For September, we are happy to have researchers from the NUS Saw Swee Hock School of Public Health (SSHSPH) for the Data Science SG meetup.
The population health modelling group within SSHSPH has developed an individual based simulation model that can represent each individual in the resident population over their lifetime and track theirs, and the population’s, aging and onset of chronic diseases like diabetes. This individual based framework allows complex dynamics of risk factors and diseases to be accounted for and in silica trials of programmes to reduce this impact, serving as a virtual test bed for campaigns in the war on diabetes. Computational models are helpful to investigate the spread of infectious diseases in human populations too. Incorporating spatial data in these models allows us to study the geographical-related exposures for vector-borne diseases such as Zika and Dengue.
Associate Professor Alex Cook leads the modelling group in the Biostatistics and Modelling Domain in the Saw Swee Hock School of Public Health. He obtained his PhD in statistics and mathematical modelling at Heriot-Watt University. Subsequently, he worked as a postdoctoral fellow in the Gibson and Gilligan labs at Heriot-Watt and Cambridge, respectively. Associate Prof Cook is best known for his research in computational statistics and modelling in the fields of infectious disease epidemiology, public health and the environment.
Kiesha Prem is a Research Assistant at the Saw Swee Hock School of Public Health, where she does modelling work with the Biostatistics and Modelling Domain. She trained at the Department of Statistics at the National University of Singapore where she obtained her BSc. (Hons) in Statistics. Currently, Kiesha is a PhD candidate with Saw Swee Hock School of Public Health. Her research interests is in infectious disease modelling using Bayesian statistics.