Dr Sam Clifford

B AppSc PhD

Research Fellow
in Machine (Statistical) Learning


Keppel Street
United Kingdom

Sam obtained a Bachelors Degree in Applied Science (with Honours 2A) from Queensland University of Technology (QUT, Brisbane, Australia), majoring in Applied and Computational Mathematics. After a short break teaching mathematics to video game developers at Krome Studios, Sam undertook his Doctoral studies at the International Laboratory for Air Quality and Health.

Under Professors Lidia Morawska and Kerrie Mengersen and Dr Samantha Low-Choy, Sam's thesis investigated spatio-temporal modelling of ultrafine particles in Brisbane, Australia. After five and a half years of postdoctoral work at QUT, Sam joins us at the London School of Hygiene and Tropical Medicine for 2.5 years as a postdoctoral fellow.


Department of Infectious Disease Epidemiology
Faculty of Epidemiology and Population Health


Centre for the Mathematical Modelling of Infectious Diseases (CMMID)


Sam has five years experience in undergraduate lecturing at QUT, teaching mathematics and statistics in the R computational environment to first year Bachelor of Science students. His teaching makes use of blended learning approaches to prepare students for lecture material, and collaborative workshops with project-based learning.

In 2015, Sam and his team were awarded a Vice Chancellor's Award for Innovation on the basis of their work transforming SEB113.

Sam's current teaching at LSHTM includes the following short courses:


Sam's research at LSHTM includes the following:

  • Spatio-temporal variation in Streptococcus pneumoniae serotypes
  • Maternal colonisation of Group B Streptococcus
  • Modelling the health and economic impact of dengue vaccination

In addition to his doctoral thesis on spatio-temporal modelling of ultrafine particle number concentration, Sam's research interests include

  • exposure assessment
  • personal monitoring equipment for air pollution
  • non-parametric regression
  • jaguar conservation
  • Great Barrier Reef conservation
  • machine learning for spatial data
  • Bayesian hierarchical modelling
  • data visualisation
  • mathematics and statistics education
Research Area
Statistical methods
Bayesian Analysis
Environmental Health
Mobile technologies
Spatial analysis
Mathematical modelling
Disease and Health Conditions
Respiratory disease

Selected Publications

Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study.
Clark A; Jit M; Warren-Gash C; Guthrie B; Wang HHX; Mercer SW; Sanderson C; McKee M; Troeger C; Ong KL
The Lancet. Global Health
Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study.
Davies NG; Kucharski AJ; Eggo RM; Gimma A; Edmunds WJ; Centre for the Mathematical Modelling of Infectious Diseases COV
The Lancet. Public health
Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China
Endo A; Abbott S; Kucharski AJ; Funk S
Wellcome Open Research
Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK.
Jarvis CI; Van Zandvoort K; Gimma A; Prem K; CMMID COVID-19 working group; Klepac P; Rubin GJ; Edmunds WJ
BMC medicine
Inferring the number of COVID-19 cases from recently reported deaths
Jombart T; van Zandvoort K; Russell T; Jarvis C; Gimma A; Abbott S; Clifford S; Funk S; Gibbs H; Liu Y
A Modelling Study for Designing a Multi-layered Surveillance Approach to Detect the Potential Resurgence of SARS-CoV-2
Liu Y; Gong W; Clifford S; Sundaram M; Jit M; Flasche S; Klepac P; CMMID COVID19 Working Group
COVID-19 length of hospital stay: a systematic review and data synthesis
Rees E; Nightingale E; Jafari Y; Waterlow N; Clifford S; Pearson C; Jombert T; Procter S; Knight G; CMMID Working Group
The effect of international travel restrictions on internal spread of COVID-19
Russell T; Wu J; Clifford S; Edmunds J; Kucharski A; Jit M
See more Publications