Socioeconomic inequalities of Long COVID: a retrospective population-based cohort study in the United Kingdom.

OBJECTIVES: To estimate the risk of Long COVID by socioeconomic deprivation and to further examine the inequality by sex and occupation. DESIGN: We conducted a retrospective population-based cohort study using data from the ONS COVID-19 Infection Survey between 26 April 2020 and 31 January 2022. This is the largest nationally representative survey of COVID-19 in the UK with longitudinal data on occupation, COVID-19 exposure and Long COVID. SETTING: Community-based survey in the UK. PARTICIPANTS: A total of 201,799 participants aged 16 to 64 years and with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. MAIN OUTCOME MEASURES: The risk of Long COVID at least 4 weeks after SARS-CoV-2 infection by index of multiple deprivation (IMD) and the modifying effects of socioeconomic deprivation by sex and occupation. RESULTS: Nearly 10% (n = 19,315) of participants reported having Long COVID. Multivariable logistic regression models, adjusted for a range of variables (demographic, co-morbidity and time), showed that participants in the most deprived decile had a higher risk of Long COVID (11.4% vs. 8.2%; adjusted odds ratio (aOR): 1.46; 95% confidence interval (CI): 1.34, 1.59) compared to the least deprived decile. Significantly higher inequalities (most vs. least deprived decile) in Long COVID existed in healthcare and patient-facing roles (aOR: 1.76; 95% CI: 1.27, 2.44), in the education sector (aOR: 1.68; 95% CI: 1.31, 2.16) and in women (aOR: 1.56; 95% CI: 1.40, 1.73) than men (aOR: 1.32; 95% CI: 1.15, 1.51). CONCLUSIONS: This study provides insights into the heterogeneous degree of inequality in Long COVID by deprivation, sex and occupation. These findings will help inform public health policies and interventions in incorporating a social justice and health inequality lens.

Estimating the Effectiveness of First Dose of COVID-19 Vaccine Against Mortality in England: A Quasi-Experimental Study.

Estimating real-world vaccine effectiveness is vital to assess the COVID-19 vaccination programme and to inform the ongoing policy response. However, estimating vaccine effectiveness using observational data is inherently challenging because of the non-randomised design and potential for unmeasured confounding. We used a Regression Discontinuity Design (RDD) to estimate vaccine effectiveness against COVID-19 mortality in England using. the fact that people aged 80 or over were prioritised for the vaccine roll-out. The prioritisation led to a large discrepancy in vaccination rates in people 80-84 compared to those 75-79 at the beginning of the vaccination campaign. We found a corresponding difference in COVID-19 mortality, but not in non-COVID-19 mortality, suggesting that our approach appropriately addresses the issue of unmeasured confounding factors. Our results suggest that the first vaccine dose reduced the risk of COVID-19 death by 52.6% (95% Cl 26.6-84.2) in those aged 80, supporting existing evidence that a first dose of a COVID-19 vaccine has a strong protective effect against COVID-19 mortality in older adults. The RDD estimate of vaccine effectiveness is only slightly lower to previously published studies using different methods, suggesting that these estimates are unlikely to be substantially affected by unmeasured confounding factors.

Ethnic differences in COVID-19 mortality in the second and third waves of the pandemic in England during the vaccine rollout: a retrospective, population-based cohort study.

