Digital Epidemiology after COVID-19, some examples and a new definition

On February 9th, at 2:00 pm, Joana Gonçalves de Sá will present a seminar entitled “Digital Epidemiology after COVID-19, some examples and a new definition”.

Abstract: Epidemiology and Public Health have increasingly relied on structured and unstructured data, collected inside and outside of typical health systems, to study, identify, and mitigate diseases at the population level. During the talk I will expand on the notion of Digital Epidemiology (DE) and, focusing on infectious diseases, highlight the statistical nature of the datasets. I will give examples for our current work and offer some recommendations to reduce inequity and threats to privacy and argue in favour of complex multidisciplinary approaches to tackling infectious diseases.

Short Bio: Joana Gonçalves de Sá is a researcher at LIP and the coordinator investigator of the Social Physics and Complexity (SPAC) research group. She has a degree in Physics Engineering from Instituto Superior Técnico – University of Lisbon, and a PhD in Systems Biology from NOVA – ITQB, having developed her thesis at Harvard University, USA. Her current research uses data analytics and machine learning to study complex problems at the interface between Biomedicine, Social Sciences, and Computation, with a large ethical and societal focus. She received two ERC grants (Stg_2019 and PoC_2022) to study human and algorithmic biases using fake news as a model system and an epidemiological approach and she routinely works with health authorities to improve disease monitoring.