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

During a disease outbreak, timely non-medical interventions are critical inpreventing the disease from growing into an epidemic and ultimately a pandemic.However, taking quick measures requires the capability to detect the earlywarning signs of the outbreak. This work collects Twitter posts surrounding the2020 COVID-19 pandemic expressing the most common symptoms of COVID-19including cough and fever, geolocated to the United States. Through examiningthe variation in Twitter activities at the state level, we observed a temporallag between the rises in the number of symptom reporting tweets and officiallyreported positive cases which varies between 5 to 19 days.

Early Outbreak Detection for Proactive Crisis Management Using Twitter Data: COVID-19 a Case Study in the US