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Conference Paper: Data science and COVID-19
Title | Data science and COVID-19 |
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Authors | |
Issue Date | 2020 |
Citation | InnoCarnival 2020 Online Public Talks, Hong Kong, 23 December 2020 How to Cite? |
Abstract | We will discuss: i) how big data have been integrated into infectious disease modeling in real-time to monitor and forecast the spread of COVID-19; ii) how our digital culture has both strengthened and hindered our ability to control the pandemic. |
Description | Organizer: The Hong Kong Academy of Sciences |
Persistent Identifier | http://hdl.handle.net/10722/311559 |
DC Field | Value | Language |
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dc.contributor.author | Wu, JTK | en_HK |
dc.date.accessioned | 2022-03-23T05:17:35Z | - |
dc.date.available | 2022-03-23T05:17:35Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | InnoCarnival 2020 Online Public Talks, Hong Kong, 23 December 2020 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/311559 | - |
dc.description | Organizer: The Hong Kong Academy of Sciences | en_HK |
dc.description.abstract | We will discuss: i) how big data have been integrated into infectious disease modeling in real-time to monitor and forecast the spread of COVID-19; ii) how our digital culture has both strengthened and hindered our ability to control the pandemic. | en_HK |
dc.language | eng | - |
dc.relation.ispartof | InnoCarnival 2020 | - |
dc.title | Data science and COVID-19 | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.email | Wu, JTK: joewu@hku.hk | - |
dc.identifier.authority | Wu, JTK=rp00517 | - |
dc.identifier.hkuros | 320767 | - |