Global analysis of the COVID-19 pandemic using simple epidemiological models

被引:39
作者
Amaro, Jose Enrique [1 ,2 ]
Dudouet, Jeremie [3 ]
Orce, Jose Nicolas [4 ]
机构
[1] Univ Granada, Dept Fis Atom Mol & Nucl, E-18071 Granada, Spain
[2] Univ Granada, Inst Carlos Fis Teor & Computac 1, E-18071 Granada, Spain
[3] Univ Claude Bernard Lyon 1, Univ Lyon, IP2I Lyon, CNRS,IN2P3,UMR 5822, F-69622 Villeurbanne, France
[4] Univ Western Cape, Dept Phys & Astron, P-B X17, ZA-7535 Bellville, South Africa
基金
新加坡国家研究基金会;
关键词
COVID-19; coronavirus; Death model; Extended SIR model; Monte Carlo Planck model; A-PRIORI PATHOMETRY; PROBABILITIES;
D O I
10.1016/j.apm.2020.10.019
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Several analytical models have been developed in this work to describe the evolution of fatalities arising from coronavirus COVID-19 worldwide. The Death or 'D' model is a simpli-fied version of the well-known SIR (susceptible-infected-recovered) compartment model, which allows for the transmission-dynamics equations to be solved analytically by assuming no recovery during the pandemic. By fitting to available data, the D-model provides a precise way to characterize the exponential and normal phases of the pandemic evolution, and it can be extended to describe additional spatial-time effects such as the release of lockdown measures. More accurate calculations using the extended SIR or ESIR model, which includes recovery, and more sophisticated Monte Carlo grid simulations - also developed in this work - predict similar trends and suggest a common pandemic evolution with universal parameters. The evolution of the COVID-19 pandemic in several countries shows the typical behavior in concord with our model trends, characterized by a rapid increase of death cases followed by a slow decline, typically asymmetric with respect to the pandemic peak. The fact that the D and ESIR models predict similar results - without and with recovery, respectively - indicates that COVID-19 is a highly contagious virus, but that most people become asymptomatic (D model) and eventually recover (ESIR model). (c) 2020 Elsevier Inc. All rights reserved.
引用
收藏
页码:995 / 1008
页数:14
相关论文
共 26 条
[1]  
Amaro J. E., 2020, ARXIV200313747
[2]  
Amaro J.E., 2020, UNPUB
[3]   THE KERMACK-MCKENDRICK EPIDEMIC THRESHOLD THEOREM - DISCUSSION [J].
ANDERSON, RM .
BULLETIN OF MATHEMATICAL BIOLOGY, 1991, 53 (1-2) :3-32
[4]  
Bartlett M.S., 1956, P 3 BERK S MATH STAT, V4, P81, DOI DOI 10.2307/2342553
[5]   MEASLES PERIODICITY AND COMMUNITY SIZE [J].
BARTLETT, MS .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-GENERAL, 1957, 120 (01) :48-70
[6]  
Brauer Fred, 2017, Infect Dis Model, V2, P113, DOI 10.1016/j.idm.2017.02.001
[7]   SEASONALITY AND THE EFFECTIVENESS OF MASS VACCINATION [J].
Chao, Dennis L. ;
Dimitrov, Dobromir T. .
MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2016, 13 (02) :249-259
[8]  
Chauhan S., 2014, Am. J. Comput. Math, V4, P17, DOI DOI 10.5923/J.AJCAM.20140401.03
[9]  
Dehning J., 2020, Inferring COVID-19 spreading rates and potential change points for case number forecasts
[10]   BASIC MODELS FOR DISEASE OCCURRENCE IN EPIDEMIOLOGY [J].
FLANDERS, WD ;
KLEINBAUM, DG .
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 1995, 24 (01) :1-7