Sam Brand
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Samuel P. C. BrandPost-doctoral Research Assistant Email: S.Brand@warwick.ac.uk |
Background: I studied mathematics at King's College, University of London leaving in 2006 with a Bsc in Mathematics and a Msc in "Information processing and Neural Networks". I completed the 3+1 year Msc and Phd programme at the Complexity Science centre, University of Warwick, between 2008 and 2012 finishing with a Msc and Phd in Complexity science. My thesis title was "Spatial and stochastic epidemics: Theory, simulation and control". Since 2012 I have been a post-doctoral researcher at the University of Warwick.
Research interests: My current focus is on transmission pathways for respiratory viruses in low- and middle- income countries, mainly respiratory syncytial virus (RSV) and SARS-CoV-2. My wider interests include: the phylodynamics of respiratory viruses, diseases of livestock (in particular Bluetongue virus; BTV), vector-borne diseases with climatic forcing (in particular the European spread of BTV), optimal vaccination in reaction to a developing epidemic, efficient simulation of large stochastic and spatial models of epidemics, household-structured epidemic models, inferring latent variables within epidemic models, and moment closure for epidemic models.
Research methodology and software packages: Efficient ODE solvers (Julia/DifferentialEquations, Sundials/CVODE), BEAST2/phydyn, stochastic process modelling, reinforcement learning coupled to epidemic models, classical/Bayesian likelihood-based inference, regression methods for capture data, machine-learning techniques (e.g. MDS, neural networks etc).
I have a wide range of interests in mathematical epidemiology, encompassing both theoretical aspects such as moment closure, and, highly applied research question such as determining how household-structured transmission models affect estimates of maternally derived protection to respiratory syncytial virus (RSV). My current focus is on forecasting the impact of SARS-CoV-2 transmission, leading to COVID-19 disease, in East Africa as part of the COVID-19 Intervention modelling for East Africa project (CIMEA; https://wellcome.org/grant-funding/people-and-projects/grants-awarded/covid-19-intervention-modelling-east-africa-cimea).
I currently work as a PDRA (PI: D. James Nokes) modelling the spread of respiratory viruses at different spatial scales, from household to countrywide, in Kenya, with a focus on potentially effective vaccination policies. This work forms part of the Application of Genomics and Modelling to the Control of Virus Pathogens (Gemvi, https://kemri-wellcome.org/gemvi/) project.
The respiratory transmission pathways in Kenya are inferred from a mixture of hospitalisation data, and, extensive genomic surveillance data. Therefore, my interests include both 'classical' inference for epidemic models and phylodynamic inference, based on the coalescent rates of inferred viral phylogenies.
Previously, I have worked on modelling the emergence of novel infections amongst European livestock herds (Animal health and welfare ERA-NET project LIVEepi). As part of this project I developed methods for integrating large-scale climate datasets, extensive vector field capturing and mechanistic epidemic models. This elucidates both the current true risk of epizootic invasion amongst European livestocks, and the potential risk in the future as the European climate changes.
Relevant recent publications:
M Otiende, ..., SPC Brand, ..., JAG Scott. The impact of Covid-19 on mortality in coastal Kenya: a longitudinal open cohort study. Medrxiv. 2022. https://www.medrxiv.org/content/10.1101/2022.10.12.22281019v1
SPC Brand et al. The role of vaccinations and public awareness in medium-term forecasts of monkeypox incidence in the United Kingdom. Medrxiv. 2022.
Joe Hilton, ..., Sam Brand,..., Thomas House, et al. A computational framework for modelling infectious disease policy based on age and household structure with applications to the COVID-19 pandemic. Accepted at PLoS Computational Biology. (2022).
S. P. C. Brand et al., COVID-19 transmission dynamics underlying epidemic waves in Kenya. Science, eabk0414 (2021).
Parisi A, Brand SPC, Hilton J, Aziza R, Keeling MJ, Nokes DJ, Spatially resolved simulations of the spread of COVID-19 in three European countries. PLoS Computational Biology. 17, e1009090 (2021).
Ojal J., and, Brand S. P. C., et al, Revealing the extent of the first wave of the COVID-19 pandemic in Kenya based on serological and PCR-test data. Wellcome Open Research (2021).
Mohlmann TWR, Keeling MJ, Wennergren U, Flavia G, Santman-Berends I, Takken W, Koenraadt CJM, Brand SPC. Biting midge dynamics and bluetongue transmission: A multiscale model linking catch data with climate and disease outbreaks. Nature Scientific Reports. 11:1892. 2021.
Brand, S.P., Munywoki, P., Walumbe, D., Keeling, M.J. and Nokes, D.J., Reducing RSV hospitalisation in a lower-income country by vaccinating mothers-to-be and their households. Elife, 9, p.e47003. 2020.
Tildesley MJ, Brand S, Brooks Pollock E, Bradbury NV, Werkman M, Keeling MJ. The role of movement restrictions in limiting the economic impact of livestock infections. Nature Sustainability. 2019.
Mahamat MH, ..., Brand SPC, et al. Adding tsetse control to medical activities contributes to decreasing transmission of sleeping sickness in the Mandoul focus (Chad). PLoS neglected tropical diseases. Jul 27;11(7):e0005792–16. 2017
Brand SPC, Keeling MJ. The impact of temperature changes on vector-borne disease transmission: Culicoides midges and bluetongue virus. Journal of the Royal Society Interface. 14(128):20160481–13. 2017.
Rock K, Brand S, Moir J, Keeling MJ. Dynamics of infectious diseases. Reports on progress in physics. 77(2):026602. 2014.
Github repository: https://github.com/SamuelBrand1/ Feel free to contact me and get involved on any of my open repos. I've transitioned to pretty much 100% using Julia. Anyone who wants to join me in thinking about the best way to code up epidemic models in Julia get in touch!