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A Novel Causal Risk‐Based Decision‐Making Methodology: The Case of Coronavirus
Author(s) -
Stavroglou Stavros K.,
Ayyub Bilal M.,
Kallinterakis Vasileios,
Pantelous Athanasios A.,
Stanley H. Eugene
Publication year - 2021
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/risa.13678
Subject(s) - pandemic , interdependence , action (physics) , risk analysis (engineering) , covid-19 , operations research , coronavirus , computer science , management science , environmental planning , business , political science , economics , engineering , geography , medicine , law , physics , disease , pathology , quantum mechanics , infectious disease (medical specialty)
Either in the form of nature's wrath or a pandemic, catastrophes cause major destructions in societies, thus requiring policy and decisionmakers to take urgent action by evaluating a host of interdependent parameters, and possible scenarios. The primary purpose of this article is to propose a novel risk‐based, decision‐making methodology capable of unveiling causal relationships between pairs of variables. Motivated by the ongoing global emergency of the coronavirus pandemic, the article elaborates on this powerful quantitative framework drawing on data from the United States at the county level aiming at assisting policy and decision makers in taking timely action amid this emergency. This methodology offers a basis for identifying potential scenarios and consequences of the ongoing 2020 pandemic by drawing on weather variables to examine the causal impact of changing weather on the trend of daily coronavirus cases.