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Review
. 2020;100(4):901-915.
doi: 10.1007/s41745-020-00206-0. Epub 2020 Nov 16.

Data-Driven Modeling for Different Stages of Pandemic Response

Aniruddha Adiga  1 , Jiangzhuo Chen  1 , Madhav Marathe  1   2 , Henning Mortveit  1   3 , Srinivasan Venkatramanan  1 , Anil Vullikanti  1   2
Affiliations
Review

Data-Driven Modeling for Different Stages of Pandemic Response

Aniruddha Adiga et al. J Indian Inst Sci. 2020.

Abstract

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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Figures

Figure 1:
Figure 1:
CDC Pandemic Intervals Framework and WHO phases for influenza pandemic.
Figure 2:
Figure 2:
Summary of the data needs in different stages described in Sect. 3.
See this image and copyright information in PMC

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