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

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...

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Detalles Bibliográficos
Autores principales: Silva, Thiago Christiano, Anghinoni, Leandro, Chagas, Cassia Pereira das, Zhao, Liang, Tabak, Benjamin Miranda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10531329/
https://www.ncbi.nlm.nih.gov/pubmed/37754616
http://dx.doi.org/10.3390/ijerph20186758
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author Silva, Thiago Christiano
Anghinoni, Leandro
Chagas, Cassia Pereira das
Zhao, Liang
Tabak, Benjamin Miranda
author_facet Silva, Thiago Christiano
Anghinoni, Leandro
Chagas, Cassia Pereira das
Zhao, Liang
Tabak, Benjamin Miranda
author_sort Silva, Thiago Christiano
collection PubMed
description 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.
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spelling pubmed-105313292023-09-28 Analysis of the Effectiveness of Public Health Measures on COVID-19 Transmission Silva, Thiago Christiano Anghinoni, Leandro Chagas, Cassia Pereira das Zhao, Liang Tabak, Benjamin Miranda Int J Environ Res Public Health Article 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. MDPI 2023-09-14 /pmc/articles/PMC10531329/ /pubmed/37754616 http://dx.doi.org/10.3390/ijerph20186758 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Silva, Thiago Christiano
Anghinoni, Leandro
Chagas, Cassia Pereira das
Zhao, Liang
Tabak, Benjamin Miranda
Analysis of the Effectiveness of Public Health Measures on COVID-19 Transmission
title Analysis of the Effectiveness of Public Health Measures on COVID-19 Transmission
title_full Analysis of the Effectiveness of Public Health Measures on COVID-19 Transmission
title_fullStr Analysis of the Effectiveness of Public Health Measures on COVID-19 Transmission
title_full_unstemmed Analysis of the Effectiveness of Public Health Measures on COVID-19 Transmission
title_short Analysis of the Effectiveness of Public Health Measures on COVID-19 Transmission
title_sort analysis of the effectiveness of public health measures on covid-19 transmission
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10531329/
https://www.ncbi.nlm.nih.gov/pubmed/37754616
http://dx.doi.org/10.3390/ijerph20186758
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