COVID-19 Modeling
An interactive notebook for a COVID-19 model
by Haiyun Damon-Feng, Henry Zhao and Zhilan Feng.
It demonstrates scenarios of relaxing the lockdown restrictions and suggests that continuous efforts of an appropriate level of physical distancing may be necessary to avoid a second wave with high peak. More explanations of the model are here.
Staggered release policies for COVID-19 control: Costs and benefits of relaxing restrictions by age and risk
by Henry Zhao and Zhilan Feng.
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.
A CDM Lecture on Mathematics and COVID-19
A Letter in Science, April 30, 2020
Signed the letter "Call for transparency of COVID-19 models" (PDF) as the current chair of the Mathematical Epidemiology Subgroup of the Society for Mathematical Biology. Having the models more transparent will help evaluate them when things calm down. It will take smart modelers to understand what worked and what didn't work in the models, but by having them available and transparent, it will be possible.
On the benefits of flattening the curve: A perspective
by Zhilan Feng, John W. Glasser, Andrew N. Hill.
The many variations on a graphic illustrating the impact of non-pharmaceutical measures to mitigate pandemic influenza that have appeared in recent news reports about COVID-19 suggest a need to better explain the mechanism by which social distancing reduces the spread of infectious diseases.
Research support on mathematical modeling of COVID-19
The Mathematical Biology program and other programs in DMS of the NSF funded RAPID proposals in response to the Dear Colleague Letter on the Coronavirus Disease 2019 (COVID-19). Some of the awards are mentioned in this article published in SIAM News: "Mathematicians Quickly Respond to the COVID-19 Pandemic", Juan C. Meza, Zhilan Feng, Tie Luo, Junping Wang.