Difference In COVID-19 Mortality Research Articles

Racial and Ethnic Disparities in COVID-19 Mortality

This cross-sectional study examines racial and ethnic differences in COVID-19 mortality in the United States across 4 case surges between February 2020 and September 2023.

From test to rest: evaluating socioeconomic differences along the COVID-19 care pathway in the Netherlands.

The COVID-19 pandemic exacerbated healthcare needs and caused excess mortality, especially among lower socioeconomic groups. This study describes the emergence of socioeconomic differences along the COVID-19 pathway of testing, healthcare use and mortality in the Netherlands. This retrospective observational Dutch population-based study combined individual-level registry data from June 2020 to December 2020 on personal socioeconomic characteristics, COVID-19 administered tests, test results, general practitioner (GP) consultations, hospital admissions, Intensive Care Unit (ICU) admissions and mortality. For each outcome measure, relative differences between income groups were estimated using log-link binomial regression models. Furthermore, regression models explained socioeconomic differences in COVID-19 mortality by differences in ICU/hospital admissions, test administration and test results. Among the Dutch population, the lowest income group had a lower test probability (RR = 0.61) and lower risk of testing positive (RR = 0.77) compared to the highest income group. However, among individuals with at least one administered COVID-19 test, the lowest income group had a higher risk of testing positive (RR = 1.40). The likelihood of hospital admissions and ICU admissions were higher for low income groups (RR = 2.11 and RR = 2.46, respectively). The lowest income group had an almost four times higher risk of dying from COVID-19 (RR = 3.85), which could partly be explained by a higher risk of hospitalization and ICU admission, rather than differences in test administration or result. Our findings indicated that socioeconomic differences became more pronounced at each step of the care pathway, culminating to a large gap in mortality. This underlines the need for enhancing social security and well-being policies and incorporation of health equity in pandemic preparedness plans.

Differences in Covid-19 mortality among persons 70 years and older in an integrated care setting in region Stockholm: a multi-level analysis between March 2020-February 2021

BackgroundIn Norrtälje municipality, within Region Stockholm, there is a joint integrated care organisation providing health and social care, which may have facilitated a more coordinated response to the covid-19 pandemic compared to the otherwise decentralised Swedish system. This study compares the risk of covid-19 mortality among persons 70 years and older, in the municipalities of Stockholm, Södertälje, and Norrtälje, while considering area and individual risk factors.MethodsA population-based study using linked register data to examine covid-19 mortality among those 70 + years (N = 127,575) within the municipalities of interest between the periods March-August 2020 and September 2020-February 2021. The effect of individual and area level variables on covid-19 mortality among inhabitants in 68 catchment areas were examined using multi-level logistic models.ResultsIndividual factors associated with covid-19 mortality were sex, older age, primary education, country of birth and poorer health as indicated by the Charlson Co-morbidity Index. The area-level variables associated were high deprivation (OR: 1.56, CI: 1.18–2.08), population density (OR: 1.14, CI: 1.08–1.21), and usual care. Together, this explained 85.7% of the variation between catchment areas in period 1 and most variation was due to individual risk factors in period 2. Little of the residual variation was attributed to differences between catchment areas.ConclusionIntegrated care in Norrtälje may have facilitated a more coordinated response during period 1, compared to municipalities with usual care. In the future, integrated care should be considered as an approach to better protect and meet the care needs of older people during emergency situations.

Sex differences in COVID-19 mortality: A large US-based cohort study (2020–2022)

