The exposure risk to COVID-19 in most affected countries: a vulnerability assessment model

Detalhes bibliográficos
Autor(a) principal: Cartaxo, Adriana Nascimento Santos
Data de Publicação: 2021
Outros Autores: Barbosa, Francisco Iran Cartaxo, Bermejo, Paulo Henrique de Souza, Moreira, Marina Figueiredo, Prata, David Nadler
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/48487
Resumo: The world is facing the coronavirus pandemic (COVID-19), which began in China. By August 18, 2020, the United States, Brazil, and India were the most affected countries. Health infrastructure and socioeconomic vulnerabilities may be affecting the response capacities of these countries. We compared official indicators to identify which vulnerabilities better determined the exposure risk to COVID-19 in both the most and least affected countries. To achieve this purpose, we collected indicators from the Infectious Disease Vulnerability Index (IDVI), the World Health Organization (WHO), the World Bank, and the Brazilian Geography and Statistics Institute (IBGE). All indicators were normalized to facilitate comparisons. Speed, incidence, and population were used to identify the groups of countries with the highest and lowest risks of infection. Countries’ response capacities were determined based on socioeconomic, political, and health infrastructure conditions. Vulnerabilities were identified based on the indicator sensitivity. The highest-risk group included the U.S., Brazil, and India, whereas the lowest-risk group (with the largest population by continent) consisted of China, New Zealand, and Germany. The high-sensitivity cluster had 18 indicators (50% extra IDVI), such as merchandise trade, immunization, public services, maternal mortality, life expectancy at birth, hospital beds, GINI index, adolescent fertility, governance, political stability, transparency/corruption, industry, and water supply. The greatest vulnerability of the highest-risk group was related first to economic factors (merchandise trade), followed by public health (immunization), highlighting global dependence on Chinese trade, such as protective materials, equipment, and diagnostic tests. However, domestic political factors had more indicators, beginning with high sensitivity and followed by healthcare and economic conditions, which signified a lesser capacity to guide, coordinate, and supply the population with protective measures, such as social distancing.
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spelling The exposure risk to COVID-19 in most affected countries: a vulnerability assessment modelCOVID-19CoronavirusPandemicsMedical risk factorsPandemiasFatores de risco médicoThe world is facing the coronavirus pandemic (COVID-19), which began in China. By August 18, 2020, the United States, Brazil, and India were the most affected countries. Health infrastructure and socioeconomic vulnerabilities may be affecting the response capacities of these countries. We compared official indicators to identify which vulnerabilities better determined the exposure risk to COVID-19 in both the most and least affected countries. To achieve this purpose, we collected indicators from the Infectious Disease Vulnerability Index (IDVI), the World Health Organization (WHO), the World Bank, and the Brazilian Geography and Statistics Institute (IBGE). All indicators were normalized to facilitate comparisons. Speed, incidence, and population were used to identify the groups of countries with the highest and lowest risks of infection. Countries’ response capacities were determined based on socioeconomic, political, and health infrastructure conditions. Vulnerabilities were identified based on the indicator sensitivity. The highest-risk group included the U.S., Brazil, and India, whereas the lowest-risk group (with the largest population by continent) consisted of China, New Zealand, and Germany. The high-sensitivity cluster had 18 indicators (50% extra IDVI), such as merchandise trade, immunization, public services, maternal mortality, life expectancy at birth, hospital beds, GINI index, adolescent fertility, governance, political stability, transparency/corruption, industry, and water supply. The greatest vulnerability of the highest-risk group was related first to economic factors (merchandise trade), followed by public health (immunization), highlighting global dependence on Chinese trade, such as protective materials, equipment, and diagnostic tests. However, domestic political factors had more indicators, beginning with high sensitivity and followed by healthcare and economic conditions, which signified a lesser capacity to guide, coordinate, and supply the population with protective measures, such as social distancing.PLoS ONE2021-11-17T17:05:12Z2021-11-17T17:05:12Z2021info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfCARTAXO, A. N. S. et al. The exposure risk to COVID-19 in most affected countries: a vulnerability assessment model. PLoS ONE, [S. l.], v. 16, n. 3, e0248075, 2021. DOI: 10.1371/journal.pone.0248075.http://repositorio.ufla.br/jspui/handle/1/48487PLoS ONEreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessCartaxo, Adriana Nascimento SantosBarbosa, Francisco Iran CartaxoBermejo, Paulo Henrique de SouzaMoreira, Marina FigueiredoPrata, David Nadlereng2023-05-03T13:18:04Zoai:localhost:1/48487Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-03T13:18:04Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv The exposure risk to COVID-19 in most affected countries: a vulnerability assessment model
