Communicating COVID-19 Vaccine Safety: Knowledge and Attitude Among Residents of South East, Nigeria

Association between wealth, insurance coverage, urban residence, median age and COVID-19 deaths across states in Nigeria

This study measures associations between COVID-19 deaths and sociodemographic factors (wealth, insurance coverage, urban residence, age, state population) for states in Nigeria across two waves of the COVID-19 pandemic: February 27th 2020 to October 24th 2020 and October 25th 2020 to July 25th 2021. Data sources include 2018 Nigeria Demographic and Health Survey and Nigeria Centre for Disease Control (NCDC) COVID-19 daily reports. It uses negative binomial models to model deaths, and stratifies results by respondent gender. It finds that overall mortality rates were concentrated within three states: Lagos, Edo and Federal Capital Territory (FCT) Abuja. Urban residence and insurance coverage are positively associated with differences in deaths for the full sample. The former, however, is significant only during the early stages of the pandemic. Associative differences in gender-stratified models suggest that wealth was a stronger protective factor for men and insurance a stronger protective factor for women. Associative strength between sociodemographic measures and deaths varies by gender and pandemic wave, suggesting that the pandemic impacted men and women in unique ways, and that the effectiveness of interventions should be evaluated for specific waves or periods.

COVID-19 vaccine hesitancy in Latin America and Africa: a scoping review

Vaccination has played an important role in the containment of COVID-19 pandemic advances. However, SARS-CoV-2 vaccine hesitancy has caused a global concern. This scoping review aims to map the scientific literature on COVID-19 vaccine hesitancy in Latin America and Africa from a Global Health perspective, observing the particularities of the Global South and using parameters validated by the World Health Organization (WHO). The review reporting observes the recommendations of the PRISMA for Scoping Reviews (PRISMA-ScR) model. Search was conducted in PubMed, Scopus, Web of Science, and Virtual Health Library (VHL) databases, selecting studies published from January 1, 2020 to January 22, 2022. Selected studies indicate that COVID-19 vaccine hesitancy involves factors such as political scenario, spread of misinformation, regional differences in each territory regarding Internet access, lack of access to information, history of vaccination resistance, lack of information about the disease and the vaccine, concern about adverse events, and vaccine efficacy and safety. Regarding the use of conceptual and methodology references from the WHO for vaccine hesitancy, few studies (6/94) use research instruments based on these references. Then, the replication in Global South of conceptual and methodological parameters developed by experts from the Global North contexts has been criticized from the perspective of Global Health because of it may not consider political and sociocultural particularities, the different nuances of vaccine hesitancy, and issues of access to vaccines.

Reducing COVID-19 vaccine hesitancy and improving vaccine uptake in Nigeria

By May 30, 2022, there were 526,182,662 confirmed COVID- 19 cases and 6,286,057 deaths globally; of which Nigeria had recorded 256,028 confirmed cases and 3143 deaths. By the same time, Nigeria had received a total of 93.9 million doses of the COVID-19 vaccine, enough to vaccinate 25% of the population; however, only 27.4 million people (13.3% of the population) had received at least one dose of the vaccine. This article examines available evidence on COVID-19 vaccine hesitancy in Nigeria and makes recommendations for improving its uptake. Major causes of COVID-19 vaccine hesitancy identified in Nigeria were concerns around vaccine efficacy and safety, disbelief in the existence and severity of the disease, and distrust of the government. To reduce COVID-19 vaccine hesitancy and improve vaccine coverage in Nigeria, mapping vaccine acceptance and hesitancy across geographies and demographics is needed, as well as increased stakeholder communication, and effective community engagement.

Knowledge and Perception of the Employees Towards COVID-19 Vaccination at Palestinian Universities

Introduction

Major efforts are being made to control the spread and impact of the coronavirus pandemic using vaccines. However, willingness to be vaccinated depends largely on factors beyond the availability of vaccines.

Objective

This study aimed to investigate the knowledge and perception of university employees towards the COVID-19 vaccination.

Methods

A cross-sectional study was conducted between February and June 2021. A total of 310 university employees from six Palestinian universities participated in the study. A self-reported questionnaire was used for data collection and included the following: personal and medical characteristics of the university employees' knowledge and perception regarding receiving the COVID-19 vaccination.

Results

Three hundred and ten out of 336 questionnaires (92.3% response rate) were completed and returned by the participants. The results revealed that 41.9% of university employees had good knowledge of the COVID-19 vaccination. On the other hand, 51.9% of them had a positive perception of the COVID-19 vaccination. Also, there is a significant difference between the level of knowledge and perception of the COVID-19 vaccine (p < .05).

Conclusion

Less than half of the university employees had good knowledge, and half of them had a positive attitude towards the COVID-19 vaccination. Also, it has been determined that there is a relationship between the level of knowledge and perception of the COVID-19 vaccine. The study recommended that employees should be involved in educational campaigns to increase their knowledge of the importance of vaccines in COVID-19 prevention.

Estimating the COVID-19 prevalence and mortality using a novel data-driven hybrid model based on ensemble empirical mode decomposition

In this study, we proposed a new data-driven hybrid technique by integrating an ensemble empirical mode decomposition (EEMD), an autoregressive integrated moving average (ARIMA), with a nonlinear autoregressive artificial neural network (NARANN), called the EEMD-ARIMA-NARANN model, to perform time series modeling and forecasting based on the COVID-19 prevalence and mortality data from 28 February 2020 to 27 June 2020 in South Africa and Nigeria. By comparing the accuracy level of forecasting measurements with the basic ARIMA and NARANN models, it was shown that this novel data-driven hybrid model did a better job of capturing the dynamic changing trends of the target data than the others used in this work. Our proposed mixture technique can be deemed as a helpful policy-supportive tool to plan and provide medical supplies effectively. The overall confirmed cases and deaths were estimated to reach around 176,570 [95% uncertainty level (UL) 173,607 to 178,476] and 3454 (95% UL 3384 to 3487), respectively, in South Africa, along with 32,136 (95% UL 31,568 to 32,641) and 788 (95% UL 775 to 804) in Nigeria on 12 July 2020 using this data-driven EEMD-ARIMA-NARANN hybrid technique. The contributions of this study include three aspects. First, the proposed hybrid model can better capture the dynamic dependency characteristics compared with the individual models. Second, this new data-driven hybrid model is constructed in a more reasonable way relative to the traditional mixture model. Third, this proposed model may be generalized to estimate the epidemic patterns of COVID-19 in other regions.