Self-reported side effects of COVID-19 vaccines among health professions students in India.

Studies focusing on the safety and common side effects of vaccines play a crucial role in enhancing public acceptance of vaccination. Research is scarce regarding the usage of COVID-19 vaccines and the side effects experienced by health professions students in India and other countries. This study aimed to document self-reported side effects associated with COVID-19 vaccination among medical and dental students of six medical and dental colleges and teaching hospitals in four states (Tamil Nadu, Madhya Pradesh, Gujarat, and West Bengal) of India. A cross-sectional survey using purposive sampling of medical and dental students was conducted from 26 April to 26 May 2021. Data was collected using a Google Forms questionnaire capturing information regarding receiving COVID-19 vaccines, side effects and symptoms, onset and duration of symptoms, use of treatment to alleviate symptoms, awareness of haematologic risks associated with vaccination, and side effects from previous (non-COVID-19) vaccinations. The majority (94.5%) of participants received both doses of the Covishield/AstraZeneca COVID-19 vaccine. Among participants (n = 492), 45.3% (n = 223) reported one or more side effects. The most frequently reported side effects were soreness of the injected arm (80.3%), tiredness (78.5%), fever (71.3%), headache (64.1%), and hypersomnia (58.7%). The two most common severe symptoms were fever (14.8%) and headache (13%). Most side effects appeared on the day of vaccination: soreness of the injection site (57%), fever (43.1%), and tiredness (42.6%). Most reported symptoms persisted for one to three days-soreness of the injection site (53%), fever (47.1%), and headache (42.6%). Logistic regression showed that women were almost 85% less likely to report side effects. The study's findings corroborate the safety of the Covishield/AstraZeneca vaccine's first dose, evidenced by the relatively minor and transient nature of the side effects. However, the study underscores the necessity for ongoing research to assess the long-term impacts of COVID-19 vaccines, especially in the context of booster doses, thereby contributing to the global understanding of vaccine safety and efficacy.

Personal protective equipment (PPE) related adverse skin reactions among healthcare workers at the main COVID-19 isolation center in Barbados.

Background: The use of personal protective equipment (PPE) reduces the risk of transmission of infectious agents significantly among healthcare workers (HCWs). The study aimed to investigate the prevalence and characteristics of PPE-related adverse skin reactions among HCWs working at the main COVID-19 isolation center in Barbados. Methods: A cross-sectional web-based online survey was conducted during April to June 2021 which recorded demographic information, details of PPE use and adverse skin reactions including severity and duration of onset of symptoms. Results: Most of the respondents used PPE for consecutive days (77.9%), 1-6 h/day (59.2%), and more than a year (62.5%). Fewer than half of the participants (45.6%) experienced adverse skin reactions from the use of PPE. The reactions were mostly observed in the cheeks (40.4%) and nose bridges (35.6%). Females had more reactions than their male counterparts (p = 0.003). The use of N95 masks and a combination of surgical and N95 masks produced adverse effects predominantly in the ears (60%) and cheeks (56.4%). Binary logistic regression showed that female HCWs (OR = 5.720 95% CI: 1.631, 20.063), doctors (OR = 5.215 95% CI: 0.877, 31.002), and longer duration of PPE use (>1 year) (OR = 2.902 95% CI: 0.958, 8.787) caused a significantly higher prevalence of adverse skin reactions. Conclusion: The PPE-related skin reactions were common among HCWs which mainly occurred due to prolonged use. Preventive measures inclusive of appropriate training of HCWs on the use of PPE are recommended to minimize these adverse events.

Prevalence of COVID-19 vaccine reactogenicity among Bangladeshi physicians.

Increased COVID-19 vaccine hesitancy presents a major hurdle in global efforts to contain the COVID-19 pandemic. This study was designed to estimate the prevalence of adverse events after the first dose of the Covishield (AstraZeneca) vaccine among physicians in Bangladesh. A cross-sectional study was conducted using an online questionnaire for physicians (n = 916) in Bangladesh. Physicians who received at least one dose of the COVID-19 vaccine were included. The study was carried out from April 12 to May 31, 2021. More than 58% of respondents (n = 533) reported one or more adverse events. Soreness of the injected arm (71.9%), tiredness (56.1%), fever (54.4%), soreness of muscles (48.4%), headache (41.5%) and sleeping more than usual (26.8%) were the most commonly reported adverse events. Most vaccine-related reactogenicities were reported by the younger cohorts (<45 years). The majority of respondents reported severity of reactogenicity as "mild," experienced on the day of vaccination, and lasting for 1-3 days. The most common reactogenicity was pain at the injection site; the second most common was tiredness. Almost half (49.2%) of the physicians took acetaminophen (paracetamol) to minimize the effects of vaccine reactogenicity. Multivariate logistic regression analyses showed that physicians with diabetes and hypertension (OR = 2.729 95% CI: 1.282-5.089) and asthma with other comorbidities (OR = 1.885 95% CI: 1.001-3.551) had a significantly higher risk of vaccine-related reactogenicities than physicians without comorbidities. Further safety studies with larger cohorts are required to monitor vaccine safety and provide assurance to potential vaccine recipients.

Mortality Forecasting with the Lee-Carter Method: Adjusting for Smoothing and Lifespan Disparity.

Reliable mortality forecasts are an essential component of healthcare policies in ageing societies. The Lee-Carter method and its later variants are widely accepted probabilistic approaches to mortality forecasting, due to their simplicity and the straightforward interpretation of the model parameters. This model assumes an invariant age component and linear time component for forecasting. We apply the Lee-Carter method on smoothed mortality rates obtained by LASSO-type regularization and hence adjust the time component with the observed lifespan disparity. Smoothing with LASSO produces less error during the fitting period than do spline-based smoothing techniques. As a more informative indicator of longevity, matching with lifespan disparity makes the time component more reflective of mortality improvements. The forecasts produced by the new method were more accurate during out-of-sample evaluation and provided optimistic forecasts for many low-mortality countries.

Mortality and life expectancy forecast for (comparatively) high mortality countries.

BACKGROUND: The Lee-Carter method and its later variants are widely accepted extrapolative methods for forecasting mortality and life expectancy in industrial countries due to their simplicity and availability of high quality long time series data. OBJECTIVE: We compared and contrasted mortality forecasting models for higher mortality regimes that lack long time series data of good quality, which is common in several Central and Eastern European (CEE) countries. DATA AND METHODS: We utilized seven different variants of the Lee-Carter method and coherent mortality forecasts of various CEE countries, and the Bayesian Hierarchical Model used by the United Nations to produce probabilistic forecasts. The data of nine CEE countries with comparatively higher mortality have been considered. RESULTS: The performance of the forecasting models for the nine CEE countries was found to be lower than that observed for low-mortality countries. No model gives uniquely best performance for all the nine CEE countries. Most of the LC variants produced lower forecasts of life expectancies than current life expectancy values for Belarus, Russia, and Ukraine. A coherent mortality forecast could not overcome the limitations of single population forecasting techniques due to increasing mortality differences between these countries over the fitting period (mortality divergence). In the same context, the use of the probabilistic forecasting technique from the Bayesian framework resulted in a better forecast than some of the extrapolative methods but also produced a wider prediction interval for several countries. The more detailed analysis for Hungary indicates that a better fit of certain forecasting methods may occur in the later part of the life span rather than the whole life span. CONCLUSION: These findings imply the necessity of inventing a new forecasting technique for high-mortality countries.