Mathematical modeling of the effect of quarantine rate on controlling the infection of COVID19 in the population of Saudi Arabia

被引:2
作者
Alsheri, Ahuod S. [1 ]
Alraeza, Aeshah A. [2 ]
Afia, Mona R. [1 ]
机构
[1] Univ Bisha, Dept Math, Alnamas 673985644, Saudi Arabia
[2] King Khalid Univ, Dept Math, Abha 62529, Saudi Arabia
关键词
COVID19; Epidemiological disease; Epidemic; Stability; Basic reproduction number; EPIDEMIC;
D O I
10.1016/j.aej.2021.12.033
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
With the development of communications and transportation worldwide, the challenge of controlling epidemiological diseases becomes higher. The COVID19 has put all nations in a lethal confront with a severe disease that needed serious and painful actions. The sooner the actions, the less destructive the impact. In this paper, we incorporate what we believe is crucial but applicable to control the spread of COVID19 in the populations, that is, quarantine. We keep the model as simple as SI Kermack-McKendrick model with an additional compartment of quarantined patients. We established the system's basic properties and studied the stability of the disease-free equilibrium and its relation to the basic reproduction number R0 in which we calculated its formula. The focus of our study is to measure the effect of quarantine rate on controlling the spread of COVID19. We use the data collected from the Ministry of Health in Saudi Arabia. We studied three different values of the quarantine rate where newly infectious patients are detected and isolated within 14, 7, and 5 days. The simulations show a significant effect of the quarantine where COVID19 can be fully controlled if the newly infected patient enters the quarantine within five days. These results were proposed to the Public Health Authority in Saudi Arabia and approved by the Ministry of Health in which they applied promptly.(c) 2021 Production and hosting by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
引用
收藏
页码:6843 / 6850
页数:8
相关论文
共 22 条
[1]   An epidemic prediction from analysis of a combined HIV-COVID-19 co-infection model via ABC-fractional operator [J].
Ahmed, Idris ;
Goufo, Emile F. Doungmo ;
Yusuf, Abdullahi ;
Kumam, Poom ;
Chaipanya, Parin ;
Nonlaopon, Kamsing .
ALEXANDRIA ENGINEERING JOURNAL, 2021, 60 (03) :2979-2995
[2]  
Bassetti M., 2020, EUR J CLIN INVEST, V50, P3
[3]  
Centers for Disease Control and Prevention, 2018, NAT CTR IMM RESP DIS
[4]   Immunological memory to SARS-CoV-2 assessed for up to 8 months after infection [J].
Dan, Jennifer M. ;
Mateus, Jose ;
Kato, Yu ;
Hastie, Kathryn M. ;
Yu, Esther Dawen ;
Faliti, Caterina E. ;
Grifoni, Alba ;
Ramirez, Sydney, I ;
Haupt, Sonya ;
Frazier, April ;
Nakao, Catherine ;
Rayaprolu, Vamseedhar ;
Rawlings, Stephen A. ;
Peters, Bjoern ;
Krammer, Florian ;
Simon, Viviana ;
Saphire, Erica Ollmann ;
Smith, Davey M. ;
Weiskopf, Daniela ;
Sette, Alessandro ;
Crotty, Shane .
SCIENCE, 2021, 371 (6529) :587-+
[5]  
Diekmann O., 1995, EPIDEMIC MODELS THEI, V5, P95
[6]  
Hoppenstaedt F., 1975, SOC IND APPL MATH
[7]   Mathematical modeling of the spread of the coronavirus disease 2019 (COVID-19) taking into account the undetected infections. The case of China [J].
Ivorra, B. ;
Ferrandez, M. R. ;
Vela-Perez, M. ;
Ramos, A. M. .
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2020, 88
[8]   Controlling COVID-19 Pandemic: A Mass Screening Experience in Saudi Arabia [J].
Khan, Anas A. ;
Alahdal, Hadil M. ;
Alotaibi, Reem M. ;
Sonbol, Hana S. ;
Almaghrabi, Rana H. ;
Alsofayan, Yousef M. ;
Althunayyan, Saqer M. ;
Alsaif, Faisal A. ;
Almudarra, Sami S. ;
Alabdulkareem, Khaled I. ;
Assiri, Abdullah M. ;
Jokhdar, Hani A. .
FRONTIERS IN PUBLIC HEALTH, 2021, 8
[9]  
Kingdom of Saudi Arabia Ministry of Health, 2020, COVID19 COMM CONTR C
[10]   Drug treatment options for the 2019-new coronavirus (2019-nCoV) [J].
Lu, Hongzhou .
BIOSCIENCE TRENDS, 2020, 14 (01) :69-71