James D Munday, PhD

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Infectious disease epidemiology and surveillance, ETH Zürich but in Basel
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Interests

Epidemics have a profound impact on health and society, control measures can also severely disrupt daily life. Improving epidemic response requires better understanding of transmission and dynamics in various populations. In my research I principally focus on how spatial and social factors contribute to infectious disease dynamics and how these factors should be considered when responding to outbreaks. My current research activities include using mathematical and statistical models to improve situational awareness during epidemics through real-time analysis and understanding how infections spread between school-aged children in different contexts.

Contexts

Postdoctoral Researcher Department of Biosystems Science and Engineering (D-BSSE) ETH Zürich (2023 - Present)
Research Fellow Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine (2020 - 2022)
PhD Candidate Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine (2016 - 2020)

Pre-prints

  1. Quilty BJ, Chapman LAC, Munday JD, Wong KLM, Gimma A, Pickering S, et al. (2024) Disentangling the drivers of heterogeneity in SARS-CoV-2 transmission from data on viral load and daily contact rates. MedRxiv, 2024-08.
  2. Munday JD, Rosello A, Edmunds WJ, Funk S. (2024). Forecasting the spatial spread of an Ebola epidemic in real-time: comparing predictions of mathematical models and experts. MedRxiv, 2024-03.
  3. Funk S, Abbott S, Atkins BD, Baguelin M, … Munday JD, et al. (2020). Short-term forecasts to inform the response to the Covid-19 epidemic in the UK. MedRxiv, 2020-11.

Publications

  1. Munday JD, Atkins KE, Klinkenberg D, Meurs M, Fleur E, Hahné SJM, Wallinga J, van Hoek AJ. (2024). Estimating the risk and spatial spread of measles in populations with high MMR uptake: using school-household networks to understand the 2013-2014 outbreak in the Netherlands. PLoS medicine, 21(10), e1004466.
  2. Jarvis CI, Coletti P, Backer JA, Munday JD, Faes C, Beutels P, et al. (2024). Social contact patterns following the COVID-19 pandemic: a snapshot of post-pandemic behaviour from the CoMix study. Epidemics, 48, 100778.
  3. Munday JD, Abbott S, Meakin S, Funk S. (2023). Evaluating the use of social contact data to produce age-specific short-term forecasts of SARS-CoV-2 incidence in England. PLoS Computational Biology, 19(9), e1011453.
  4. van Iersel SCJL, Backer JA, van Gaalen RD, Andeweg SP, Munday JD, Wallinga J, van Hoek AJ, et al. (2023). Empirical evidence of transmission over a school-household network for SARS-CoV-2; exploration of transmission pairs stratified by primary and secondary school. Epidemics, 43, 100675.
  5. Meakin S, Abbott S, Bosse NI, Munday JD, Gruson H, Hellewell J, Sherratt K, Funk S. (2022). Comparative assessment of methods for short-term forecasts of COVID-19 hospital admissions in England at the local level. BMC Medicine, 20(1), 86.
  6. Gimma A, Munday JD, Wong KLM, Coletti P, van Zandvoort K, Prem K, CMMID COVID-19 working group, Klepac P, Rubin GJ, Funk S, et al. (2022). Changes in social contacts in England during the COVID-19 pandemic between March 2020 and March 2021 as measured by the CoMix survey: A repeated cross-sectional study. PLoS Medicine, 19(3), e1003907.
  7. Hargreaves JR, Langan SM, Oswald WE, Halliday KE, Sturgess J, Phelan J, … Munday JD, … et al. (2022). Epidemiology of SARS-CoV-2 infection among staff and students in a cohort of English primary and secondary schools during 2020-2021. The Lancet Regional Health–Europe, 21.
  8. Munday JD, Jarvis CI, Gimma A, Wong KLM, van Zandvoort K, Funk S, Edmunds WJ. (2021). Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data. BMC Medicine, 19, 1-13.
  9. Munday JD, Pebody R, Atkins KE, van Hoek AJ. (2021). Changing socio-economic and ethnic disparities in influenza/A/H1N1 infection early in the 2009 UK epidemic: a descriptive analysis. BMC Infectious Diseases, 21(1), 1243.
  10. Munday JD, Sherratt K, Meakin S, Endo A, Pearson CAB, Hellewell J, Abbott S, Bosse NI, Atkins KE, et al. (2021). Implications of the school-household network structure on SARS-CoV-2 transmission under school reopening strategies in England. Nature Communications, 12(1), 1942.
  11. Sherratt K, Abbott S, Meakin SR, Hellewell J, Munday JD, Bosse N, CMMID Covid-19 working group, Jit M, Funk S. (2021). Exploring surveillance data biases when estimating the reproduction number: with insights into subpopulation transmission of COVID-19 in England. Philosophical Transactions of the Royal Society B, 376(1829), 20200283.
  12. Davies NG, Munday JD, Abbott S, Barnard RC, Jarvis CI, Kucharski AJ, Pearson CAB, Russell TW, Tully DC, Washburne AD, et al. (2021). Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England. Science, 372(6538), eabg3055.
  13. Hellewell J, Abbott S, Gimma A, Bosse NI, Jarvis CI, Russell TW, Munday JD, Kucharski AJ, Edmunds WJ, Funk S, et al. (2020). Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. Lancet Glob Health, 8(4), e488-e496.
  14. Abbott S, Hellewell J, Munday JD, Funk S, CMMID nCoV working group, et al. (2020). The transmissibility of novel Coronavirus in the early stages of the 2019-20 outbreak in Wuhan: Exploring initial point-source exposure sizes and durations using scenario analysis. Wellcome Open Research, 5.
  15. Gostic KM, McGough L, Baskerville EB, Abbott S, Joshi K, Tedijanto C… Munday JD, et al. (2020). Practical considerations for measuring the effective reproductive number, R_t. PLoS Computational Biology, 16(12), e1008409.
  16. Abbott S, Hellewell J, Thompson RN, Sherratt K, Gibbs HP, Bosse NI, Munday JD, Meakin S, Doughty EL, Chun JY, et al. (2020). Estimating the time-varying reproduction number of SARS-CoV-2 using national and subnational case counts. Wellcome Open Research, 5(112), 112.
  17. Munday JD, van Hoek AJ, Edmunds WJ, Atkins KE. (2018). Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model. BMC Medicine, 16, 1-12.

