TY - JOUR
T1 - Modeling the impact of unreported cases of the COVID-19 in the North African countries
AU - Djilali, Salih
AU - Benahmadi, Lahbib
AU - Tridane, Abdessamad
AU - Niri, Khadija
N1 - Funding Information:
Acknowledgments: The authors would like to thank the anonymous reviewers for their valuable comments and suggestions which helped us to improve the quality of our work. S. Djilali is partially supported by the DGRSDT of Algeria. A. Tridane is supported by the United Arab Emirates University.
Funding Information:
Funding: This research was funded by United Arab Emirates University (UAEU), Grant Number G00003409.
Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2020/11
Y1 - 2020/11
N2 - In this paper, we study a mathematical model investigating the impact of unreported cases of the COVID-19 in three North African countries: Algeria, Egypt, and Morocco. To understand how the population respects the restriction of population mobility implemented in each country, we use Google and Apple’s mobility reports. These mobility reports help to quantify the effect of the population movement restrictions on the evolution of the active infection cases. We also approximate the number of the population infected unreported, the proportion of those that need hospitalization, and estimate the end of the epidemic wave. Moreover, we use our model to estimate the second wave of the COVID-19 Algeria and Morocco and to project the end of the second wave. Finally, we suggest some additional measures that can be considered to reduce the burden of the COVID-19 and would lead to a second wave of the spread of the virus in these countries.
AB - In this paper, we study a mathematical model investigating the impact of unreported cases of the COVID-19 in three North African countries: Algeria, Egypt, and Morocco. To understand how the population respects the restriction of population mobility implemented in each country, we use Google and Apple’s mobility reports. These mobility reports help to quantify the effect of the population movement restrictions on the evolution of the active infection cases. We also approximate the number of the population infected unreported, the proportion of those that need hospitalization, and estimate the end of the epidemic wave. Moreover, we use our model to estimate the second wave of the COVID-19 Algeria and Morocco and to project the end of the second wave. Finally, we suggest some additional measures that can be considered to reduce the burden of the COVID-19 and would lead to a second wave of the spread of the virus in these countries.
KW - Basic reproduction number
KW - COVID-19
KW - Hospitalized individuals
KW - Lockdown
KW - Unreported cases
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U2 - 10.3390/biology9110373
DO - 10.3390/biology9110373
M3 - Article
AN - SCOPUS:85095988211
VL - 9
SP - 1
EP - 18
JO - Biology
JF - Biology
SN - 2079-7737
IS - 11
M1 - 373
ER -