THE IMPORTANCE OF PROVEN TREATMENT AS A VACCINE MODEL FOR COVID-19

被引:1
作者
Kim, B. N. [1 ,2 ]
Abbas, W. [3 ,4 ]
Kim, H. K. [5 ]
Yoon, G. [6 ]
Kim, H. [7 ]
Kim, Y. [7 ]
Kim, S. [3 ,4 ,8 ]
机构
[1] Pusan Natl Univ, Finance Fishery Manufacture Ind Math Ctr Big Data, Busan 46241, South Korea
[2] Kyung Hee Univ, Dept Appl Math, Yongin 17104, Gyeonggi Do, South Korea
[3] Pusan Natl Univ, Inst Math Sci, Busan 46241, South Korea
[4] Pusan Natl Univ, Dept Math, Busan 46241, South Korea
[5] Hannam Univ, Dept Math Educ, Daejeon 34430, South Korea
[6] Natl Inst Math Sci, Daejeon 34047, South Korea
[7] Kyungpook Natl Univ, Dept Math, Daegu 41566, South Korea
[8] Pusan Natl Univ, Inst Future Earth, Busan 46241, South Korea
基金
新加坡国家研究基金会;
关键词
COVID-19; Mathematical Model; Vaccine; Treatment; EPIDEMIC MODEL; HERD-IMMUNITY; DYNAMICS; SPREAD; REVEAL;
D O I
10.30546/1683-6154.23.4.2024.504
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
. The COVID-19 global pandemic has posed the biggest medical challenge of the past three years, and efforts to eradicate it have involved cross-border collaborations. Recent studies claim that the development and distribution of vaccines is an effective approach to end this infectious disease. However, this study demonstrates that a vaccine alone may not be enough due to differences in the rates of waning immunity induced by infection and vaccination. We propose that both vaccination and treatment are required to halt COVID-19 disease transmission and end the pandemic. From an epidemiological perspective, we employ the SVEIRS model by introducing vaccination and treatment into the compartmental epidemic The experimental results suggest that the pandemic can be ended by performing both vaccination and treatment. However, the development and distribution of vaccines and treatments take time, and control measures must continue until the disease is completely eradicated.
引用
收藏
页码:504 / 519
页数:16
相关论文
共 37 条
[1]  
[Anonymous], Draft landscape of COVID-19 candidate vaccines
[2]   Accounting for symptomatic and asymptomatic in a SEIR-type model of COVID-19 [J].
Arcede, Jayrold P. ;
Caga-Anan, Randy L. ;
Mentuda, Cheryl Q. ;
Mammeri, Youcef .
MATHEMATICAL MODELLING OF NATURAL PHENOMENA, 2020, 15
[3]   Global results for an epidemic model with vaccination that exhibits backward bifurcation [J].
Arino, J ;
McCluskey, CC ;
Van den Driessche, P .
SIAM JOURNAL ON APPLIED MATHEMATICS, 2003, 64 (01) :260-276
[4]   The challenges of modeling and forecasting the spread of COVID-19 [J].
Bertozzi, Andrea L. ;
Franco, Elisa ;
Mohler, George ;
Short, Martin B. ;
Sledge, Daniel .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2020, 117 (29) :16732-16738
[5]   The SEIRS model for infectious disease dynamics [J].
Bjornstad, Ottar N. ;
Shea, Katriona ;
Krzywinski, Martin ;
Altman, Naomi .
NATURE METHODS, 2020, 17 (06) :557-558
[6]   Transmission dynamics reveal the impracticality of COVID-19 herd immunity strategies [J].
Brett, Tobias S. ;
Rohani, Pejman .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2020, 117 (41) :25897-25903
[7]   A mathematical model reveals the influence of population heterogeneity on herd immunity to SARS-CoV-2 [J].
Britton, Tom ;
Ball, Frank ;
Trapman, Pieter .
SCIENCE, 2020, 369 (6505) :846-+
[8]  
Chen W, 2020, APPL COMPUT MATH-BAK, V19, P360
[9]  
Choisy M., 2007, Encyclopedia of Infectious Diseases: Modern Methodologies, P379
[10]   Immune surveillance for vaccine-preventable diseases [J].
den Hartog, Gerco ;
van Binnendijk, Rob ;
Buisman, Anne-Marie ;
Berbers, Guy A. M. ;
van der Klis, Fiona R. M. .
EXPERT REVIEW OF VACCINES, 2020, 19 (04) :327-339