14
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Longitudinal Surveillance for SARS-CoV-2 Among Staff in Six Colorado Long-Term Care Facilities: Epidemiologic, Virologic and Sequence Analysis

      Preprint
      research-article

      Read this article at

      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

          Background:

          SARS-CoV-2 emerged in 2019 and has become a major global pathogen. Its emergence is notable due to its impacts on individuals residing within long term care facilities (LTCFs) such as rehabilitation centers and nursing homes. LTCF residents tend to possess several risk factors for more severe SARS-CoV-2 outcomes, including advanced age and multiple comorbidities. Indeed, residents of LTCFs represent approximately 40% of SARS-CoV-2 deaths in the United States.

          Methods:

          To assess the prevalence and incidence of SARS-CoV-2 among LTCF workers, determine the extent of asymptomatic SARS-CoV-2 infection, and provide information on the genomic epidemiology of the virus within these unique care settings, we collected nasopharyngeal swabs from workers for 8–11 weeks at six Colorado LTCFs, determined the presence and level of viral RNA and infectious virus within these samples, and sequenced 54 nearly complete genomes.

          Findings:

          Our data reveal a strikingly high degree of asymptomatic/mildly symptomatic infection, a strong correlation between viral RNA and infectious virus, prolonged infections and persistent RNA in a subset of individuals, and declining incidence over time.

          Interpretation:

          Our data suggest that asymptomatic SARS-CoV-2 infected individuals contribute to virus persistence and transmission within the workplace, due to high levels of virus. Genetic epidemiology revealed that SARS-CoV-2 likely spreads between staff within an LTCF.

          Funding:

          Colorado State University Colleges of Health and Human Sciences, Veterinary Medicine and Biomedical Sciences, Natural Sciences, and Walter Scott, Jr. College of Engineering, the Columbine Health Systems Center for Healthy Aging, and the National Institute of Allergy and Infectious Diseases.

          Related collections

          Most cited references44

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

          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
            Bookmark
            • 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: not found

              The REDCap consortium: Building an international community of software platform partners

              The Research Electronic Data Capture (REDCap) data management platform was developed in 2004 to address an institutional need at Vanderbilt University, then shared with a limited number of adopting sites beginning in 2006. Given bi-directional benefit in early sharing experiments, we created a broader consortium sharing and support model for any academic, non-profit, or government partner wishing to adopt the software. Our sharing framework and consortium-based support model have evolved over time along with the size of the consortium (currently more than 3200 REDCap partners across 128 countries). While the "REDCap Consortium" model represents only one example of how to build and disseminate a software platform, lessons learned from our approach may assist other research institutions seeking to build and disseminate innovative technologies.
                Bookmark

                Author and article information

                Journal
                medRxiv
                MEDRXIV
                medRxiv
                Cold Spring Harbor Laboratory
                05 November 2020
                : 2020.06.08.20125989
                Affiliations
                [1 ]Arthropod-Borne and Infectious Diseases Laboratory, Department of Microbiology, Immunology and Pathology, Colorado State University, Ft. Collins, CO 80526.
                [2 ]Department of Geriatric Medicine, University of Colorado Medical Center
                [3 ]Vivage Senior Living, Denver, CO 80228
                [4 ]Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado, Anschutz, Aurora, CO 80045
                [5 ]Columbine Health Systems Center for Healthy Aging and Department of Clinical Sciences, Colorado State University, Fort Collins, CO 80523
                Author notes
                [*]

                Co-first authors

                Addresses for Correspondence: Gregory D. Ebel, Sc.D., Professor, Department of Microbiology, Immunology and Pathology, Director, Arthropod-Borne and Infectious Diseases Laboratories, Colorado State University, Ft. Collins, CO 80526, gregory.ebel@ 123456colostate.edu , Nicole Ehrhart, VMD, MS, Diplomate ACVS, Professor, Surgical Oncology, Department of Clinical Sciences, School of Biomedical Engineering, Flint Animal Cancer Center, Colorado State University, Ft. Collins, CO 80526, nicole.ehrhart@ 123456colostate.edu
                Article
                10.1101/2020.06.08.20125989
                7302309
                32577700
                52f90188-2265-4aff-a645-33671689f65b

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

                History
                Categories
                Article

                Comments

                Comment on this article