![Show Menu](styles/mobile-menu.png)
![Page Background](./../common/page-substrates/page0018.png)
Page 73
Notes:
conferenceseries
.com
Volume 8, Issue 4 (Suppl)
J Health Med Inform, an open access journal
ISSN: 2157-7420
Medical Informatics 2017
August 31- 01 September, 2017
August 31- 01 September, 2017 | Prague, Czech Republic
5
th
International Conference on
Medical Informatics & Telemedicine
J Health Med Informat 2017, 8:4 (Suppl)
DOI: 10.4172/2157-7420-C1-019
NETWORK SCIENCE IN DISASTERAND PUBLIC HEALTH PREPAREDNESS
Liaquat Hossain
a
and
Shihui Feng
a
a
University of Hong Kong, Hong Kong
N
etwork science provides us with theoretical and methodological foundations drawn from physics, graph theory, sociology
and social psychology to make sense of various complex systems in disaster and public health preparedness. Disaster
and public health preparedness is a collective action conducted by a group of individuals and organizations, in which
information and communication flow frommulti levels becomes critical to the functioning of the complex systems. Awareness
of locally situated knowledge and shared understanding of disasters among public and hierarchical governing systems can be
instrumental in supporting decision making, early warning and outbreak detection. Network science enables us to analyze the
underlying structures and model the dynamics of networks representative of real-world systems in disasters. From this, we can
examine the effectiveness of disaster management, monitor public awareness, achieve early recognition of disaster occurrence,
and enhance the robustness of response systems. Data availability provided by digital evolution can further promote the study
of large scale network in disaster at local and global level. Our proposition is here to suggest effective strategies using network
science to study social and organizational systems at play in disaster preparedness and response. In our presentation, we will
discuss a series of work related to modelling social systems for detecting early warning signs, improving our understanding
of locally situated information of disaster affected areas, and supporting communication and collaboration across public and
hierarchical governing systems.