Many recent studies have investigated the role of either Chloroquine (CQ) or Hydroxychloroquine (HCQ) alone or in combination with azithromycin (AZM) in the management of the emerging coronavirus. This systematic review and meta-analysis of either published or preprint observational studies or randomized control trials (RCT) aimed to assess mortality rate, duration of hospital stay, need for mechanical ventilation (MV), virologic cure rate (VQR), time to a negative viral polymerase chain reaction (PCR), radiological progression, experiencing drug side effects, and clinical worsening. A search of the online database through June 2020 was performed and examined the reference lists of pertinent articles for in-vivo studies only. Pooled relative risks (RRs), standard mean differences of 95% confidence intervals (CIs) were calculated with the random-effects model. Mortality was not different between the standard care (SC) and HCQ groups (RR = 0.99, 95% CI 0.61–1.59, I² = 82%), meta-regression analysis proved that mortality was significantly different across the studies from different countries. However, mortality among the HCQ + AZM was significantly higher than among the SC (RR = 1.8, 95% CI 1.19–2.27, I² = 70%). The duration of hospital stay in days was shorter in the SC in comparison with the HCQ group (standard mean difference = 0.57, 95% CI 0.20–0.94, I² = 92%), or the HCQ + AZM (standard mean difference = 0.77, 95% CI 0.46–1.08, I² = 81). Overall VQR, and that at days 4, 10, and 14 among patients exposed to HCQ did not differ significantly from the SC [(RR = 0.92, 95% CI 0.69–1.23, I² = 67%), (RR = 1.11, 95% CI 0.26–4.69, I² = 85%), (RR = 1.21, 95% CI 0.70–2.01, I² = 95%), and (RR = 0.98, 95% CI 0.76–1.27, I² = 85% )] respectively. Exposure to HCQ + AZM did not improve the VQR as well (RR = 3.23, 95% CI 0.70–14.97, I² = 58%). The need for MV was not significantly different between the SC and HCQ (RR = 1.5, 95% CI 0.78–2.89, I² = 81%), or HCQ + AZM (RR = 1.27, 95% CI 0.7–2.13, I² = 88%). Side effects were more reported in the HCQ group than in the SC (RR = 3.14, 95% CI 1.58–6.24, I² = 0). Radiological improvement and clinical worsening were not statistically different between HCQ and SC [(RR = 1.11, 95% CI 0.74–1.65, I² = 45%) and (RR = 1.28, 95% CI 0.33–4.99), I² = 54%] respectively. Despite the scarcity of published data of good quality, the effectiveness and safety of either HCQ alone or in combination with AZM in treating COVID-19 cannot be assured. Future high-quality RCTs need to be carried out.PROSPERO registration: CRD42020192084.

Background: Following the emergency approval of the coronavirus disease 2019 (COVID-19) vaccines, research into its vaccination hesitancy saw a substantial increase. However, the psychological behaviors associated with this hesitancy are still not completely understood. This study assessed the psychological antecedents associated with COVID-19 vaccination in the Arab population. Methodology: The validated Arabic version of the 5C questionnaire was distributed online across various social media platforms in Arabic-speaking countries. The questionnaire had three sections, namely, socio-demographics, COVID-19 related infection and vaccination, and the 5C scale of vaccine psychological antecedents of confidence, complacency, constraints, calculation, and collective responsibility. Results: In total, 4,474 participants with a mean age of 32.48 ± 10.76 from 13 Arab countries made up the final sample, 40.8% of whom were male. Around 26.7% of the participants were found to be confident about the COVID-19 vaccination, 10.7% indicated complacency, 96.5% indicated they had no constraints, 48.8% had a preference for calculation and 40.4% indicated they had collective responsibility. The 5C antecedents varied across the studied countries with the confidence and collective responsibility being the highest in the United Arab Emirates (59.0% and 58.0%, respectively), complacency and constraints in Morocco (21.0% and 7.0%, respectively) and calculation in Sudan (60.0%). The regression analyses revealed that sex, age, educational degrees, being a health care professional, history of COVID-19 infection and having a relative infected or died from COVID-19 significantly predicted the 5C psychological antecedents by different degrees. Conclusion: There are wide psychological antecedent variations between Arab countries, and different determinants can have a profound effect on the COVID-19 vaccine’s psychological antecedents.

