Latent Growth Curve Modeling for COVID-19 Cases in Presence of Time-Variant Covariate

For the past two years, the entire world has been fighting against the COVID-19 pandemic. The rapid increase in COVID-19 cases can be attributed to several factors. Recent studies have revealed that changes in environmental temperature are associated with the growth of cases. In this study, we model...

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Detalles Bibliográficos
Autores principales: Panwar, M. S., Yadav, C. P., Singh, Harendra, Jawa, Taghreed M., Sayed-Ahmed, Neveen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8881161/
https://www.ncbi.nlm.nih.gov/pubmed/35222625
http://dx.doi.org/10.1155/2022/3538866
Descripción
Sumario:For the past two years, the entire world has been fighting against the COVID-19 pandemic. The rapid increase in COVID-19 cases can be attributed to several factors. Recent studies have revealed that changes in environmental temperature are associated with the growth of cases. In this study, we modeled the monthly growth rate of COVID-19 cases per million infected in 126 countries using various growth curves under structural equation modeling. Moreover, the environmental temperature has been introduced as a time-varying covariate to enhance the performance of the models. The parameters of growth curve models have been estimated, and accordingly, the results are discussed for the affected countries from August 2020 to July 2021.

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