作者：
Aaskov J
影响因子：
10.7
作者：
Drummond, Alexei J.;Suchard, Marc A.;Rambaut, Andrew
通讯作者：
Rambaut, Andrew