Sam Abbott

Sam Abbott is an Assistant Professor in Infectious Disease Epidemiology and Dynamics at the London School of Hygiene and Tropical Medicine (LSHTM), where he is based in the Epiforecasts group. He also holds concurrent appointments as a Research Fellow at LSHTM (January 2020-present) and as a Research Associate at SACEMA in South Africa (December 2021-present). Prior to his current academic position, he worked as a Data Scientist at Funding Circle (2017-2019) and completed his PhD at the University of Bristol.

His educational background includes:

• PhD in Epidemiology from the University of Bristol (2015-2019)
• MSc in Advanced Mathematical Biology from the University of York (2014-2015)
• MMath in Mathematics from the University of Durham (2010-2014)

Abbott's research focuses on developing, evaluating, and applying methods for improving our understanding of infectious disease dynamics in real-time. He is particularly interested in nowcasting right-truncated data, forecasting variant dynamics, reconstructing unobserved infections from various data sources, and estimating key epidemiological parameters such as the effective reproduction number, growth rate, and generation interval distribution. He is committed to open and collaborative science, with much of his recent work focused on the COVID-19 response, though his underlying focus is pathogen-agnostic sparse data settings.

Analysis of his recent publications reveals a strong emphasis on methodological development for real-time infectious disease surveillance and forecasting. His work frequently addresses challenges in nowcasting, forecasting accuracy, model evaluation, and integration of diverse data sources for improved epidemic understanding, with significant contributions to understanding variant dynamics (Delta, Omicron), the impact of public health measures, and collaborative forecasting approaches.

Abbott received the Directors Early Career Researcher Award in 2020 and has secured grant funding including 'Surge-capacity public health modelling support for COVID-19 Omicron wave and post-wave' from Stellenbosch University (May-October 2022).

As an educator, Abbott teaches on the modern methods for infectious disease modelling short course, particularly leading the best practices session. He is active in the epinowcast community, developing open-source tools and methods for current surveillance of infectious diseases and preparing for future outbreaks. His technical expertise includes R, Julia, and Stan programming languages.