<sec><title>Background</title><p>In the present study, we aim to assess the trend in mortality in COVID-19 by time and sex in a large cohort using Datavant's Death Index database. The main objectives of this study are to analyze mortality cases over time, which are categorized by sex and age, and to identify potential reasons for the observed differences.</p></sec><sec><title>Methods</title><p>This is a retrospective cohort containing information on deceased individuals in the United States and Canada (n = 4,384,265). We included adult male and female patients with a clinical diagnosis of COVID-19 (January–December 2022) (ICD-10 code: U07.1). Mortality cases for males and females were presented over a three-year period of COVID-19 pandemic. Sex ratios presenting the change of mortality cases over time was also computed as the number of diagnosed males over female patients. Sex-differences in the mortality rates were illustrated by age groups.</p></sec><sec><title>Results</title><p>In 2020, mortality cases increased to reach up to 200,000 cases per day and fluctuated due to social and/or cultural events in the US. In 2021, mortality cases reached the highest peak over the time period despite the US vaccine rollout due to holiday gatherings during November and December 2021, as well as the spread of a more contagious strain of the virus. In 2022, mortality cases decreased due to widespread vaccinations and a rise in natural immunity following the first Omicron surge. Furthermore, the proportion of COVID-19 cases in males and females remained stable during the pandemic; however, the number of diagnosed male patients markedly increased during the first months of 2022. Gender discrepancies suggest the role of various factors such as occupation, underlying comorbidities, and behavioral and immunological factors.</p></sec><sec><title>Conclusion</title><p>Our study highlights higher mortality rates observed among males, suggesting that several factors may contribute to such differences, including social, behavioral, and biological factors. Our findings highlight the importance of implementing sex-specific treatment approaches in COVID-19 patients.</p></sec>

Sex differences in COVID-19 mortality: A large US-based cohort study (2020–2022)

<sec><title>Background</title><p>In the present study, we aim to assess the trend in mortality in COVID-19 by time and sex in a large cohort using Datavant's Death Index database. The main objectives of this study are to analyze mortality cases over time, which are categorized by sex and age, and to identify potential reasons for the observed differences.</p></sec><sec><title>Methods</title><p>This is a retrospective cohort containing information on deceased individuals in the United States and Canada (n = 4,384,265). We included adult male and female patients with a clinical diagnosis of COVID-19 (January–December 2022) (ICD-10 code: U07.1). Mortality cases for males and females were presented over a three-year period of COVID-19 pandemic. Sex ratios presenting the change of mortality cases over time was also computed as the number of diagnosed males over female patients. Sex-differences in the mortality rates were illustrated by age groups.</p></sec><sec><title>Results</title><p>In 2020, mortality cases increased to reach up to 200,000 cases per day and fluctuated due to social and/or cultural events in the US. In 2021, mortality cases reached the highest peak over the time period despite the US vaccine rollout due to holiday gatherings during November and December 2021, as well as the spread of a more contagious strain of the virus. In 2022, mortality cases decreased due to widespread vaccinations and a rise in natural immunity following the first Omicron surge. Furthermore, the proportion of COVID-19 cases in males and females remained stable during the pandemic; however, the number of diagnosed male patients markedly increased during the first months of 2022. Gender discrepancies suggest the role of various factors such as occupation, underlying comorbidities, and behavioral and immunological factors.</p></sec><sec><title>Conclusion</title><p>Our study highlights higher mortality rates observed among males, suggesting that several factors may contribute to such differences, including social, behavioral, and biological factors. Our findings highlight the importance of implementing sex-specific treatment approaches in COVID-19 patients.</p></sec>

Spatial patterns of COVID-19 and non-COVID-19 mortality across waves of infection in England, Wales, and Scotland

Recent studies have established the key individual-level risk factors of COVID-19 mortality such as age, gender, ethnicity, and socio-economic status. However, the spread of infectious diseases is a spatial and temporal process implying that COVID-19 mortality and its determinants may vary sub-nationally and over time. We investigate the spatial patterns of age-standardised death rates due to COVID-19 and their correlates across local authority districts in England, Wales, and Scotland across three waves of infection. Using a Spatial Durbin model, we explore within- and between-country variation and account for spatial dependency. Areas with a higher share of ethnic minorities and higher levels of deprivation had higher rates of COVID-19 mortality. However, the share of ethnic minorities and population density in an area were more important predictors of COVID-19 mortality in earlier waves of the pandemic than in later waves, whereas area-level deprivation has become a more important predictor over time. Second, during the first wave of the pandemic, population density had a significant spillover effect on COVID-19 mortality, indicating that the pandemic spread from big cities to neighbouring areas. Third, after accounting for differences in ethnic composition, deprivation, and population density, initial cross-country differences in COVID-19 mortality almost disappeared. COVID-19 mortality remained higher in Scotland than in England and Wales in the third wave when COVID-19 mortality was relatively low in all three countries. Interpreting these results in the context of higher overall (long-term) non-COVID-19 mortality in Scotland suggests that Scotland may have performed better than expected during the first two waves. Our study highlights that accounting for both spatial and temporal factors is essential for understanding social and demographic risk factors of mortality during pandemics.

