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      Temporal changes in factors associated with COVID-19 vaccine hesitancy and uptake among adults in Hong Kong: Serial cross-sectional surveys

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          Summary

          Background

          COVID-19 vaccine hesitancy can lead to reduced vaccine uptake and hinder the safe relaxation of other public health measures. This study aims to explore the factors associated with vaccine hesitancy and uptake among adults before and after the implementation of the COVID-19 vaccination program in Hong Kong.

          Methods

          Cross-sectional telephone surveys were conducted every four weeks over a nine-month period from November 2020 through July 2021. Target respondents were Hong Kong resident aged 18 or above and recruited by random-digit dialling. In each survey, responses on COVID-19 vaccine hesitancy and COVID-19 vaccine uptake were collected as primary and secondary outcomes, respectively. Data of potentially associated factors, including socio-demographics, chronic medical conditions, perceived risk of COVID-19, perceived personal efficacy in self-protection, confidence in the government's ability to control the pandemic, compliance with social distancing measures, and confidence in COVID-19 vaccines, were also collected. Multivariable logistic regression models were used to examine the factors associated with COVID-19 vaccine hesitancy at different time points.

          Findings

          Ten cross-sectional surveys were conducted, including 7411 respondents. The levels of vaccine hesitancy fluctuated over time. From December 2020 to May 2021, the age group with the highest vaccine hesitancy was young adults 18–34y, while the vaccine hesitancy was highest among adults ≥ 65y in June-July 2021 (Fig. 2C). Our regression analyses (Fig. 3) showed that before and at the beginning of the rollout of the mass vaccination program, there was no statistically significant association between chronic medical conditions and vaccine hesitancy. However, two-five months after the program implementation respondents with chronic medical conditions were more likely to be hesitant. From January to June 2021, higher confidence in the government was associated with lower vaccine hesitancy (Fig. 3). Confidence in COVID-19 vaccines was consistently associated with lower vaccine hesitancy at different stages of the program.

          Interpretation

          The factors associated with COVID-19 vaccine hesitancy changed over time. This study highlighted the importance to monitor temporal changes in COVID-19 vaccine hesitancy and associated factors, and adjust promotion strategies correspondingly to boost vaccination uptake.

          Funding

          Health and Medical Research Fund, Hong Kong.

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          Most cited references26

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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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            Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis

            Background An epidemic of Coronavirus Disease 2019 (COVID-19) began in December 2019 and triggered a Public Health Emergency of International Concern (PHEIC). We aimed to find risk factors for the progression of COVID-19 to help reducing the risk of critical illness and death for clinical help. Methods The data of COVID-19 patients until March 20, 2020 were retrieved from four databases. We statistically analyzed the risk factors of critical/mortal and non-critical COVID-19 patients with meta-analysis. Results Thirteen studies were included in Meta-analysis, including a total number of 3027 patients with SARS-CoV-2 infection. Male, older than 65, and smoking were risk factors for disease progression in patients with COVID-19 (male: OR = 1.76, 95% CI (1.41, 2.18), P 40U/L, creatinine(Cr) ≥ 133mol/L, hypersensitive cardiac troponin I(hs-cTnI) > 28pg/mL, procalcitonin(PCT) > 0.5ng/mL, lactatede hydrogenase(LDH) > 245U/L, and D-dimer > 0.5mg/L predicted the deterioration of disease while white blood cells(WBC) 40U/L:OR=4.00, 95% CI (2.46, 6.52), P 28 pg/mL: OR = 43.24, 95% CI (9.92, 188.49), P 0.5 ng/mL: OR = 43.24, 95% CI (9.92, 188.49), P 245U/L: OR = 43.24, 95% CI (9.92, 188.49), P 0.5mg/L: OR = 43.24, 95% CI (9.92, 188.49), P < 0.00001; WBC < 4 × 109/L: OR = 0.30, 95% CI (0.17, 0.51), P < 0.00001]. Conclusion Male, aged over 65, smoking patients might face a greater risk of developing into the critical or mortal condition and the comorbidities such as hypertension, diabetes, cardiovascular disease, and respiratory diseases could also greatly affect the prognosis of the COVID-19. Clinical manifestation such as fever, shortness of breath or dyspnea and laboratory examination such as WBC, AST, Cr, PCT, LDH, hs-cTnI and D-dimer could imply the progression of COVID-19.
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              Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine through 6 Months

              Background BNT162b2 is a lipid nanoparticle–formulated, nucleoside-modified RNA vaccine encoding a prefusion-stabilized, membrane-anchored severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) full-length spike protein. BNT162b2 is highly efficacious against coronavirus disease 2019 (Covid-19) and is currently approved, conditionally approved, or authorized for emergency use worldwide. At the time of initial authorization, data beyond 2 months after vaccination were unavailable. Methods In an ongoing, placebo-controlled, observer-blinded, multinational, pivotal efficacy trial, we randomly assigned 44,165 participants 16 years of age or older and 2264 participants 12 to 15 years of age to receive two 30-μg doses, at 21 days apart, of BNT162b2 or placebo. The trial end points were vaccine efficacy against laboratory-confirmed Covid-19 and safety, which were both evaluated through 6 months after vaccination. Results BNT162b2 continued to be safe and have an acceptable adverse-event profile. Few participants had adverse events leading to withdrawal from the trial. Vaccine efficacy against Covid-19 was 91.3% (95% confidence interval [CI], 89.0 to 93.2) through 6 months of follow-up among the participants without evidence of previous SARS-CoV-2 infection who could be evaluated. There was a gradual decline in vaccine efficacy. Vaccine efficacy of 86 to 100% was seen across countries and in populations with diverse ages, sexes, race or ethnic groups, and risk factors for Covid-19 among participants without evidence of previous infection with SARS-CoV-2. Vaccine efficacy against severe disease was 96.7% (95% CI, 80.3 to 99.9). In South Africa, where the SARS-CoV-2 variant of concern B.1.351 (or beta) was predominant, a vaccine efficacy of 100% (95% CI, 53.5 to 100) was observed. Conclusions Through 6 months of follow-up and despite a gradual decline in vaccine efficacy, BNT162b2 had a favorable safety profile and was highly efficacious in preventing Covid-19. (Funded by BioNTech and Pfizer; ClinicalTrials.gov number, NCT04368728 .)
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                Author and article information

                Contributors
                Journal
                Lancet Reg Health West Pac
                Lancet Reg Health West Pac
                The Lancet Regional Health: Western Pacific
                Elsevier
                2666-6065
                29 March 2022
                June 2022
                29 March 2022
                : 23
                : 100441
                Affiliations
                [a ]World Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong Special Administrative Region, China
                [b ]Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China
                [c ]State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong Special Administrative Region, China
                [d ]Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Hong Kong Special Administrative Region, China
                Author notes
                [* ]Corresponding author at: World Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong Special Administrative Region, China. bcowling@ 123456hku.hk
                Article
                S2666-6065(22)00056-6 100441
                10.1016/j.lanwpc.2022.100441
                8961079
                35359914
                3bcca2ae-111c-4846-aa43-9d2c15d22f2b
                © 2022 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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