What we do
The focus of the real-time outbreak analysis theme is the use of mathematical and statistical models and data to provide real-time insights into ongoing outbreaks, such as estimating key epidemiological parameters, making short-term forecasts and evaluating intervention strategies.
Theme members have contributed research to several outbreaks, including:
- the COVID-19 pandemic
- the 2018-20 Ebola outbreak in the Democratic Republic of the Congo
- the ongoing cholera outbreak in Yemen
Research is done in collaboration with partners such as the WHO, the European Centre for Disease Prevention and Control (ECDC), Médecins sans Frontières (MSF) and the UK Public Health Rapid Support Team, which is jointly run by Public Health England and LSHTM.
Members of the theme meet on a monthly basis on the first Thursday of the month, 2:00pm - 3:00pm UK time. All interested are welcome to attend. Contact the theme coordinators Sophie Meakin and James Munday for details.
Papers and other outputs are shared through the CMMID Twitter feed.
Real-time analysis theme members have contributed to many aspects of real-time outbreak analysis, including journal papers, data curation and software development. Below are a selection of these outputs:
- European Covid-19 Forecast Hub, coordinated in collaboration with the European Centre for Disease Control (ECDC).
- Davies, Nicholas G., Sam Abbott, Rosanna C. Barnard, Christopher I. Jarvis, Adam J. Kucharski, James D. Munday, Carl AB Pearson et al. Estimated transmissibility and impact of SARS-CoV-2 lineage B. 1.1. 7 in England. Science 372, no. 6538 (2021).
- Palmer, J., Sherratt, K., Martin-Nielsen, R., Bevan, J., Gibbs, H., Funk, S., Abbott, S. and CMMID COVID-19 Working Group, 2021. covidregionaldata: Subnational data for COVID-19 epidemiology. Journal of Open Source Software, 6(63), p.3290.
- Quilty, Billy J., Samuel Clifford, Joel Hellewell, Timothy W. Russell, Adam J. Kucharski, Stefan Flasche, W. John Edmunds et al. Quarantine and testing strategies in contact tracing for SARS-CoV-2: a modelling study. The Lancet Public Health 6, no. 3 (2021): e175-e183.
- Munday, J.D., Jarvis, C.I., Gimma, A. et al. Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data. BMC Med 19, 233 (2021).
- Endo, A., Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Leclerc, Q. J., Knight, G. M., Medley, G. F., Atkins, K. E., Funk, S., & Kucharski, A. J. (2021). Implication of backward contact tracing in the presence of overdispersed transmission in COVID-19 outbreaks. Wellcome open research, 5, 239.
- Camacho, A., Bouhenia, M., Alyusfi, R., Alkohlani, A., Naji, M.A.M., de Radiguès, X., Abubakar, A.M., Almoalmi, A., Seguin, C., Sagrado, M.J. and Poncin, M., 2018. Cholera epidemic in Yemen, 2016–18: an analysis of surveillance data. The Lancet Global Health, 6(6), pp.e680-e690.
- Finger, F., Funk, S., White, K., Siddiqui, R., Edmunds, W.J. and Kucharski, A.J., 2018. Real-time analysis of the diphtheria outbreak in forcibly displaced Myanmar nationals in Bangladesh. bioRxiv, p.388645.