Welcome to the Asia Summer School
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Asia is one of the most vulnerable regions to climate change in the world.
This course introduces research tools to examine evidence on the health risks associated with environmental risk exposures and to assess the health benefits of mitigation policies in Asia. |
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About previous editions |
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Time-series regression analysis has become a key methodological tool in public health for investigating the short-term health effects of environmental exposures. The course provides an introduction to the ecological time-series design and guides participants through the main stages of the statistical modelling process, from data preparation and exploratory analysis to model specification, interpretation, and presentation of results. Particular attention is given to commonly studied environmental exposures in Asian settings, including temperature, air pollution, desert dust, and haze.
Who should attendThe course is designed for postgraduate students, early career researchers, and personnel from universities, as well as researchers and practitioners working in public and private institutions across various research fields and nationalities. Places are allocated on a first-come, first-served basis. The course will be taught in English.
FacultyOur faculty includes professors and researchers from Japanese universities with extensive experience in environmental epidemiology.
VenueThe course will be held on The University of Tokyo main campus, conveniently located next to Ueno Park with good access to three subway stations and in close proximity to many museums, hotels, and restaurants.
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The 4th edition brought more than 40 participants from 19 countries, reflecting the growing reach of this training across Asia and the Western Pacific region. Participants included postgraduate students and researchers working in public health, environmental epidemiology, and infectious disease epidemiology.
What participants saidParticipants gave the course top ratings for satisfaction and expressed their intention to recommend it to others.
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