Covid Crisis Lab - Seminar Series - Julia Koltai

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3-B3-SR01, ROENTGEN
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Link zoom

https://unibocconi-it.zoom.us/j/99165512755

 

COVID CRISIS LAB Seminar Series 2023 — Fall edition

Julia Koltai, “Social characteristics in epidemics: role and consequences” 

ABSTRACT

The presentation will provide an overview of three research strands carried out by the social science team of the National Laboratory for Health Security in Hungary, in which we are exploring the role of social characteristics on a range of epidemic-related research.

The first part concentrates on the role of social-demographic characteristics in epidemic modelling. We will first demonstrate how large-scale convenient online samples often used for the measurement of contact dynamics may be biased by various social characteristics in a manner that could produce inaccurate epidemic predictions. We offer a solution for the correction of these biases combining large-scale and temporally more detailed online data with cross-sectional offline surveys. Nevertheless, social-demographic information is not only important in the sample’s composition, but also in modeling. Most traditional mathematical models widely used in epidemic modeling only take age into account as a factor that shapes epidemic dynamics. However, additional social characteristics contribute to epidemic spreading as well, yet these factors are often disregarded in such models. We will present a methodology for detecting social characteristics that impact contact dynamics – additionally to age – and demonstrate how we can integrate them into the concept of contact matrices and thus, into epidemic modeling.

The second part of the presentation will focus on the understanding of vaccine hesitancy, which is the primary barrier of vaccine acceptance among high-income countries. Firstly, our aim is to comprehend vaccination homophily’s role by the analysis of egocentric networks collected during the COVID-19 pandemic. The results indicate strong clustering based on vaccination status, which varies across people’s diverse social circles. Even controlling for multiple factors, we found that the network’s vaccination rate is indeed the strongest predictor of vaccination status. Secondly, we concentrate on the role of COVID-19 related conspiracy theories and their influence on people’s attitude towards vaccination. Our findings suggest that individuals who believe in such theories are less inclined to get vaccinated. Nevertheless, we observed that the strength of this effect tends to weaken when some has experienced severe symptoms or hospitalization, either directly, or indirectly. We investigated the development of vaccination attitudes and the reasons for vaccine refusal, whilst exploring the socio-demographic features most likely to impact vaccine hesitancy. Individuals in younger age groups, those with limited education and incomes level, were more inclined to refuse vaccination. Those residing in the capital city showed the lowest likelihood of refusal. Among the three main reasons behind vaccine non-acceptance, it can be unequivocally stated that lack of trust, particularly distrust in science, constitutes the most important factor in vaccine refusal.

Finally, the presentation will exhibit preliminary findings from a project, that seeks to comprehend pandemic-related attitudes and social behaviour with the aid of digital footprints. Using a unique data donation approach, we collected all information stored by Facebook and Google about our research participants. Additionally, these individuals completed a questionnaire, which included questions about their social-demographic characteristics and attitudes and behaviour regarding the COVID-19 pandemic. The analysis of the individuals’ posts and reactions to COVID-19 related content on social media and their location data histories can bring us closer to the understanding of diverse pandemic behavior witnessed among diverse societal groups.

SHORT BIO

Julia Koltai is a senior researcher in the HUN-REN Centre for Social Sciences and an Associate Professor at Eötvös Loránd University, Budapest. She is a sociologist and a statistician by training, has been working on computational social science- and COVID-19 related problems in the recent years. She is the author of more than 30 book chapters and papers published in journals including Scientific Reports, Social Networks, Vaccines, and New Media and Society.

 

For further information on the talk, please contact covidcrisislab@unibocconi.it