Predicting COVID-19 Mortalities for Patients with Special Health Conditions Using an Agent-Based Model
20th International Learning and Technology Conference, L and T 2023
; : 42-47, 2023.
Article
in English
| Scopus | ID: covidwho-2317086
ABSTRACT
The spread of COVID-19 has thrown the world into a panic. We are constantly learning more about the virus every day, from how it spreads to who is more susceptible to becoming infected by different variants. Those with underlying respiratory conditions and other immunocompromised individuals need to be extra cautious regarding the virus. Many researchers have created COVID-19 trackers to detect the spread of COVID-19 around the world and show hot spots where COVID-19 cases are more prevalent. Previous work lacks the consideration of comorbidity as a factor of death rate. This work aims to create an agent-based model to predict comorbidity death rate caused by a health condition in addition to COVID-19. The model is evaluated using the symmetric mean absolute percentage error metric and proved to be very efficient. © 2023 IEEE.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Language:
English
Journal:
20th International Learning and Technology Conference, L and T 2023
Year:
2023
Document Type:
Article
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