Spatial-temporal monitoring risk analysis and decision-making of COVID-19 distribution by region
International Journal of Simulation and Process Modelling
; 18(1):23-35, 2022.
Article
in English
| Scopus | ID: covidwho-1923730
ABSTRACT
The purpose of this study is to model, map, and identify why some areas present a completely different dispersion pattern of COVID-19, as well as creating a risk model, composed of variables such as probability, susceptibility, danger, vulnerability, and potential damage, that characterises each of the defined regions. The model is based on a risk conceptual model proposed by Bachmann and Allgower in 2001, based on the wildfire terminology, analysing the spatial distribution. Additionally, a model based on population growth, chaotic maps, and turbulent flows is applied in the calculation of the variable probability, based on the work of Bonasera (2020). The results for the Portuguese case are promising, regarding the fitness of the said models and the outcome results of a conceptual model for the epidemiological risk assessment for the spread of coronavirus for each region. © 2022 Inderscience Enterprises Ltd.. All rights reserved.
chaos theory; COVID-19; gravity model; risk analysis; spatial-temporal; Chaotic systems; Decision making; Population statistics; Risk assessment; Spatial variables measurement; Conceptual model; Decisions makings; Dispersion patterns; Gravity modeling; Model maps; Model-based OPC; Monitoring risks; Population growth; Risk modeling; Spatial temporals
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Language:
English
Journal:
International Journal of Simulation and Process Modelling
Year:
2022
Document Type:
Article
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