Nursing workforce plays a significant role in reducing COVID-19 deaths worldwide: A cross-sectional analysis of data from 178 countries

Worldwide, the role of nursing workforce in reducing COVID-19 case fatality ratio (CFR) is analyzed with scatter plots, Pearson's r and nonparametric, partial correlation and multiple linear regression models. The potential confounders, median age, health expenditure, physician density, and urbanization were incorporated for calculating the independent role of nursing workforce in protecting against COVID-19 CFR. The study findings suggested that (1) the nursing workforce inversely and significantly correlates with COVID-19 CFR; (2) this relationship remained independent of the confounding effects of each individual confounder or their combination; (3) Nursing workforce was the only variable identified as a significant contributor for reducing COVID-19 CFR, when it was incorporated into stepwise regression model with health expenditure, median age, physician density, and urbanization for analyzing their individual predicting effects on COVID-19 CFR. A strong message for the health authorities is that, although in shortage, nursing workforce showed their significant role in reducing COVID-19 deaths worldwide. This study highlights that the role of nursing workforce should be incorporated into population health research.

COVID-19 DEATHS AND VACCINATION IN NIGERIA: AN APPRAISAL

Background/Aim

Some estimates indicates that by 2021 ending, more people as a share of the vulnerable population in Africa, Nigeria inclusive, have died than elsewhere due to late and inadequate vaccination. With the pandemic phase of high daily deaths formally declared over, COVID-19 deaths before and after vaccination commenced were compared to observe how vaccination impacted COVID-19 deaths.

Method

COVID-19 cases, deaths and vaccination rates in World Health Organization databases up to 07 June 2023 and other variables of interest unavailable there but found in other open- sources were all extracted and examined. Case fatality rate (CFR) per 1,000 for the period prior to vaccination (CFR1) and the period after vaccination commenced (CFR2) was computed. Simple statistics were used in data analysis.

Results

Between when the first case was documented and 05 June 2023, Nigeria recorded 3,155 COVID-19 deaths and majority (61.84%) occurred between 19 March 2020 and March 5, 2021 when vaccination commenced. COVID-19 deaths declined to 61.7% of pre-vaccination figure coinciding with vaccination that delivered partial, primary and booster rates of 39.94%, 33.86% and 5.97% respectively. The cumulative COVID-19 deaths by population size was 8.94/106 pre-vaccination while COVID-19 deaths in vaccination era added 5.510/106mortalities to the final mortality figure of 14. 44/106. The calculated CFR1 and CFR2 rebased were 1.24% and 1.04% respectively.

Conclusion

More COVID-19 deaths occurred before vaccination commenced than in over two years of ongoing vaccination.

[Places of death of COVID-19 patients: an observational study based on evaluated death certificates from the city of Muenster, Germany (2021)]

INTRODUCTION

The places of death of COVID-19 patients have so far hardly been investigated in Germany.

METHODS

In a places of death study in Westphalia (Germany), statistical evaluations were carried out in the city of Muenster on the basis of all death certificates from 2021. Persons who had died with or from a COVID-19 infection were identified by medical information on cause of death and analyzed with descriptive statistical methods using SPSS.

RESULTS

A total of 4044 death certificates were evaluated, and 182 deceased COVID-19 patients were identified (4.5%). In 159 infected patients (3.9%), the viral infection was fatal, whereby the distribution of places of death was as follows: 88.1% in hospital (57.2% in the intensive care unit; 0.0% in the palliative care unit), 0.0% in hospice, 10.7% in nursing homes, 1.3% at home, and 0.0% in other places. All infected patients < 60 years and 75.4% of elderly patients ≥ 80 years died in hospital. Only two COVID-19 patients, both over 80 years old, died at home. COVID-19 deaths in nursing homes (17) affected mostly elderly female residents. Ten of these residents had received end-of-life care from a specialized outpatient palliative care team.

DISCUSSION

The majority of COVID-19 patients died in hospital. This can be explained by the rapid course of the disease with a high symptom burden and the frequent young age of the patients. Inpatient nursing facilities played a certain role as a place of death in local outbreaks. COVID-19 patients rarely died at home. Infection control measures may be one reason why no patients died in hospices or palliative care units.

Social-Economic Backgrounds to US County-Based COVID-19 Deaths: PLS-SEM Analysis

A complex interplay of social, economic, and environmental factors drove the COVID-19 epidemic. Understanding these factors is crucial in explaining the racial disparities observed in COVID-19 deaths. This research investigated various hypotheses, including ecological, racial, demographic, economic, and political party factors, to determine their impact on COVID-19 deaths. The study utilized data from the National Center for Health Statistics (NCHS), specifically focusing on COVID-19 deaths categorized by race and Hispanic origin in US counties, with over 100 recorded deaths as of July 11, 2022.

