Application of a Generalized SEIR Model for COVID-19 in Algeria
Mohamed Lounis 1 * , Juarez dos Santos Azevedo 2
More Detail
1 Department of Agro-veterinary Science, Faculty of Natural and Life Sciences, University of Ziane Achour, BP 3117, Road of Moudjbara, Djelfa 17000, ALGERIA2 Federal University of Bahia (UFBA), Institute of Sciences, Technology and Innovation, Centro, 42802-721, Camaçari-BA, BRAZIL* Corresponding Author


The novel coronavirus disease 2019 (COVID-19) reported in Wuhan is continuing to impress the world by its fast spread and the number of affected persons attracting an unprecedented attention.
In this article, the classical SEIR model and a generalized SEIR model called SEIRDP were applied to predict the evolution of COVID-19 in Algeria for a future period of 100 days using official reported data from early April to early August, 2020. Initial evaluation showed that the two models had a net correspondence with the reported data during this period for cumulative infected cases but the number of cumulative deaths was underestimated with the classical SEIR model. Model prediction with the SEIRDP concluded that the number of cumulative infected cases will increase in the next days reaching a number of about 60 k in middle November with a median of about 300 daily cases. Also, the number of estimated deaths will be around 2k. These results suggest that the COVID-19 is ongoing to infect more persons which may push national authorities to carefully act in the probable leaving of containment.


This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EUR J SUSTAIN DEV RES, Volume 5, Issue 1, 2021, Article No: em0150

Publication date: 03 Feb 2021

Article Views: 1299

Article Downloads: 934

Open Access References How to cite this article