The Effects of Stringent and Mild Interventions for Coronavirus Pandemic

Abstract

Department

Description

Provenance

Subjects

Compartmental model, Counterfactual, COVID-19, Synthetic control method, Treatment effect

Citation

Published Version (Please cite this version)

10.1080/01621459.2021.1897015

Publication Info

Tian, Ting, Jianbin Tan, Wenxiang Luo, Yukang Jiang, Minqiong Chen, Songpan Yang, Canhong Wen, Wenliang Pan, et al. (2021). The Effects of Stringent and Mild Interventions for Coronavirus Pandemic. Journal of the American Statistical Association, 116(534). pp. 481–491. 10.1080/01621459.2021.1897015 Retrieved from https://hdl.handle.net/10161/30494.

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Scholars@Duke

Tan

Jianbin Tan

Postdoctoral Associate

My research interests lie in statistical learning for data with dynamic-, longitudinal-, or trajectory- based structures. Such data often exhibit complicated intrinsic mechanisms, dependencies, and heterogeneity, as well as challenges such as noise, irregular sampling, and high- or even infinite-dimensionality. To address these, I focus on developing new methodologies for statistical learning of functions, differential equations, and operators, supporting effective analysis in biology, health, epidemiology, and environmental science.


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