The coronavirus disease 2019 (COVID-19) pandemic has threatened global health and prompted the need for mass vaccination. We aimed to assess the efficacy and effectiveness of COVID-19 vaccines to prevent mortality and reduce the risk of developing severe disease after the 1st and 2nd doses. From conception to 28 June 2021, we searched PubMed, Cochrane, EBSCO, Scopus, ProQuest, Web of Science, WHO-ICTRP, and Google Scholar. We included both observational and randomized controlled trials. The pooled vaccine efficacy and effectiveness following vaccination, as well as their 95 percent confidence intervals (CI), were estimated using the random-effects model. In total, 22 of the 21,567 screened articles were eligible for quantitative analysis. Mortality 7 and 14 days after full vaccination decreased significantly among the vaccinated group compared to the unvaccinated group (OR = 0.10, ([95% CI, 0.04–0.27], I² = 54%) and (OR = 0.46, [95% CI, 0.35–0.61], I² = 0%), respectively. The probability of having severe disease one or two weeks after 2nd dose decreased significantly (OR = 0.29 [95% CI, 0.19–0.46], I² = 25%) and (OR = 0.08 [95% CI, 0.03–0.25], I² = 74%), respectively. The incidence of infection any time after the 1st and 2nd doses diminished significantly (OR = 0.14 [95% CI, 0.07–0.4], I² = 100%) and (OR = 0.179 [95% CI, 0.15–0.19], I² = 98%), respectively. Also, incidence of infection one week after 2nd dose decreased significantly, (OR = 0.04, [95% CI (0.01–0.2], I² = 100%). After meta-regression, the type of vaccine and country were the main predictors of outcome [non-mRNA type, ß = 2.99, p = 0.0001; country UK, ß = −0.75, p = 0.038; country USA, ß = 0.8, p = 0.02]. This study showed that most vaccines have comparable effectiveness, and it is purported that mass vaccination may help to end this pandemic.

Objective: The presented meta-analysis (MA) aims at identifying the vaccine safety and immunogenicity in published trials about SARS-CoV-2 vaccines. Methods: All relevant publications were systematically searched and collected from different databases (Embase, Scopus, EBSCO, MEDLINE central/PubMed, Science Direct, Cochrane Central Register for Clinical Trials (CENTRAL), Clinical Trials.gov, WHO International Clinical Trials Registry Platform (ICTRP), COVID Trial, COVID Inato, Web of Science, ProQuest Thesis, ProQuest Coronavirus Database, SAGE Thesis, Google Scholar, Research Square, and Medxriv) up to January 10, 2021. The pooled vaccine safety and immunogenicity following vaccination in phase 1 and 2 vaccine clinical trials, as well as their 95% confidence intervals (CI), were estimated using the random-effects model. Results: The predefined inclusion criteria were met in 22 out of 8592 articles. The proportion of anti-severe acute respiratory distress coronavirus 2 (SARS-CoV-2) antibody responses after 7 days among 72 vaccinated persons included in 1 study was 81% (95% CI: 70-89), after 14 days among 888 vaccinated persons included in 6 studies was 80% (95% CI: 58-92), after 28 days among 1589 vaccinated persons included in 6 studies was 63% (95% CI: 59-67), after 42 days among 478 vaccinated persons included in 5 studies was 93% (95% CI: 80-98), and after 56 days among 432 vaccinated persons included in 2 studies was 93% (95% CI: 83-97). Meta regression explains more than 80% of this heterogeneity, where the main predictors were; the inactivated vaccine type (β = 2.027, P = 0.0007), measurement of antibodies at week 1 (β = −4.327, P < 0.0001) and at week 3 of the first dose (β = −2.02, P = 0.0025). Furthermore, the pooled proportion adverse effects 7 days after vaccination was 0.01 (0.08-0.14) for fever, headache 0.23 (0.19-0.27), fatigue 0.10 (0.07-0.13), and 0.18 (0.14-0.23) for muscle pain. Conclusion: Immunogenicity following vaccination ranged from 63% to 93% depending on the time at which the antibody levels were measured.

