Integral Model of COVID-19 Spread and Mitigation in UK: Identification of Transmission Rate

被引：1

作者：

Hritonenko, Natali ^{[1
]}

Satsky, Caroline ^{[2
]}

Yatsenko, Yuri ^{[3
]}

机构：

[1] Prairie View A&M Univ, Dept Math, Prairie View, TX 77446 USA

[2] Texas Tech Univ Lubbock, Dept Math & Stat, Lubbock, TX 79401 USA

[3] Houston Baptist Univ, Dunham Coll Business, Houston, TX 77074 USA

来源：

MATHEMATICAL MODELLING AND ANALYSIS | 2022年 / 27卷 / 04期

关键词：

integral epidemiologic models; COVID-19; mitigation; Volterra integral equa-tions; ill-posed problems; regularizing algorithm; EPIDEMIC MODELS;

D O I：

10.3846/mma.2022.15708

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

The integral model with finite memory is employed to analyze the time-line of COVID-19 epidemic in the United Kingdom and government actions to miti-gate it. The model uses a realistic infection distribution. The time-varying transmis-sion rate is determined from Volterra integral equation of the first kind. The authors construct and justify an efficient regularization algorithm for finding the transmission rate. The model and algorithm are approbated on the UK data with several waves of COVID-19 and demonstrate a remarkable resemblance between real and simulated dynamics. The timing of government preventive measures and their impact on the epidemic dynamics are discussed.

引用

页码：573 / 589

页数：17

共 30 条

[1]

Acemoglu D, 2020, Optimal targeted lockdowns in a multi-group SIR prototype (No. w27102), DOI DOI 10.3386/W27102

[2]

Alva-Manchego F, 2020, COMPUT LINGUIST, V46, P135, DOI [10.1162/coli_a_00370, 10.1162/COLI_a_00370]

[3]

[Anonymous], 1991, Integral Equations and Applications

[4]

[Anonymous], 2000, Mathematical Modelling: Theory and Applications

[5] A simple model for COVID-19 [J].

Arino, Julien ;

Portet, Stephanie .

INFECTIOUS DISEASE MODELLING, 2020, 5 :309-315

[6]

Atkeson Andrew, 2020, NBER Working Paper 26867, DOI DOI 10.3386/W26867

[7]

Baker C.T.H., 1974, NUMERICAL SOLUTION I, P162

[8]

Barlow B, 2020, BBC NEWS

[9] Oscillations in U.S. COVID-19 Incidence and Mortality Data Reflect Diagnostic and Reporting Factors [J].

Bergman, Aviv ;

Sella, Yehonatan ;

Agre, Peter ;

Casadevall, Arturo .

MSYSTEMS, 2020, 5 (04)

[10]

Brauer F, 2019, TEXTS APPL MATH, V69, P1, DOI 10.1007/978-1-4939-9828-9

← 1 2 3 →