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Modelling spatio temporal COVID-19 trends through wastewater surveillance

Video in TIB AV-Portal: Modelling spatio temporal COVID-19 trends through wastewater surveillance

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Title
Modelling spatio temporal COVID-19 trends through wastewater surveillance
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CC Attribution 3.0 Germany:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Release Date
2021
Language
English
Producer
Delconte, Valentina
Production Year
2021
Production Place
Wageningen

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Abstract
Theresa Smith is a Lecturer in Statistics at the University of Bath. She received her PhD in Statistics from the University of Washington and went on to work as a postdoctoral researcher in spatial epidemiology in the Center for Health Informatics, Computing and Statistics at Lancaster University from 2014 to 2016. In current role at the University of Bath, Theresa specialises in working collaboratively with multidisciplinary teams to develop predictive analytics tools with applications to clinical and public health. In this talk, Theresa discussed the statistics and data science challenges arising from her ongoing work to develop community-scale monitoring systems for COVID-19 and other diseases using regular sampling and testing of wastewater. More on this project can be found at https://ewsresearch.com/our-projects/ews-c19/
Keywords COVID-19 wastewater modelling predictive analytics
mathematics
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redundancy system Witt-Algebra boundaries Smith
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