Understanding the Impact of Varied Testing and Infection Rates on Covid-19 Impact Across Age-Based Populations
Description
Covid-19 is unlike any coronavirus we have seen before, characterized mostly by the ease with which it spreads. This analysis utilizes an SEIR model built to accommodate various populations to understand how different testing and infection rates may affect hospitalization and death. This analysis finds that infection rates have a significant impact on Covid-19 impact regardless of the population whereas the impact that testing rates have in this simulation is not as pronounced. Thus, policy-makers should focus on decreasing infection rates through targeted lockdowns and vaccine rollout to contain the virus, and decrease its spread.
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2021-05
Agent
- Author (aut): Shah, Aashney Lalita
- Thesis director: Pedrielli, Giulia
- Committee member: Candan, Kasim Selcuk
- Contributor (ctb): Industrial, Systems & Operations Engineering Prgm
- Contributor (ctb): Industrial, Systems & Operations Engineering Prgm
- Contributor (ctb): Economics Program in CLAS
- Contributor (ctb): Barrett, The Honors College