This work aimed to identify the mathematical model and ecological pattern of COVID-19 infection and mortality across different countries during the first six months of the pandemic. In this pilot study, authors used the online available data sources of randomly selected 18 countries to collect ecological predictors of COVID-19 transmissibility and mortality. The studied determinants were environmental factors (daily average temperature, daily humidity) and socioeconomic attributes (population age structure, count and density, human development index, per capita income (PCI), gross domestic product, internet coverage, mobility trends, chronic diseases). Researchers used the linear and exponential time series analysis, and further utilize multivariate techniques to explain the variance in the monthly exponential growth rates of new cases and deaths. In the first two months, the R2 of linear models for the cases and deaths were higher than that of the corresponding R2 of the exponential model. Later one, R2 of the exponential model was occasionally relatively higher than that of the linear models. The exponential growth rate of new cases was significantly associated with mobility trends (β=0.00398, P=0.002), temperature (β=0.000679, P=0.011), humidity (β=0.000249, P=0.000), and the proportion of patients aged above 65 years (β=-0.000959, P=0.012). Similarly, the exponential growth rate of deaths was significantly associated with mobility trends (β=0.0027, P=0.049), temperature (β=0.0014, P<0.001), humidity (β=-0.0026, P=0.000), and PCI of countries. During this period, COVID-19 transmissibility was evident to be controlled as soon as social mobility is decreased by about 40% of the baseline over 3 months controlling for the other predictors. Controlling of COVID-19 pandemic is based mainly on controlling social mobility. Role of environmental determinants like temperature and humidity was well noticed on disease fatality and transmissibility. COVID-19 contagiousness and fatality were additionally affected by human modifiable risk factors like income and non-modifiable risk factors (ageing) affected.

Effective calibration transfer is essential for ensuring accurate and reliable measurements on altering one or more components of spectroscopic measurements, including the spectrometers, sample characteristics, environmental conditions, and measurement settings. Taking a unique perspective, this review aims to provide a guide for pharmaceutical researchers, offering insights into calibration transfer and maintenance applications. The systematic review lists all documented applications of calibration transfer and maintenance algorithms in the pharmaceutical industry up until the time of manuscript preparation. These studies covered various types of calibration transfer scenarios, including intravendor, intervendor, different spectral technologies, and transfers from benchtop to miniaturized instruments. Calibration maintenance cases revealed sources of variation like production scale, temperature changes, sample physical properties, and varied dynamic nature of processes. The review links algorithms to practice while highlighting research gaps. These gaps include limited applications on semi-solid or liquid pharmaceutical products, limited inline applications, and a lack of consensus on best practices. By addressing these shortcomings, this review contributes to advancing calibration transfer in the pharmaceutical industry, supporting precise measurements, improved process control, and the development of high-quality pharmaceutical products.

Quality by Design (QbD) and chemometric models are different sides of the same coin. While QbD models utilize experimentally designed settings for optimization of some quality attributes, these settings can also be utilized for chemometric prediction of the same attributes. We aimed to synchronize optimization of comparative dissolution results of carvedilol immediate release tablets with chemometric prediction of dissolution profile and content uniformity of the product. As an industrial application, selection of variables for optimization was done by performing risk assessment utilizing the archived product records at the pharmaceutical site. Experimental tablets were produced with 20 different settings with the variables being contents of sucrose, sodium starch glycolate, lactose monohydrate, and avicel Ph 101. Contents of the excipients were modelled with F1 dissimilarity factor and F2 similarity factor in HCL, acetate, and USP dissolution media to determine the design space. We initiatively utilized Partial Least Square based Structural Equation Modelling (PLS-SEM) to explore how the excipients and their NIR records explained dissolution of the product. Finally, the optimized formula was utilized with varied content of carvedilol for chemometric prediction of the content uniformity.

Background To understand the impact and volume of coronavirus (COVID-19) crisis, univariate analysis is tedious for describing the datasets reported daily. However, to capture the full picture and be able to compare situations and consequences for different countries, multivariate analytical models are suggested in order to visualize and compare the situation of different countries more accurately and precisely. Aims We aimed to utilize data analysis tools that display the relative positions of data points in fewer dimensions while keeping the variation of the original data set as much as possible, and cluster countries according to their scores on the formed dimensions. Methods Principal component analysis (PCA) and Partitioning around medoids (PAM) clustering algorithms were used to analyze data of 56 countries, 82 countries and 91 countries with COVID-19 at three time points, eligible countries included in the analysis are those with total cases of 500 or more with no missing data. Results After performing PCA, we generated two scores: Disease Magnitude score that represents total cases, total deaths, total actives cases, and critically ill cases, and Mortality Recovery Ratio score that represents the ratio between total deaths to total recoveries in any given country. Conclusion Accurate multivariate analyses can be of great value as they can simplify difficult concepts, explore and communicate findings from health datasets, and support the decision-making process.