Formal Concept Analysis Applied to a Longitudinal Study of COVID-19

Paulo Lana, Cristiane Nobre, Luis Zarate, Mark Song

2022

Abstract

The COVID-19 pandemic, and consequently the difficulty of obtaining feedback on the effectiveness of contamination prevention methods, has caused an increased need to produce a relevant and consistent analysis from collected data. Through Formal Concept Analysis, applying the triadic approach, called Triadic Concept Analysis (TCA), it is possible to evaluate the correlation between prevention measures and the number of contaminated people by performing concept extraction and implication rules. The advantage of using this method is the possibility of correlating the waves, which allows us to explain and understand the evolution of the data over the collection waves, helping us draw a more assertive conclusion from the data analyzed. This paper uses the data collected from the 2020 National Population Survey of Nigeria to depict how Nigerian society’s essential and everyday behaviors impacted the evolution of the COVID-19 pandemic in that country. The results obtained from this research can assist governments, and public entities in developing better public policies to combat highly infectious diseases. Furthermore, it provides practical evidence of how TCA can be applied, bringing benefits to different areas and fields of science.

Paper Citation

in Harvard Style

Lana P., Nobre C., Zarate L. and Song M. (2022). Formal Concept Analysis Applied to a Longitudinal Study of COVID-19. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-569-2, pages 148-154. DOI: 10.5220/0011036000003179

in Bibtex Style

@conference{iceis22,
author={Paulo Lana and Cristiane Nobre and Luis Zarate and Mark Song},
title={Formal Concept Analysis Applied to a Longitudinal Study of COVID-19},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2022},
pages={148-154},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011036000003179},
isbn={978-989-758-569-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Formal Concept Analysis Applied to a Longitudinal Study of COVID-19
SN - 978-989-758-569-2
AU - Lana P.
AU - Nobre C.
AU - Zarate L.
AU - Song M.
PY - 2022
SP - 148
EP - 154
DO - 10.5220/0011036000003179