MAM: Flexible Monte-Carlo Agent based model for modelling COVID-19 spread.
J Biomed Inform
; 141: 104364, 2023 05.
Artículo
en Inglés
| MEDLINE | ID: covidwho-2294058
ABSTRACT
In the three years since SARS-CoV-2 was first detected in China, hundreds of millions of people have been infected and millions have died. Along with the immediate need for treatment solutions, the COVID-19 epidemic has reinforced the need for mathematical models that can predict the spread of the pandemic in an ever-changing environment. The susceptible-infectious-removed (SIR) model has been widely used to model COVID-19 transmission, however, with limited success. Here, we present a novel, dynamic Monte-Carlo Agent-based Model (MAM), which is based on the basic principles of statistical physics. Using public aggregative data from Israel on three major outbreaks, we compare predictions made by SIR and MAM, and show that MAM outperforms SIR in all aspects. Furthermore, MAM is a flexible model and allows to accurately examine the effects of vaccinations in different subgroups, and the effects of the introduction of new variants.
Palabras clave
Texto completo:
Disponible
Colección:
Bases de datos internacionales
Base de datos:
MEDLINE
Asunto principal:
COVID-19
Tipo de estudio:
Estudio observacional
/
Estudio pronóstico
Tópicos:
Vacunas
/
Variantes
Límite:
Humanos
Idioma:
Inglés
Revista:
J Biomed Inform
Asunto de la revista:
Informática Médica
Año:
2023
Tipo del documento:
Artículo
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