Literature DB >> 33662028

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

Adriana Nascimento Santos Cartaxo1, Francisco Iran Cartaxo Barbosa2, Paulo Henrique de Souza Bermejo3, Marina Figueiredo Moreira4, David Nadler Prata5.   

Abstract

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.

Entities:  

Year:  2021        PMID: 33662028     DOI: 10.1371/journal.pone.0248075

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  5 in total

1.  5G, Big Data, and AI for Smart City and Prevention of Virus Infection.

Authors:  Shumin Ren; Bairong Shen
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 2.622

2.  COVID-19 and Pro-environmental Behaviour at Destinations Amongst International Travellers.

Authors:  Gary Calder; Aleksandar Radic; Hyungseo Bobby Ryu; Antonio Ariza-Montes; Heesup Han
Journal:  Front Psychol       Date:  2022-04-14

3.  A Proactive Approach to Identify the Exposure Risk to COVID-19: Validation of the Pandemic Risk Exposure Measurement (PREM) Model Using Real-World Data.

Authors:  Simon Grima; Ramona Rupeika-Apoga; Murat Kizilkaya; Inna Romānova; Rebecca Dalli Gonzi; Mihajlo Jakovljevic
Journal:  Risk Manag Healthc Policy       Date:  2021-11-26

4.  Investigating the effect of macro-scale estimators on worldwide COVID-19 occurrence and mortality through regression analysis using online country-based data sources.

Authors:  Sabri Erdem; Fulya Ipek; Aybars Bars; Volkan Genç; Esra Erpek; Shabnam Mohammadi; Anıl Altınata; Servet Akar
Journal:  BMJ Open       Date:  2022-02-14       Impact factor: 2.692

Review 5.  Global mapping of epidemic risk assessment toolkits: A scoping review for COVID-19 and future epidemics preparedness implications.

Authors:  Bach Xuan Tran; Long Hoang Nguyen; Linh Phuong Doan; Tham Thi Nguyen; Giang Thu Vu; Hoa Thi Do; Huong Thi Le; Carl A Latkin; Cyrus S H Ho; Roger C M Ho
Journal:  PLoS One       Date:  2022-09-23       Impact factor: 3.752

  5 in total

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