For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
5
views
15
references
 Top references
cited by
128
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
2 collections
    0
    shares
      367
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Elderly people and responses to COVID-19 in 27 Countries

      research-article
      Author(s): 1 , 2 , *
      Editor(s):
      Publication date (Electronic):
      Journal: PLoS ONE
      Publisher: Public Library of Science

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Amongst the most robust consensus related to the COVID-19 disease is that the elderly are by far the most vulnerable population group. Hence, public authorities target older people in order to convince them to comply with preventive measures. However, we still know little about older people’s attitudes and compliance toward these measures. In this research, I aim to improve our understanding of elderly people’s responses to the pandemic using data from 27 countries. Results are surprising and quite troubling. Elderly people’s response is substantially similar to their fellow citizens in their 50’s and 60’s. This research (i) provides the first thorough description of the most vulnerable population’s attitudes and compliance in a comparative perspective (ii) suggest that governments’ strategies toward elderly people are far from successful and (iii) shows that methodologically, we should be more cautious in treating age as having a linear effect on COVID-19 related outcomes.

          Related collections

          Most cited references15

          • Record: found
          • Abstract: found
          • Article: not found

          Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

          Fei Zhou, Ting Yu, Ronghui Du … (2020)
          Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
          Article 0 comments Cited 13463 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Covid-19: risk factors for severe disease and death

            Rachel E Jordan, Peymané Adab, K K Cheng (2020)
            Article 0 comments Cited 740 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Demographic science aids in understanding the spread and fatality rates of COVID-19

              Jennifer Dowd, Liliana Andriano, David M. Brazel … (2020)
              Governments around the world must rapidly mobilize and make difficult policy decisions to mitigate the coronavirus disease 2019 (COVID-19) pandemic. Because deaths have been concentrated at older ages, we highlight the important role of demography, particularly, how the age structure of a population may help explain differences in fatality rates across countries and how transmission unfolds. We examine the role of age structure in deaths thus far in Italy and South Korea and illustrate how the pandemic could unfold in populations with similar population sizes but different age structures, showing a dramatically higher burden of mortality in countries with older versus younger populations. This powerful interaction of demography and current age-specific mortality for COVID-19 suggests that social distancing and other policies to slow transmission should consider the age composition of local and national contexts as well as intergenerational interactions. We also call for countries to provide case and fatality data disaggregated by age and sex to improve real-time targeted forecasting of hospitalization and critical care needs.
              Article 0 comments Cited 402 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Contributors
                J. -F. Daoust:
                ORCID: http://orcid.org/0000-0002-2736-7430
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Wen-Jun Tu: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 2 July 2020
                Publication date Collection: 2020
                Publication date PMC-release: 2 July 2020
                Volume: 15
                Issue: 7
                Electronic Location Identifier: e0235590
                Affiliations
                [1 ] School of Social and Political Science, Politics and International Relations, University of Edinburgh, Edinburgh, Scotland, United Kingdom
                [2 ] Center for the Study of Democratic Citizenship, Montreal, Quebec, Canada
                Chinese Academy of Medical Sciences and Peking Union Medical College, CHINA
                Author notes

                Competing Interests: YouGov provided the datasets pro bono to Imperial College London and the Institute of Global Health Innovation. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Author information
                http://orcid.org/0000-0002-2736-7430
                Article
                Publisher ID: PONE-D-20-14858
                DOI: 10.1371/journal.pone.0235590
                PMC ID: 7332014
                PubMed ID: 32614889
                SO-VID: a8935c05-09c3-4910-9304-42587cfdbda4
                Copyright © © 2020 J. -F. Daoust
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 19 May 2020
                Date accepted : 19 June 2020
                Page count
                Figures: 4, Tables: 0, Pages: 13
                Funding
                The author received no specific funding (or salary) for this work.
                Categories
                Subject: Research Article
                Subject: People and Places
                Subject: Population Groupings
                Subject: Age Groups
                Subject: Elderly
                Subject: Medicine and Health Sciences
                Subject: Geriatrics
                Subject: Medicine and Health Sciences
                Subject: Public and Occupational Health
                Subject: People and Places
                Subject: Population Groupings
                Subject: Age Groups
                Subject: Physical Sciences
                Subject: Mathematics
                Subject: Operator Theory
                Subject: Kernel Functions
                Subject: Social Sciences
                Subject: Sociology
                Subject: Social Research
                Subject: Biology and Life Sciences
                Subject: Population Biology
                Subject: Population Metrics
                Subject: Death Rates
                Subject: Research and Analysis Methods
                Subject: Research Design
                Subject: Survey Research
                Subject: Surveys
                Custom metadata
                Data Availability The data were downloaded from the publicly accessible github of ICL and YouGov: https://github.com/YouGov-Data/covid-19-tracker. The replications files (datasets and code) are available on Harvard dataverse: https://doi.org/10.7910/DVN/8UTBVA.
                Outbreaks COVID-19

                ScienceOpen disciplines: Uncategorized
                Data availability:
                ScienceOpen disciplines: Uncategorized

                Comments

                Comment on this article

                scite_

                Similar content367

                See all similar

                Cited by125

                See all cited by

                Most referenced authors456

                See all reference authors