Modeling the spread of COVID-19 in spatio-temporal context.
Math Biosci Eng
; 20(6): 10552-10569, 2023 Apr 11.
Artículo
en Inglés
| MEDLINE | ID: covidwho-2303152
ABSTRACT
This study aims to use data provided by the Virginia Department of Public Health to illustrate the changes in trends of the total cases in COVID-19 since they were first recorded in the state. Each of the 93 counties in the state has its COVID-19 dashboard to help inform decision makers and the public of spatial and temporal counts of total cases. Our analysis shows the differences in the relative spread between the counties and compares the evolution in time using Bayesian conditional autoregressive framework. The models are built under the Markov Chain Monte Carlo method and Moran spatial correlations. In addition, Moran's time series modeling techniques were applied to understand the incidence rates. The findings discussed may serve as a template for other studies of similar nature.
Palabras clave
Texto completo:
Disponible
Colección:
Bases de datos internacionales
Base de datos:
MEDLINE
Asunto principal:
COVID-19
Tipo de estudio:
Estudio experimental
/
Estudio observacional
/
Estudio pronóstico
Límite:
Humanos
Idioma:
Inglés
Revista:
Math Biosci Eng
Año:
2023
Tipo del documento:
Artículo
País de afiliación:
Mbe.2023466
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