Research Interests
Zoltán Brys serves as a Junior Research Fellow at the Centre for Social Sciences and is also enrolled in a PhD program at Semmelweis University. His research focus encompasses the sociology of health, primarily examining clustering of health behavours, especially smoking. In 2021, Brys obtained his MA degree from Károli Gáspár Reformed University and participated in the human ecology research group of Eötvös Loránd University – UNESCO Agenda 2030. This participation added sustainability and environmental sociology to his research interests. Brys also takes on editorial responsibilities for Lege Artis Medicinae and the European Journal of Mental Health. Zoltán received the Róbert Kolossváry Memorial Prize in 2021. Methodologically, he uses both traditional frequentist methods and modern techniques such as machine learning and network analysis. As a member of the LINK group led by Péter Csermely, he continues to understand more network science. Currently, Brys is coordinating a research at the institution titled "Understanding vaccination intention in various social contexts”.
Selected Publications
Brys, Z., Albert , F., Pénzes , M. (2023). A romantikus partner dohányhasználattal kapcsolatos normatív attitűdje: mit és hogyan mérünk a kutatásban? – Scoping review . Lege Artis Medicinae, 33(4), 173-181.
Brys, Z., Albert, F., & Pénzes, M. (2022). A COVID–19 elleni oltóanyagot elutasítók az aktív korú felnőtt magyar lakosság körében 2021 decemberében. Orvosi Hetilap, 163(29), 1135-1143. DOI: 10.1556/650.2022.32531
Brys, Z., Tóth, G., Urbán, R., Vitrai, J., Magyar, G., Bakacs, M., Pénzes, M. (2022). The epidemiology of smoking and e-cigarette use in the Hungarian adult population in 2018. Orvosi Hetilap, 163(1), 31-38.
Brys, Z. (2022). Megérteni, kik vagyunk. Pannonhalmi Szemle, 30(1), 33-40.
Bóta, A., Hajdu, L., Brys, Z., & Krész, M. (2022). Válogatás a hálózatalapú járványterjedési modellek eredményeiből. Lege Artis Medicinae, 32(11-12), 515-520.
Research Projects
MTA/Post-Covid/2021-35 – Understanding vaccination intention in various social contexts - a machine learning approach.
IV/8531-1/2021/EKU – Assessing the impact of the Covid-19 pandemic in the Hungarian population.
