Differential Evolution to Optimize A Long-term Multi-strain Model of COVID-19 in South Africa
2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022
; 2022.
Article
in English
| Scopus | ID: covidwho-2152426
ABSTRACT
A limited number of studies have been conducted to investigate the dynamics of COVID-19 disease spread in South Africa and these existing studies have mostly focussed on mathematical analysis of a relatively short time period near the initial outbreak of COVID-19 in South Africa. The current study therefore attempted to extend on previous studies by applying a Susceptible- Exposed - Infected - Removed (SEIR) disease model to analyse the long-term dynamics of COVID-19 in South Africa, taking into account multiple waves of infection potentially caused by different virus strains. A Differential Evolution (DE) algorithm was used to fit the proposed model to real-world data, and this was done on both a geographically local and global scale to investigate the differences between these two approaches. Results revealed that a local approach provided a more accurate model fit to data than a global approach and that the method proposed in this work could give valuable insights into disease dynamics. © 2022 IEEE.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Topics:
Long Covid
Language:
English
Journal:
2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022
Year:
2022
Document Type:
Article
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