Signs, Symptoms, and Side-Effects Presented by Different Types of COVID-19 Vaccines: A Prospective Cohort Study.

The concern about post-COVID-19 vaccine complications still remains. In addition, the evidence on Sinopharm, Sputnik V, Covaxin, and, in particular, COVIran Barekat, as well as comparisons between them by dosage after post-vaccination, is scarce. This study aimed to investigate and compare the prevalence of self-reported post-vaccination signs and symptoms following the first and second doses of different types of COVID-19 vaccines. Research design and methods: This prospective cohort study was conducted on more than 1500 health professionals who had received at least one dose of any type of Sputnik V, Sinopharm, Oxford AstraZeneca, Covaxin, and COVIran Barekat vaccines in Iran. The survey questionnaire was sent to participants online, 28 days after receiving each dose of the vaccine. Results: About 73% of health professionals reported at least one post-vaccination sign or symptom, developing mostly within the first 12 h (69.9%) and lasting up to 12 h (59.0%). Pain and tenderness at the injection site, fever, and muscle pain were the most common post-vaccination signs and symptoms in all vaccines, which were significantly higher in the Oxford AstraZeneca vaccine (p < 0.001) for both the first and second doses. The incidence rate of all post-vaccination signs and symptoms was significantly higher in the first dose than in the second dose (p < 0.05). Conclusion: The Oxford AstraZeneca vaccine showed the highest incidence rate, onset, and lasting time of signs and symptoms in both doses; however, they were not life-threatening. The onset time of signs and symptoms was significantly higher for the COVIran Barekat and Oxford AstraZeneca vaccines in both the first and second doses.

The effectiveness of COVID-19 vaccines in reducing the incidence, hospitalization, and mortality from COVID-19: A systematic review and meta-analysis.

Background: Vaccination, one of the most important and effective ways of preventing infectious diseases, has recently been used to control the COVID-19 pandemic. The present meta-analysis study aimed to evaluate the effectiveness of COVID-19 vaccines in reducing the incidence, hospitalization, and mortality from COVID-19. Methods: A systematic search was performed independently in Scopus, PubMed via Medline, ProQuest, and Google Scholar electronic databases as well as preprint servers using the keywords under study. We used random-effect models and the heterogeneity of the studies was assessed using I 2 and χ2 statistics. In addition, the Pooled Vaccine Effectiveness (PVE) obtained from the studies was calculated by converting based on the type of outcome. Results: A total of 54 studies were included in this meta-analysis. The PVE against SARS-COV 2 infection were 71% [odds ratio (OR) = 0.29, 95% confidence intervals (CI): 0.23-0.36] in the first dose and 87% (OR = 0.13, 95% CI: 0.08-0.21) in the second dose. The PVE for preventing hospitalization due to COVID-19 infection was 73% (OR = 0.27, 95% CI: 0.18-0.41) in the first dose and 89% (OR = 0.11, 95% CI: 0.07-0.17) in the second dose. With regard to the type of vaccine, mRNA-1273 and combined studies in the first dose and ChAdOx1 and mRNA-1273 in the second dose had the highest effectiveness in preventing infection. Regarding the COVID-19-related mortality, PVE was 68% (HR = 0.32, 95% CI: 0.23-0.45) in the first dose and 92% (HR = 0.08, 95% CI: 0.02-0.29) in the second dose. Conclusion: The results of this meta-analysis indicated that vaccination against COVID-19 with BNT162b2 mRNA, mRNA-1273, and ChAdOx1, and also their combination, was associated with a favorable effectiveness against SARS-CoV2 incidence rate, hospitalization, and mortality rate in the first and second doses in different populations. We suggest that to prevent the severe form of the disease in the future, and, in particular, in the coming epidemic picks, vaccination could be the best strategy to prevent the severe form of the disease. Systematic review registration: PROSPERO International Prospective Register of Systematic Reviews: http://www.crd.york.ac.uk/PROSPERO/, identifier [CRD42021289937].

