Abstract
The recent pandemic has been accompanied by an unprecedented "infodemic"—an overwhelming surge of both accurate and misleading information. During periods of unpredictability, mis/disinformation can spread rapidly online and have major real-world effects on population behavior and health outcomes. This study examines the correlation between the dissemination of mis/disinformation during health crises and its impacts on pandemic progression and associated health consequences. I linked existing digital data, public health records, and civil unrest events across 32 countries to quantify the (lagged) influence of the infodemic and public resistance to non-pharmaceutical interventions (NPI) on public health outcomes, adjusting for time and country-level differences.
The preliminary findings reveal a significant association between the level of infodemic and the severity of the epidemic spread in terms of the number of cases and excess mortality. Public protests against NPI measures also play a mediating role. To complement the infodemic measure, I collected data from Google Trends, Twitter/X, and YouTube to explore the different methods for classifying and quantifying mis/disinformation based on a taxonomy of topics linked to COVID-19 conspiracies. The results aim to highlight the possible real-world repercussions of online activities during times of uncertainty and to enhance readiness for future health, climate, or political emergencies where the spread of mis/disinformation often prevails over rational thinking at the collective level.
Short bio
Yuxi Wang is a Marie Curie fellow based in the French National Institute of Demographic Studies (INED). She finished her PhD in Health Economics and Public Policy at Bocconi University, where she focused her research on various aspects of health disparity. She is interested in how societal shocks and information, good or bad, influence perception, choice, behaviour and outcome at the population level. She is experienced in utilizing observational data, particularly administrative data, and is presently investigating the potential of integrating digital data with epidemiological data to generate evidence.
