Vaccination compartmental epidemiological models for the delta and omicron SARS-CoV-2 variants

被引:1
|
作者
Cuevas-Maraver, J. [1 ,2 ]
Kevrekidis, P. G. [3 ]
Chen, Q. Y. [3 ]
Kevrekidis, G. A. [4 ,5 ,6 ]
Drossinos, Y. [7 ]
机构
[1] Univ Seville, Escuela Politecn Super, Dept Fis Aplicada 1, Grp Fis No Lineal, C Virgen Africa 7, Seville 41011, Spain
[2] Univ Sevilla IMUS, Inst Matemat, Edificio Celestino Mutis Avda Reina Mercedes s-n, Seville 41012, Spain
[3] Univ Massachusetts Amherst, Dept Math & Stat, Amherst, MA 01003 USA
[4] Johns Hopkins Univ, Dept Appl Math & Stat, Baltimore, MD 21218 USA
[5] Los Alamos Natl Lab, Los Alamos, NM USA
[6] Johns Hopkins Univ, Math Inst Data Sci, Baltimore, MD USA
[7] NCSR Demokritos, Inst Nucl & Radiol Sci & Technol Energy & Safety, Thermal Hydraul & Multiphase Flow Lab, GR-15341 Aghia Paraskevi, Greece
关键词
Epidemiological model; SARS-CoV-2; Vaccination; Delta variant; Omicron variant; SYSTEMS;
D O I
10.1016/j.mbs.2023.109109
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
We explore the inclusion of vaccination in compartmental epidemiological models concerning the delta and omicron variants of the SARS-CoV-2 virus that caused the COVID-19 pandemic. We expand on our earlier compartmental-model work by incorporating vaccinated populations. We present two classes of models that differ depending on the immunological properties of the variant. The first one is for the delta variant, where we do not follow the dynamics of the vaccinated individuals since infections of vaccinated individuals were rare. The second one for the far more contagious omicron variant incorporates the evolution of the infections within the vaccinated cohort. We explore comparisons with available data involving two possible classes of counts, fatalities and hospitalizations. We present our results for two regions, Andalusia and Switzerland (including the Principality of Liechtenstein), where the necessary data are available. In the majority of the considered cases, the models are found to yield good agreement with the data and have a reasonable predictive capability beyond their training window, rendering them potentially useful tools for the interpretation of the COVID-19 and further pandemic waves, and for the design of intervention strategies during these waves.
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页数:14
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