Open AccessThe COVID-19 Crisis and Complexity in the United States
Author(s) -
K. Basel,
Milagros Campos,
Gray Handley,
Daniella R Hébert,
Enrique Meléndez,
F. Onatoye,
O. Phearum,
Salam Sawadogo,
J. Steckbeck,
G. Tekell,
Abdülselam Ertaş,
Utku Gülbulak
Publication year - 2021
Publication title -
transdisciplinary journal of engineering and science
Language(s) - English
Resource type - Journals
ISSN - 1949-0569
DOI - 10.22545/2020/00157
Subject(s) - cyclomatic complexity , covid-19 , component (thermodynamics) , key (lock) , process (computing) , measure (data warehouse) , computer science , data science , management science , data mining , computer security , medicine , engineering , virology , physics , disease , software , pathology , outbreak , infectious disease (medical specialty) , thermodynamics , programming language , operating system
The main objective of this research is to present a transdisciplinary research process which identifies the complexity of the issues surrounding COVID-19 using collective intelligence through transdisciplinarycollaborative effort. Interpretive Structural Modeling (ISM), a methodology for dealing with complexsystem design and development has been the key component of this research. Building collective intelligence to understand how factors affecting COVID-19 transmission and fatality and their relationships were investigated. The complexity measure of the COVID-19 was investigated by using cyclomatic complexity. The results showed that the complexity of the COVID-19 is difficult to understand and handle.