Comparative analysis of dengue and Zika outbreaks reveals differences by setting and virus
Comparative analysis of dengue and Zika outbreaks reveals differences by setting and virus
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登革热和寨卡疫情的比较分析揭示了不同环境和病毒的差异
DOI：
10.1101/043265
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Funk S
中科院分区：
文献类型：
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作者：
Funk S
太平洋岛屿密克罗尼西亚在过去十年中经历了几次蚊媒疾病的爆发。在小岛屿暴发时，易感人群通常是明确界定的，病原体没有共同传播。正因为如此，分析此类疫情可能有助于了解相关病原体的传播动态，特别是对于尚未充分研究的病原体，如寨卡病毒。在这里，我们使用传播动力学的数学模型，并充分利用疾病和疫情之间的共同点，比较了密克罗尼西亚两个不同岛屿环境中登革热和寨卡病毒的三次爆发，即雅普主岛和费斯岛。我们发现，在相同的环境中考虑寨卡病毒和登革热的估计繁殖数量是相似的，但相反，同一疾病的繁殖数量可能因环境而异。在雅普主岛，我们估计登革热疫情的繁殖数量为8.0-16（95%可信区间（CI）），寨卡疫情为4.8-14（95% CI），而对于Fais的登革热疫情，我们的估计为28-102（95% CI）。我们进一步发现，报告的寨卡病例比例（95%CI 1.4%-1.9%）小于登革热病例比例（95%CI：47%-61%）。我们在广泛的敏感性分析中证实了这些结果。他们认为，登革热传播模型对于估计寨卡病毒传播的预测动态可能是有用的，但在将发现从一种环境外推到另一种环境时必须小心。
The pacific islands of Micronesia have experienced several outbreaks of mosquito-borne diseases over the past decade. In outbreaks on small islands, the susceptible population is usually well defined, and there is no co-circulation of pathogens. Because of this, analysing such outbreaks can be useful for understanding the transmission dynamics of the pathogens involved, and particularly so for yet understudied pathogens such as Zika virus. Here, we compared three outbreaks of dengue and Zika virus in two different island settings in Micronesia, the Yap Main Islands and Fais, using a mathematical model of transmission dynamics and making full use of commonalities in disease and setting between the outbreaks. We found that the estimated reproduction numbers for Zika and dengue were similar when considered in the same setting, but that, conversely, reproduction number for the same disease can vary considerably by setting. On the Yap Main Islands, we estimated a reproduction number of 8.0–16 (95% Credible Interval (CI)) for the dengue outbreak and 4.8–14 (95% CI) for the Zika outbreak, whereas for the dengue outbreak on Fais our estimate was 28–102 (95% CI). We further found that the proportion of cases of Zika reported was smaller (95% CI 1.4%–1.9%) than that of dengue (95% CI: 47%–61%). We confirmed these results in extensive sensitivity analysis. They suggest that models for dengue transmission can be useful for estimating the predicted dynamics of Zika transmission, but care must be taken when extrapolating findings from one setting to another.