title The exposure risk to COVID-19 in most affected countries: a vulnerability assessment model
spellingShingle The exposure risk to COVID-19 in most affected countries: a vulnerability assessment model
Cartaxo, Adriana Nascimento Santos
COVID-19
Coronavirus
Pandemics
Medical risk factors
Pandemias
Fatores de risco médico
title_short The exposure risk to COVID-19 in most affected countries: a vulnerability assessment model
title_full The exposure risk to COVID-19 in most affected countries: a vulnerability assessment model
title_fullStr The exposure risk to COVID-19 in most affected countries: a vulnerability assessment model
title_full_unstemmed The exposure risk to COVID-19 in most affected countries: a vulnerability assessment model
title_sort The exposure risk to COVID-19 in most affected countries: a vulnerability assessment model
author Cartaxo, Adriana Nascimento Santos
author_facet Cartaxo, Adriana Nascimento Santos
Barbosa, Francisco Iran Cartaxo
Bermejo, Paulo Henrique de Souza
Moreira, Marina Figueiredo
Prata, David Nadler
author_role author
author2 Barbosa, Francisco Iran Cartaxo
Bermejo, Paulo Henrique de Souza
Moreira, Marina Figueiredo
Prata, David Nadler
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Cartaxo, Adriana Nascimento Santos
Barbosa, Francisco Iran Cartaxo
Bermejo, Paulo Henrique de Souza
Moreira, Marina Figueiredo
Prata, David Nadler
dc.subject.por.fl_str_mv COVID-19
Coronavirus
Pandemics
Medical risk factors
Pandemias
Fatores de risco médico
topic COVID-19
Coronavirus
Pandemics
Medical risk factors
Pandemias
Fatores de risco médico
description The world is facing the coronavirus pandemic (COVID-19), which began in China. By August 18, 2020, the United States, Brazil, and India were the most affected countries. Health infrastructure and socioeconomic vulnerabilities may be affecting the response capacities of these countries. We compared official indicators to identify which vulnerabilities better determined the exposure risk to COVID-19 in both the most and least affected countries. To achieve this purpose, we collected indicators from the Infectious Disease Vulnerability Index (IDVI), the World Health Organization (WHO), the World Bank, and the Brazilian Geography and Statistics Institute (IBGE). All indicators were normalized to facilitate comparisons. Speed, incidence, and population were used to identify the groups of countries with the highest and lowest risks of infection. Countries’ response capacities were determined based on socioeconomic, political, and health infrastructure conditions. Vulnerabilities were identified based on the indicator sensitivity. The highest-risk group included the U.S., Brazil, and India, whereas the lowest-risk group (with the largest population by continent) consisted of China, New Zealand, and Germany. The high-sensitivity cluster had 18 indicators (50% extra IDVI), such as merchandise trade, immunization, public services, maternal mortality, life expectancy at birth, hospital beds, GINI index, adolescent fertility, governance, political stability, transparency/corruption, industry, and water supply. The greatest vulnerability of the highest-risk group was related first to economic factors (merchandise trade), followed by public health (immunization), highlighting global dependence on Chinese trade, such as protective materials, equipment, and diagnostic tests. However, domestic political factors had more indicators, beginning with high sensitivity and followed by healthcare and economic conditions, which signified a lesser capacity to guide, coordinate, and supply the population with protective measures, such as social distancing.
publishDate 2021
dc.date.none.fl_str_mv 2021-11-17T17:05:12Z
2021-11-17T17:05:12Z
2021
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv CARTAXO, A. N. S. et al. The exposure risk to COVID-19 in most affected countries: a vulnerability assessment model. PLoS ONE, [S. l.], v. 16, n. 3, e0248075, 2021. DOI: 10.1371/journal.pone.0248075.
http://repositorio.ufla.br/jspui/handle/1/48487
identifier_str_mv CARTAXO, A. N. S. et al. The exposure risk to COVID-19 in most affected countries: a vulnerability assessment model. PLoS ONE, [S. l.], v. 16, n. 3, e0248075, 2021. DOI: 10.1371/journal.pone.0248075.
url http://repositorio.ufla.br/jspui/handle/1/48487
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv PLoS ONE
publisher.none.fl_str_mv PLoS ONE
dc.source.none.fl_str_mv PLoS ONE
reponame:Repositório Institucional da UFLA
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instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
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reponame_str Repositório Institucional da UFLA
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