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Model with transmission delays for COVID‐19 control: Theory and empirical assessment
Author(s) -
Hritonenko Natali,
Yatsenko Olga,
Yatsenko Yuri
Publication year - 2022
Publication title -
journal of public economic theory
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.809
H-Index - 32
eISSN - 1467-9779
pISSN - 1097-3923
DOI - 10.1111/jpet.12554
Subject(s) - covid-19 , pandemic , government (linguistics) , epidemic model , transmission (telecommunications) , econometrics , control (management) , economics , infectious disease (medical specialty) , mathematical economics , computer science , virology , biology , environmental health , medicine , population , telecommunications , disease , management , pathology , outbreak , linguistics , philosophy
The paper focuses on modeling of public health measures to control the COVID‐19 pandemic. The authors suggest a flexible integral model with distributed lags, which realistically describes COVID‐19 infectiousness period from clinical data. It contains susceptible–infectious–recovered (SIR), susceptible–exposed–infectious–recovered (SEIR), and other epidemic models as special cases. The model is used for assessing how government decisions to lockdown and reopen the economy affect epidemic spread. The authors demonstrate essential differences in transition and asymptotic dynamics of the integral model and the SIR model after lockdown. The provided simulation on real data accurately describes several waves of the COVID‐19 epidemic in the United States and is in good correspondence with government actions to curb the epidemic.