COVID-19 prevalence estimation: Four most affected African countries.

Lukman, Adewale F; Rauf, Rauf I; Abiodun, Oluwakemi; Oludoun, Olajumoke; Ayinde, Kayode; Ogundokun, Roseline O

Lukman, Adewale F; Rauf, Rauf I; Abiodun, Oluwakemi; Oludoun, Olajumoke; Ayinde, Kayode; Ogundokun, Roseline O.

Afiliação

Lukman AF; Department of Mathematics and Computer Science, Landmark University, Omu-Aran, Kwara State, Nigeria.
Rauf RI; Department of Statistics, University of Abuja, Abuja, Nigeria.
Abiodun O; Department of Mathematics and Computer Science, Landmark University, Omu-Aran, Kwara State, Nigeria.
Oludoun O; Department of Mathematics and Computer Science, Landmark University, Omu-Aran, Kwara State, Nigeria.
Ayinde K; Department of Statistics, Federal University of Technology, Akure, Nigeria.
Ogundokun RO; Department of Mathematics and Computer Science, Landmark University, Omu-Aran, Kwara State, Nigeria.

Infect Dis Model ; 5: 827-838, 2020.

Article em En | MEDLINE | ID: mdl-33073068

Palavras-chave

ARIMA models; COVID-19; Exponential growth; Forecasting; Prevalence; Statistical tools; Time series model

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prevalence_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

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