COVID-19 vaccine acceptance and associated determinants in Addis Ketema Sub-city, Addis Ababa, Ethiopia: A community-based study.

Background: Despite the global surge in the Corona virus disease (COVID-19) pandemic, people's efforts to combat the pandemic have been insufficient. The world has experienced a number of challenges in terms of COVID-19 vaccine acceptance. Therefore, understanding the community's willingness to receive the vaccine will aid in the creation and implementation of effective COVID-19 immunization. As a result, the aim of this study was to assess the magnitude of COVID-19 vaccine acceptance and associated factors among adults in Addis Ababa, Ethiopia. Methods: A community-based cross-sectional study with 419 household heads was undertaken in Addis Ababa, Ethiopia. To identify factors associated with the outcome and independent variables, bi-variable and multi-variable logistic regression analyses were used. A 95% confidence interval and a p-value of less than 0.05 were deemed sufficient to declare a significant association. Results: The level of COVID-19 vaccine acceptance was 46.3 % (95 % CI: 43.87-48.73). Moreover, age groups above 58 years (AOR = 0.38, 95: CI: 0.17, 0.84), chronic disease (AOR: 2.09, 95 % CI: 1.28-3.42), a positive attitude (AOR: 1.64, 95 % CI: 1.29-2.04), being a Muslim (AOR: 0.36, 95 % CI: 0.19-0.71) and social support (AOR: 1.7, 95 % CI: 1.04-2.79) were all significantly related to COVID-19 vaccine acceptance. Conclusion: The findings of this study revealed a lower rate of COVID-19 vaccination acceptance. Age, chronic disease, attitude, and social support were significant predictors of COVID-19 vaccine acceptance. Therefore, emphasis should be given for community mobilization, especially for the elderly, those with limited social engagement, and those who have a negative attitude toward COVID-19 vaccination.

Mistrust in government and COVID-19 vaccination acceptance in Nigeria: investigating the indirect roles of attitudes towards vaccination.

BACKGROUND: Research shows that trust in government is associated with the acceptance of COVID-19 vaccination. However, there is no empirical evidence suggesting the pathway by which this association is formed. This study examines how dimensional attitudes towards vaccination explain the relationship between mistrust in government and COVID-19 vaccination acceptance. METHODS: The study was an online cross-sectional survey involving 1026 adults (of which 58.9% are female) resident in Nigeria with a mean age of 26.09 (±8.46) years. Data were collected using structured questionnaires assessing the level of mistrust in government, dimensional attitudes towards vaccination, and acceptance to be vaccinated for COVID-19. Structural equation modeling was used to analyze data. RESULTS: Results show that 56.8% of participants mistrust the government, while COVID-19 vaccination acceptance rate was 28.2%. Mistrust in government was significantly associated with low acceptance of COVID-19 vaccination. Furthermore, mistrust in the government was predictive of negative attitudes towards COVID-19 vaccination which include worries about unforeseen future effects of vaccines, mistrust of vaccine benefits (MVB), concerns about commercial profiteering (CCP), and preference for natural immunity. The outcomes of indirect effect analyses indicated that mistrust in government was associated with high mistrust in vaccine benefits (MVB) and increased concerns about commercial profiteering (CCP), which in turn lead to low acceptance of COVID-19 vaccination. CONCLUSIONS: Mistrust in the government was high and was coupled with low vaccination acceptance. It is important to initiate culturally relevant awareness programs aiming at combating false notions about COVID-19 vaccination such as MVB and CCP arising from mistrust in government.

Sparse spatially clustered coefficient model via adaptive regularization.

Large spatial datasets with many spatial covariates have become ubiquitous in many fields in recent years. A question of interest is to identify which covariates are likely to influence a spatial response, and whether and how the effects of these covariates vary across space, including potential abrupt changes from region to region. To solve this question, a new efficient regularized spatially clustered coefficient (RSCC) regression approach is proposed, which could achieve variable selection and identify latent spatially heterogeneous covariate effects with clustered patterns simultaneously. By carefully designing the regularization term of RSCC as a chain graph guided fusion penalty plus a group lasso penalty, the RSCC model is computationally efficient for large spatial datasets while still achieving the theoretical guarantees for estimation. RSCC also adopts the idea of adaptive learning to allow for adaptive weights and adaptive graphs in its regularization terms and further improves the estimation performance. RSCC is applied to study the acceptance of COVID-19 vaccines using county-level data in the United States and discover the determinants of vaccination acceptance with varying effects across counties, revealing important within-state and across-state spatially clustered patterns of covariates effects.

Predictors of COVID-19 Stress and COVID-19 Vaccination Acceptance among Adolescents in Ghana.