Background: In the Arab countries, there has not been yet a specific validated Arabic questionnaire that can assess the psychological antecedents of COVID-19 vaccine among the general population. This study, therefore, aimed to translate, culturally adapt, and validate the 5C scale into the Arabic language.Methods: The 5C scale was translated into Arabic by two independent bilingual co-authors, and then translated back into English. After reconciling translation disparities, the final Arabic questionnaire was disseminated into four randomly selected Arabic countries (Egypt, Libya, United Arab Emirates (UAE), and Saudi Arabia). Data from 350 Arabic speaking adults (aged ≥18 years) were included in the final analysis. Internal consistency was assessed by Cronbach’s alpha. Construct validity was determined by concurrent, convergent, discriminant, exploratory and confirmatory factor analyses.Results: Age of participants ranged between 18 to 73 years; 57.14% were females, 37.43% from Egypt, 36.86%, from UAE, 30% were healthcare workers, and 42.8% had the intention to get COVID-19 vaccines. The 5 sub-scales of the questionnaire met the criterion of internal consistency (Cronbach’s alpha ≥0.7). The predictors of intention to get COVID-19 vaccines (concurrent validity) were young age and the 5C sub-scales. Convergent validity was identified by the significant inter-item and item-mean score of the sub-scale correlation (P<0.001). Discriminant validity was reported as inter-factor correlation matrix (<0.7). Kaiser-Meyer-Olkin sampling adequacy measure was 0.80 and Bartlett’s sphericity test was highly significant (P<0.001). Exploratory factor analysis indicated that the 15 items of the questionnaire could be summarized into five factors. Confirmatory factor analysis confirmed that the hypothesized five-factor model of the 15-item questionnaire was satisfied with adequate psychometric properties and fit with observed data (RMSEA = 0.060, GFI = 0.924, CFI = 0.957, TLI = 0.937, SRMR = 0.076 & NFI = 906).Conclusion: The Arabic version of the 5C scale is a valid and reliable tool to assess the psychological antecedents of COVID-19 vaccine among Arab population.

Vaccine hesitancy (VH) is defined as a delayed in acceptance or refusal of vaccines despite availability of vaccination services. This multinational study examined user interaction with social media about COVID-19 vaccination. The study analyzed social media comments in 24 countries from five continents. In total, 5856 responses were analyzed; 83.5% of comments were from Facebook, while 16.5% were from Twitter. In Facebook, the overall vaccine acceptance was 40.3%; the lowest acceptance rates were evident in Jordan (8.5%), Oman (15.0%), Senegal (20.0%) and Morocco (20.7%) and the continental acceptance rate was the lowest in North America 22.6%. In Twitter, the overall acceptance rate was (41.5%); the lowest acceptance rate was found in Oman (14.3%), followed by USA (20.5%), and UK (23.3%) and the continental acceptance rate was the lowest in North America (20.5%), and Europe (29.7%). The differences in vaccine acceptance across countries and continents in Facebook and Twitter were statistically significant. Regarding the tone of the comments, in Facebook, countries that had the highest number of serious tone comments were Sweden (90.9%), USA (61.3%), and Thailand (58.8%). At continent level, serious comments were the highest in Asia (58.4%), followed by Africa (46.2%) and South America (46.2%). In Twitter, the highest serious tone was reported in Egypt (72.2%) while at continental level, the highest proportion of serious comments was observed in Asia (59.7%), followed by Europe (46.5%). The differences in tone across countries and continents in Facebook and Twitter and were statistically significant. There was a significant association between the tone and the position of comments. We concluded that the overall vaccine acceptance in social media was relatively low and varied across the studied countries and continents. Consequently, more in-depth studies are required to address causes of such VH and combat infodemics.

Seasonal influenza vaccine is the most effective strategy for reducing influenza incidence and severity. Parental decision-making regarding childhood vaccination is influenced by one’s vaccine-related beliefs. A cross-sectional study was conducted to determine the role of the Health Belief Model (HBM) in predicting parental intention to vaccinate their children against influenza in the Eastern Mediterranean Region (EMR). An anonymous online survey was distributed to parents of children aged 6 months to 18 years in 14 EMR countries. Out of the 5964 participants, 28.2% intended to vaccinate their children against influenza. Urban residents (OR = 0.55, 95%CI: 0.35–0.85), decision-making regarding child’s health by the father alone (OR = 0.43, 95%CI: 0.34–0.55) or the mother alone (OR = 0.78, 95%CI: 0.65–0.93), having a child with a chronic illness (OR = 0.45, 95%CI: 0.38–0.53), reporting high perceived severity, susceptibility, and benefits (OR = 0.35, 95%CI: 0.30–0.40), and cues to action (OR = 0.45, 95%CI: 0.39–0.51) were inversely associated with parental unwillingness to vaccinate their children against influenza. While parents with a higher number of children in the household (OR = 1.08, 95%CI:1.03–1.12) and higher perceived barriers (OR = 2.92, 95%CI: 2.56–3.34) showed an increased likelihood of unwillingness to vaccinate their children. Interventions targeting parental beliefs and perceptions are necessary to improve influenza vaccination acceptance and coverage among children.

Occasionally intravenous insertion forms a challenge to a number of patients. Inserting an IV needle is a difficult task that requires a lot of skill. At the moment, only doctors and medical personnel are allowed to do this because it requires finding the right vein, inserting the needle properly, and carefully injecting fluids or drawing out blood. Even for trained professionals, this can be done incorrectly, which can cause bleeding, infection, or damage to the vein. It is especially difficult to do this on children, elderly people, and people with certain skin conditions. In these cases, the veins are harder to see, so it is less likely to be done correctly the first time and may cause blood clots. In this research, a low-cost embedded system utilizing Near-Infrared (NIR) light technology is developed, and two novel approaches are proposed to detect and select the best candidate veins. The two approaches utilize multiple computer vision tools and are based on contrast-limited adaptive histogram equalization (CLAHE). The accuracy of the proposed algorithm is 91.3% with an average 1.4 s processing time on Raspberry Pi 4 Model B.