BACKGROUND: Ethnic minority groups in England have been disproportionately affected by the COVID-19 pandemic and have lower vaccination rates than the White British population. We examined whether ethnic differences in COVID-19 mortality in England have continued since the vaccine rollout and to what extent differences in vaccination rates contributed to excess COVID-19 mortality after accounting for other risk factors. METHODS: We conducted a retrospective, population-based cohort study of 28.8 million adults aged 30-100 years in England. Self-reported ethnicity was obtained from the 2011 Census. The outcome was death involving COVID-19 during the second (8 December 2020 to 12 June 2021) and third wave (13 June 2021 to 1 December 2021). We calculated hazard ratios (HRs) for death involving COVID-19, sequentially adjusting for age, residence type, geographical factors, sociodemographic characteristics, pre-pandemic health, and vaccination status. RESULTS: Age-adjusted HRs of death involving COVID-19 were elevated for most ethnic minority groups during both waves, particularly for groups with lowest vaccination rates (Bangladeshi, Pakistani, Black African, and Black Caribbean). HRs were attenuated after adjusting for geographical factors, sociodemographic characteristics, and pre-pandemic health. Further adjusting for vaccination status substantially reduced residual HRs for Black African, Black Caribbean, and Pakistani groups in the third wave. Fully adjusted HRs only remained elevated for the Bangladeshi group (men: 2.19 [95% CI 1.72-2.78]; women: 2.12 [1.58-2.86]) and Pakistani men (1.24 [1.06-1.46]). CONCLUSIONS: Lower COVID-19 vaccination uptake in several ethnic minority groups may drive some of the differences in COVID-19 mortality compared to White British. Public health strategies to increase vaccination uptake in ethnic minority groups would help reduce inequalities in COVID-19 mortality, which have remained substantial since the start of the vaccination campaign.

Neonatal surgery during Covid-19 pandemic: Our experience in a tertiary care hospital in Bangladesh

Background: The impact of Covid-19 on global health and especially on the low-resource countries’ health system has been serious. The lack of personal protective equipment, masks, sanitizers, and lack of testing has made the surgical delivery even more challenging. These delays in management of these surgical cases are going to stack up in the future and increase mortality and morbidity. However, the emergent nature of some of the neonatal surgical cases cannot be postponed. Materials and Methods: This is a retrospective observational study done from April 2020 to September 2020 in Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh. Surgical neonates were tested for SARS-CoV-2 by using the real-time PCR on oropharyngeal swabs. The reports of the tests were received only 24 h later. Results: A total of 22 neonates with surgical conditions were admitted during the study period. Eighteen were tested for Covid-19, whereas 4 were tested but reports were not awaited for surgery. All the babies tested negative for Covid-19. There were a variety of cases admitted, predominately hydronephrosis, clubfoot, meningocele, intestinal obstruction, cleft lip, and palate. Among the 22 surgical neonates, 6 received the surgical management, whereas 16 were managed conservatively and kept on follow-up. Regarding the outcome, 17 patients (3 managed surgically and 14 nonemergent cases were managed conservatively) were discharged to home. Mortality were 5 in number (3 postoperative patient and 2 while managing conservatively). Conclusion: During the unprecedented times of Covid-19, extreme precaution and protocol must be followed to carry on neonatal surgeries to protect both health workers and children.

Effects of the COVID-19 pandemic on secondary care for cardiovascular disease in the UK: an electronic health record analysis across three countries.

BACKGROUND: Although morbidity and mortality from COVID-19 have been widely reported, the indirect effects of the pandemic beyond 2020 on other major diseases and health service activity have not been well described. METHODS: Analyses used national administrative electronic hospital records in England, Scotland and Wales for 2016-2021. Admissions and procedures during the pandemic (2020-2021) related to six major cardiovascular conditions (acute coronary syndrome, heart failure, stroke/transient ischaemic attack, peripheral arterial disease, aortic aneurysm, and venous thromboembolism) were compared to the annual average in the pre-pandemic period (2016-2019). Differences were assessed by time period and urgency of care. RESULTS: In 2020, there were 31 064 (-6%) fewer hospital admissions (14 506 [-4%] fewer emergencies, 16 560 [-23%] fewer elective admissions) compared to 2016-2019 for the six major cardiovascular diseases combined. The proportional reduction in admissions was similar in all three countries. Overall, hospital admissions returned to pre-pandemic levels in 2021. Elective admissions remained substantially below expected levels for almost all conditions in all three countries (-10 996 [-15%] fewer admissions). However, these reductions were offset by higher than expected total emergency admissions (+25 878 [+6%] higher admissions), notably for heart failure and stroke in England, and for venous thromboembolism in all three countries. Analyses for procedures showed similar temporal variations to admissions. CONCLUSION: This study highlights increasing emergency cardiovascular admissions during the pandemic, in the context of a substantial and sustained reduction in elective admissions and procedures. This is likely to increase further the demands on cardiovascular services over the coming years.

