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      Trust and experiences of National Health Service healthcare do not fully explain demographic disparities in coronavirus vaccination uptake in the UK: a cross-sectional study

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          Abstract

          Objective

          To test whether demographic variation in vaccine hesitancy can be explained by trust and healthcare experiences.

          Design

          Cross-sectional study.

          Setting

          Data collected online in April 2021.

          Participants

          Data were collected from 4885 UK resident adults, of whom 3223 had received the invitation to be vaccinated against the novel coronavirus and could therefore be included in the study. 1629 included participants identified as female and 1594 as male. 234 identified as belonging to other than white ethnic groups, while 2967 identified as belonging to white ethnic groups.

          Primary and secondary outcome measures

          Uptake of coronavirus vaccination.

          Results

          Membership of an other than white ethnic group (adjusted OR (AOR)=0.53, 95% CI 0.35 to 0.84, p=0.005) and age (AOR=1.61, 95% CI 1.39 to 1.87, p<0.001 for a 1 SD change from the mean) were the only statistically significant demographic predictors of vaccine uptake. After controls for National Health Service (NHS) healthcare experiences and trust in government, scientists and medical professionals, the effect associated with membership of an other than white ethnic group appears more marginal (AOR=0.61, 95% CI 0.38 to 1.01, p=0.046), while the effect associated with age remains virtually unchanged. Exploratory analysis suggests that NHS healthcare experiences mediate 24% (95% CI 8% to 100%, p=0.024) of the association between ethnicity and uptake, while trust mediates 94% (95% CI 56% to 100%, p=0.001) of the association between NHS healthcare experiences and uptake.

          Conclusions

          Members of other than white ethnic groups report inferior NHS healthcare experiences, potentially explaining their lower reported trust in government, scientists and medical professionals. However, this does not fully explain the ethnic gap in coronavirus vaccination uptake.

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          Most cited references29

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          Vaccine hesitancy: Definition, scope and determinants.

          The SAGE Working Group on Vaccine Hesitancy concluded that vaccine hesitancy refers to delay in acceptance or refusal of vaccination despite availability of vaccination services. Vaccine hesitancy is complex and context specific, varying across time, place and vaccines. It is influenced by factors such as complacency, convenience and confidence. The Working Group retained the term 'vaccine' rather than 'vaccination' hesitancy, although the latter more correctly implies the broader range of immunization concerns, as vaccine hesitancy is the more commonly used term. While high levels of hesitancy lead to low vaccine demand, low levels of hesitancy do not necessarily mean high vaccine demand. The Vaccine Hesitancy Determinants Matrix displays the factors influencing the behavioral decision to accept, delay or reject some or all vaccines under three categories: contextual, individual and group, and vaccine/vaccination-specific influences.
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            High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2

            Severe acute respiratory syndrome coronavirus 2 is the causative agent of the ongoing coronavirus disease pandemic. Initial estimates of the early dynamics of the outbreak in Wuhan, China, suggested a doubling time of the number of infected persons of 6–7 days and a basic reproductive number (R0) of 2.2–2.7. We collected extensive individual case reports across China and estimated key epidemiologic parameters, including the incubation period (4.2 days). We then designed 2 mathematical modeling approaches to infer the outbreak dynamics in Wuhan by using high-resolution domestic travel and infection data. Results show that the doubling time early in the epidemic in Wuhan was 2.3–3.3 days. Assuming a serial interval of 6–9 days, we calculated a median R0 value of 5.7 (95% CI 3.8–8.9). We further show that active surveillance, contact tracing, quarantine, and early strong social distancing efforts are needed to stop transmission of the virus.
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              R: A languange and environment for statistical computing

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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2022
                18 March 2022
                18 March 2022
                : 12
                : 3
                : e053827
                Affiliations
                [1 ]departmentDepartment of Digital Humanities , King's College London , London, UK
                [2 ]departmentSheffield Methods Institute , University of Sheffield , Sheffield, UK
                [3 ]departmentPolicy Institute , King's College London , London, UK
                Author notes
                [Correspondence to ] Dr Daniel Allington; daniel.allington@ 123456kcl.ac.uk
                Author information
                http://orcid.org/0000-0002-5378-0552
                Article
                bmjopen-2021-053827
                10.1136/bmjopen-2021-053827
                8935008
                35304394
                eb175e36-994b-4b5a-82d3-7c362c30fde4
                © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/.

                History
                : 29 May 2021
                : 02 February 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000269, Economic and Social Research Council;
                Award ID: ES/V015494/1
                Categories
                Public Health
                1506
                2474
                1724
                Original research
                Custom metadata
                unlocked

                Medicine
                public health,covid-19
                Medicine
                public health, covid-19

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