This theme provides a space for the exploration of ideas for efficient computation, to learn new methodologies for inference and to share knowledge across CMMID.
In the CMMID we use mathematical and statistical tools to understand the dynamics and control of infection. Members use methods of inference to inform data based decisions which can account for large and/or complex data, models and questions. In addition, to deal with these complexities, there is a need for efficient computation.
From methods to account for partial observation of cases and uncertainty in confirmation of cases, to tools for creating fast and reproducible code, challenges arise in both computation and inference that are common to many infectious disease research questions.
People
Danny Scarponi and Sam Abbott (theme leads), Katherine Atkins, Marc Baguelin, Lloyd Chapman, Sam Clifford, Nick Davies, Roz Eggo, Jon Emery, Akira Endo, Flavio Finger, Stefan Flasche, Seb Funk, Liza Hadley, Alasdair Henderson, Chris Jarvis, Petra Klepac, Gwen Knight, Adam Kucharski, Yang Liu, Nicky McCreesh, Hannah Meredith, James Munday, Amy Pinsent, Billy Quilty, Kathleen O’Reilly, Alexis Robert, Tom Sumner, Moritz Wagner, Naomi R Waterlow, Nayantara Wijayanandana, Kevin van Zandvoort.
Upcoming events
On 8 December 2022, Durham University is hosting a two-day online workshop on the calibration of deterministic and stochastic infectious disease models using history matching with emulation and the R package hmer.
We are also looking for speakers to lead sessions on Statistical Inference.
If interested, please contact Danny Scarponi.
Publications
- Chatzilena A,, van Leeuwen E., Ratmann O., Baguelin M., Demiris, N. (2019). Contemporary statistical inference for infectious disease models using Stan. https://arxiv.org/abs/1903.00423
- Chapman LAC, Jewell CP, Spencer SEF, Pellis L, Datta S, et al. (2018) The role of case proximity in transmission of visceral leishmaniasis in a highly endemic village in Bangladesh. PLOS Neglected Tropical Diseases 12(10): e0006453. https://doi.org/10.1371/journal.pntd.0006453
- O’Reilly KM, Cori A, Durry E, Wadood MZ, Bosan A, Aylward RB, et al. (2015) A new method to estimate the coverage of mass vaccination campaigns against poliomyelitis from surveillance data. https://doi.org/10.1093/aje/kwv199
- Kucharski AJ, Edmunds WJ (2015) Characterizing the transmission potential of zoonotic infections from minor outbreaks. PLOS Comput Biol 11(4):e1004154
- Kucharski AJ, Lessler J, Read JM, Zhu H, Jiang CQ et al. (2015) Estimating the life course of influenza A(H3N2) antibody responses from cross-sectional data. PLOS Biol 13(3):e1002082
- Kucharski AJ, Mills HL, Pinsent A, Fraser C, Van Kerkhove MD et al. (2014) Distinguishing between reservoir exposure and human-to-human transmission for emerging pathogens using case onset data. PLOS Curr. 7:6