Publications

This page contains a list of research articles published by members of the Oxford RSE team, grouped by project.

Chaste

• Cooper, F., Baker, R., Bernabeu, M., Bordas, R., Bowler, L., Bueno-Orovio, A., Byrne, H., Carapella, V., Cardone-Noott, L., Cooper, J., Dutta, S., Evans, B., Fletcher, A., Grogan, J., Guo, W., Harvey, D., Hendrix, M., Kay, D., Kursawe, J., … Gavaghan, D. (2020). Chaste: Cancer, Heart and Soft Tissue Environment. Journal of Open Source Software, 5(47), 1848. https://doi.org/10.21105/joss.01848

Global.health

• Kraemer, M. U. G., Tsui, J. L.-H., Chang, S. Y., Lytras, S., Khurana, M. P., Vanderslott, S., Bajaj, S., Scheidwasser, N., Curran-Sebastian, J. L., Semenova, E., Zhang, M., Unwin, H. J. T., Watson, O. J., Mills, C., Dasgupta, A., Ferretti, L., Scarpino, S. V., Koua, E., Morgan, O., … Bhatt, S. (2025). Artificial intelligence for modelling infectious disease epidemics. Nature, 638(8051), 623–635. https://doi.org/10.1038/s41586-024-08564-w

• Tsui, J. L.-H., Pena, R. E., Moir, M., Inward, R. P. D., Wilkinson, E., San, J. E., Poongavanan, J., Bajaj, S., Gutierrez, B., Dasgupta, A., de Oliveira, T., Kraemer, M. U. G., Tegally, H., & Sambaturu, P. (2024). Impacts of climate change-related human migration on infectious diseases. Nature Climate Change, 14(8), 793–802. https://doi.org/10.1038/s41558-024-02078-z

• Gonçalves, B. P., Jassat, W., Baruch, J., Hashmi, M., Rojek, A., Dasgupta, A., Martin-Loeches, I., Reyes, L. F., Piubelli, C., Citarella, B. W., Kartsonaki, C., Lefèvre, B., López Revilla, J. W., Lunn, M., Harrison, E. M., Kraemer, M. U. G., Shrapnel, S., Horby, P., Bisoffi, Z., … Zambon, M. (2023). A multi-country analysis of COVID-19 hospitalizations by vaccination status. Med, 4(11), 797-812.e2. https://doi.org/10.1016/j.medj.2023.08.005

• Tsui, J. L.-H., McCrone, J. T., Lambert, B., Bajaj, S., Inward, R. P. D., Bosetti, P., Pena, R. E., Tegally, H., Hill, V., Zarebski, A. E., Peacock, T. P., Liu, L., Wu, N., Davis, M., Bogoch, I. I., Khan, K., Kall, M., Abdul Aziz, N. I. B., Colquhoun, R., … Kraemer, M. U. G. (2023). Genomic assessment of invasion dynamics of SARS-CoV-2 Omicron BA.1. Science, 381(6655), 336–343. https://doi.org/10.1126/science.adg6605

• Schultheiss, M., Han, A., Varrelman, T., Sewalk, K., Dasgupta, A., Sheldon, J., Pigott, D., Zarzeczny, M., Brownstein, J., & Kraemer, M. (2023). GLOBAL HEALTH: AN AGILE OPEN-SOURCE REPOSITORY OF INFECTIOUS DISEASE OUTBREAKS TO SUPPORT GLOBAL SURVEILLANCE AND RESEARCH EFFORTS. International Journal of Infectious Diseases, 130, S77. https://doi.org/10.1016/j.ijid.2023.04.191

• Inward, R. P. D., Jackson, F., Dasgupta, A., Lee, G., Battle, A. L., Parag, K. V., & Kraemer, M. U. G. (2022). Impact of spatiotemporal heterogeneity in COVID-19 disease surveillance on epidemiological parameters and case growth rates. Epidemics, 41, 100627. https://doi.org/10.1016/j.epidem.2022.100627

• Gonçalves, B. P., Hall, M., Jassat, W., Balan, V., Murthy, S., Kartsonaki, C., Semple, M. G., Rojek, A., Baruch, J., Reyes, L. F., Dasgupta, A., Dunning, J., Citarella, B. W., Pritchard, M., Martín-Quiros, A., Sili, U., Baillie, J. K., Aryal, D., Arabi, Y., … Olliaro, P. L. (2022). An international observational study to assess the impact of the Omicron variant emergence on the clinical epidemiology of COVID-19 in hospitalised patients. eLife, 11. https://doi.org/10.7554/elife.80556

