Spotting the next pandemic: prospecting or preparedness?
53 mins 5 secs,
97.11 MB,
MP3
44100 Hz,
249.78 kbits/sec
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| Description: |
Holmes, E
Thursday 10th September 2020 - 09:30 to 10:15 |
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| Created: | 2020-09-10 17:29 |
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| Collection: | Infectious Dynamics of Pandemics: Mathematical and statistical challenges in understanding the dynamics of infectious disease pandemics |
| Publisher: | Isaac Newton Institute |
| Copyright: | Holmes, E |
| Language: | eng (English) |
| Distribution: |
World
(downloadable)
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| Explicit content: | No |
| Aspect Ratio: | 16:9 |
| Screencast: | No |
| Bumper: | UCS Default |
| Trailer: | UCS Default |
| Abstract: | Zoonotic diseases have long been a major burden on human societies and are expected to increase in frequency and impact as we interact more with the animal world and as the global population increases in both size and productivity. Fortunately, new genomic tools, particularly metagenomic next-generation sequencing (mNGS), provide a uniquely powerful means to rapidly reveal the microbial composition of any sample without bias, provide key information on the diversity, structure and evolution of the virosphere, help determine how microbes move across the human-animal interface and the drivers of disease emergence, and reveal the origins of specific epidemics. Herein, I demonstrate the utility of mNGS for pathogen discovery and understanding disease emergence on clinically actionable time-scales. In doing so, I will demonstrate how these genomic tools can form a key component to new approaches to pandemic preparedness. As a case study will focus on the initial emergence of COVID-19 (SARS-CoV-2) at the end of 2019. I will discuss the most likely theories for its origin and emergence, and consider why coronaviruses seem particularly able to jump species boundaries and emerge in new hosts. I will conclude by outlining the ways in which we can potentially prevent pandemics like that of COVID-19 ever happening again.
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| iPod Video | 480x270 | 483.98 kbits/sec | 187.99 MB | View | Download | |
| MP3 * | 44100 Hz | 249.78 kbits/sec | 97.11 MB | Listen | Download | |
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