Global.health

Global.health: Epidemiological data platform for tracking infectious diseases

 

Global.health

 

Global.health is an epidemiological platform established during the COVID-19 pandemic to provide open access to de-identified line list case data, facilitating research into infectious diseases and emerging outbreaks. The platform’s primary mission is to deliver timely and accurate data to decision-makers, researchers, and the public during the critical first 100 days of an outbreak. The development of the platform was a global collaboration involving researchers from Oxford, Harvard, Northeastern, The Gorgas Institute, Boston Children’s Hospital, Georgetown, the University of Washington, and the Johns Hopkins Center for Health Security.

The OxRSE group has been involved from the outset, contributing to architecture planning and software development alongside the initial team from Google.org. They have also trained students in processing automated data sources and have overseen the ongoing development and expansion of the platform to address outbreaks such as Mpox, Ebola, and Marburg. Currently, four OxRSE staff members are actively working on the Global.health platform, engaging in a range of projects, including graphical analytical pipeline development, the creation of clinical and multimodal data pipelines that incorporate meteorological and mobility data, the application of large language models for structured data extraction and epidemiological use cases and developing clinical data pipelines. OxRSE staff have made significant contributions across all aspects of the platform, from frontend development in TypeScript to backend development, data pipelines with Python, and infrastructure provisioning using MongoDB, AWS services, Kubernetes, and Terraform.

 

Website: https://global.health

 

RSEs: Abhishek Dasgupta, John Brittain, Pip Liggins, Alasdair Wilson

 

Collaborators: Prof. Moritz Kraemer, Department of Biology

 

Funder: Google.org, Oxford Martin School, Rockefeller, Wellcome Trust

 

Public Repos:

 

Publications:

  • 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

 

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