Staff Directory

Zhilan Julie Feng

Email:
zfeng@nsf.gov
Phone:
(703) 292-7523
Room:
E 8436
Organization:
DMS
Title:
Program Director
Website:
https://www.math.purdue.edu/people/bio/fengz/

Program Responsibilities:
Focused Research Groups in the Mathematical Sciences (FRGMS)
Joint DMS/NIGMS Initiative to Support Research at the Interface of the Biological and Mathematical Sciences (DMS/NIGMS)
Mathematical Biology

Biography:

An interactive notebook based on a COVID-19 model by Haiyun Damon-Feng, Henry Zhao, and Zhilan Feng. It demonstrates scenarios of relaxing the lockdown restrictions and illustrates that continuous efforts of physical distancing may be necessary to avoid a second wave with high peak. Get simple explanations by clicking on the words or curves in the notebook. More explanations of the model are provided here. Many examples of epidemiological models can be found in the book "Mathematical Models in Epidemiology" by Fred Brauer, Carlos Castillo-Chavez, and Zhilan Feng.

Staggered release policies for COVID-19 control: Costs and benefits of relaxing restrictions by age and riskHenry Zhao and Zhilan Feng 

Abstract: Lockdown and social distancing restrictions have been widely used as part of policy efforts aimed at controlling the ongoing COVID-19 pandemic. Since these restrictions have a negative impact on the economy, there exists a strong incentive to relax these policies while protecting public health. Using a modified SEIR epidemiological model, this paper explores the costs and benefits associated with the sequential release of specific groups based on age and risk from lockdown and social distancing measures. The results in this paper suggest that properly designed staggered-release policies can do better than simultaneous-release policies in terms of protecting the most vulnerable members of a population, reducing health risks overall, and increasing economic activity.

On the benefits of flattening the curve: A perspective, by Zhilan Feng, John W. Glasser and Andrew N. Hill

Mathematicians Quickly Respond to the COVID-19 Pandemic, by Juan Meza, Zhilan Feng, Tie Luo, Junping Wang.