Digital learning and the lopsidedness of the education in government and private primary schools during the COVID-19 pandemic in West Bengal, India

Since March 2020, all academic institutions have been closed due to the COVID-19 pandemic and have been encouraged online mode of education to the students in West Bengal, India. The most profound negative effect of the school closure has been noticed on primary education. This research examines how school closures in both government and private primary schools in West Bengal result in uneven teaching-learning opportunities in formal and non-formal education during the COVID-19 pandemic. The present study was conducted based on an online survey in West Bengal using a structured questionnaire. The Kolmogorov-Smirnov Test, Shapiro-Wilk Test, Pearson Chi-squared (?2) test, and logistic regression were used to check the relationships among the variables. Based on 473 responses to an online survey administered to the parents and educated family members of 3?10 years aged children from both government and private primary schools in West Bengal. The authors' analysis shows the teaching-learning opportunities varied significantly. Further, the study revealed a noticeable gap between government and private primary schools. The study depicts that students from urban areas have more accessibility to online education than those living in rural areas. The study revealed that 98.7% of private schools and 33.7% of students from government primary schools could access online education. Statistically significant differences were observed between both categories of schools in academic affairs during the pandemic.

Developing a mental health index using a machine learning approach: Assessing the impact of mobility and lockdown during the COVID-19 pandemic.

Governments worldwide have implemented stringent restrictions to curtail the spread of the COVID-19 pandemic. Although beneficial to physical health, these preventive measures could have a profound detrimental effect on the mental health of the population. This study focuses on the impact of lockdowns and mobility restrictions on mental health during the COVID-19 pandemic. We first develop a novel mental health index based on the analysis of data from over three million global tweets using the Microsoft Azure machine learning approach. The computed mental health index scores are then regressed with the lockdown strictness index and Google mobility index using fixed-effects ordinary least squares (OLS) regression. The results reveal that the reduction in workplace mobility, reduction in retail and recreational mobility, and increase in residential mobility (confinement to the residence) have harmed mental health. However, restrictions on mobility to parks, grocery stores, and pharmacy outlets were found to have no significant impact. The proposed mental health index provides a path for theoretical and empirical mental health studies using social media.

Rapid Assay for the Therapeutic Drug Monitoring of Edoxaban.

Edoxaban is a direct oral anticoagulant (DOAC) that has been recently indicated for the treatment of pulmonary embolism (PE) in SARS-CoV-2 infections. Due to its pharmacokinetic variability and a narrow therapeutic index, the safe administration of the drug requires its therapeutic drug monitoring (TDM) in patients receiving the treatment. In this work, we present a label-free method for the TDM of edoxaban by surface enhanced Raman spectroscopy (SERS). The new method utilises the thiol chemistry of the drug to chemisorb its molecules onto a highly sensitive SERS substrate. This leads to the formation of efficient hotspots and a strong signal enhancement of the drug Raman bands, thus negating the need for a Raman reporter for its SERS quantification. The standard samples were run with a concentration range of 1.4 × 10-4 M to 10-12 M using a mobile phase comprising of methanol/acetonitrile (85:15 v/v) at 291 nm followed by the good linearity of R2 = 0.997. The lowest limit of quantification (LOQ) by the SERS method was experimentally determined to be 10-12 M, whereas LOQ for HPLC-UV was 4.5 × 10-7 M, respectively. The new method was used directly and in a simple HPLC-SERS assembly to detect the drug in aqueous solutions and in spiked human blood plasma down to 1 pM. Therefore, the SERS method has strong potential for the rapid screening of the drug at pathology labs and points of care.

Developing a mental health index using a machine learning approach: Assessing the impact of mobility and lockdown during the COVID-19 pandemic

Governments worldwide have implemented stringent restrictions to curtail the spread of the COVID-19 pandemic. Although beneficial to physical health, these preventive measures could have a profound detrimental effect on the mental health of the population. This study focuses on the impact of lockdowns and mobility restrictions on mental health during the COVID-19 pandemic. We first develop a novel mental health index based on the analysis of data from over three million global tweets using the Microsoft Azure machine learning approach. The computed mental health index scores are then regressed with the lockdown strictness index and Google mobility index using fixed-effects ordinary least squares (OLS) regression. The results reveal that the reduction in workplace mobility, reduction in retail and recreational mobility, and increase in residential mobility (confinement to the residence) have harmed mental health. However, restrictions on mobility to parks, grocery stores, and pharmacy outlets were found to have no significant impact. The proposed mental health index provides a path for theoretical and empirical mental health studies using social media.