• Kraemer, M. U. G., Tegally, H., Pigott, D. M., Dasgupta, A., Sheldon, J., Wilkinson, E., Schultheiss, M., Han, A., Oglia, M., Marks, S., Kanner, J., O’Brien, K., Dandamudi, S., Rader, B., Sewalk, K., Bento, A. I., Scarpino, S. V., de Oliveira, T., Bogoch, I. I., … Brownstein, J. S. (2022). Tracking the 2022 monkeypox outbreak with epidemiological data in real-time. The Lancet Infectious Diseases, 22(7), 941–942. https://doi.org/10.1016/s1473-3099(22)00359-0

• Kraemer, M. U. G., Scarpino, S. V., Marivate, V., Gutierrez, B., Xu, B., Lee, G., Hawkins, J. B., Rivers, C., Pigott, D. M., Katz, R., & Brownstein, J. S. (2021). Data curation during a pandemic and lessons learned from COVID-19. Nature Computational Science, 1(1), 9–10. https://doi.org/10.1038/s43588-020-00015-6

• Brittain, J.-S., Tsui, J., Inward, R., Gutierrez, B., Mwanyika, G., Tegally, H., Huynh, T., Githinji, G., Tessema, S. K., McCrone, J. T., Bhatt, S., Dasgupta, A., Ratcliffe, S., & Kraemer, M. U. G. (2025). GRAPEVNE - Graphical Analytical Pipeline Development Environment for Infectious Diseases. Wellcome Open Research, 10, 279. https://doi.org/10.12688/wellcomeopenres.23824.1

LanguageScreen

• Hulme, C., West, G., Rios Diaz, M., Hearne, S., Korell, C., Duta, M., & Snowling, M. J. (2025). The Nuffield Early Language Intervention (NELI) programme is associated with lasting improvements in children’s language and reading skills. Journal of Child Psychology and Psychiatry. https://doi.org/10.1111/jcpp.14157

• West, G., Lervåg, A., Birchenough, J. M. H., Korell, C., Rios Diaz, M., Duta, M., Cripps, D., Gardner, R., Fairhurst, C., & Hulme, C. (2024). Oral language enrichment in preschool improves children’s language skills: a cluster randomised controlled trial. Journal of Child Psychology and Psychiatry, 65(8), 1087–1097. https://doi.org/10.1111/jcpp.13947

• Hulme, C., McGrane, J., Duta, M., West, G., Cripps, D., Dasgupta, A., Hearne, S., Gardner, R., & Snowling, M. (2024). LanguageScreen: The Development, Validation, and Standardization of an Automated Language Assessment App. Language, Speech, and Hearing Services in Schools, 55(3), 904–917. https://doi.org/10.1044/2024_lshss-24-00004

• West, G., Lervåg, A., Snowling, M. J., Buchanan-Worster, E., Duta, M., & Hulme, C. (2022). Early language intervention improves behavioral adjustment in school: Evidence from a cluster randomized trial. Journal of School Psychology, 92, 334–345. https://doi.org/10.1016/j.jsp.2022.04.006

OCSPlus

• Demeyere, N., Haupt, M., Webb, S. S., Strobel, L., Milosevich, E. T., Moore, M. J., Wright, H., Finke, K., & Duta, M. D. (2021). Introducing the tablet-based Oxford Cognitive Screen-Plus (OCS-Plus) as an assessment tool for subtle cognitive impairments. Scientific Reports, 11(1). https://doi.org/10.1038/s41598-021-87287-8

• Humphreys, G. W., Duta, M. D., Montana, L., Demeyere, N., McCrory, C., Rohr, J., Kahn, K., Tollman, S., & Berkman, L. (2016). Cognitive Function in Low-Income and Low-Literacy Settings: Validation of the Tablet-Based Oxford Cognitive Screen in the Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa (HAALSI). The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 72(1), 38–50. https://doi.org/10.1093/geronb/gbw139

• Webb, S. S., Jespersen, A., Chiu, E. G., Payne, F., Basting, R., Duta, M. D., & Demeyere, N. (2021). The Oxford digital multiple errands test (OxMET): Validation of a simplified computer tablet based multiple errands test. Neuropsychological Rehabilitation, 32(6), 1007–1032. https://doi.org/10.1080/09602011.2020.1862679

