8
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Monitoring trends and differences in COVID-19 case-fatality rates using decomposition methods: Contributions of age structure and age-specific fatality

      research-article

      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

          The population-level case-fatality rate (CFR) associated with COVID-19 varies substantially, both across countries at any given time and within countries over time. We analyze the contribution of two key determinants of the variation in the observed CFR: the age-structure of diagnosed infection cases and age-specific case-fatality rates. We use data on diagnosed COVID-19 cases and death counts attributable to COVID-19 by age for China, Germany, Italy, South Korea, Spain, the United States, and New York City. We calculate the CFR for each population at the latest data point and also for Italy, Germany, Spain, and New York City over time. We use demographic decomposition to break the difference between CFRs into unique contributions arising from the age-structure of confirmed cases and the age-specific case-fatality. In late June 2020, CFRs varied from 2.2% in South Korea to 14.0% in Italy. The age-structure of detected cases often explains more than two-thirds of cross-country variation in the CFR. In Italy, the CFR increased from 4.2% to 14.0% between March 9 and June 30, 2020, and more than 90% of the change was due to increasing age-specific case-fatality rates. The importance of the age-structure of confirmed cases likely reflects several factors, including different testing regimes and differences in transmission trajectories; while increasing age-specific case-fatality rates in Italy could indicate other factors, such as the worsening health outcomes of those infected with COVID-19. Our findings lend support to recommendations for data to be disaggregated by age, and potentially other variables, to facilitate a better understanding of population-level differences in CFRs. They also show the need for well-designed seroprevalence studies to ascertain the extent to which differences in testing regimes drive differences in the age-structure of detected cases.

          Related collections

          Most cited references23

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

          Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia

          Abstract Background The initial cases of novel coronavirus (2019-nCoV)–infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the first 425 confirmed cases in Wuhan to determine the epidemiologic characteristics of NCIP. Methods We collected information on demographic characteristics, exposure history, and illness timelines of laboratory-confirmed cases of NCIP that had been reported by January 22, 2020. We described characteristics of the cases and estimated the key epidemiologic time-delay distributions. In the early period of exponential growth, we estimated the epidemic doubling time and the basic reproductive number. Results Among the first 425 patients with confirmed NCIP, the median age was 59 years and 56% were male. The majority of cases (55%) with onset before January 1, 2020, were linked to the Huanan Seafood Wholesale Market, as compared with 8.6% of the subsequent cases. The mean incubation period was 5.2 days (95% confidence interval [CI], 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days. In its early stages, the epidemic doubled in size every 7.4 days. With a mean serial interval of 7.5 days (95% CI, 5.3 to 19), the basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9). Conclusions On the basis of this information, there is evidence that human-to-human transmission has occurred among close contacts since the middle of December 2019. Considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere. Measures to prevent or reduce transmission should be implemented in populations at risk. (Funded by the Ministry of Science and Technology of China and others.)
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found

            Case-Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy

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

              Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis

              Highlights • COVID -19 cases are now confirmed in multiple countries. • Assessed the prevalence of comorbidities in infected patients. • Comorbidities are risk factors for severe compared with non-severe patients. • Help the health sector guide vulnerable populations and assess the risk of deterioration.
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: SoftwareRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: SoftwareRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                10 September 2020
                2020
                10 September 2020
                : 15
                : 9
                Affiliations
                [1 ] Max Planck Institute for Demographic Research, Rostock, Germany
                [2 ] Sapienza University of Rome, Rome, Italy
                [3 ] Interdisciplinary Centre on Population Dynamics, University of Southern Denmark, Odense, Denmark
                [4 ] Population Research Unit, University of Helsinki, Helsinki, Finland
                University of Louvain, BELGIUM
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Article
                PONE-D-20-12360
                10.1371/journal.pone.0238904
                7482960
                7f1af514-f1b7-457b-9b34-3c17454e3e0f
                © 2020 Dudel et al

                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.

                Page count
                Figures: 1, Tables: 3, Pages: 11
                Product
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100010663, H2020 European Research Council;
                Award ID: 716323
                Award Recipient :
                Funded by: Social Sciences and Humanities Research Council
                Award Recipient :
                Funded by: Fonds de recherche du Québec – Société et culture
                Award Recipient :
                AvR received funding from the European Research Council (Grant # 716323; https://erc.europa.eu/). EA was financially supported by the Social Sciences and Humanities Research Council ( https://www.sshrc-crsh.gc.ca) and the Fonds de recherche du Québec – Société et culture ( http://www.scientifique-en-chef.gouv.qc.ca/le-scientifique-en-chef/les-fonds-de-recherche-du-quebec/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. All other authors received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Viral Diseases
                Covid 19
                People and places
                Geographical locations
                Europe
                European Union
                Italy
                People and places
                Geographical locations
                Asia
                South Korea
                Medicine and Health Sciences
                Diagnostic Medicine
                Virus Testing
                People and places
                Geographical locations
                Europe
                European Union
                Germany
                People and Places
                Population Groupings
                Age Groups
                People and places
                Geographical locations
                Europe
                European Union
                Spain
                People and places
                Geographical locations
                North America
                United States
                New York
                Custom metadata
                All code and data is available from a repository on the Open Science Framework, DOI 10.17605/OSF.IO/VDGWT.
                COVID-19

                Uncategorized
                Uncategorized

                Comments

                Comment on this article