Air quality index variation before and after the onset of COVID-19 pandemic: a comprehensive study on 87 capital, industrial and polluted cities of the world.

BACKGROUND: Coronavirus disease 2019 (COVID-19) pandemic provided an opportunity for the environment to reduce ambient pollution despite the economic, social and health disruption to the world. The purpose of this study was to investigate the changes in the air quality indexes (AQI) in industrial, densely populated and capital cities in different countries of the world before and after 2020. In this ecological study, we used AQI obtained from the free available databases such as the World Air Quality Index (WAQI). Bivariate correlation analysis was used to explore the correlations between meteorological and AQI variables. Mean differences (standard deviation: SD) of AQI parameters of different years were tested using paired-sample t-test or Wilcoxon signed-rank test as appropriate. Multivariable linear regression analysis was conducted to recognize meteorological variables affecting the AQI parameters. RESULTS: AQI-PM2.5, AQI-PM10 and AQI-NO2 changes were significantly higher before and after 2020, simultaneously with COVID-19 restrictions in different cities of the world. The overall changes of AQI-PM2.5, AQI-PM10 and AQI-NO2 in 2020 were - 7.36%, - 17.52% and - 20.54% compared to 2019. On the other hand, these results became reversed in 2021 (+ 4.25%, + 9.08% and + 7.48%). In general, the temperature and relative humidity were inversely correlated with AQI-PM2.5, AQI-PM10 and AQI-NO2. Also, after adjusting for other meteorological factors, the relative humidity was inversely associated with AQI-PM2.5, AQI-PM10 and AQI-NO2 (ß = - 1.55, ß = - 0.88 and ß = - 0.10, P < 0.01, respectively). CONCLUSIONS: The results indicated that air quality generally improved for all pollutants except carbon monoxide and ozone in 2020; however, changes in 2021 have been reversed, which may be due to the reduction of some countries' restrictions. Although this quality improvement was temporary, it is an important result for planning to control environmental pollutants.

COVID-19, body mass index and cholesterol: an ecological study using global data.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is now globally considered a serious economic, social and health threat. A wide range of health related factors including Body Mass Index (BMI) is reported to be associated with the disease. In the present study, we analyzed global databases to assess the correlation of BMI and cholesterol with the risk of COVID-19. METHODS: In this ecological study, we used age-standardized BMI and cholesterol levels as well as the incidence and mortality ratio of COVID-19 at the national-levels obtained from the publicly available databases such as the World Health Organization (WHO) and NCD Risk Factor Collaboration (NCD-RisC). Bivariate correlation analysis was applied to assess the correlations between the study variables. Mean differences (standard deviation: SD) of BMI and cholesterol levels of different groups were tested using independent sample t-test or Mann-Whitney rank test as appropriate. Multivariable linear regression analysis was performed to identify variables affecting the incidence and mortality ratio of COVID-19. RESULTS: Incidence and mortality ratio of COVID-19 were significantly higher in developed (29,639.85 ± 20,210.79 for cases and 503.24 ± 414.65 for deaths) rather than developing (8153.76 ± 11,626.36 for cases and 169.95 ± 265.78 for deaths) countries (P < 0.01). Results indicated that the correlations of BMI and cholesterol level with COVID-19 are stronger in countries with younger population. In general, the BMI and cholesterol level were positively correlated with COVID-19 incidence ratio (ß = 2396.81 and ß = 30,932.80, p < 0.01,| respectively) and mortality ratio (ß = 38.18 and ß = 417.52, p < 0.05,| respectively) after adjusting for socioeconomic and demographic factors. CONCLUSION: Countries with higher BMI or cholesterol at aggregate levels had a higher ratios of COVID-19 incidence and mortality. The aggregated level of cholesterol and BMI are important risk factors for COVID-19 major outcomes, especially in developing countries with younger populations. We recommend monitoring and promotion of health indicices to better prevent morbidity and mortality of COVID-19.