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

BackgroundEthnic 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.MethodsWe 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.ResultsAge-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]).ConclusionsLower 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.

Methodological Considerations for Design of Studies Investigating Gender Differences in COVID-19 Mortality

Methodological Considerations for Design of Studies Investigating Gender Differences in COVID-19 Mortality

COVID-19 and the ecological crisis: What do they have in common?

This lecture transcript is divided in four parts. First, I examine the main public-health strategies in managing the COVID-19 pandemic. Although there are numerous factors capable of explaining national differences in COVID-19 mortality that are not attributable to merits or demerits of governments, I have identified five lethal errors (lack of preparation, misinformation, medicalisation, a policy approach based on a 'laissez-faire' attitude to the virus and social inequity) and four vital actions (testing, tracing, isolating with support, timeliness and immunisation) that best distinguish success or failure in tackling the pandemic. In the second part, I analyse the origin of SARS-CoV-2 and major risk factors for emerging zoonotic diseases (e.g. exploitation of animal wildlife, deforestation, agricultural intensification and climate change) to be addressed to prevent future pandemics. Then, I discuss the interrelationships between the COVID-19 pandemic and the ecological crisis in the context of the so-called neoliberal variant of capitalism. Both crises are largely determined by anthropogenic risk factors influenced by a model of economic development that prioritises infinite economic growth, free trade and a global self-regulating market over any other values of society (including human survival). An alternative economic approach, capable of creating a new balance between the health of humans, animals, and the environment (by modifying their structural drivers), is the most important antidote against new spillovers and climate change. It is the humanitarian immune response we need to protect global health from future pandemics and ecological collapse.

A year and a half into the pandemic in Mexico: evidence of differences in COVID-19 mortality between Indigenous and non-Indigenous populations continues to accumulate.

Among the groups most vulnerable to COVID-19 are Indigenous populations around the world, and in particular, the Mexican Indigenous population. We used public data made available by the General Directorate of Epidemiology of the Mexican Ministry of Health to compare the risk of COVID-19 mortality among the Indigenous and non-Indigenous Mexican population one and a half years into the pandemic. The analytical sample comprises 3,545,952 Mexicans who were diagnosed as infected with severe acute respiratory syndrome coronavirus-2 between March 18, 2020, and September 16, 2021, of which 1.0% (36,195) are Indigenous. Based on parametric survival models, our results show that the risk of death among Indigenous individuals is 52% higher than that of their non-Indigenous counterparts, regardless of age, sex, area of residence, health service, number of chronic diseases, and obesity status. These results suggest that certain structural conditions of the Mexican Indigenous population increase their vulnerability to the pandemic.

Differences in COVID-19 mortality in males and females: Is estrogen hormone attributing to sex differences?

Objectives: Globally, the case fatality ratio is more in males versus females. Some studies have suggested estrogen hormone decreases susceptibility to SARS CoV-2. We have analyzed the observed sex differences in COVID-19 behavior in males and females and the clinical profiles of females of different age groups of COVID-19 patients and discussed their symptoms, laboratory evaluations, and associated comorbidities. Material and Methods: The patients were tested for COVID-19 through real-time RT-PCR (Reverse Transcription Polymerase Chain Reaction) assay. The data obtained were studied for the epidemiological, clinical, and laboratory characteristics from their medical records. Results: The mortality rate in females was 12.33% (36/292) whereas mortality in males was 19.63% (84/428). In between group analysis, 8.7% (14/161) of females died in the <40 years age group versus 16.8% (22/131) in more than 40 years age group whereas in males, the mortality was 13.7% (21/153) in <40 years versus 22.9%(63/275). The mortality rate in women older than 40 years was greater than mortality in younger females emphasizing the protection provided by estrogen hormone in them. The proportion of patients who expired due to COVID-19 significantly differs by age cutoff of 40 years, X2 (1, n = 428). The difference is statistically significant at P < 0.05. Males more than 40 years are more likely to expire. Conclusion: Sex-related differences in coronavirus pandemic have been found pointing toward the protective role of estrogen hormone and other differences in immunological behavior in males and females. Downregulation of ACE2 expression, thereby reducing viral entry, might also be contributory to decreasing mortality in females.

