Analysis of the Effectiveness of Public Health Measures on COVID-19 Transmission

Author:

Silva Thiago Christiano12ORCID,Anghinoni Leandro2,Chagas Cassia Pereira das1,Zhao Liang2,Tabak Benjamin Miranda3

Affiliation:

1. Universidade Católica de Brasília, Brasilia 71966-700, Brazil

2. Department of Computing and Mathematics, Faculty of Philosophy, Sciences, and Literatures in Ribeirão Preto, Universidade de São Paulo, São Paulo 14040-901, Brazil

3. FGV/EPPG Escola de Políticas Públicas e Governo, Fundação Getúlio Vargas (School of Public Policy and Government, Getulio Vargas Foundation), Brasilia 70830-020, Brazil

Abstract

In this study, we investigate the COVID-19 epidemics in Brazilian cities, using early-time approximations of the SIR model in networks and combining the VAR (vector autoregressive) model with machine learning techniques. Different from other works, the underlying network was constructed by inputting real-world data on local COVID-19 cases reported by Brazilian cities into a regularized VAR model. This model estimates directional COVID-19 transmission channels (connections or links between nodes) of each pair of cities (vertices or nodes) using spectral network analysis. Despite the simple epidemiological model, our predictions align well with the real COVID-19 dynamics across Brazilian municipalities, using data only up until May 2020. Given the rising number of infectious people in Brazil—a possible indicator of a second wave—these early-time approximations could be valuable in gauging the magnitude of the next contagion peak. We further examine the effect of public health policies, including social isolation and mask usage, by creating counterfactual scenarios to quantify the human impact of these public health measures in reducing peak COVID-19 cases. We discover that the effectiveness of social isolation and mask usage varies significantly across cities. We hope our study will support the development of future public health measures.

Funder

Brazilian National Council for Scientific and Technological Development

São Paulo Research Foundation

Center for Artificial Intelligence

IBM Corporation

Fundação de Apoio à Pesquisa do Distrito Federal

Publisher

MDPI AG

Subject

Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The Intersection of Health Literacy and Public Health: A Machine Learning-Enhanced Bibliometric Investigation;International Journal of Environmental Research and Public Health;2023-10-20

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