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      Experiences with COVID-19 case investigation and contact tracing: A qualitative analysis

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          Abstract

          Case investigation and contact tracing (CI/CT) is a critical part of the public health response to COVID-19. Individuals’ experiences with CI/CT for COVID-19 varied based on geographic location, changes in knowledge and guidelines, access to testing and vaccination, as well as demographic characteristics including age, race, ethnicity, income, and political ideology. In this paper, we explore the experiences and behaviors of adults with positive SARS-CoV-2 test results, or who were exposed to a person with COVID-19, to understand their knowledge, motivations, and facilitators and barriers to their actions. We conducted focus groups and one-on-one interviews with 94 cases and 90 contacts from across the United States. We found that participants were concerned about infecting or exposing others, which motivated them to isolate or quarantine, notify contacts, and get tested. Although most cases and contacts were not contacted by CI/CT professionals, those who were reported a positive experience and received helpful information. Many cases and contacts reported seeking information from family, friends, health care providers, as well as television news and Internet sources. Although participants reported similar perspectives and experiences across demographic characteristics, some highlighted inequities in receiving COVID-19 information and resources.

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          The Social Amplification of Risk: A Conceptual Framework

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            Is Open Access

            Reducing and meta-analysing estimates from distributed lag non-linear models

            Background The two-stage time series design represents a powerful analytical tool in environmental epidemiology. Recently, models for both stages have been extended with the development of distributed lag non-linear models (DLNMs), a methodology for investigating simultaneously non-linear and lagged relationships, and multivariate meta-analysis, a methodology to pool estimates of multi-parameter associations. However, the application of both methods in two-stage analyses is prevented by the high-dimensional definition of DLNMs. Methods In this contribution we propose a method to synthesize DLNMs to simpler summaries, expressed by a reduced set of parameters of one-dimensional functions, which are compatible with current multivariate meta-analytical techniques. The methodology and modelling framework are implemented in R through the packages dlnm and mvmeta. Results As an illustrative application, the method is adopted for the two-stage time series analysis of temperature-mortality associations using data from 10 regions in England and Wales. R code and data are available as supplementary online material. Discussion and Conclusions The methodology proposed here extends the use of DLNMs in two-stage analyses, obtaining meta-analytical estimates of easily interpretable summaries from complex non-linear and delayed associations. The approach relaxes the assumptions and avoids simplifications required by simpler modelling approaches.
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              Trends in Racial and Ethnic Disparities in COVID-19 Hospitalizations, by Region — United States, March–December 2020

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                Author and article information

                Journal
                SSM Qual Res Health
                SSM Qual Res Health
                Ssm. Qualitative Research in Health
                Published by Elsevier Ltd.
                2667-3215
                3 March 2023
                3 March 2023
                : 100244
                Affiliations
                [a ]U.S. Centers for Disease Control and Prevention, COVID-19 Response Team, Atlanta, GA, USA
                [b ]Mathematica, Cambridge, MA, USA
                Author notes
                []Corresponding author. US Centers for Disease Control and Prevention, 1600 Clifton Road NE, Atlanta, GA, 30333, USA.
                Article
                S2667-3215(23)00028-8 100244
                10.1016/j.ssmqr.2023.100244
                9981264
                36896252
                6318cbc0-2f5c-4cc6-b9a2-a142711e21f5
                © 2023 Published by Elsevier Ltd.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 28 October 2022
                : 27 February 2023
                : 1 March 2023
                Categories
                Article

                covid-19,case investigation,contact tracing,isolation,quarantine,health equity

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