Celluloepidemiology—A paradigm for quantifying infectious disease dynamics on a population level

To complement serology as a tool in public health interventions, we introduced the "celluloepidemiology" paradigm where we leveraged pathogen-specific T cell responses at a population level to advance our epidemiological understanding of infectious diseases, using SARS-CoV-2 as a model. Applying flow cytometry and machine learning on data from more than 500 individuals, we showed that the number of T cells with positive expression of functional markers not only could distinguish patients who recovered from COVID-19 from controls and pre-COVID donors but also identify previously unrecognized asymptomatic patients from mild, moderate, and severe recovered patients. The celluloepidemiology approach was uniquely capable to differentiate health care worker groups with different SARS-CoV-2 exposures from each other. T cell receptor (TCR) profiling strengthened our analysis by revealing that SARS-CoV-2-specific TCRs were more abundant in patients than in controls. We believe that adding data on T cell reactivity will complement serology and augment the value of infection morbidity modeling for populations.

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Publication Details

Journal
Science Advances
Published
2025-05-16
DOI
https://doi.org/10.1126/sciadv.adt2926
Citations
1
Primary Topic
SARS-CoV-2 and COVID-19 Research
Type
article
Field-Weighted Citation Impact
1.40
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article

Celluloepidemiology—A paradigm for quantifying infectious disease dynamics on a population level

Samuel Coenen, Sabrina H. van Ierssel, Esther Bartholomeus, Benson Ogunjimi et al.
1 citations
Science Advances
SARS-CoV-2 and COVID-19 Research
1.40
article

Celluloepidemiology—A paradigm for quantifying infectious disease dynamics on a population level

Samuel Coenen, Sabrina H. van Ierssel, Esther Bartholomeus, Benson Ogunjimi, Eva Lion, Pieter Meysman, Kris Laukens, Joachim Mariën, Hans De Reu, Pierre Van Damme, Kevin K. Ariën, Maria Kuznetsova, Koen Vercauteren, Erika Vlieghe, Leo Heyndríckx, Philippe Beutels, Betty Willems, Hajar Besbassi, Reinout Naesens, Karin Peeters, My Kieu Ha, Anna Postovskaya, Vincent M.L. Van Deuren, Jolien Schippers
article en
1 citations

Abstract

To complement serology as a tool in public health interventions, we introduced the "celluloepidemiology" paradigm where we leveraged pathogen-specific T cell responses at a population level to advance our epidemiological understanding of infectious diseases, using SARS-CoV-2 as a model. Applying flow cytometry and machine learning on data from more than 500 individuals, we showed that the number of T cells with positive expression of functional markers not only could distinguish patients who recovered from COVID-19 from controls and pre-COVID donors but also identify previously unrecognized asymptomatic patients from mild, moderate, and severe recovered patients. The celluloepidemiology approach was uniquely capable to differentiate health care worker groups with different SARS-CoV-2 exposures from each other. T cell receptor (TCR) profiling strengthened our analysis by revealing that SARS-CoV-2-specific TCRs were more abundant in patients than in controls. We believe that adding data on T cell reactivity will complement serology and augment the value of infection morbidity modeling for populations.

Science AdvancesVol. 11(20)
University of Antwerp (BE), Antwerp Management School (BE), Antwerp University Hospital (BE), Infectious Diseases Institute (UG), Biomedical Informatics Research Center Antwerp (BE), Instituut voor Tropische Geneeskunde (BE)
Good health and well-being
Openalex Percentile: Top 21%
SARS-CoV-2 and COVID-19 Research
1.40
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