Literature DB >> 33879824

Decision support for the quickest detection of critical COVID-19 phases.

Paolo Braca1, Domenico Gaglione2, Stefano Marano3, Leonardo M Millefiori2, Peter Willett4, Krishna Pattipati4.   

Abstract

During the course of an epidemic, one of the most challenging tasks for authorities is to decide what kind of restrictive measures to introduce and when these should be enforced. In order to take informed decisions in a fully rational manner, the onset of a critical regime, characterized by an exponential growth of the contagion, must be identified as quickly as possible. Providing rigorous quantitative tools to detect such an onset represents an important contribution from the scientific community to proactively support the political decision makers. In this paper, leveraging the quickest detection theory, we propose a mathematical model of the COVID-19 pandemic evolution and develop decision tools to rapidly detect the passage from a controlled regime to a critical one. A new sequential test-referred to as MAST (mean-agnostic sequential test)-is presented, and demonstrated on publicly available COVID-19 infection data from different countries. Then, the performance of MAST is investigated for the second pandemic wave, showing an effective trade-off between average decision delay [Formula: see text] and risk [Formula: see text], where [Formula: see text] is inversely proportional to the time required to declare the need to take unnecessary restrictive measures. To quantify risk, in this paper we adopt as its proxy the average occurrence rate of false alarms, in that a false alarm risks unnecessary social and economic disruption. Ideally, the decision mechanism should react as quick as possible for a given level of risk. We find that all the countries share the same behaviour in terms of quickest detection, specifically the risk scales exponentially with the delay, [Formula: see text], where [Formula: see text] depends on the specific nation. For a reasonably small risk level, say, one possibility in ten thousand (i.e., unmotivated implementation of countermeasures every 27 years, on the average), the proposed algorithm detects the onset of the critical regime with delay between a few days to 3 weeks, much earlier than when the exponential growth becomes evident. Strictly from the quickest-detection perspective adopted in this paper, it turns out that countermeasures against the second epidemic wave have not always been taken in a timely manner. The developed tool can be used to support decisions at different geographic scales (regions, cities, local areas, etc.), levels of risk, instantiations of controlled/critical regime, and is general enough to be applied to different pandemic time-series. Additional analysis and applications of MAST are made available on a dedicated website.

Entities:  

Year:  2021        PMID: 33879824     DOI: 10.1038/s41598-021-86827-6

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  19 in total

1.  Monitoring and prediction of an epidemic outbreak using syndromic observations.

Authors:  Alex Skvortsov; Branko Ristic
Journal:  Math Biosci       Date:  2012-06-13       Impact factor: 2.144

2.  Global supply-chain effects of COVID-19 control measures.

Authors:  Dabo Guan; Daoping Wang; Stephane Hallegatte; Steven J Davis; Jingwen Huo; Shuping Li; Yangchun Bai; Tianyang Lei; Qianyu Xue; D'Maris Coffman; Danyang Cheng; Peipei Chen; Xi Liang; Bing Xu; Xiaosheng Lu; Shouyang Wang; Klaus Hubacek; Peng Gong
Journal:  Nat Hum Behav       Date:  2020-06-03

3.  How will country-based mitigation measures influence the course of the COVID-19 epidemic?

Authors:  Roy M Anderson; Hans Heesterbeek; Don Klinkenberg; T Déirdre Hollingsworth
Journal:  Lancet       Date:  2020-03-09       Impact factor: 79.321

4.  Evaluation and prediction of the COVID-19 variations at different input population and quarantine strategies, a case study in Guangdong province, China.

Authors:  Zengyun Hu; Qianqian Cui; Junmei Han; Xia Wang; Wei E I Sha; Zhidong Teng
Journal:  Int J Infect Dis       Date:  2020-04-22       Impact factor: 3.623

5.  Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2).

Authors:  Ruiyun Li; Sen Pei; Bin Chen; Yimeng Song; Tao Zhang; Wan Yang; Jeffrey Shaman
Journal:  Science       Date:  2020-03-16       Impact factor: 47.728

Review 6.  The socio-economic implications of the coronavirus pandemic (COVID-19): A review.

Authors:  Maria Nicola; Zaid Alsafi; Catrin Sohrabi; Ahmed Kerwan; Ahmed Al-Jabir; Christos Iosifidis; Maliha Agha; Riaz Agha
Journal:  Int J Surg       Date:  2020-04-17       Impact factor: 6.071

7.  Effective containment explains subexponential growth in recent confirmed COVID-19 cases in China.

Authors:  Benjamin F Maier; Dirk Brockmann
Journal:  Science       Date:  2020-04-08       Impact factor: 47.728

8.  The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak.

Authors:  Matteo Chinazzi; Jessica T Davis; Marco Ajelli; Corrado Gioannini; Maria Litvinova; Stefano Merler; Ana Pastore Y Piontti; Kunpeng Mu; Luca Rossi; Kaiyuan Sun; Cécile Viboud; Xinyue Xiong; Hongjie Yu; M Elizabeth Halloran; Ira M Longini; Alessandro Vespignani
Journal:  Science       Date:  2020-03-06       Impact factor: 47.728

9.  Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions.

Authors:  Jonas Dehning; Johannes Zierenberg; F Paul Spitzner; Michael Wilczek; Viola Priesemann; Michael Wibral; Joao Pinheiro Neto
Journal:  Science       Date:  2020-05-15       Impact factor: 47.728

10.  Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts.

Authors:  Joel Hellewell; Sam Abbott; Amy Gimma; Nikos I Bosse; Christopher I Jarvis; Timothy W Russell; James D Munday; Adam J Kucharski; W John Edmunds; Sebastian Funk; Rosalind M Eggo
Journal:  Lancet Glob Health       Date:  2020-02-28       Impact factor: 26.763

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  2 in total

1.  Quickest Detection of COVID-19 Pandemic Onset.

Authors:  P Braca; D Gaglione; S Marano; L M Millefiori; P Willett; K Pattipati
Journal:  IEEE Signal Process Lett       Date:  2021-03-24       Impact factor: 3.109

2.  Decision-making algorithms for learning and adaptation with application to COVID-19 data.

Authors:  Stefano Marano; Ali H Sayed
Journal:  Signal Processing       Date:  2021-12-07       Impact factor: 4.662

  2 in total

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