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Volume 3, Issue 4
Modeling and Reviewing Analysis of the COVID-19 Epidemic in Algeria with Diagnostic Shadow

Jiwei Jia, Siyu Liu, Yawen Liu, Ruitong Shan, Khaled Zennir & Ran Zhang

DOI: 10.4208/csiam-am.SO-2021-0019

CSIAM Trans. Appl. Math., 3 (2022), pp. 792-809.

Published online: 2022-11

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  • Abstract

In this paper, we formulate a special epidemic dynamic model to describe the transmission of COVID-19 in Algeria. We derive the threshold parameter control reproduction number $(\mathcal{R}^0_c),$ and present the effective control reproduction number $(\mathcal{R}_c(t))$ as a real-time index for evaluating the epidemic under different control strategies. Due to the limitation of the reported data, we redefine the number of accumulative confirmed cases with diagnostic shadow and then use the processed data to do the optimal numerical simulations. According to the control measures, we divide the whole research period into six stages. And then the corresponding medical resource estimations and the average effective control reproduction numbers for each stage are given. Meanwhile, we use the parameter values which are obtained from the optimal numerical simulations to forecast the whole epidemic tendency under different control strategies.

  • Keywords

COVID-19, Algeria, diagnostic shadow, medical resource.

  • AMS Subject Headings

92D30, 37N25

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{CSIAM-AM-3-792, author = {Jia , JiweiLiu , SiyuLiu , YawenShan , RuitongZennir , Khaled and Zhang , Ran}, title = {Modeling and Reviewing Analysis of the COVID-19 Epidemic in Algeria with Diagnostic Shadow}, journal = {CSIAM Transactions on Applied Mathematics}, year = {2022}, volume = {3}, number = {4}, pages = {792--809}, abstract = {

In this paper, we formulate a special epidemic dynamic model to describe the transmission of COVID-19 in Algeria. We derive the threshold parameter control reproduction number $(\mathcal{R}^0_c),$ and present the effective control reproduction number $(\mathcal{R}_c(t))$ as a real-time index for evaluating the epidemic under different control strategies. Due to the limitation of the reported data, we redefine the number of accumulative confirmed cases with diagnostic shadow and then use the processed data to do the optimal numerical simulations. According to the control measures, we divide the whole research period into six stages. And then the corresponding medical resource estimations and the average effective control reproduction numbers for each stage are given. Meanwhile, we use the parameter values which are obtained from the optimal numerical simulations to forecast the whole epidemic tendency under different control strategies.

}, issn = {2708-0579}, doi = {https://doi.org/10.4208/csiam-am.SO-2021-0019}, url = {http://global-sci.org/intro/article_detail/csiam-am/21156.html} }
TY - JOUR T1 - Modeling and Reviewing Analysis of the COVID-19 Epidemic in Algeria with Diagnostic Shadow AU - Jia , Jiwei AU - Liu , Siyu AU - Liu , Yawen AU - Shan , Ruitong AU - Zennir , Khaled AU - Zhang , Ran JO - CSIAM Transactions on Applied Mathematics VL - 4 SP - 792 EP - 809 PY - 2022 DA - 2022/11 SN - 3 DO - http://doi.org/10.4208/csiam-am.SO-2021-0019 UR - https://global-sci.org/intro/article_detail/csiam-am/21156.html KW - COVID-19, Algeria, diagnostic shadow, medical resource. AB -

In this paper, we formulate a special epidemic dynamic model to describe the transmission of COVID-19 in Algeria. We derive the threshold parameter control reproduction number $(\mathcal{R}^0_c),$ and present the effective control reproduction number $(\mathcal{R}_c(t))$ as a real-time index for evaluating the epidemic under different control strategies. Due to the limitation of the reported data, we redefine the number of accumulative confirmed cases with diagnostic shadow and then use the processed data to do the optimal numerical simulations. According to the control measures, we divide the whole research period into six stages. And then the corresponding medical resource estimations and the average effective control reproduction numbers for each stage are given. Meanwhile, we use the parameter values which are obtained from the optimal numerical simulations to forecast the whole epidemic tendency under different control strategies.

Jia , JiweiLiu , SiyuLiu , YawenShan , RuitongZennir , Khaled and Zhang , Ran. (2022). Modeling and Reviewing Analysis of the COVID-19 Epidemic in Algeria with Diagnostic Shadow. CSIAM Transactions on Applied Mathematics. 3 (4). 792-809. doi:10.4208/csiam-am.SO-2021-0019
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