Published in arXiv, 2026
We apply a hypoexponential generalization of the linear chain technique to published models and data.
Recommended citation: Belluccini, G. et al. (2026). "An efficient and flexible generalization of transit compartment models for delayed biological processes." arXiv.
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Published in BioRxiv, 2026
We use organ donor tissue samples to study the relationship between circulating and tissue-resident immune cells and antibody titers specific to SARS-CoV-2.
Recommended citation: Schroeter, J. et al. (2026). "Beyond the blood: Tissue-resident immunity shapes SARS-CoV-2 vaccine antibody responses." BioRxiv.
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Published in MedRxiv, 2026
We use PDE models implemented in Julia to assess age-dependent vaccination strategies in aging populations.
Recommended citation: van Boven, M. et al. (2026). "Optimal vaccination in aging populations under age-dependent infection fatality risks." MedRxiv.
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Published in Communications Medicine, 2026
We retrospectively compare school-closure scenarios for the SARS-CoV-2 pandemic in Portugal.
Recommended citation: Canfora B. et al. (2026). "Retrospective evaluation of school-related measures on pre-vaccination transmission dynamics of SARS-CoV-2." Communications Medicine.
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Published in Cell Reports, 2026
We profile 1,075 transcriptomes from 167 patients with multiple sclerosis and 42 healthy participants across six peripheral immune cell-type-states.
Recommended citation: Roostaei, T. et al (2026). "Cell-type- and state-resolved transcriptomics uncovers distinct T cell and monocyte dysregulation in multiple sclerosis." Cell Reports.
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Published in PLOS Computational Biology, 2025
We fit ODE models to single-cell flow data to infer memory T cell loss and differentiation
Recommended citation: van Dorp, CH. et al. (2025). "A variational deep-learning approach to modeling memory T cell dynamics." PLOS Computational Biology. 21(7): e1013242.
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Published in eLife, 2025
We use mathematical models to identify progenitors and turnover rates of TRM in skin and gut lamina propria
Recommended citation: Chandler J. et al (2025). "Tissue resident memory CD4+ T cells are sustained by site-specific levels of self-renewal and continuous replacement." eLife.
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Published in PLOS Biology, 2024
T cell data from mice with chimeric bone marrow are analyzed with Bayesian ODE models.
Recommended citation: Bullock, ME. et al (2024). "The dynamics and longevity of circulating CD4+ memory T cells depend on cell age and not the chronological age of the host." Plos Biology. 22(8): e3002380.
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Published in Science, 2024
Combination treatment with an IL-15 superagonist and bNAbs can lead to SHIV control after ART interruption.
Recommended citation: Lim, SY. et al (2024). "Induction of durable remission by combination immunotherapy in SHIV infected, ART-suppressed macaques." Science. 383,1104-1111.
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Published in PLOS Computational Biology, 2024
Bayesian analysis of a prospective SARS-CoV-2 household study
Recommended citation: van Boven, M. et al (2024). "Estimation of introduction and transmission rates of SARS-CoV-2 in a prospective household study." Plos Computational Biology. 20(1): e1011832.
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Published in IMA Journal of Applied Mathematics, 2022
Integration schemes for delay-differential equations, and a relaxation of the linear chain trick that is useful for estimating the shape parameter of the Gamma distribution.
Recommended citation: Cassidy T. et al (2022). "Numerical methods and hypoexponential approximations for gamma distributed delay differential equations." IMA Journal of Applied Mathematics. 87(6): 1043–1089.
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Published in Virus Evolution, 2022
We estimate region-specific selective advantages of the Omicron variant of SARS-CoV-2 using renewal equation models, genetic data and COVID-19 case counts.
Recommended citation: van Dorp CH. et al (2022). "Global estimates of the fitness advantage of SARS-CoV-2 variant Omicron." Virus Evolution. 8(2): veac089.
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Published in Nature Communications, 2021
We use isotonic regression, hierarchical logistic regression and stochastic modeling to estimate the fitness advantage of SARS-CoV-2 variants in different regions.
Recommended citation: van Dorp CH. et al (2021). "Estimating the strength of selection for new SARS-CoV-2 variants." Nature Communications 12, 7239.
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Published in Nature Communications, 2021
We make projections using a model fit to Portugese SARS-CoV-2 data to assess if and how non-pharmaceutical interventions can be lifted during planned mass-vaccination campaigns.
Recommended citation: Viana J et al (2021). "Controlling the pandemic during the SARS-CoV-2 vaccination rollout." Nature Communications 12, 3674.
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Published in Journal of Experimental Medicine, 2021
Using a humanized mouse model of an HIV infection, we explore immunotherapies that enhance the CD8+ T-cell response using an N-803 nanogen.
Recommended citation: McCann CD (2021). "A Participant-Derived Xenograft Model of HIV Enables Long-Term Evaluation of Autologous Immunotherapies." Journal of Experimental Medicine. 218(7): e20201908.
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Published in Nature Communications, 2021
We use an age-structured transmission model fit to data to study the effect of school closure on SARS-CoV-2 spread in 2020.
Recommended citation: Rozhnova G et al (2021). "Model-based evaluation of school- and non-school-related measures to control the COVID-19 pandemic." Nature Communications 12, 1614.
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Published in PLOS Computational Biology, 2020
We derive a probability distribution for the time to SIV rebound after ART interruption that takes into account the possibility that multiple latently infected cells can reactivate and contribute to viral recrudescence.
Recommended citation: van Dorp, CH. et al (2020). "Models of SIV rebound after treatment interruption that involve multiple reactivation events." PLOS Computational Biology. 16(10): e1008241.
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Published in The Journal of Infectious Diseases, 2020
We fit age-structure transmission models to multiple RSV data streams and use the fitted models to investigate the impact of pediatric vaccination.
Recommended citation: van Boven, M et al (2020). "Estimating Transmission Parameters for Respiratory Syncytial Virus and Predicting the Impact of Maternal and Pediatric Vaccination." The Journal of Infectious Diseases. 222(Supplement_7): S688–S694.
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Published in PLOS Computational Biology, 2017
We fit PDE transmission models to CMV antibody titer data to investigate the effect of reactivation on infectiousness.
Recommended citation: van Boven, M et al (2017). "Infectious reactivation of cytomegalovirus explaining age- and sex-specific patterns of seroprevalence." PLOS Computational Biology. 13(9): e1005719.
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Published in Scientific Reports, 2016
We investigate T-cell antigenic drift of influenza.
Recommended citation: Woolthuis, RG et al (2016). "Long-term adaptation of the influenza A virus by escaping cytotoxic T-cell recognition." Scientific Reports. 6: 33334.
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Published in PLOS Computational Biology, 2014
We use a multi-level model of HIV evolution to investigate the effect of within-host selection and host-heterogeneity on virulence evolution.
Recommended citation: van Dorp, CH. et al (2014). "Immuno-epidemiological Modeling of HIV-1 Predicts High Heritability of the Set-Point Virus Load, while Selection for CTL Escape Dominates Virulence Evolution." PLOS Computational Biology. 10(12): e1003899.
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