Association between household size and COVID-19: A UK Biobank observational study.

OBJECTIVE: To assess the association between household size and risk of non-severe or severe COVID-19. DESIGN: A longitudinal observational study. SETTING: This study utilised UK Biobank linked to national SARS-CoV-2 laboratory test data. PARTICIPANTS: 401,910 individuals with available data on household size in UK Biobank. MAIN OUTCOME MEASURES: Household size was categorised as single occupancy, two-person households and households of three or more. Severe COVID-19 was defined as a positive SARS-CoV-2 test on hospital admission or death with COVID-19 recorded as the underlying cause; and non-severe COVID-19 as a positive test from a community setting. Logistic regression models were fitted to assess associations, adjusting for potential confounders. RESULTS: Of 401,910 individuals, 3612 (1%) were identified as having suffered from a severe COVID-19 infection and 11,264 (2.8%) from a non-severe infection, between 16 March 2020 and 16 March 2021. Overall, the odds of severe COVID-19 was significantly higher among individuals living alone (adjusted odds ratio: 1.24 [95% confidence interval: 1.14 to 1.36], or living in a household of three or more individuals (adjusted odds ratio: 1.28 [1.17 to 1.39], when compared to individuals living in a household of two. For non-severe COVID-19 infection, individuals living in a single-occupancy household had lower odds compared to those living in a household of two (adjusted odds ratio: 0.88 [0.82 to 0.93]. CONCLUSIONS: Odds of severe or non-severe COVID-19 infection were associated with household size. Increasing understanding of why certain households are more at risk is important for limiting spread of the infection.

A population-based cohort study of obesity, ethnicity and COVID-19 mortality in 12.6 million adults in England.

Obesity and ethnicity are known risk factors for COVID-19 outcomes, but their combination has not been extensively examined. We investigate the association between body mass index (BMI) and COVID-19 mortality across different ethnic groups using linked national Census, electronic health records and mortality data for adults in England from the start of pandemic (January 2020) to December 2020. There were 30,067 (0.27%), 1,208 (0.29%), 1,831 (0.29%), 845 (0.18%) COVID-19 deaths in white, Black, South Asian and other ethnic minority groups, respectively. Here we show that BMI was more strongly associated with COVID-19 mortality in ethnic minority groups, resulting in an ethnic risk of COVID-19 mortality that was dependant on BMI. The estimated risk of COVID-19 mortality at a BMI of 40 kg/m2 in white ethnicities was equivalent to the risk observed at a BMI of 30.1 kg/m2, 27.0 kg/m2, and 32.2 kg/m2 in Black, South Asian and other ethnic minority groups, respectively.

Ethnic minorities and COVID-19: examining whether excess risk is mediated through deprivation.

BACKGROUND: People from South Asian and black minority ethnic groups are disproportionately affected by the COVID-19 pandemic. It is unknown whether deprivation mediates this excess ethnic risk. METHODS: We used UK Biobank with linked COVID-19 outcomes occurring between 16th March 2020 and 24th August 2020. A four-way decomposition mediation analysis was used to model the extent to which the excess risk of testing positive, severe disease and mortality for COVID-19 in South Asian and black individuals, relative to white individuals, would be eliminated if levels of high material deprivation were reduced within the population. RESULTS: We included 15 044 (53.0% women) South Asian and black and 392 786 (55.2% women) white individuals. There were 151 (1.0%) positive tests, 91 (0.6%) severe cases and 31 (0.2%) deaths due to COVID-19 in South Asian and black individuals compared with 1471 (0.4%), 895 (0.2%) and 313 (0.1%), respectively, in white individuals. Compared with white individuals, the relative risk of testing positive for COVID-19, developing severe disease and COVID-19 mortality in South Asian and black individuals were 2.73 (95% CI: 2.26, 3.19), 2.96 (2.31, 3.61) and 4.04 (2.54, 5.55), respectively. A hypothetical intervention moving the 25% most deprived in the population out of deprivation was modelled to eliminate between 40 and 50% of the excess risk of all COVID-19 outcomes in South Asian and black populations, whereas moving the 50% most deprived out of deprivation would eliminate over 80% of the excess risk of COVID-19 outcomes. CONCLUSIONS: The excess risk of COVID-19 outcomes in South Asian and black communities could be substantially reduced with population level policies targeting material deprivation.

