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LEVERAGING A MULTIPLE-STRAIN MODEL WITH MUTATIONS IN ANALYZING THE SPREAD OF COVID-19
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; : 8163-8167, 2021.
Article in English | Web of Science | ID: covidwho-1532690
ABSTRACT
The spread of COVID-19 has been among the most devastating events affecting the health and well-being of humans worldwide since World War II. A key scientific goal concerning COVID-19 is to develop mathematical models that help us to understand and predict its spreading behavior, as well as to provide guidelines on what can be done to limit its spread. In this paper, we discuss how our recent work on a multiple-strain spreading model with mutations can help address some key questions concerning the spread of COVID-19. We highlight the recent reports on a mutation of SARS-CoV-2 that is thought to be more transmissible than the original strain and discuss the importance of incorporating mutation and evolutionary adaptations (together with the network structure) in epidemic models. We also demonstrate how the multiplestrain transmission model can be used to assess the effectiveness of mask-wearing in limiting the spread of COVID19. Finally, we present simulation results to demonstrate our ideas and the utility of the multiple-strain model in the context of COVID-19.

Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Year: 2021 Document Type: Article