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Dr Sam Clifford

B AppSc PhD

Assistant Professor
in Machine (Statistical) Learning

Room
120

LSHTM
Keppel Street
London
WC1E 7HT
United Kingdom

Sam obtained a Bachelors Degree in Applied Science (with Honours) 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 (ILAQH), a WHO Collaborating Centre, at QUT.

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 (ILAQH and the ARC Centre of Excellence for Mathematical and Statistical Frontiers), Sam joined us at the London School of Hygiene and Tropical Medicine for 2.5 years as a postdoctoral fellow.

In 2020 Sam was promoted to Assistant Professor, where he continues his work on streptococcus pneumoniae, SARS-CoV-2/COVID-19 and Dengue.

Affiliations

Faculty of Epidemiology and Population Health
Department of Infectious Disease Epidemiology

Centres

Centre for the Mathematical Modelling of Infectious Diseases (CMMID)

Teaching

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:

and the following modules:

  • Data Challenge module in the new MSc in Health Data Science (Module Organiser)
  • Statistics for Epidemiology and Population Health (practicals)
  • Introduction to Statistical Computing (guest lectures)

Research

Sam's research at LSHTM includes the following:

  • Traveller screening and quarantine for SARS-CoV-2/COVID-19
  • 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
Vaccines
Bayesian Analysis
Environmental Health
Mobile technologies
Outbreaks
Schools
Spatial analysis
Modelling
Education
Discipline
Mathematics
Mathematical modelling
Statistics
Disease and Health Conditions
Asthma
Respiratory disease
Dengue
Coronavirus

Selected Publications

The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories.
Liu Y; Morgenstern C; Kelly J; Lowe R; CMMID COVID-19 Working Group; Jit M
2021
BMC Medicine
The importance of supplementary immunisation activities to prevent measles outbreaks during the COVID-19 pandemic in Kenya.
Mburu CN; Ojal J; Chebet R; Akech D; Karia B; Tuju J; Sigilai A; Abbas K; Jit M; Funk S
2021
BMC medicine
Quarantine and testing strategies in contact tracing for SARS-CoV-2: a modelling study.
Quilty BJ; Clifford S; Hellewell J; Russell TW; Kucharski AJ; Flasche S; Edmunds WJ; Centre for the Mathematical Modelling of Infectious Diseases COV
2021
The Lancet Public Health
Effect of internationally imported cases on internal spread of COVID-19: a mathematical modelling study.
Russell TW; Wu JT; Clifford S; Edmunds WJ; Kucharski AJ; Jit M; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group
2021
The Lancet. Public health
Changing travel patterns in China during the early stages of the COVID-19 pandemic.
Gibbs H; Liu Y; Pearson CAB; Jarvis CI; Grundy C; Quilty BJ; Diamond C; LSHTM CMMID COVID-19 working group; Eggo RM
2020
Nature communications
COVID-19 length of hospital stay: a systematic review and data synthesis.
Rees EM; Nightingale ES; Jafari Y; Waterlow NR; Clifford S; B Pearson CA; Group CW; Jombart T; Procter SR; Knight GM
2020
BMC MEDICINE
Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections.
Russell TW; Golding N; Hellewell J; Abbott S; Wright L; Pearson CAB; van Zandvoort K; Jarvis CI; Gibbs H; Liu Y
2020
BMC medicine
Response strategies for COVID-19 epidemics in African settings: a mathematical modelling study.
van Zandvoort K; Jarvis CI; Pearson CAB; Davies NG; CMMID COVID-19 working group; Ratnayake R; Russell TW; Kucharski AJ; Jit M; Flasche S
2020
BMC medicine
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