学术报告【EARLY DETECTION AND CONTROL OF POTENTIAL PANDEMICS】
时间：2018年7月16日 (星期一) 上午10:00
地点：旗山校区理工南楼616
主讲：University of Louisville,Prof.Wei-Bin Zeng
主办： 数学与信息学院、数学研究中心、福建省分析数学及应用重点实验室
参加对象：数信学院相关方向师生
报告摘要：For centuries, human beings have been inflicted with a variety of contagious diseases, resulting in
tens of millions of respiratory illnesses and deaths worldwide. Early detection of disease spread
facilitates timely responses that can greatly reduce its impact on a population. Therefore, early
information becomes a major public health objective and is crucial for policy makers and public
health officials responsible for protecting the public from the virulent spread of contagious
diseases.
Current indicators of the spread of contagious outbreaks lag behind its actual spread, leaving no
time for a planned response. The studies of Christakis et al. in 2010 have shown that social
networks can provide more timely information for prediction. However, the reported social
network methods used to monitor disease spread do not consider contact patterns of individuals
over space and time, such as during their movement from place to place. In this project, we propose
a more effective model to chart the spread of contagious outbreaks, in a spatio-temporal sense,
using “contact networks.” This enables more effective control of the spread of contagious
outbreaks in their early stages so as to “nip a potential pandemic in the bud.”
By applying data mining methodologies as well as predictive modeling technologies, such as
logistics regression, decision trees and neural networks, we are able to estimate the infection risk
based on an individual’s demographic information and health status. The information used in the
models can be obtained from a wide variety of data sources, including historical medical records
from hospitals and clinics.
报告人简介：Prof. Wei-Bin Zeng received his Ph.D from University of Pittsburgh in 1998. Wei-Bin Zeng is currently an associate professor at University of Louisville.