Petter Holme is a specially appointed professor of the Institute of Innovative Research at Tokyo Institute of Technology. His research interest is to bridge data science and theory in social sciences and public health. He often starts his research in collaboration with social and medical researchers on large data sets, then he delves into theoretical issues influenced by the data science projects. Recently his interests have focused on temporal networks—networks where the timing of contacts are known, in addition to who interacts with whom. Asking questions such as, how do structures in the time when people meet affect the spreading of infectious diseases? Before joining Tokyo Tech, Holme has been a Professor at Sungkyunkwan University, Korea and junior faculty members of Royal Institute of Technology and Umeå University, Sweden. Holme has around 150 scientific publications.
WRHI is a bridge connecting Tokyo Tech to international academia, just as I see my own research as a connection between different methodologies and disciplines. My research needs to be in such an active, multifaceted environment. Furthermore, the Tokyo region in general and Tokyo Tech in particular has so much creativity and knowledge, that I am happy WRHI can help me access.
Social effects on epidemics: A temporal network approach
Facing an epidemic outbreak, people change their behavior—wear masks, meet people more carefully, etc.—which, in turn, affects the epidemic. Such behavioral change happens both in response to information from media and social influence by peers. Our goal is to measure such feedback loops and ultimately contribute to effective intervention strategies.
Periods : 2018–2022
Members : Petter Holme (Tokyo Tech), Tsuyoshi Murata (Tokyo Tech), Naoki Masuda (University of Bristol)
Funding source : JSPS, Kakenhi kiban B
network theorytheoretical epidemiologydigital healthtemporal networks
Umea University, Department of Physics Senior Lecturer
Sungkyunkwan University, Department of Energy Science, 教授
“Freedom of choice adds value to public goods”
“Small inter-event times govern epidemic spreading on temporal networks”
”Beyond ranking nodes: Predicting epidemic outbreak sizes by network centralities”
“Rare and everywhere: Perspectives on scale-free networks”
“Efficient sentinel surveillance strategies for preventing epidemics on networks”
“Detecting sequences of system states in temporal networks”