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Lin Wang

Researcher at University of Cambridge

Publications -  90
Citations -  7300

Lin Wang is an academic researcher from University of Cambridge. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 32, co-authored 65 publications receiving 5356 citations. Previous affiliations of Lin Wang include City University of Hong Kong & Fudan University.

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The Impact of Spring Festival Travel on Epidemic Spreading in China

TL;DR: Wang et al. as mentioned in this paper analyzed the impact of Spring Festival travel on the peak timing and peak magnitude nationally and in each city, assuming an R0 (basic reproduction number) of 15 and the initial conditions as the reported COVID-19 infections on 17 December 2022.
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Cost effectiveness of fractional doses of COVID-19 vaccine boosters in India

TL;DR: In this paper , the potential economic benefit and cost of using fractions of the standard dose of SARS-CoV-2 booster vaccines based on a data-driven model of severe acute respiratory syndrome coronavirus 2 transmission that incorporates waning immunity induced by vaccination or infection was evaluated.
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Protocol for the automatic extraction of epidemiological information via a pre-trained language model

TL;DR: Wang et al. as discussed by the authors presented a protocol for using CCIE, a COVID-19 Cases Information Extraction system based on the pre-trained language model, to automatically extract epidemiological fields from open-access COVID19 cases.
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Editorial: Infectious Disease Epidemiology and Transmission Dynamics

Zhanwei Du, +2 more
- 01 Jan 2023 - 
TL;DR: Infectious diseases such as COVID-19 as discussed by the authors have been identified as a major threat in the development of COVID19 [1] . . . ] and COVID
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Characterizing human collective behaviours of COVID-19 in Hong Kong

TL;DR: In this article , the authors evaluated interactions among individuals emotions, perception, and online behaviours in Hong Kong during the first two waves (February to June 2020) and found a strong correlation between online behaviours of Google search and the real-time reproduction numbers.