Immunophenotypes of anti-SARS-CoV-2 responses associated with fatal COVID-19.

BackgroundThe relationship between anti-SARS-CoV-2 humoral immune response, pathogenic inflammation, lymphocytes and fatal COVID-19 is poorly understood.MethodsLongitudinal prospective cohort of hospitalized patients with COVID-19 (N=254) was followed up to 35 d after admission (median, 8 d). We measured early anti-SARS-CoV-2 S1 antibody IgG levels and dynamic (698 samples) of quantitative circulating T, B, NK lymphocyte subsets and serum interleukin-6 response. We used machine learning to identify patterns of the immune response, and related these patterns to the primary outcome of 28-day mortality in analyses adjusted for clinical severity factors.ResultsOverall, 45 (18%) patients died within 28 days after hospitalization. We identified six clusters representing discrete anti-SARS-CoV-2 immunophenotypes. Clusters differed considerably in COVID-19 survival. Two clusters, the anti-S1-IgGlowestTlowestBlowestNKmodIL-6mod, and the anti-S1-IgGhighTlowBmodNKmodIL-6highest had a high risk of fatal COVID-19 (HR, 3.36–21.69; 95% CI, 1.51–163.61 and HR, 8.39–10.79; 95% CI, 1.20–82.67; P≤0.03, respectively). The anti-S1-IgGhighestTlowestBmodNKmodIL-6mod and anti-S1-IgGlowThighestBhighestNKhighestIL-6low cluster were associated with moderate risk of mortality. In contrast, two clusters the anti-S1- anti-S1-IgGhighThighBmodNKmodIL-6low and anti-S1-IgGhighestThighestBhighNKhighIL-6lowest clusters were characterized by a very low risk of mortality.ConclusionsBy employing unsupervised machine learning we identified multiple anti-SARS-CoV-2 immune response clusters and observed major differences in COVID-19 mortality between these clusters. Two discrete immune pathways may lead to fatal COVID-19. One is driven by impaired or delayed antiviral humoral immunity, independently of hyper-inflammation, and the other may arise through excessive IL-6 mediated host inflammation response, independently of the protective humoral response. Those observations could be explored further for application in clinical practice.

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 roll-out.

ObjectivesThis study aims to assess whether ethnic differences in COVID-19 mortality in England have continued into the third wave and to what extent differences in vaccination rates contributed to excess COVID-19 mortality after accounting for other risk factors. 
 ApproachThis Cohort study of 28.8 million adults living in private households or communal establishments in England is based on data from the Office for National Statistics (ONS) Public Health Data Asset (PHDA). The ONS PHDA is a linked dataset combining the 2011 Census, mortality records, the General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR), Hospital Episode Statistics (HES) and vaccination data from the National Immunisation Management System (NIMS). We calculated hazard ratios (HRs) for death involving COVID-19 during the second (8 December 2020 to 12 June 2021) and third wave (13 June 2021 to 1 December 2021) of the pandemic separately for males to females to assess the association between ethnic group and death involving COVID-19 in each wave, sequentially adjusting for age, residence type, geographical factors, sociodemographic characteristics, pre-pandemic health, and vaccination status.
 ResultsAge-adjusted HRs of death involving COVID-19 were higher for most ethnic minority groups than the White British group during both waves, particularly for groups with lowest vaccination rates (Bangladeshi, Pakistani, Black African and Black Caribbean). In both waves, 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. The only groups where fully-adjusted HRs remained elevated were the Bangladeshi group (men: 2.19, 95% CI 1.72 to 2.78; women: 2.12, 95% CI 1.58 to 2.86) and men from the Pakistani group (1.24, 95% CI 1.06 to 1.46). 
 ConclusionPublic health strategies to increase vaccination uptake in ethnic minority groups could reduce disparities in COVID-19 mortality that cannot be accounted for by pre-existing risk factors.

