Non-traditional Data Sources for Innovation in Public Health during the COVID-19 Crises
On-campus talk
Daniela Paolotti
Senior Research Scientist, ISI Foundation
Past Talk
In-person talk
Tuesday
Oct 10, 2023
Watch video
11:00 am
EST
Virtual
177 Huntington Ave.
11th floor
Devon House
58 St Katharine's Way
London E1W 1LP, UK
Online
Register here
The COVID-19 pandemic has highlighted the need for responsive and adequate surveillance systems to detect disease outbreaks and accurately monitor disease circulation among the general population. Traditional surveillance systems usually rely on healthcare providers and generally suffer from reporting lags that prevent immediate response plans. Participatory surveillance, a digital approach whereby individuals voluntarily monitor and report on their own health status via Web-based surveys, has emerged in the past decade to complement traditional data collections approaches. This talk will describe the experience of Influenzanet, a Europe-wide network of Web-based platforms for participatory surveillance of Influenza-like Illness and COVID-19 and how the COVID-19 pandemic has impacted and, in a way, enhanced the capabilities of this approach.
About the speaker
About the speaker
Daniela Paolotti is a Senior Research Scientist at ISI Foundation, in Turin, Italy. She is part of the Data Science for Social Impact Research Area. She has a background in Physics (Bsc, MSc, Ph.D.). Her work has a strong interdisciplinary approach. For more than ten years, she has been working on applying tools from complex systems and networks science, applied mathematics, computer science, data science, behavioral sciences to study disease spreading from an epidemiological as well as social point of view. Since 2008, Daniela has been developing and coordinating a Europe-wide network of Web-based platforms for participatory surveillance of Influenza-like Illness.
Daniela Paolotti is a Senior Research Scientist at ISI Foundation, in Turin, Italy. She is part of the Data Science for Social Impact Research Area. She has a background in Physics (Bsc, MSc, Ph.D.). Her work has a strong interdisciplinary approach. For more than ten years, she has been working on applying tools from complex systems and networks science, applied mathematics, computer science, data science, behavioral sciences to study disease spreading from an epidemiological as well as social point of view. Since 2008, Daniela has been developing and coordinating a Europe-wide network of Web-based platforms for participatory surveillance of Influenza-like Illness.