Quantifying the transmission dynamics using illness onset data

2016 Fiscal Year Final Research Report

• Project/Area Number: 26700028
• Research Category: Grant-in-Aid for Young Scientists (A)
• Allocation Type: Partial Multi-year Fund
• Research Field: Life / Health / Medical informatics
• Research Institution: Hokkaido University (2016); The University of Tokyo (2014-2015)
• Principal Investigator: NISHIURA Hiroshi 北海道大学, 医学(系)研究科(研究院), 教授 (70432987)
• Project Period (FY): 2014-04-01 – 2017-03-31
• Keywords: 感染症情報 / 理論疫学 / 逆計算 / 統計学的推定 / 疫学

Outline of Final Research Achievements

Mathematical modeling of infectious diseases often rests on bottom-up approach to capturing the transmission dynamics and natural history. However, the infection event is not directly observable, and thus, the infection process has to be statistically inferred using the readily observable information. The present study expanded the scientific opportunities of inference, collecting the illness onset data and utilizing such models to evaluate infectious disease interventions. Multitudes of publications including those applied to MERS (Middle East respiratory syndrome) and Zika fever have resulted from this project.

Free Research Field

理論疫学