Impact of cardiometabolic multimorbidity and ethnicity on cardiovascular/renal complications in patients with COVID-19.

OBJECTIVE: Using a large national database of people hospitalised with COVID-19, we investigated the contribution of cardio-metabolic conditions, multi-morbidity and ethnicity on the risk of in-hospital cardiovascular complications and death. METHODS: A multicentre, prospective cohort study in 302 UK healthcare facilities of adults hospitalised with COVID-19 between 6 February 2020 and 16 March 2021. Logistic models were used to explore associations between baseline patient ethnicity, cardiometabolic conditions and multimorbidity (0, 1, 2, >2 conditions), and in-hospital cardiovascular complications (heart failure, arrhythmia, cardiac ischaemia, cardiac arrest, coagulation complications, stroke), renal injury and death. RESULTS: Of 65 624 patients hospitalised with COVID-19, 44 598 (68.0%) reported at least one cardiometabolic condition on admission. Cardiovascular/renal complications or death occurred in 24 609 (38.0%) patients. Baseline cardiometabolic conditions were independently associated with increased odds of in-hospital complications and this risk increased in the presence of cardiometabolic multimorbidity. For example, compared with having no cardiometabolic conditions, 1, 2 or ≥3 conditions was associated with 1.46 (95% CI 1.39 to 1.54), 2.04 (95% CI 1.93 to 2.15) and 3.10 (95% CI 2.92 to 3.29) times higher odds of any cardiovascular/renal complication, respectively. A similar pattern was observed for all-cause death. Compared with the white group, the South Asian (OR 1.19, 95% CI 1.10 to 1.29) and black (OR 1.53 to 95% CI 1.37 to 1.72) ethnic groups had higher risk of any cardiovascular/renal complication. CONCLUSIONS: In hospitalised patients with COVID-19, cardiovascular complications or death impacts just under half of all patients, with the highest risk in those of South Asian or Black ethnicity and in patients with cardiometabolic multimorbidity.

Personality and travel intentions during and after the COVID-19 pandemic: An artificial neural network (ANN) approach.

The tourism sector has been deeply ravaged by the COVID-19 pandemic as many individuals abstained entirely from travel. Thus, before contemplating the trajectory of the sector's recovery, it is essential to understand individuals' travel intentions both during and after the pandemic. The present study contributes in this regard by examining the impact of individuals' personality traits categorised by the five-factor model, or the Big Five, on their leisure travel intentions during and after the pandemic. To this end, we utilised an artificial neural network (ANN) approach to analyse 500 responses from individuals residing in Japan. The results reveal that extraversion has the strongest relative influence on intentions to travel during the pandemic, whereas openness to experience has the strongest influence on travel intentions after the pandemic. This study is the first of its kind to examine the influence of the Big Five personality traits on travel intentions in the context of a pandemic.

Diabetes, obesity, hypertension and risk of severe COVID-19: a protocol for systematic review and meta-analysis.

