Academic Profile : Faculty

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Asst Prof Jue Tao Lim
Assistant Professor, Infectious Disease Modelling, Lee Kong Chian School of Medicine
Assistant Professor, Lee Kong Chian School of Medicine
Assistant Professor Lim Jue Tao is an Assistant Professor in the Lee Kong Chian School of Medicine at Nanyang Technological University. He holds a BSc (Hons) in Economics, as well as a Masters in Statistics. He obtained his PhD in Public Health from the Saw Swee Hock School of Public Health in 2021, where his work was focused on modelling the transmission dynamics of vector-borne diseases.

Prior to joining LKCMedicine, he was Head of Informatics at the Environmental Health Institute, National Environment Agency, Singapore. He has led the Informatics group which focused on translating and adapting tools from statistics, econometrics and computational epidemiology to conduct inference on the transmission dynamics of pathogens, such as dengue and SARS-CoV-2.

Asst Prof Lim is a biostatistician and infectious disease modeller with a long-standing and deep interest in developing new models for infectious disease forecasting, transmission and control. He uses these tools to advise and design disease control implementation and policy, and has contributed to more than 40 publications in journals such as Lancet Infectious Diseases and Lancet Western Pacific and is involved in multiple local and international collaborations.
Our group combines computational methods in statistics, econometrics and computational epidemiology to understand the risk factors leading to increased infectious disease morbidity and mortality. In particular, vector-borne diseases in endemic regions, such as dengue as well as respiratory pathogens such as SARS-CoV-2.

Asst Prof Lim’s main research interests include (1) using transmission dynamics modelling and computational epidemiology to characterise the onward spread of infectious diseases in the short to long term; (2) using large and fine-spatial scale disease surveillance and environmental data to identify factors which contribute to elevated disease risk (3) using computational tools to advise and design disease control implementation and policy and (4) understand the associated cost-effectiveness of intervention strategies in different disease settings.
 
  • Delineating long-term implications of climate change on endemic and emerging vector-borne disease transmission in Singapore
  • Delineating the transmission of vector- and air-borne diseases over large spatial scales to inform public health interventions
  • Exploring the interface of dengue, other vector-borne diseases and the environment in the Western Pacific region
  • Mixed data sampling models to infer the impacts of exposomes on disease burden
  • Modelling sexually transmitted diseases for outbreak resilience
  • Understanding and triangulating interventions to mitigate healthcare-associated infections and multi-drug resistant organisms burden