Outputs (8)

A mixed-method approach to determining contact matrices in the Cox’s Bazar refugee settlement (2023)
Journal Article
Walker, J., Aylett-Bullock, J., Shi, D., Kahindo Maina, A. G., Samir Evers, E., Harlass, S., & Krauss, F. (2023). A mixed-method approach to determining contact matrices in the Cox’s Bazar refugee settlement. Royal Society Open Science, 10(12), Article 231066. https://doi.org/10.1098/rsos.231066

Contact matrices are an important ingredient in age-structured epidemic models to inform the simulated spread of the disease between subgroups of the population. These matrices are generally derived using resource-intensive diary-based surveys and fe... Read More about A mixed-method approach to determining contact matrices in the Cox’s Bazar refugee settlement.

Bayesian Emulation and History Matching of JUNE (2022)
Journal Article
Vernon, I., Owen, J., Aylett-Bullock, J., Cuestra-Lazaro, C., Frawley, J., Quera-Bofarull, A., Sedgewick, A., Shi, D., Truong, H., Turner, M., Walker, J., Caulfield, T., Fong, K., & Krauss, F. (2022). Bayesian Emulation and History Matching of JUNE. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 380(2233), Article 20220039. https://doi.org/10.1098/rsta.2022.0039

We analyse JUNE: a detailed model of Covid-19 transmission with high spatial and demographic resolution, developed as part of the RAMP initiative. JUNE requires substantial computational resources to evaluate, making model calibration and general unc... Read More about Bayesian Emulation and History Matching of JUNE.

Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward (2022)
Journal Article
Aylett-Bullock, J., Gilman, R. T., Hall, I., Kennedy, D., Evers, E. S., Katta, A., Ahmed, H., Fong, K., Adib, K., Al Ariqi, L., Ardalan, A., Nabeth, P., von Harbou, K., Hoffmann Pham, K., Cuesta-Lazaro, C., Quera-Bofarull, A., Gidraf Kahindo Maina, A., Valentijn, T., Harlass, S., Krauss, F., …Luengo-Oroz, M. (2022). Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward. BMJ Global Health, 7(3), Article e007822. https://doi.org/10.1136/bmjgh-2021-007822

The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world’s most vulnerable populations at risk. Epidemiological modelling i... Read More about Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward.

Operational response simulation tool for epidemics within refugee and IDP settlements: A scenario-based case study of the Cox’s Bazar settlement (2021)
Journal Article
Aylett-Bullock, J., Cuesta-Lazaro, C., Quera-Bofarull, A., Katta, A., Hoffmann Pham, K., Hoover, B., Strobelt, H., Moreno Jimenez, R., Sedgewick, A., Samir Evers, E., Kennedy, D., Harlass, S., Gidraf Kahindo Maina, A., Hussien, A., & Luengo-Oroz, M. (2021). Operational response simulation tool for epidemics within refugee and IDP settlements: A scenario-based case study of the Cox’s Bazar settlement. PLoS Computational Biology, 17(10), https://doi.org/10.1371/journal.pcbi.1009360

The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world’s most vulnerable populations most affected. Given their density a... Read More about Operational response simulation tool for epidemics within refugee and IDP settlements: A scenario-based case study of the Cox’s Bazar settlement.

Optimising simulations for diphoton production at hadron colliders using amplitude neural networks (2021)
Journal Article
Aylett-Bullock, J., Badger, S., & Moodie, R. (2021). Optimising simulations for diphoton production at hadron colliders using amplitude neural networks. Journal of High Energy Physics, 2021(8), https://doi.org/10.1007/jhep08%282021%29066

Machine learning technology has the potential to dramatically optimise event generation and simulations. We continue to investigate the use of neural networks to approximate matrix elements for high-multiplicity scattering processes. We focus on the... Read More about Optimising simulations for diphoton production at hadron colliders using amplitude neural networks.

JUNE: open-source individual-based epidemiology simulation (2021)
Journal Article
Aylett-Bullock, J., Cuesta-Lazaro, C., Quera-Bofarull, A., Icaza-Lizaola, M., Sedgewick, A., Truong, H., Curran, A., Elliott, E., Caulfield, T., Fong, K., Vernon, I., Williams, J., Bower, R., & Krauss, F. (2021). JUNE: open-source individual-based epidemiology simulation. Royal Society Open Science, 8(7), https://doi.org/10.1098/rsos.210506

We introduce June, an open-source framework for the detailed simulation of epidemics on the basis of social interactions in a virtual population constructed from geographically granular census data, reflecting age, sex, ethnicity and socio-economic i... Read More about JUNE: open-source individual-based epidemiology simulation.

Fully Convolutional Neural Network for Rapid Flood Segmentation in Synthetic Aperture Radar Imagery (2020)
Journal Article
Nemni, E., Bullock, J., Belabbes, S., & Bromley, L. (2020). Fully Convolutional Neural Network for Rapid Flood Segmentation in Synthetic Aperture Radar Imagery. Remote Sensing, 12(16), Article 2532. https://doi.org/10.3390/rs12162532

Rapid response to natural hazards, such as floods, is essential to mitigate loss of life and the reduction of suffering. For emergency response teams, access to timely and accurate data is essential. Satellite imagery offers a rich source of informat... Read More about Fully Convolutional Neural Network for Rapid Flood Segmentation in Synthetic Aperture Radar Imagery.

Using neural networks for efficient evaluation of high multiplicity scattering amplitudes (2020)
Journal Article
Badger, S., & Bullock, J. (2020). Using neural networks for efficient evaluation of high multiplicity scattering amplitudes. Journal of High Energy Physics, 2020(6), Article 114. https://doi.org/10.1007/jhep06%282020%29114

Precision theoretical predictions for high multiplicity scattering rely on the evaluation of increasingly complicated scattering amplitudes which come with an extremely high CPU cost. For state-of-the-art processes this can cause technical bottleneck... Read More about Using neural networks for efficient evaluation of high multiplicity scattering amplitudes.