Modelling

MO Yin

Senior Lecturer (Joint) Email mdcmy@nus.edu.sg MO Yin Dr Mo Yin is driven by the ideal of using quality clinical research to influence patient care and propel health policies. She has been active in clinical research, medical education, as well as hospital administration. She has received numerous awards for her achievements in clinical care, research and teaching. Dr Mo Yin’s career goal is to serve her community focusing on translational research to influence regional and global policies. Affiliation NUS Saw Swee Hock School of Public Health (Joint) NUS Yong Loo LinRead more

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JIT Mark

Honorary Visiting Professor Email mark.jit@lshtm.ac.uk JIT Mark Mark Jit is professor of vaccine epidemiology and head of the Department of Infectious Disease Epidemiology at the London School of Hygiene & Tropical Medicine (LSHTM). He also holds visiting professorial appointments at the NUS Saw Swee Hock School of Public Health and the School of Public Health, University of Hong Kong. His research group focuses on epidemiological and economic modelling of vaccines to support evidence-based public health decision making. Mark has published over 250 papers covering a range of vaccine-preventable or potentially

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Caro Jaime

CARO J. Jaime

Honorary Visiting Professor Email jaime.caro@mcgill.ca CARO J. Jaime I trained in medicine and epidemiology at McGill University but early on focused on health technology assessment. Most of my work is on methods development and teaching these new approaches. For Germany’s IQWiG, I proposed the use of efficiency frontiers as they rejected using the QALY. Recently, I have developed the DICE simulation method, a unified approach to modeling that enables rapid, standardized and less error-prone forecasting models. Work on a broader approach than QALYs to value health benefits is ongoing. Leveraging mixed

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Jörgen Möller

MÖLLER Jörgen

Honorary Visiting Associate Professor Email Jorgen.moller@evidera.com MÖLLER Jörgen To be able to predict the future with any credibility, data from multiple sources is required. This is regardless if it is epidemiology, public health or even production or demand you are looking at. The data then must be joint, typically in a model which extrapolates the information and thus paints a picture of a likely future. Depending on the nature of the research question, and the available data, different modeling paradigms can and should be chosen and an appropriate combination of

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Hongfei Yang

YANG Hongfei

Research Fellow Email hfyang@nus.edu.sg YANG Hongfei Yang Hongfei is interested in applying deep learning methods and image processing methods to tackle healthcare challenges. Affiliation NUS Saw Swee Hock School of Public Health Research Areas Deep learning methods and their applications in medical image processing and healthcare data analysis Academic/Professional Qualifications Post-doc (2018-2020), the Chinese University of Hong Kong and the City University of Hong Kong PhD (2013-2018), University of Nottingham MSc (2011-2012), University of Nottingham Bachelor (2007-2011), the Hong Kong Baptist University Selected Publications Yang, H.; Ding, X.; Chan, R.;

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CLAPHAM Hannah

Programme Leader (Infectious Diseases); Assistant Professor Email hannah.clapham@nus.edu.sg CLAPHAM HannahAffiliation NUS Saw Swee Hock School of Public Health Research Areas Infectious disease dynamics and control Impact of vaccination Dengue epidemiology and control Japanese Encephalitis epidemiology and control Inference from serological data Academic/Professional Qualifications BA Hons Mathematics University of Oxford (2004-2007) MSc Modern Epidemiology, Imperial College London (2008-2009) PhD Disease Dynamics, Imperial College London (2009-2013) Career History 2016-2019: Mathematical Epidemiologist and Head of Mathematical Modelling Group, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam 2013-2016: Postdoctoral Fellow, Department of Epidemiology,

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TEERAWATTANANON Yot

Visiting Professor Email yot.t@hitap.net TEERAWATTANANON Yot Yot is a medical doctor and health economist by training. He found the Thai Ministry of Public Health’s Health Intervention and Technology Assessment Program (HITAP) before joining the Saw Swee Hock School of Public Health at the National University of Singapore as a Visiting Professor. He is also a co-founder of the HTAsiaLink and the international Decision Support Initiative (iDSI). His works have been used to inform health benefits packages in Thailand and elsewhere across the globe. He has provided capacity building in health technology

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PREM Kiesha

Assistant Professor Email kiesha.prem@nus.edu.sg PREM Kiesha Kiesha Prem is an Assistant Professor at the NUS Saw Swee Hock School of Public Health and the London School of Hygiene & Tropical Medicine. As an infectious disease modeller, she builds computational models to understand the population impact and cost-effectiveness of interventions against infectious diseases. Her research involves evaluating the population impact and cost-effectiveness of single-dose schedules for Human Papillomavirus (HPV) vaccination globally, reviewing new evidence on HPV vaccination and responding to questions from governments and other decision-makers. Kiesha led the development and updates

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MA Stefan

Adjunct Associate Professor Email ephmsls@nus.edu.sg / stefan_ma@moh.gov.sg MA StefanAffiliation NUS Saw Swee Hock School of Public Health (Adjunct) Deputy Director (Biostatistics & Research), Epidemiology & Disease Control Division, Public Health Group, Ministry of Health Singapore (Primary) Research Areas Risk modelling, Burden of disease, Comparative risk assessment Disease projection, Small area analysis, Environmental health modelling, Disease dynamics modelling Teaching Areas Statistical Methods in Epidemiology Academic/Professional Qualifications Doctor of Philosophy (Biostatistics), The University of Hong Kong Master in Statistics, The University of Hong Kong Bachelor of Science (Statistics & Operations Research), University

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CHEN Huijun Cynthia

Assistant Professor Tel (65) 6601 5526 Email ephchc@nus.edu.sg CHEN Huijun Cynthia Teach us to number our days, that we may apply our hearts to wisdom. While growing old is inevitable, the twilight years could be spent in good physical and mental health. With the impending demographic shift, the elderly population in Singapore will triple to 900,000 by 2030. This has major implications for both the young and old. Are we prepared? Can we learn from the past and do better? Dr Chen’s passion for ageing research started a decade ago. She now

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