INTRODUCTION: Previous evidence from several countries, including China, Italy, Mexico, UK and the USA, indicates that among patients with confirmed COVID-19 who were hospitalised, diabetes, obesity and hypertension might be important risk factors for severe clinical outcomes. Several preliminary systematic reviews and meta-analyses have been conducted on one or more of these non-communicable diseases, but the findings have not been definitive, and recent evidence has become available from many more populations. Thus, we aim to conduct a systematic review and meta-analysis of observational studies to assess the relationship of diabetes, obesity and hypertension with severe clinical outcomes in patients with COVID-19. METHOD AND ANALYSIS: We will search 16 major databases (MEDLINE, Embase, Global Health, CAB Abstracts, PsycINFO, CINAHL, Academic Research Complete, Africa Wide Information, Scopus, PubMed Central, ProQuest Central, WHO Virtual Health Library, Homeland Security COVID-19 collection, SciFinder, Clinical Trials and Cochrane Library) for articles published between December 2019 and December 2020. We will follow the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2016 guidelines for the design and reporting the results. We will include observational studies that assess the associations of pre-existing diabetes, obesity and hypertension in patients with COVID-19 with risk of severe clinical outcomes such as intensive care unit admission, receiving mechanical ventilation or death. Stata V.16.1 and R-Studio V.1.4.1103 statistical software will be used for statistical analysis. Meta-analysis will be used to estimate the pooled risks and to assess potential heterogeneities in risks. ETHICS AND DISSEMINATION: The study was reviewed for human subjects concerns by the US CDC Center for Global Health and determined to not represent human subjects research because it uses data from published studies. We plan to publish results in a peer-reviewed journal and present at national and international conferences. PROSPERO REGISTRATION NUMBER: CRD42021204371.

Effects of covid-19 pandemic on life expectancy and premature mortality in 2020: time series analysis in 37 countries.

OBJECTIVE: To estimate the changes in life expectancy and years of life lost in 2020 associated with the covid-19 pandemic. DESIGN: Time series analysis. SETTING: 37 upper-middle and high income countries or regions with reliable and complete mortality data. PARTICIPANTS: Annual all cause mortality data from the Human Mortality Database for 2005-20, harmonised and disaggregated by age and sex. MAIN OUTCOME MEASURES: Reduction in life expectancy was estimated as the difference between observed and expected life expectancy in 2020 using the Lee-Carter model. Excess years of life lost were estimated as the difference between the observed and expected years of life lost in 2020 using the World Health Organization standard life table. RESULTS: Reduction in life expectancy in men and women was observed in all the countries studied except New Zealand, Taiwan, and Norway, where there was a gain in life expectancy in 2020. No evidence was found of a change in life expectancy in Denmark, Iceland, and South Korea. The highest reduction in life expectancy was observed in Russia (men: -2.33, 95% confidence interval -2.50 to -2.17; women: -2.14, -2.25 to -2.03), the United States (men: -2.27, -2.39 to -2.15; women: -1.61, -1.70 to -1.51), Bulgaria (men: -1.96, -2.11 to -1.81; women: -1.37, -1.74 to -1.01), Lithuania (men: -1.83, -2.07 to -1.59; women: -1.21, -1.36 to -1.05), Chile (men: -1.64, -1.97 to -1.32; women: -0.88, -1.28 to -0.50), and Spain (men: -1.35, -1.53 to -1.18; women: -1.13, -1.37 to -0.90). Years of life lost in 2020 were higher than expected in all countries except Taiwan, New Zealand, Norway, Iceland, Denmark, and South Korea. In the remaining 31 countries, more than 222 million years of life were lost in 2020, which is 28.1 million (95% confidence interval 26.8m to 29.5m) years of life lost more than expected (17.3 million (16.8m to 17.8m) in men and 10.8 million (10.4m to 11.3m) in women). The highest excess years of life lost per 100 000 population were observed in Bulgaria (men: 7260, 95% confidence interval 6820 to 7710; women: 3730, 2740 to 4730), Russia (men: 7020, 6550 to 7480; women: 4760, 4530 to 4990), Lithuania (men: 5430, 4750 to 6070; women: 2640, 2310 to 2980), the US (men: 4350, 4170 to 4530; women: 2430, 2320 to 2550), Poland (men: 3830, 3540 to 4120; women: 1830, 1630 to 2040), and Hungary (men: 2770, 2490 to 3040; women: 1920, 1590 to 2240). The excess years of life lost were relatively low in people younger than 65 years, except in Russia, Bulgaria, Lithuania, and the US where the excess years of life lost was >2000 per 100 000. CONCLUSION: More than 28 million excess years of life were lost in 2020 in 31 countries, with a higher rate in men than women. Excess years of life lost associated with the covid-19 pandemic in 2020 were more than five times higher than those associated with the seasonal influenza epidemic in 2015.