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Activity Number: 158 - Statistical Demography
Type: Topic Contributed
Date/Time: Tuesday, August 4, 2020 : 10:00 AM to 11:50 AM
Sponsor: Social Statistics Section
Abstract #311031
Title: Detecting Disease Outbreak Using Travelers Data -- a Case Study of COVID-19 Epidemic
Author(s): Le Bao* and Xiaoyue Maggie Niu and Ying Zhang
Companies: Penn State University and Penn State University and Penn State University
Keywords: COVID-19; size estimation; Bayesian hierarchical model; Value of Information
Abstract:

The increasing volume of travelers can make a highly infectious disease quickly spread out from the origin to the whole nation and to other countries. To ensure a timely response to an emerging disease outbreak, we discuss how the traveler data shall be used to strengthen the global disease surveillance utilizing the resources from all countries. We investigate the impacts of different data sources and information on understanding the initial phase of COVID-19 epidemic in multiple countries using the traveler data and the value of information approach. We evaluate the data impacts with respect to different factors that are likely to affect the decision making process such as the basic reproduction number, the doubling time, the number of infected individuals, the probability of severe cases exceeding the hospital capacity. Finally we make recommendations on the critical information that shall be share between countries for disease outbreak detection purposes.


Authors who are presenting talks have a * after their name.

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