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COVID-19 Symptoms app analysis to foresee healthcare impacts: Evidence from Northern Ireland – the new paper is available!

Could be a better beginning of the New Year than the new publication by one of the Sano Team Leaders? 
Congratulations Jose Sousa, Personal Health Data Science Team Leader at Sano Centre, and all the authors: João Barata, Hugo C. Van Woerden, and Frank Kee
The paper “COVID-19 Symptoms app analysis to foresee healthcare impacts: Evidence from Northern Ireland” is already available!   
This paper presents a semantic network approach to model COVID-19 entanglement using mobile data to extract explicit (e.g., self-reported symptoms) and implicit knowledge (e.g., location, social factors, trends). The scientists’ proposal extends past research, including a health-wealth layer and AI self-supervised learning capacity to profile symptoms in specific contexts. 
Modelling social and health-related data at the meso level is essential to understanding the dynamics of the virus in the community, complementing, or even replacing test results (e.g., Lateral Flow or PCR tests) when these are unavailable. 

Highlights from the publication:

  • COVID-19 symptoms modelling using mobile data and complex networks. 
  • Monitoring the progression of COVID-19 in specific regions. 
  • Evaluating the severity of COVID-19 symptoms in specific groups of the population. 
  • Characterising the symptom pattern for the circulating viral strains. 
  • Supporting public health decisions in selective lockdown strategies.

We highly recommend the lecture! 


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