Relationship between COVID-19 Mortality, Hospital Beds, and Primary Care by Italian Regions: A Lesson for the Future.

One of the characteristics of the SARS-CoV-2 infection in Italy is the significant regional difference in terms of lethality and mortality. These geographical variances were clear in the first wave and confirmed in the second one as well. The study aimed to analyze the correlation between regional differences in COVID-19 mortality and different regional care models, by retrospectively analyzing the association between the Italian COVID-19 deaths and the number of hospital beds, long-term care facilities, general practitioners (GPs), and the health expenditure per capita. The period considered was from 1 March 2020 to 1 March 2021. The number of hospital beds (p < 0.0001) and the number of GPs (p = 0.0094) significantly predicted the COVID-19 death rate. The Italian regions with a higher number of hospital beds and a lower number of GPs showed a higher number of deaths. Multivariate analyses confirmed the results. The Italian regions with a higher amount of centralized healthcare, as represented by the number of hospital beds, experienced a higher number of deaths, while the regions with greater community support, as exemplified by the number of the GPs, faced higher survival. These results suggest the need for a change in the current healthcare system organization.

COVID-19 mortality in the United States: It's been two Americas from the start.

During the summer of 2021, a narrative of "two Americas" emerged: one with high demand for the COVID-19 vaccine and the second with widespread vaccine hesitancy and opposition to masks and vaccines. We analyzed "excess mortality" rates (the difference between total deaths and what would have been expected based on earlier time periods) prepared by the CDC for the United States from January 3, 2020 to September 26, 2021. Between Jan. 3, 2020 and Sept. 26, 2021, there were 895,693 excess deaths associated with COVID-19, 26% more than reported as such. The proportion of deaths estimated by the excess mortality method that was reported as COVID-19 was highest in the Northeast (92%) and lowest in the West (72%) and South (76%). Of the estimated deaths, 43% occurred between Oct. 4, 2020 and Feb. 27, 2021. Before May 31, 2020, approximately 56% of deaths were in the Northeast, where 17% of the population resides. Subsequently, 48% of deaths were in the South, which makes up 38% of the population. Since May 31, 2020, the South experienced COVID-19 mortality 26% higher than the national rate, whereas the Northeast's rate was 42% lower. If each region had the same mortality rate as the Northeast, more than 316,234 COVID-19 deaths between May 31, 2020 and Sept. 26, 2021 were "avoidable." More than half (63%) of the avoidable deaths occurred between May 31, 2020 and February, 2021, and more than half (60%) were in the South. Regional differences in COVID-19 mortality have been strong throughout the pandemic. The South has had higher mortality rates than the rest of the U.S. since May 31, 2020, and experienced 62% of the avoidable deaths. A comprehensive COVID-19 policy, including population-based restrictions as well as vaccines, is needed to control the pandemic.

Impact of Immune Checkpoint Inhibitors on COVID-19 Severity in Patients with Cancer.

