December 2022 Estimating functional parameters for understanding the impact of weather and government interventions on COVID-19 outbreak
Chih-Li Sung
Author Affiliations +
Ann. Appl. Stat. 16(4): 2505-2522 (December 2022). DOI: 10.1214/22-AOAS1601


As the coronavirus disease 2019 (COVID-19) has shown profound effects on public health and the economy worldwide, it becomes crucial to assess the impact on the virus transmission and develop effective strategies to address the challenge. A new statistical model, derived from the SIR epidemic model with functional parameters, is proposed to understand the impact of weather and government interventions on the virus spread in the presence of asymptomatic infections among eight metropolitan areas in the United States. The model uses Bayesian inference with Gaussian process priors to study the functional parameters nonparametrically, and sensitivity analysis is adopted to investigate the main and interaction effects of these factors. This analysis reveals several important results, including the potential interaction effects between weather and government interventions, which shed new light on the effective strategies for policymakers to mitigate the COVID-19 outbreak.

Funding Statement

The author was supported by NSF Grant DMS-2113407.


The author gratefully acknowledges the conscientious efforts of the Editor and two anonymous reviewers whose comments greatly strengthen this paper. The author is grateful to Dr. Ying Hung for the initial discussion which inspires the author to work on this problem.


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Chih-Li Sung. "Estimating functional parameters for understanding the impact of weather and government interventions on COVID-19 outbreak." Ann. Appl. Stat. 16 (4) 2505 - 2522, December 2022.


Received: 1 January 2021; Revised: 1 December 2021; Published: December 2022
First available in Project Euclid: 26 September 2022

MathSciNet: MR4489221
zbMATH: 1498.62256
Digital Object Identifier: 10.1214/22-AOAS1601

Keywords: asymptomatic infections , Basic reproduction number , Epidemic model , Nonparametric regression , sensitivity analysis

Rights: Copyright © 2022 Institute of Mathematical Statistics


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Vol.16 • No. 4 • December 2022
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