プリンストン・東京大学合同シンポジウム

2017年7月29日(土) 10:30-15:00
東京大学駒場キャンパス 数理科学研究科棟大講義室
参加費無料・予約不要

UTokyo-Princeton International Workshop of Infectious Disease Modeling
"Infectious Diseases in Aging Populations: Unifying Statistical and Dynamical Approaches"

Speakers:
Bryan Grenfell (Princeton University)
Jessica Metcalf (Princeton University)
Micaela Martinez (Princeton University)
Hisashi Inaba (The University of Tokyo)
Akira Sasaki (The Graduate University for Advanced Studies)
Hiroshi Nishiura (Hokkaido University)

Abstract:
Demography has considerable implications for infectious disease transmission and risk across populations. For example, it is well known that high birth rates lead to annual patterns of incidence due to the numbers of individuals who are susceptible to disease being constantly replenished (e.g., measles in the United States and United Kingdom during the post-World War II baby boom). However, many countries - most notably Japan and South Korea - have passed through a rapid demographic transition that is characterized by lower birth rates and lower death rates. Japan in the post-demographic transition era has been revealed to be the world's first "aging population". The demographic features of Japan and its implications for disease dynamics will be important for other countries to follow. We form a new research exchange between UTokyo and Princeton to leverage our complementary approaches to infectious diseases. Japan team has been trying to improve epidemic forecasting using statistical approaches. Such forecasting techniques offer estimates of epidemiological parameters such as the force of infection and the basic reproductive number of infectious diseases in both outbreak and endemic contexts. Meanwhile, the Princeton team has been developing mechanistic models to study the transmission dynamics of vaccine-preventable infectious diseases. These models incorporate aspects of demography (e.g., birth rate, late-age survival rate, and population size) as well as epidemiological parameters such as the basic reproductive number and seasonality of diseases. We create an integrated UTokyo-Princeton program focusing on the impact of demography on infectious disease forecasting and dynamical modelling.

連絡先:北海道大学大学院医学研究院 衛生学教室 遠藤彰 akiraendo@outlook.com

連携基盤センター 数物フロンティア・リーディング大学院 Math Sci Univ Tokyo KAVLI IPMU iBMath 数理ビデオアーカイブス 東京大学玉原国際セミナーハウス