UCL Computer Science


Online search activity can help predict peaks in COVID-19 cases

23 February 2021

Researchers used COVID-19’s symptom profile from existing epidemiological reports to develop models of its prevalence by looking at symptom-related searches through Google.

hands typing on a keyboard

Dr Vasileios Lampos of UCL Computer Science is lead author of the study, which uses online search data to help inform the public health response to COVID-19. According to a report from UCL, allowing experts to predict a peak in cases on average 17 days in advance.

Adding to previous research that has showcased the utility of online search activity in modelling infectious diseases such as influenza, this study provides a new set of tools that can be used to track COVID-19.  Dr Lampos

Read more about the study on Nature.com

Read an overview of the study

Read press coverage related to the study