Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study
Introduction: Before the mass vaccination, epidemiological control measures were the only means of containing the COVID-19 epidemic. Their effectiveness determined the consequences of the COVID-19 epidemic. Our study evaluated the impact of sociodemographic, lifestyle, and clinical factors on patien...
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MDPI AG
2023-04-01
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Online Access: | https://www.mdpi.com/2227-9032/11/9/1220 |
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author | Rahul Naresh Wasnik Ferenc Vincze Anett Földvári Anita Pálinkás János Sándor |
author_facet | Rahul Naresh Wasnik Ferenc Vincze Anett Földvári Anita Pálinkás János Sándor |
author_sort | Rahul Naresh Wasnik |
collection | DOAJ |
description | Introduction: Before the mass vaccination, epidemiological control measures were the only means of containing the COVID-19 epidemic. Their effectiveness determined the consequences of the COVID-19 epidemic. Our study evaluated the impact of sociodemographic, lifestyle, and clinical factors on patient-reported epidemiological control measures. Methods: A nationwide representative sample of 1008 randomly selected adults were interviewed in person between 15 March and 30 May 2021. The prevalence of test-confirmed SARS-CoV-2 infection was 12.1%, of testing was 33.7%, and of contact tracing among test-confirmed infected subjects was 67.9%. The vaccination coverage was 52.4%. Results: According to the multivariable logistic regression models, the occurrence of infection was not influenced by sociodemographic and lifestyle factors or by the presence of chronic disease. Testing was more frequent among middle-aged adults (aOR = 1.53, 95% CI 1.10–2.13) and employed adults (aOR = 2.06, 95% CI 1.42–3.00), and was more frequent among adults with a higher education (aOR<sub>secondary</sub> = 1.93, 95% CI 1.20–3.13; aOR<sub>tertiary</sub> = 3.19, 95% CI 1.81–5.63). Contact tracing was more frequently implemented among middle-aged (aOR41-7y = 3.33, 95% CI 1.17–9.45) and employed (aOR = 4.58, 95% CI 1.38–15.22), and those with chronic diseases (aOR = 5.92, 95% CI 1.56–22.47). Positive correlation was observed between age groups and vaccination frequency (aOR41-70y = 2.94, 95% CI 2.09–4.15; aOR71+y = 14.52, 95% CI 7.33–28.77). Higher than primary education (aOR<sub>secondary</sub> = 1.69, 95% CI 1.08–2.63; aOR<sub>tertiary</sub> = 4.36, 95% CI 2.46–7.73) and the presence of a chronic disease (aOR = 2.58, 95% CI 1.75–3.80) positively impacted vaccination. Regular smoking was inversely correlated with vaccination (aOR = 0.60; 95% CI 0.44–0.83). Conclusions: The survey indicated that testing, contact tracing, and vaccination were seriously influenced by socioeconomic position; less so by chronic disease prevalence and very minimally by lifestyle. The etiological role of socioeconomic inequalities in epidemic measure implementation likely generated socioeconomic inequality in COVID-19-related complication and death rates. |
first_indexed | 2024-03-11T04:17:56Z |
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spelling | doaj.art-2f4407aea85b4b63a755256ea6410dd82023-11-17T22:56:59ZengMDPI AGHealthcare2227-90322023-04-01119122010.3390/healthcare11091220Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional StudyRahul Naresh Wasnik0Ferenc Vincze1Anett Földvári2Anita Pálinkás3János Sándor4Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, H-4002 Debrecen, HungaryDepartment of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, H-4002 Debrecen, HungaryDoctoral School of Health Sciences, University of Debrecen, H-4002 Debrecen, HungaryELKH-DE Public Health Research Group, Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, H-4002 Debrecen, HungaryDepartment of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, H-4002 Debrecen, HungaryIntroduction: Before the mass vaccination, epidemiological control measures were the only means of containing the COVID-19 epidemic. Their effectiveness determined the consequences of the COVID-19 epidemic. Our study evaluated the impact of sociodemographic, lifestyle, and clinical factors on patient-reported epidemiological control measures. Methods: A nationwide representative sample of 1008 randomly selected adults were interviewed in person between 15 March and 30 May 2021. The prevalence of test-confirmed SARS-CoV-2 infection was 12.1%, of testing was 33.7%, and of contact tracing among test-confirmed infected subjects was 67.9%. The vaccination coverage was 52.4%. Results: According to the multivariable logistic regression models, the occurrence of infection was not influenced by sociodemographic and lifestyle factors or by the presence of chronic disease. Testing was more frequent among middle-aged adults (aOR = 1.53, 95% CI 1.10–2.13) and employed adults (aOR = 2.06, 95% CI 1.42–3.00), and was more frequent among adults with a higher education (aOR<sub>secondary</sub> = 1.93, 95% CI 1.20–3.13; aOR<sub>tertiary</sub> = 3.19, 95% CI 1.81–5.63). Contact tracing was more frequently implemented among middle-aged (aOR41-7y = 3.33, 95% CI 1.17–9.45) and employed (aOR = 4.58, 95% CI 1.38–15.22), and those with chronic diseases (aOR = 5.92, 95% CI 1.56–22.47). Positive correlation was observed between age groups and vaccination frequency (aOR41-70y = 2.94, 95% CI 2.09–4.15; aOR71+y = 14.52, 95% CI 7.33–28.77). Higher than primary education (aOR<sub>secondary</sub> = 1.69, 95% CI 1.08–2.63; aOR<sub>tertiary</sub> = 4.36, 95% CI 2.46–7.73) and the presence of a chronic disease (aOR = 2.58, 95% CI 1.75–3.80) positively impacted vaccination. Regular smoking was inversely correlated with vaccination (aOR = 0.60; 95% CI 0.44–0.83). Conclusions: The survey indicated that testing, contact tracing, and vaccination were seriously influenced by socioeconomic position; less so by chronic disease prevalence and very minimally by lifestyle. The etiological role of socioeconomic inequalities in epidemic measure implementation likely generated socioeconomic inequality in COVID-19-related complication and death rates.https://www.mdpi.com/2227-9032/11/9/1220COVID-19 epidemicepidemiological measureseffectivenesssocial statusinequalities |
spellingShingle | Rahul Naresh Wasnik Ferenc Vincze Anett Földvári Anita Pálinkás János Sándor Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study Healthcare COVID-19 epidemic epidemiological measures effectiveness social status inequalities |
title | Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study |
title_full | Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study |
title_fullStr | Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study |
title_full_unstemmed | Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study |
title_short | Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study |
title_sort | effectiveness of and inequalities in covid 19 epidemic control strategies in hungary a nationwide cross sectional study |
topic | COVID-19 epidemic epidemiological measures effectiveness social status inequalities |
url | https://www.mdpi.com/2227-9032/11/9/1220 |
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