An Evaluation of Non-Communicable Diseases and Risk Factors Associated with COVID-19 Disease Severity in Dubai, United Arab Emirates: An Observational Retrospective Study.

The aim of this study was to determine the prevalence of non-communicable diseases and their correlation with COVID-19 disease severity among patients infected in Dubai. Clinical and demographic data were extracted from hospital records of 34,687 COVID-19 patients who visited or were admitted into Dubai hospitals between 28 January 2020 and 30 September 2020. Prevalence of co-morbidities in COVID-19 patients were assessed. The main risk factors associated with COVID-19 disease severity were also identified using three regression models. All co-morbidities were significantly associated with COVID-19 severity in the bivariate analysis (p-value ≤ 0.05) except for vitamin-D deficiency and chronic lower respiratory diseases. Patients with ischemic heart diseases (AOR: 2.08; 95% CI: 1.37, 3.15), pulmonary and other heart diseases (AOR: 2.13; 95% CI: 1.36, 3.32) and chronic kidney diseases (AOR: 1.81; 95% CI: 1.01, 3.25) had higher odds of severe COVID-19 symptoms. Suffering from multiple co-morbidities increased the odds of developing severe COVID-19 symptoms substantially in comparison to having only one co-morbidity i.e., (AOR: 1.52; 95% CI 1.76-2.60) to (AOR: 2.33; 95% CI: 1.37, 3.97). Identifying these risk factors could assist in the early recognition of high-risk populations and ensure the most appropriate preventive measures and required medical management during the pandemic.

The impact of environmental and climate parameters on the incidence and mortality of COVID-19 in the six Gulf Cooperation Council countries: A cross-country comparison study.

BACKGROUND: Environmental factors can influence the epidemiological dynamics of COVID-19. To estimate the true impact of these factors on COVID-19, climate and disease data should be monitored and analyzed over an extended period of time. The Gulf Cooperation Council (GCC) countries are particularly lacking in such studies. This ecological study investigates the association between climate parameters and COVID-19 cases and deaths in the GCC. METHODS: Data on temperature, wind-speed and humidity and COVID-19 cases and deaths from the six countries of the GCC were collected between 29/1/2020 and 30/3/2021. Using Spearman's correlation coefficient, we examined associations between climate parameters and COVID-19 cases and deaths by month, over four different time periods. A two-step cluster analysis was conducted to identify distinct clusters of data using climate parameters and linear regression analysis to determine which climate parameters predicted COVID-19 new cases and deaths. RESULTS: The United Arab Emirates (UAE) had the highest cumulative number of COVID-19 cases while Bahrain had the highest prevalence rate per 100,000. The Kingdom of Saudi Arabia (KSA) reported the highest cumulative number of deaths while Oman recorded the highest death rate per 100,000. All GCC countries, except the UAE, reported a positive correlation between temperature and cases and deaths. Wind speed was positively correlated with cases in Qatar, but negatively correlated with cases in the UAE and deaths in KSA. Humidity was positively correlated with cases and deaths in Oman, negatively correlated in Bahrain, Kuwait, Qatar and KSA but there was no correlation in the UAE. The most significant predictors in cluster analysis were temperature and humidity, while in the regression analysis, temperature, humidity and wind speed predicted new COVID-19 cases and deaths. CONCLUSION: This study provides comprehensive epidemiological information on COVID-19 and climate parameters and preliminary evidence that climate may play a key role in the transmission of the COVID-19 virus. This study will assist decision makers in translating findings into specific guidelines and policies for the prevention and elimination of COVID-19 transmission and infection.

Social stigma towards health care workers during COVID pandemic: a hospital based cross-sectional study in Kolkata

Introduction: With the rise of COVID-19 pandemic, the health staffs have faced resistance and disrespect by the society. They have been stigmatised unnecessarily that has been resulted from fear and poor knowledge of general population regarding spread of COVID-19 infection. Objective : To estimate the proportion of health care workers who experienced social stigma during COVID-19 pandemic and to determine the association of social stigma with their socio-demographic and other background characteristics. Method: A descriptive type of observational study, cross-sectional in design was carried out among health care workers(HCWs) of a tertiary care hospital in Kolkata during the COVID-19 lockdown period (19th May 2020-20th July 2020) using a pre-designed, pre-tested, structured schedule. By simple random sampling, 422 HCWs were selected and 410 of them had given consent to participate in this study. MS Excel 2010 and SPSS v20.0 were used for data entry and binary logistic regression. Results : About 52.68% had experienced 'Significant Social Stigma', 32.92% experienced 'Insignificant Social Stigma' and only 14.39% had 'no stigma'. Age groups of 25-40 years and mode of transport by hospital vehicle had significant association with social stigma.

