English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

A wide range of approaches have been applied to manage the spread of globalpandemic events such as COVID-19, which have met with varying degrees ofsuccess. Given the large-scale social and economic impact coupled with theincreasing time span of the pandemic, it is important to not only manage thespread of the disease but also put extra efforts on measures that expediteresumption of social and economic life. It is therefore important to identifysituations that carry high risk, and act early whenever such situations areidentified. While a large number of mobile applications have been developed,they are aimed at obtaining information that can be used for contact tracing,but not at estimating the risk of social situations. In this paper, weintroduce an infection risk score that provides an estimate of the infectionrisk arising from human contacts. Using a real-world human contact dataset, weshow that the proposed risk score can provide a realistic estimate of the levelof risk in the population. We also describe how the proposed infection riskscore can be implemented on smartphones. Finally, we identify representativeuse cases that can leverage the risk score to minimize infection propagation.

Infection Risk Score: Identifying the risk of infection propagation based on human contact