| Abstract: |
| COVID-19 has presented unprecedented global public health challenges. This talk will discuss some mathematical modeling works for COVID-19, divided into two parts. The first part introduces a multiscale modeling framework that integrates both within-host and between-host dynamics of COVID-19. It explores various transmission routes (human-to-human and environment-to-human) and scales (population and individual). The analysis reveals complex dynamics and underscores the environment`s critical role in transmission. While antiviral treatments can delay outbreaks, they cannot prevent them, highlighting the need for environmental control measures in addition to human-to-human interventions like social distancing and mask-wearing. The second part focuses on a multi-strain model that investigates how asymptomatic or pre-symptomatic infections impact strain transmission and control strategies. Our findings indicate that Omicron variants are more transmissible but less fatal than earlier strains. We also show that implementing mask mandates before the peak can reduce and delay it, with the timing of lifting mandates affecting subsequent waves. |
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