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[Preprint]. 2020 Sep 21:arXiv:2009.10014v1.

Models for COVID-19 Pandemic: A Comparative Analysis

Aniruddha Adiga  1 , Devdatt Dubhashi  2 , Bryan Lewis  1 , Madhav Marathe  1   3 , Srinivasan Venkatramanan  1 , Anil Vullikanti  1   3
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Models for COVID-19 Pandemic: A Comparative Analysis

Aniruddha Adiga et al. ArXiv. .

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Abstract

COVID-19 pandemic represents an unprecedented global health crisis in the last 100 years. Its economic, social and health impact continues to grow and is likely to end up as one of the worst global disasters since the 1918 pandemic and the World Wars. Mathematical models have played an important role in the ongoing crisis; they have been used to inform public policies and have been instrumental in many of the social distancing measures that were instituted worldwide. In this article we review some of the important mathematical models used to support the ongoing planning and response efforts. These models differ in their use, their mathematical form and their scope.

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Figures

Figure 1.
Figure 1.
The SIR process on a graph. The contact graph G = (V, E) is defined on a population V = {a, b, c, d}. The node colors white, black and grey represent the Susceptible, Infected and Recovered states, respectively. Initially, only node a is infected, and all other nodes are susceptible. A possible outcome at t = 1 is shown, in which node c becomes infected, while node a recovers. Node a tries to independently infect both its neighbors b and c, but only node c gets infected— this is indicated by the solid edge (a, c). The probability of getting this outcome is (1 − p(a, b))p(a, c).
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References

    1. Christopher Avery, William Bossert, Adam Clark, Glenn Ellison, and Sara Fisher Ellison. Policy implications of models of the spread of coronavirus: Perspectives and opportunities for economists. Technical report, National Bureau of Economic Research, 2020.
    1. Allen Linda JS, Brauer Fred, Pauline Van den Driessche, and Jianhong Wu. Mathematical epidemiology, volume 1945 Springer, 2008.
    1. Adam David. Modelling the pandemic the simulations driving the world’s response to covid-19. Nature, 580(7803):316–318, 2020. - PubMed
    1. Adhikari Bijaya, Xu Xinfeng, Ramakrishnan Naren, and Prakash B. Aditya. Epideep: Exploiting embeddings for epidemic forecasting In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD ‘19, page 577–586, New York, NY, USA, 2019. Association for Computing Machinery.
    1. Barrett Christopher L, Bisset Keith R, Eubank Stephen G, Feng Xizhou, and Marathe Madhav V. Episimdemics: an efficient algorithm for simulating the spread of infectious disease over large realistic social networks In Proceedings of the 2008 ACM/IEEE conference on Supercomputing, page 37 IEEE Press, 2008.

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