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Mathematical Modeling of SARS-CoV-2 Omicron Wave under Vaccination Effects
Computation ; 11(2):36.0, 2023.
Article in English | MDPI | ID: covidwho-2241062
ABSTRACT
Over the course of the COVID-19 pandemic millions of deaths and hospitalizations have been reported. Different SARS-CoV-2 variants of concern have been recognized during this pandemic and some of these variants of concern have caused uncertainty and changes in the dynamics. The Omicron variant has caused a large amount of infected cases in the US and worldwide. The average number of deaths during the Omicron wave toll increased in comparison with previous SARS-CoV-2 waves. We studied the Omicron wave by using a highly nonlinear mathematical model for the COVID-19 pandemic. The novel model includes individuals who are vaccinated and asymptomatic, which influences the dynamics of SARS-CoV-2. Moreover, the model considers the waning of the immunity and efficacy of the vaccine against the Omicron strain. This study uses the facts that the Omicron strain has a higher transmissibility than the previous circulating SARS-CoV-2 strain but is less deadly. Preliminary studies have found that Omicron has a lower case fatality rate compared to previous circulating SARS-CoV-2 strains. The simulation results show that even if the Omicron strain is less deadly it might cause more deaths, hospitalizations and infections. We provide a variety of scenarios that help to obtain insight about the Omicron wave and its consequences. The proposed mathematical model, in conjunction with the simulations, provides an explanation for a large Omicron wave under various conditions related to vaccines and transmissibility. These results provide an awareness that new SARS-CoV-2 variants can cause more deaths even if their fatality rate is lower.

Full text: Available Collection: Databases of international organizations Database: MDPI Type of study: Experimental Studies Topics: Vaccines / Variants Language: English Journal: Computation Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: MDPI Type of study: Experimental Studies Topics: Vaccines / Variants Language: English Journal: Computation Year: 2023 Document Type: Article