Joshua Blake

Joshua Blake

Epidemiological and statistical modelling of the COVID-19 pandemic

Joshua Blake - PhD student at MRC Biostatistics Unit

Hi there! I am a final-year PhD student at the MRC Biostatistics Unit, University of Cambridge. My research focuses on how to best use the ONS’s Coronavirus Infection Survey (CIS) to monitor the COVID-19 pandemic in the UK. This is an exciting dataset to work with because it contains a representative sample of the UK population, removing many of the concerns around bias present in most data relating to the pandemic.

More broadly, I am interested in understanding the most cost-effective ways to tackle novel and endemic infectious diseases. I am always excited to hear about new ideas and interventions in this space, so please do get in touch if you have any (see the sidebar for my details)!

During the pandemic I was a member of SPI-M-O, the infectious disease modelling and epidemiology subgroup of the UK Government’s SAGE. Much of the work I did was publicly available, and widely covered in the media. I also implemented the method for estimating incidence adopted by the Office for National statistics.

My supervisors are Daniela De Angelis and Paul Birrell (who is primarily based at UKHSA), and I am funded by Bayes4Health.

I also blog about a variety of things I find interesting but often not directly related to my research.

Publications

  • Dietz, E, …, Blake J et al. SARS-CoV-2, influenza A/B and respiratory syncytial virus positivity and association with influenza-like illness and self-reported symptoms, over the 2022/23 winter season in the UK: a longitudinal surveillance cohort. medRxiv, 2023.
  • Swallow B, Birrell P, Blake J, et al. Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling. Epidemics, 2022. Authors after first in alphabetical order.
  • Pellis L, Birrell PJ, Blake J, et al. Estimation of reproduction numbers in real time: conceptual and statistical challenges. Journal of the Royal Statistical Society: Series A, 2022.
  • Nyberg T, Ferguson NM, Blake J, et al. Misclassification bias in estimating clinical severity of SARS-CoV-2 variants – Authors’ reply. The Lancet, 2022.
  • Birrell P, Blake J, van Leeuwen E, et al. Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave. Phil Trans R Soc B, 2021.
  • Funk S, …, Blake J, et al. Short-term forecasts to inform the response to the Covid-19 epidemic in the UK. medRxiv; 2020. Authors after first in alphabetical order.

Talks

  • “Introducing base rate forecasting” at Meridian retreat, Apr 2024 (slides)
  • “Estimating SARS-CoV-2 transmission from a representative prevalence survey: progress and challenges” at IDD Conf 2023, Sep 2023 (slides, pptx).
  • “False negative SARS-CoV-2 PCR results in the Coronavirus Infection Survey (CIS)” at Cambridge Infectious Diseases early career researchers’ symposium, Dec 2022.
  • “Duration of PCR positivity for SARS-CoV-2: the key to unbiased incidence estimation” at Armitage week PhD talks, MRC Biostatistics Unit, University of Cambridge, Sep 2022.
  • “Estimating incidence from CIS real-time data” at ONS Covid-19 Infection Survey Analysis Team Meeting, Feb 2022.
  • “Real-time modelling of a pandemic” at First-year upgrade talks, MRC Biostatistics Unit, University of Cambridge, Apr 2021.

Posters

  • “Bayesian combination of longitudinal studies to estimate the duration of SARS-CoV-2 PCR positivity in the general population” at Bayesian Inference of Epidemics (satellite event to Bayes Comp 2023 conference), Mar 2023, and Cambridge Infectious Diseases annual symposium, Apr 2023.
  • “Estimating incidence of SARS-CoV-2 infections from the UK Coronavirus Infection Survey (CIS) real-time prevalence data” at PhD student symposium, MRC Biostatistics Unit, University of Cambridge, Dec 2022, and Epidemic8 conference, Dec 2021.