key: cord-0815217-f6suel0e
authors: Kwok, K. O.; Li, K. K.; Wei, W. I.; Tang, K. H.; Wong, S. Y. S.; Lee, S. S.
title: Are we ready when COVID-19 vaccine is available? Study on nurses' vaccine hesitancy in Hong Kong
date: 2020-07-17
journal: nan
DOI: 10.1101/2020.07.17.20156026
sha: acbc6c73534ba92f71010921b2ad7324b4747136
doc_id: 815217
cord_uid: f6suel0e

Introduction: Nurses are considered a trustworthy source of vaccine-related information to build public confidence in vaccination. This study estimated nurses' influenza vaccine uptake and intention to receive COVID-19 vaccine when available, and examined the corresponding psychological antecedents. Methods : A cross-sectional online survey among nurses was conducted during the main COVID-19 outbreak in Hong Kong between mid-March and late April 2020. Demographics, influenza vaccination, intention to have COVID-19 vaccine, the 5C vaccine hesitancy components (i.e., confidence, complacency, constraints, calculation, and collective responsibility), work stress and COVID-related work demands (i.e., insufficient supply of personal protective equipment, involvement in isolation rooms, and unfavorable attitudes towards workplace infection control policies) were reported. Results: The influenza vaccination coverage and the proportion intending to take COVID-19 vaccine were 49% and 63%, respectively, among 1205 eligible nurses. Influenza vaccine uptake was associated with working in public hospitals and all 5C constructs, whereas stronger COVID-19 vaccination intention was associated with younger age, more confidence, less complacency and more collective responsibility towards the vaccine. COVID-19-related demands were associated with greater work stress, and hence stronger COVID-19 vaccination intention. Conclusion: Vaccine uptake/intention was well predicted by the 5C constructs. With less work stress among nurses in the post-pandemic period, the intention to take COVID-19 vaccine will likely drop. The 5C constructs should be infused in vaccination campaigns. While a COVID-19 vaccine could be ready soon, communities are not ready to accept it. More research work is needed to boost the uptake.

The required sample size to estimate seasonal influenza vaccine coverage and COVID-19 121 vaccine intention was 1049 based on an estimated population of 60000 registered or enrolled nurses 122 in Hong Kong, a 3% margin of error, a 95% confidence interval, and a prevalence rate at 50%. To 123 account for a 30% loss from invalid cases (ineligible or incomplete cases), the sample size required 124 was 1499. The online survey was disabled when the sample size was achieved. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted July 17, 2020. . Work stress was measured by a single item asking participants to self-rate their level of work 141 stress after the outbreak of COVID-19 on an 11-point scale (0=no stress at all; 10=the maximum 142 stress). Insufficient supply of PPE was measured by asking participants to report any shortage of 7

PPE and an open option (1=yes; 0=no). The higher the total score, the more insufficient supply of 144 PPE was. A single item asking participants whether their job duties included work in infection 145 isolation rooms (1=yes; 0=no). Attitudes towards workplace infection control policies were measured 146 by 3 items stating if the workplace infection control policies were timely, sufficient, and effective, 147 respectively, on a 5-point rating scale (1=strongly disagree; 5=strongly agree). 148 Seasonal influenza vaccine uptake was measured by self-reported vaccination in 2019/20 149 while COVID-vaccine uptake intention was measured by a single item asking participants how likely 150 they will take the COVID-19 vaccine when available on a 11-point likert scale (0=definitely no; 151 10=definitely yes). CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted July 17, 2020. . logistic regression models were applied to identify factors associated with COVID-19 vaccine uptake 163 intention and influenza vaccine uptake decision respectively. The mediating effect was also tested Table S1) 180 Table 1 shows sample characteristics and their bivariate associations with influenza vaccine 181 uptake and COVID-19 vaccine intention, respectively. The mean age of the sample was 40.79 years 182 (SD=10.47). Most participants were female (90%) and AHKNS members (96%). More than half of 183 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted July 17, 2020. . https://doi.org/10.1101/2020.07.17.20156026 doi: medRxiv preprint the participants worked in the public hospitals (56%). Participants reported high exposure to patients 184 (M=4.35 on a scale of 1-5; SD=1.23). 185 The influenza vaccine coverage in the 2019-20 winter season was 49% (95% bCI: 47%, 52%).

Univariate associated determinants with higher influenza vaccine uptake were older age, presence of 187 chronic diseases, stronger vaccine confidence, collective responsibility, and work stress; and weaker 188 vaccine complacency and constraints. Intention to take COVID-19 vaccine when available was 6.52 189 (on a scale of 0-10; SD=2.83), which could be translated to 63% (95% bCI: 60%, 66%) reporting they 190 were likely to vaccinate (scored 6 or above). Univariate factors associated with stronger intention to 191 take COVID-19 vaccine were stronger vaccine confidence, calculation, collective responsibility, and 192 work stress; and weaker complacency and constraints. Correlations among the studied variables and 193 Cronbach's alpha coefficients for composite measures are presented in Table S2 . 194 The results of a parallel analysis showed that 5 factors should be retained for the vaccine 195 hesitancy measure (Table S3) . Bartlett's test, Table 2 219 shows the coefficients of the two regression models. When COVID-19 vaccination intention was 220 dichotomized as likely (score 6-10) and not likely (score 0-5), the pseudo R 2 of the model was 10.19%.

The coefficients of the dichotomized COVID-19 vaccination intention model are presented in Table   222 S4.

225 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted July 17, 2020. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted July 17, 2020. . https://doi.org/10.1101/2020.07.17.20156026 doi: medRxiv preprint 19 vaccine uptake intention. It is not surprising that calculation and constraints in the 5C hesitancy Significant odds ratios (95% confidence interval) are presented in bold face.

.

It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted July 17, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted July 17, 2020. 

Efficacy and effectiveness of influenza