Data-Driven Modeling for Different Stages of Pandemic Response.
Data-Driven Modeling for Different Stages of Pandemic Response.
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DOI：
10.1007/s41745-020-00206-0
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发表时间：
2020
影响因子：
2.3
通讯作者：
Vullikanti A
中科院分区：
文献类型：
--
作者：
Adiga A;Chen J;Marathe M;Mortveit H;Venkatramanan S;Vullikanti A
在COVID-19大流行（以及所有疫情）期间，人们感兴趣的一些关键问题包括：疾病从哪里开始，如何传播，谁处于风险之中，以及如何控制传播。有大量复杂的因素推动流行病的传播，因此，多种建模技术在公共政策和决策中发挥着越来越重要的作用。随着不同国家和地区经历大流行的不同阶段，问题和数据的可用性也会发生变化。特别令人感兴趣的是，调整模型开发和数据收集，以支持大流行病每个阶段的应对工作。COVID-19大流行在实时收集和传播许多不同数据集方面是前所未有的，范围从疾病结果到流动性、行为和社会经济因素。从疾病建模和分析的角度来看，这些数据集对于真实的支持决策者至关重要。在这篇概述文章中，我们调查了COVID-19的数据环境，重点是这些数据集如何在大流行的不同阶段帮助建模和应对。我们还讨论了当前的一些挑战以及在我们计划摆脱这一流行病时将出现的需求。
Some of the key questions of interest during the COVID-19 pandemic (and all outbreaks) include: where did the disease start, how is it spreading, who are at risk, and how to control the spread. There are a large number of complex factors driving the spread of pandemics, and, as a result, multiple modeling techniques play an increasingly important role in shaping public policy and decision-making. As different countries and regions go through phases of the pandemic, the questions and data availability also change. Especially of interest is aligning model development and data collection to support response efforts at each stage of the pandemic. The COVID-19 pandemic has been unprecedented in terms of real-time collection and dissemination of a number of diverse datasets, ranging from disease outcomes, to mobility, behaviors, and socio-economic factors. The data sets have been critical from the perspective of disease modeling and analytics to support policymakers in real time. In this overview article, we survey the data landscape around COVID-19, with a focus on how such datasets have aided modeling and response through different stages so far in the pandemic. We also discuss some of the current challenges and the needs that will arise as we plan our way out of the pandemic.
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DOI：
10.1073/pnas.0906910106
发表时间：
2009-12-22
影响因子：
11.1
作者：
Balcan, Duygu;Colizza, Vittoria;Vespignani, Alessandro
通讯作者：
Vespignani, Alessandro
影响因子：
2.3
作者：
Adiga A;Dubhashi D;Lewis B;Marathe M;Venkatramanan S;Vullikanti A
通讯作者：
Vullikanti A
影响因子：
19
作者：
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通讯作者：
Hens, Niel
影响因子：
56.9
作者：
Brockmann, Dirk;Helbing, Dirk
通讯作者：
Helbing, Dirk
影响因子：
56.9
作者：
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通讯作者：
Vespignani, Alessandro