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      Parental COVID-19 vaccine hesitancy for children: vulnerability in an urban hotspot

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          Abstract

          Objective

          To compare hesitancy toward a future COVID-19 vaccine for children of various sociodemographic groups in a major metropolitan area, and to understand how parents obtain information about COVID-19.

          Methods

          Cross-sectional online survey of parents with children < 18 years old in Chicago and Cook County, Illinois, in June 2020. We used logistic regression to determine the odds of parental COVID-19 vaccine hesitancy (VH) for racial/ethnic and socioeconomic groups, controlling for sociodemographic factors and the sources where parents obtain information regarding COVID-19.

          Results

          Surveys were received from 1702 parents and 1425 were included in analyses. Overall, 33% of parents reported VH for their child. COVID-19 VH was higher among non-Hispanic Black parents compared with non-Hispanic White parents (Odds Ratio (OR) 2.65, 95% Confidence Interval (CI): (1.99–3.53), parents of publicly insured children compared with privately insured (OR 1.93, (1.53–2.42)) and among lower income groups. Parents receive information about COVID-19 from a variety of sources, and those who report using family, internet and health care providers as information sources (compared to those who don’t use each respective source) had lower odds of COVID-19 VH for their children.

          Conclusions

          The highest rates of hesitancy toward a future COVID-19 vaccine were found in demographic groups that have been the most severely affected by the pandemic. These groups may require targeted outreach efforts from trusted sources of information in order to promote equitable uptake of a future COVID-19 vaccine.

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          Most cited references30

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          An interactive web-based dashboard to track COVID-19 in real time

          In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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            The Disproportionate Impact of COVID-19 on Racial and Ethnic Minorities in the United States

            Abstract The COVID-19 pandemic has disproportionately affected racial and ethnic minority groups, with high rates of death in African American, Native American, and LatinX communities. While the mechanisms of these disparities are being investigated, they can be conceived as arising from biomedical factors as well as social determinants of health. Minority groups are disproportionately affected by chronic medical conditions and lower access to healthcare that may portend worse COVID-19 outcomes. Furthermore, minority communities are more likely to experience living and working conditions that predispose them to worse outcomes. Underpinning these disparities are long-standing structural and societal factors that the COVID-19 pandemic has exposed. Clinicians can partner with patients and communities to reduce the short-term impact of COVID-19 disparities while advocating for structural change.
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              Herd Immunity: Understanding COVID-19

              The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its associated disease, COVID-19, has demonstrated the devastating impact of a novel, infectious pathogen on a susceptible population. Here, we explain the basic concepts of herd immunity and discuss its implications in the context of COVID-19.
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                Author and article information

                Contributors
                jkusma@luriechildrens.org
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                13 September 2021
                13 September 2021
                2021
                : 21
                : 1662
                Affiliations
                [1 ]GRID grid.413808.6, ISNI 0000 0004 0388 2248, Division of Advanced General Pediatrics and Primary Care, , Ann & Robert H. Lurie Children’s Hospital of Chicago, ; 225 E Chicago Ave, Box 162, Chicago, IL 60611 USA
                [2 ]GRID grid.413808.6, ISNI 0000 0004 0388 2248, Mary Ann & J. Milburn Smith Child Health Outcomes, Research, and Evaluation Center; Stanley Manne Children’s Research Institute, , Ann & Robert H. Lurie Children’s Hospital of Chicago, ; Chicago, IL USA
                [3 ]GRID grid.16753.36, ISNI 0000 0001 2299 3507, Department of Pediatrics, , Northwestern University Feinberg School of Medicine, ; Chicago, IL USA
                [4 ]GRID grid.16753.36, ISNI 0000 0001 2299 3507, Department of Medicine, Medical Social Sciences, and Preventive Medicine, , Northwestern University Feinberg School of Medicine, ; Chicago, IL USA
                [5 ]GRID grid.413808.6, ISNI 0000 0004 0388 2248, Division of Emergency Medicine, , Ann & Robert H. Lurie Children’s Hospital of Chicago, ; Chicago, IL USA
                Article
                11725
                10.1186/s12889-021-11725-5
                8436579
                34517848
                4da5eb4c-843a-4e04-899d-c3cfba6e464d
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 11 February 2021
                : 29 August 2021
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Public health
                covid-19,vaccine hesitancy,health equity
                Public health
                covid-19, vaccine hesitancy, health equity

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