Coronavirus disease 2019 (COVID-19) continues to ravage world economies, and with its recent mutations, countries worldwide are finding ways of ramping up their vaccination programmes. This cross-sectional design study, therefore, examined the predictors of COVID-19 stress and COVID-19 vaccination acceptance among adolescents in Ghana. A total of 817 participants were conveniently selected to respond to measures on fear of COVID-19, perceived stigma from COVID-19, self-stigma from COVID-19, believing COVID-19 information, COVID-19 infection prevention behaviours, COVID-19 stress, and COVID-19 vaccination acceptance. It was found that females believed COVID-19 information and accepted COVID-19 vaccination more than males did. Moreover, there were significant relationships between the majority of the COVID-19-related variables. Furthermore, fear of COVID-19, self-stigma from COVID-19, and COVID-19 infection prevention behaviours were found to be significant predictors of COVID-19 stress. Additionally, believing COVID-19 information, danger and contamination fears (a subscale of COVID-19 stress), and traumatic stress (a subscale of COVID-19 stress) were significant predictors of COVID-19 vaccination acceptance. These findings imply that different factors influence different COVID-19 variable. Therefore, careful considerations and research should be employed by health authorities and policymakers in preparing COVID-19 information to target different age groups and for different COVID-19 purposes.

COVID-19 vaccination acceptance among health care workers from a community-based clinic chain: A cross-sectional study

Background@#Since the implementation of the community quarantine by the Philippine government last March 17, 2020 the country has been living in constant fear of possibly contracting the virus. Even as vaccines have been developed and tested, not everyone is confident in having themselves vaccinated against COVID-19. This is true even for healthcare professionals who are at increased risk of exposure to the virus@*Objective@#This study aimed to determine the acceptance rate of COVID-19 vaccination among Health Care Workers from a primary care setting during the COVID-19 pandemic@*Methods@#A cross-sectional study was conducted from April to June 2021 with 101 healthcare workers from all active clinics of Healthway Family Clinics at the time of the study. The participants were given self-administered questionnaires containing 15 items regarding socio-demographic data as well as willingness to receive and perception of COVID-19 vaccination@*Results@#Overall, 97% of the 101 total participants are willing to receive the COVID-19 vaccine once it is made available to them, while 3%, displaying vaccine hesitancy, would like to wait before getting vaccinated. Most participants in the study were female (66.3%) and single (72.3%) with a mean age of 30.82 years. Majority of the participants were doctors (56.4%), followed by nurses (25.7%), clinic assistants (7.9%), pharmacists (7.9%) and radiology technicians (2.1%). There was no significant association between vaccination acceptance with sociodemographic variables and perceptions about the vaccine@*Conclusion and Recommendation@#Once the COVID-19 vaccine is available to them, majority of the healthcare workers in the study’s primary care community-based clinics will immediately avail of the vaccination and while the remaining displays vaccine hesitancy. This is encouraging because it is important for health workers to protect themselves from the risk of COVID-19 infection by getting immunized as well as be in the forefront of encouraging our patients to have themselves immunized as well. Future researchers may use this study and its recommendations to analyze possible trends and associations with regards to COVID-19 vaccine acceptance and uptake

Measurement Invariance of the Drivers of COVID-19 Vaccination Acceptance Scale: Comparison between Taiwanese and Mainland Chinese-Speaking Populations.

The impacts of novel coronavirus disease-2019 (COVID-19) on human life continue to be serious. To control the spread of COVID-19, the production of effective vaccines is likely to be one of the best solutions. However, vaccination hesitancy may decrease individuals' willingness to get vaccinated. The Drivers of COVID-19 Vaccination Acceptance Scale (DrVac-COVID19S) was recently developed to help healthcare professionals and researchers better understand vaccination acceptance. The present study examined whether DrVac-COVID19S is measurement invariant across different subgroups (Taiwanese vs. mainland Chinese university students; males vs. females; and health-related program majors vs. non-health-related program majors). Taiwanese (n = 761; mean age = 25.51 years; standard deviation (SD) = 6.42; 63.5% females) and mainland Chinese university students (n = 3145; mean age = 20.72 years; SD = 2.06; 50.2% females) were recruited using an online survey between 5 January and 21 February 2021. Factor structure and measurement invariance of the two DrVac-COVID19S scales (nine-item and 12-item) were tested using confirmatory factor analysis (CFA). The findings indicated that the DrVac-COVID19S had a four-factor structure and was measurement invariant across the subgroups. The DrVac-COVID19S's four-factor structure was supported by the CFA results is a practical and valid instrument to quickly capture university students' willingness to get COVID-19 vaccination. Moreover, the DrVac-COVID19S can be used to compare university students' underlying reasons to get COVID-19 vaccination among different subgroups.