Conferences

Past

  1. Forecasting the spatial spread of an Ebola epidemic in real-time: comparing predictions of mathematical models and experts (Oral Presentation) GEOMED2024, Hasselt, BE Slides
  2. Spatial modelling of viral loads in wastewater: an evaluation of sampling strategies for comprehensive surveillence programs (Oral Presentation) GEOMED2024, Hasselt, BE Slides
  3. Vaccine mediated time-varying school and household contact networks explain intervals between measles outbreaks in the Netherlands (Oral Presentation) NetSci2024 - International conference on network science, Quebec City, CA
  4. Evaluating the use of cross-sectional infection and antibody positivity with social contact data to produce age-specific forecasts of SARS-CoV-2 incidence (Oral Presentation) ECMTB 2022 - 12th European Conference on Mathematical and Theoretical Biology, Heidelberg, DE
  5. Reflections on using community data to evaluate the potential wider impact of school-based SARS-CoV-2 transmission (Oral presentation) Newton Gateway Institute for Mathematics (2022), Symposium: Controlling COVID-19 in Schools: Lessons Learned and Open Questions, Remote
  6. Implications of the school-household network structure on SARS-CoV-2 transmission under different school reopening strategies in England (Oral presentation) Networks 2021, Remote
  7. Who goes to school with whose sibling – Utilising national school data to study outbreaks (Oral presentation) IDDconf 2018: A Conference on Infectious Disease Dynamics, Ambleside, UK
  8. The Impaction of vaccination in inequalities in infectious disease (Poster) Epidemics: International Conference on Infectious Disease Dynamics 2017, Sitges, Spain
  9. Inequalities in infectious disease & vaccination (Oral presentation) IDDconf 2017: A Conference on Infectious Disease Dynamics, Ambleside, UK
  10. How does vaccination impact observable inequalities in infectious diseases? (Oral presentation) Public Health England, Research and Epidemiology Conference 2017, Warwick, UK

Posts

Summary of work using school-household network models

Summary of work on wastewater based epidemiology