Modeling the Effectiveness of Face Coverings in Curtailing SARS-CoV-2 Spread

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2021-01-01
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Koshti, Ajinkya Vijay
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Anthony Townsend
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Information Systems and Business Analytics
In today’s business landscape, information systems and business analytics are pivotal elements that drive success. Information systems form the digital foundation of modern enterprises, while business analytics involves the strategic analysis of data to extract meaningful insights. Information systems have the power to create and restructure industries, empower individuals and firms, and dramatically reduce costs. Business analytics empowers organizations to make precise, data-driven decisions that optimize operations, enhance strategies, and fuel overall growth. Explore these essential fields to understand how data and technology come together, providing the knowledge needed to make informed decisions and achieve remarkable outcomes.
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Information Systems and Business Analytics
Abstract

Face coverings by the general public are widely being recommended for limiting the spread of COVID-19. Several states have also mandated using masks in public places. However, its potential and correct use are still relatively unknown. Several studies have assessed the effectiveness of masks by implementing the SIR model of epidemics, but they have certain limitations. This thesis addresses these limitations by modeling for shortcomings in the practical use of masks. The primary limitation addressed is the high transmission rate through high-frequency areas in the closed settings. A multi-group Kermack-McKendrick-type compartmental mathematical model was used to model different scenarios and simulate them with actual data to evaluate the effectiveness of face coverings. It is established that perfect use of face coverings contributes significantly to lowering the spread, but its practical implementation is still highly dependent on strict compliance and effective surface-contact transmission rate.

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Fri Jan 01 00:00:00 UTC 2021