22839

A Global Comparison of COVID-19 Variant Waves and Relationships with Clinical and Demographic Factors

APA

(2022). A Global Comparison of COVID-19 Variant Waves and Relationships with Clinical and Demographic Factors. The Simons Institute for the Theory of Computing. https://old.simons.berkeley.edu/talks/global-comparison-covid-19-variant-waves-and-relationships-clinical-and-demographic-factors

MLA

A Global Comparison of COVID-19 Variant Waves and Relationships with Clinical and Demographic Factors. The Simons Institute for the Theory of Computing, Oct. 28, 2022, https://old.simons.berkeley.edu/talks/global-comparison-covid-19-variant-waves-and-relationships-clinical-and-demographic-factors

BibTex

          @misc{ scivideos_22839,
            doi = {},
            url = {https://old.simons.berkeley.edu/talks/global-comparison-covid-19-variant-waves-and-relationships-clinical-and-demographic-factors},
            author = {},
            keywords = {},
            language = {en},
            title = {A Global Comparison of COVID-19 Variant Waves and Relationships with Clinical and Demographic Factors},
            publisher = {The Simons Institute for the Theory of Computing},
            year = {2022},
            month = {oct},
            note = {22839 see, \url{https://scivideos.org/simons-institute/22839}}
          }
          
Sara del Valle (Los Alamos National Laboratory) presenting Virtually
Talk number22839
Source RepositorySimons Institute

Abstract

Abstract The ongoing COVID-19 pandemic has had devastating impacts on global public health and socioeconomic stability. Although highly efficacious COVID-19 vaccines were developed at an unprecedented rate, the ongoing evolution of SARS-CoV-2 and consequential changes in infectivity and immunological resistance of new variants continues to present challenges. Computing the growth rates of emerging variants is complicated by many issues, including vaccine uptake, regional levels of prior infection, viral resistance to protective antibodies, and the relative infectivity of new variants in complex populations. While epidemic forecasting has played an important role in decision-making, forecast accuracy has been limited, especially at key tipping points in the pandemic, by the inability to incorporate important factors, such as the emergence of phenotypically novel variants. In this talk, I will describe a flexible strategy to characterize variant transition dynamics through three simple summaries, the speed, the relative timing, and the magnitude of the variant transition. This foundational research is intended to better understand the implication of SARS-CoV-2 evolution to ultimately inform regional epidemiological forecasting.