University of Louisville,Prof.Wei-Bin Zeng学术报告7月16日上午
发布时间: 2018-07-15 访问次数: 128


时间:2018年7月16日 (星期一) 上午10:00


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


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 


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.