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Parameter estimation and prediction for coronavirus disease outbreak 2019 (COVID-19) in Algeria

BACKGROUND: The wave of the coronavirus disease outbreak in 2019 (COVID-19) has spread all over the world. In Algeria, the first case of COVID-19 was reported on 25 February, 2020, and the number of confirmed cases of it has increased day after day. To overcome this difficult period and a catastroph...

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Detalles Bibliográficos
Autores principales: Bentout, Soufiane, Chekroun, Abdennasser, Kuniya, Toshikazu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AIMS Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327392/
https://www.ncbi.nlm.nih.gov/pubmed/32617358
http://dx.doi.org/10.3934/publichealth.2020026
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author Bentout, Soufiane
Chekroun, Abdennasser
Kuniya, Toshikazu
author_facet Bentout, Soufiane
Chekroun, Abdennasser
Kuniya, Toshikazu
author_sort Bentout, Soufiane
collection PubMed
description BACKGROUND: The wave of the coronavirus disease outbreak in 2019 (COVID-19) has spread all over the world. In Algeria, the first case of COVID-19 was reported on 25 February, 2020, and the number of confirmed cases of it has increased day after day. To overcome this difficult period and a catastrophic scenario, a model-based prediction of the possible epidemic peak and size of COVID-19 in Algeria is required. METHODS: We are concerned with a classical epidemic model of susceptible, exposed, infected and removed (SEIR) population dynamics. By using the method of least squares and the best fit curve that minimizes the sum of squared residuals, we estimate the epidemic parameter and the basic reproduction number ℜ(0). Moreover, we discuss the effect of intervention in a certain period by numerical simulation. RESULTS: We find that ℜ(0) = 4.1, which implies that the epidemic in Algeria could occur in a strong way. Moreover, we obtain the following epidemiological insights: the intervention has a positive effect on the time delay of the epidemic peak; the epidemic size is almost the same for a short intervention; a large epidemic can occur even if the intervention is long and sufficiently effective. CONCLUSION: Algeria must implement the strict measures as shown in this study, which could be similar to the one that China has finally adopted.
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spelling pubmed-73273922020-07-01 Parameter estimation and prediction for coronavirus disease outbreak 2019 (COVID-19) in Algeria Bentout, Soufiane Chekroun, Abdennasser Kuniya, Toshikazu AIMS Public Health Research Article BACKGROUND: The wave of the coronavirus disease outbreak in 2019 (COVID-19) has spread all over the world. In Algeria, the first case of COVID-19 was reported on 25 February, 2020, and the number of confirmed cases of it has increased day after day. To overcome this difficult period and a catastrophic scenario, a model-based prediction of the possible epidemic peak and size of COVID-19 in Algeria is required. METHODS: We are concerned with a classical epidemic model of susceptible, exposed, infected and removed (SEIR) population dynamics. By using the method of least squares and the best fit curve that minimizes the sum of squared residuals, we estimate the epidemic parameter and the basic reproduction number ℜ(0). Moreover, we discuss the effect of intervention in a certain period by numerical simulation. RESULTS: We find that ℜ(0) = 4.1, which implies that the epidemic in Algeria could occur in a strong way. Moreover, we obtain the following epidemiological insights: the intervention has a positive effect on the time delay of the epidemic peak; the epidemic size is almost the same for a short intervention; a large epidemic can occur even if the intervention is long and sufficiently effective. CONCLUSION: Algeria must implement the strict measures as shown in this study, which could be similar to the one that China has finally adopted. AIMS Press 2020-05-22 /pmc/articles/PMC7327392/ /pubmed/32617358 http://dx.doi.org/10.3934/publichealth.2020026 Text en © 2020 the Author(s), licensee AIMS Press This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
spellingShingle Research Article
Bentout, Soufiane
Chekroun, Abdennasser
Kuniya, Toshikazu
Parameter estimation and prediction for coronavirus disease outbreak 2019 (COVID-19) in Algeria
title Parameter estimation and prediction for coronavirus disease outbreak 2019 (COVID-19) in Algeria
title_full Parameter estimation and prediction for coronavirus disease outbreak 2019 (COVID-19) in Algeria
title_fullStr Parameter estimation and prediction for coronavirus disease outbreak 2019 (COVID-19) in Algeria
title_full_unstemmed Parameter estimation and prediction for coronavirus disease outbreak 2019 (COVID-19) in Algeria
title_short Parameter estimation and prediction for coronavirus disease outbreak 2019 (COVID-19) in Algeria
title_sort parameter estimation and prediction for coronavirus disease outbreak 2019 (covid-19) in algeria
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327392/
https://www.ncbi.nlm.nih.gov/pubmed/32617358
http://dx.doi.org/10.3934/publichealth.2020026
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