OxMET

• Webb, S. S., Jespersen, A., Chiu, E. G., Payne, F., Basting, R., Duta, M. D., & Demeyere, N. (2021). The Oxford digital multiple errands test (OxMET): Validation of a simplified computer tablet based multiple errands test. Neuropsychological Rehabilitation, 32(6), 1007–1032. https://doi.org/10.1080/09602011.2020.1862679

PDQ

• Benedikt, M., Cooper, F., Germano, S., Gyorkei, G., Tsamoura, E., Moore, B., & Ortiz, C. (2023). PDQ 2.0. ACM SIGMOD Record, 51(4), 36–41. https://doi.org/10.1145/3582302.3582308

POSEIDON

• Carrella, E., Powers, J., Saul, S., Bailey, R. M., Payette, N., Vert-pre, K. A., Ananthanarayanan, A., Drexler, M., Dorsett, C., & Madsen, J. K. (2024). Rejection sampling and agent-based models for data limited fisheries. Frontiers in Marine Science, 11. https://doi.org/10.3389/fmars.2024.1243954

• Madsen, J. K., Powers, B., Bailey, R., Carrella, E., Payette, N., & Pilditch, T. (2024). Modelling Adaptive and Anticipatory Human Decision-Making in Complex Human-Environment Systems. Journal of Artificial Societies and Social Simulation, 27(1). https://doi.org/10.18564/jasss.5214

• Payette, N., Carella, E., Vert-Pre, K., Powers, B., Saul, S., Drexler, M., Ananthanarayanan, A., & Bailey, R. (2023). Attracted to Fish: A Gravity-Based Model of Purse-Seine Vessel Behaviour. In Springer Proceedings in Complexity (pp. 87–103). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-34920-1_8

PalamaraLab

• Nait Saada, J., Kalantzis, G., Shyr, D., Cooper, F., Robinson, M., Gusev, A., & Palamara, P. F. (2020). Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations. Nature Communications, 11(1). https://doi.org/10.1038/s41467-020-19588-x

• Zhang, B. C., Biddanda, A., Gunnarsson, Á. F., Cooper, F., & Palamara, P. F. (2023). Biobank-scale inference of ancestral recombination graphs enables genealogical analysis of complex traits. Nature Genetics, 55(5), 768–776. https://doi.org/10.1038/s41588-023-01379-x

• Loya, H., Kalantzis, G., Cooper, F., & Palamara, P. F. (2025). A scalable variational inference approach for increased mixed-model association power. Nature Genetics, 57(2), 461–468. https://doi.org/10.1038/s41588-024-02044-7

Petrushka

• Ostinelli, E. G., Jaquiery, M., Liu, Q., Elgarf, R., Haque, N., Potts, J., Li, Z., Efthimiou, O., Markham, S., Ede, R., Wainwright, L., Fernandes, K. B. P., Fernandes, B. B. P., Dalaqua, P. V. C., Tomlinson, A., Smith, K. A., Zangani, C., De Crescenzo, F., Liboni, M., … Cipriani, A. (2025). Personalising Antidepressant Treatment for Unipolar Depression Combining Individual Choices, Risks and big Data: The PETRUSHKA Tool: Personnalisation du traitement antidépresseur de la dépression unipolaire associant choix individuels, risques et mégadonnées: l’outil PETRUSHKA. The Canadian Journal of Psychiatry. https://doi.org/10.1177/07067437251322399

PyBAMM

• Sulzer, V., Marquis, S. G., Timms, R., Robinson, M., & Chapman, S. J. (2021). Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1), 14. https://doi.org/10.5334/jors.309

• Planden, B., Courtier, N. E., Robinson, M., Khetarpal, A., Planella, F. B., & Howey, D. A. (2024). PyBOP: A Python package for battery model optimisation and parameterisation (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2412.15859

Research Software Engineering

• Hettrick, S., Bast, R., Crouch, S., Wyatt, C., Philippe, O., Botzki, A., Carver, J., Cosden, I., D’Andrea, F., Dasgupta, A., Godoy, W., Gonzalez-Beltran, A., Hamster, U., Henwood, S., Holmvall, P., Janosch, S., Lestang, T., May, N., Philips, J., … Zhang, Q. (2022). International RSE Survey 2022 (v0.9.3) [Computer software]. Zenodo. https://doi.org/10.5281/ZENODO.7015772

• Lee, G., Bacon, S., Bush, I., Fortunato, L., Gavaghan, D., Lestang, T., Morton, C., Robinson, M., Rocca-Serra, P., Sansone, S.-A., & Webb, H. (2021). Barely sufficient practices in scientific computing. Patterns, 2(2), 100206. https://doi.org/10.1016/j.patter.2021.100206