Mathematics of the COVID-19 Pandemics: Lessons Learned and How to Mitigate the Next One

          @misc{ scivideos_22841,
            doi = {},
            url = {https://old.simons.berkeley.edu/talks/tbd-481},
            author = {},
            keywords = {},
            language = {en},
            title = {Mathematics of the COVID-19 Pandemics: Lessons Learned and How to Mitigate the Next One},
            publisher = {The Simons Institute for the Theory of Computing},
            year = {2022},
            month = {oct},
            note = {22841 see, \url{https://scivideos.org/simons-institute/22841}}
          }
          

Abstract

Abstract The novel coronavirus that emerged in December 2019, COVID-19, is the greatest public health challenge humans have faced since the 1918 influenza pandemic (it has so far caused over 615 million confirmed cases and 6.5 million deaths). In this talk, I will present some mathematical models for assessing the population-level impact of the various intervention strategies (pharmaceutical and non-pharmaceutical) being used to control and mitigate the burden of the pandemic. Continued human interference with the natural ecosystems, such as through anthropogenic climate change, environmental degradation, and land use changes, make us increasingly vulnerable to the emergence, re-emergence and resurgence of infectious diseases (particularly respiratory pathogens with pandemic potential). I will discuss some of the lessons learned from our COVID-19 modeling studies and propose ways to mitigate the next respiratory pandemic.