BackgroundAmid continued uncertainty about the management of cancer patients during the pandemic, this study sought to obtain real-world data on the use of immune checkpoint inhibitors (ICIs) before COVID-19 diagnosis and its association with severity and survival outcomes in cancer patients who contracted COVID-19.MethodsCancer patients diagnosed with COVID-19 were identified from a large electronic health record database; those treated with ICIs before COVID-19+ diagnosis were matched in a 1:2 ratio to those not treated with ICIs, using a 2-step matching procedure. A descriptive analysis examined the difference in COVID-19 mortality (30-day and overall) and severity outcomes between the 2 cohorts, and overall survival was compared.ResultsAmong 17 545 adults ≥18 years with cancer who tested positive for COVID-19 between February 20, 2020, and January 28, 2021, in the US, 228 ICI-treated patients were matched to 456 non-ICI-treated patients, comprising the 2 study cohorts. Clinical characteristics differed significantly between the 2 cohorts before matching, with metastatic disease, lung cancer, a history of smoking, and the presence of pulmonary comorbidities being more common in the ICI-treated cohort; after matching, the 2 cohorts were similar. There were no significant differences between the ICI-treated and non-ICI-treated cohorts for 30-day mortality (12.7% vs. 14.9%, P = .235), overall mortality (22.4% vs. 22.4%, P = 1.000), hospitalization (38.6% vs. 39.0%, P = .912), or emergency department visits (16.7% vs. 14.7%, P = .500). Overall survival was similar between the 2 cohorts.ConclusionThis analysis adds to the clinical evidence base that use of ICIs before SARS-CoV-2 infection does not affect COVID-19 severity or survival outcomes, supporting the continued use of ICIs in cancer patients during the pandemic.

Sex differences in COVID-19 mortality in the Netherlands

IntroductionSince the first reports of COVID-19 cases, sex-discrepancies have been reported in COVID-19 mortality. We provide a detailed description of these sex differences in relation to age and comorbidities among notified cases as well as in relation to age and sex-specific mortality in the general Dutch population.MethodsData on COVID-19 cases and mortality until May 31st 2020 was extracted from the national surveillance database with exclusion of healthcare workers. Association between sex and case fatality was analyzed with multivariable logistic regression. Subsequently, male–female ratio in standardized mortality ratios and population mortality rates relative to all-cause and infectious disease-specific mortality were computed stratified by age.ResultsMale–female odds ratio for case fatality was 1.33 [95% CI 1.26–1.41] and among hospitalized cases 1.27 [95% CI 1.16–1.40]. This remained significant after adjustment for age and comorbidities. The male–female ratio of the standardized mortality ratio was 1.70 [95%CI 1.62–1.78]. The population mortality rate for COVID-19 was 35.1 per 100.000, with a male–female rate ratio of 1.25 (95% CI 1.18–1.31) which was higher than in all-cause population mortality and infectious disease mortality.ConclusionOur study confirms male sex is a predisposing factor for severe outcomes of COVID-19, independent of age and comorbidities. In addition to general male–female-differences, COVID-19 specific mechanisms likely contribute to this mortality discrepancy.

An in silico analysis identifies drugs potentially modulating the cytokine storm triggered by SARS-CoV-2 infection

The ongoing COVID-19 pandemic is one of the biggest health challenges of recent decades. Among the causes of mortality triggered by SARS-CoV-2 infection, the development of an inflammatory “cytokine storm” (CS) plays a determinant role. Here, we used transcriptomic data from the bronchoalveolar lavage fluid (BALF) of COVID-19 patients undergoing a CS to obtain gene-signatures associated to this pathology. Using these signatures, we interrogated the Connectivity Map (CMap) dataset that contains the effects of over 5000 small molecules on the transcriptome of human cell lines, and looked for molecules which effects on transcription mimic or oppose those of the CS. As expected, molecules that potentiate immune responses such as PKC activators are predicted to worsen the CS. In addition, we identified the negative regulation of female hormones among pathways potentially aggravating the CS, which helps to understand the gender-related differences in COVID-19 mortality. Regarding drugs potentially counteracting the CS, we identified glucocorticoids as a top hit, which validates our approach as this is the primary treatment for this pathology. Interestingly, our analysis also reveals a potential effect of MEK inhibitors in reverting the COVID-19 CS, which is supported by in vitro data that confirms the anti-inflammatory properties of these compounds.

Occupation and COVID-19 mortality in England: a national linked data study of 14.3 million adults

ObjectivesTo estimate occupational differences in COVID-19 mortality and test whether these are confounded by factors such as regional differences, ethnicity and education or due to non-workplace factors, such as deprivation...