Inverse problem for adaptive SIR model:Application to COVID-19 in Latin America

作     者：Tchavdar T.Marinov Rossitza S.Marinova 

作者机构：Department of Natural SciencesSouthern University at New OrleansNew OrleansLA70126USA Department of Mathematical and Physical SciencesConcordia University of EdmontonEdmontonABT5B 4E4Canada 

出 版 物：《Infectious Disease Modelling》 (传染病建模（英文）)

年 卷 期：2022年第7卷第1期

页      面：134-148页

学科分类：1002[医学-临床医学] 100201[医学-内科学(含：心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 10[医学] 

主　　题：Inverse problem SIR epidemic Model Coefficient identification Time-dependent transmission and removal rates COVID-19 

摘      要：This work presents a method for solving an Adaptive Susceptible-Infected-Removed(ASIR)epidemic model with time-dependent transmission and removal *** COVID-19 data as of March 2021 are used for identifying the rates from an inverse *** estimated rates are used to solve the adaptive SIR system for the spread of the infectious *** method simultaneously solves the problem for the time-dependent rates and the unknown functions of the A-SIR *** results show the spread of COVID-19 in the World,Argentina,Brazil,Colombia,Dominican Republic,and *** of the reported affected by the disease individuals from the available real data and the values obtained with the A-SIR model demonstrate how well the model simulates the dynamic of the infectious disease.