Determinants of healthcare workers perceptions, acceptance and choice of COVID-19 vaccines: a cross-sectional study from the United Arab Emirates.

Acceptance of COVID-19 vaccine among health-care workers (HCWs) is crucial for controlling the pandemic and ensuring HCW and patient safety. Information on the acceptance of different COVID-19 vaccines is lacking. Despite the United Arab Emirates (UAE) having vaccinated most of its population, vaccine acceptance still raises concerns. This study explores COVID-19 vaccine acceptance, vaccine choice, and associated factors among HCWs in the UAE. An online national cross-sectional study was conducted among 517 HCWs. Acceptance and choice of COVID-19 vaccines were assessed, and logistic regression analysis identified predictors for vaccine acceptance. More than half (58%) of HCWs were willing to take the vaccine and give it to their family. Reasons for taking the vaccine were concerns for families contracting COVID-19 (67%) and social responsibility (64%). Reasons for refusals included concerns with side-effects (61%). Most HCWs knew of the Pfizer (79%) and Sinopharm (57%) vaccines; however, acceptance was higher for Pfizer (35%) and AstraZeneca (21%) vaccines. Being male and being influenza vaccinated predicted willingness to take the vaccine (aOR: 2.34; 95% CI:1.34-4.08; p ≤ 0.001) and (aOR: 2.13; 95% CI: 1.29-3.51; p ≤ 0.001), respectively. HCWs who expressed concerns with inadequate safety data were less likely to take the vaccine (aOR: 0.17; 95% CI: 0.10-0.30; p ≤ 0.001). Additionally, side effects, perception of risk, and level of trust of company and country of manufacture predicted acceptance and choice of vaccines. Effective vaccine policy campaigns to improve acceptance should target HCW's knowledge and awareness of perceived risks of COVID-19, safety data, social responsibility, and individual preferences for vaccine choice.

Urban air pollution reduction: evidence from phase-wise analysis of COVID-19 pandemic lockdown

Until 31 May 2020, more than six million confirm COVID-19 cases had been reported worldwide. Lockdown has resulted in significant air quality improvement, especially in urban regions. The lockdown has acted as a natural experiment empowering researchers, policymakers, and governing bodies. The present study focuses on quantifying and analysing the effect of lockdown on India’s metropolitan cities, namely New Delhi, Mumbai, Kolkata, Chennai, and Bangalore. The study analyses the phase-wise and diurnal variations in the air quality from 24 March 2020 to 31 May 2020 while focussing on-peak and off-peak duration concentrations. To investigate the reason behind pollutant reduction, correlation of drop percentages in pollutant concentrations with vehicle population, extent of construction activity, and meteorological parameters are analysed. The 24-h drop in PM10 and PM2.5 showed a high correlation (R2 = 0.97 and 0.72, respectively) with the city’s vehicle population. During peak hours, the inland cities (Delhi and Bangalore), with a more extensive vehicle fleet, recorded a higher drop in PM10 and PM2.5 concentrations than coastal cities (Mumbai, Chennai, and Kolkata). With respect to 2019 concentration, the maximum decrease in pollutant concentrations averaged across the five study locations was recorded in NO2 (46%), followed by PM2.5 (40%), PM10 (37%), and CO (19%). SO2 and O3 contrarily recorded an overall increase of 40% and 41%. These results wherein vehicular pollutants recorded the maximum drop indicate that reduced vehicular traffic primarily influenced air quality improvement during the lockdown.

Abortion Self-Care: A Forward-Looking Solution To Inequitable Access

Following the World Health Organization's definition of self-care, abortion self-care is the ability of pregnant individuals to manage their unwanted pregnancies with or without the support of health care providers-particularly, in the early weeks of pregnancy. The advent of medication abortion (MA) has made this possible, as early self-managed MA at home is a safe, acceptable and cost-effective method of pregnancy termination. Here, Quesada et al focus on regulatory aspects of MA that determine women's access to quality and affordable abortifacient drugs, as well as to accurate information on their use.