Bristol team emphasises the need for testing random samples of the population to establish disease prevalence and properly measure the size of the epidemic and disease severity. The comment on a paper by Verity et al. (2020) from the Imperial College infectious diseases modelling team will appear in Lancet Infectious Diseases. It is written by […]
Archive | May, 2020
Virtual Open Day
Twitter: https://twitter.com/BristolUniMaths Graduation: https://www.youtube.com/watch?v=uI2CcM8QlrE&list=PLFZ6Q-G4wIXBDpwV9FWK-wVbSeKJZhdkt&index=7&t=0s Studying at Bristol: https://www.youtube.com/watch?v=GybNpY6C_aY&t=3s
UK Covid-19 infection peak may have fallen before lockdown, new analysis shows
Simple statistical models can reliably infer the peak of infections and subsequent deaths from the virus, according to a Bristol statistician. Professor Simon Wood used simple models with few assumptions, together with Imperial College’s estimate of the distribution of times from disease onset to death for fatal cases, to infer the time course of fatal infections […]
Population density as experienced by the average person better explains variations in the rate of spread of COVID-19
A preprint by a team including Bristol statistician Professor Oliver Johnson shows the importance of ‘lived population density’ as a measure to track the spread of the disease The preprint demonstrates that population density is important in the spread of COVID-19, but that non-standard ways of measuring density do a better job of explaining it […]