METHOD

To analyze the data, the study employed partial least squares (PLS) as the statistical approach, considering the presence of multicollinearity in the county-level socioeconomic data. SmartPLS4 software was utilized to illustrate paths depicting variance and covariance and to conduct significance tests. The analysis encompassed overall COVID-19 deaths and deaths among White, Black, and Hispanic Americans, utilizing the same latent variables and paths.

RESULTS

The results revealed that the number of residents aged 65 years or older in a county was the most influential predictor of COVID-19 deaths, irrespective of race. Economic factors emerged as the second strongest predictors. However, when considering each racial group separately, distinct factors aligned with the five hypotheses emerged as significant contributors to COVID-19 deaths. Furthermore, the diagrams illustrating the relationships between these factors (covariates) varied among racial groups, indicating that the underlying social influences differed across races.

DISCUSSION

In light of these findings, it becomes evident that a "one-size-fits-all" approach to prevention strategies is suboptimal. Instead, targeted prevention efforts tailored to specific racial and social classes at high risk of COVID-19 death could have provided more precise messaging and necessitate direct engagement.

Availability of open data related to COVID-19 epidemic in Italy

Background

Since the beginning of the COVID-19 outbreak in Italy, health authorities have released epidemiologic data about this disease. These data were the most important sources of information which were periodically updated and analyzed by researchers to predict the spread of the epidemic. However, comprehensive and timely data on the evolution of COVID-19 have not always been made available to researchers and physicians.

Method

The aim of our work is to investigate quality, availability and format of epidemiologic data about COVID-19 in Italy in different territorial and temporal areas. We tried to access the online resources made available by each of the 19 Italian Regions and the two autonomous Provinces, and in more detail by the Local Health Authorities of one of them, the Emilia-Romagna Region. We analyzed the main sources and flows of data (namely new and cumulative cases of infection, total swabs, new and cumulative COVID-19 deaths, overall and divided by sex), describing their characteristics such as accessibility, format and completeness. We eventually reviewed the data published by the Italian Ministry of Health, the National Institute of Health (ISS) and the Civil Protection Department. The Tim Berners-Lee scale was used to evaluate the open data format.

Results

The flow of COVID-19 epidemiologic data in Italy originated from the Local Health Authorities that transmitted the data - on a daily basis - to the regional authorities, which in turn transferred them to the national authorities. We found a rather high heterogeneity in both the content and the format of the released data, both at the local and the regional level. Few Regions were releasing data in open format. ISS was the only national source of data that provided the number of COVID-19 health outcomes divided by sex and age groups since Spring 2020.

Conclusions

Despite multiple potential useful sources for COVID-19 epidemiology are present in Italy, very few open format data were available both at a macro geographical level (e.g. per Region) and at the provincial level. The access to open format epidemiologic data should be eased, to allow researchers to adequately assess future epidemics and therefore favor timely and effective public health interventions.

hiscovid for visualizing and identifying when policymakers made mistakes against COVID-19

There are two types of policy outcome analysis tools: snapshot tool and time-series tool. hiscovid is a time-series policy outcome scoring tool of COVID-19 policies by country where the daily cumulative population mortality is used for scoring the outcomes of COVID-19 country policies to visualize and identify when policymakers made mistakes. hiscovid allows policymakers to observe the progress and transition of scores over time to learn lessons from the past decision-making mistakes for correcting the current policies to reduce unnecessary deaths. The lower the score, the better the policy. hiscovid attracted 1480 users worldwide.

Association of greenness with COVID-19 deaths in India: An ecological study at district level

BACKGROUND

The world has witnessed a colossal death toll due to the novel coronavirus disease-2019 (COVID-19). A few environmental epidemiology studies have identified association of environmental factors (air pollution, greenness, temperature, etc.) with COVID-19 incidence and mortality, particularly in developed countries. India, being one of the most severely affected countries by the pandemic, still has a dearth of research exploring the linkages of environment and COVID-19 pandemic.

OBJECTIVES

We evaluate whether district-level greenness exposure is associated with a reduced risk of COVID-19 deaths in India.

METHODS

We used average normalized difference vegetation index (NDVI) from January to March 2019, derived by Oceansat-2 satellite, to represent district-level greenness exposure. COVID-19 death counts were obtained through May 1, 2021 (around the peak of the second wave) from an open portal: covid19india.org. We used hierarchical generalized negative binomial regressions to check the associations of greenness with COVID-19 death counts. Analyses were adjusted for air pollution (PM_2.5), temperature, rainfall, population density, proportion of older adults (50 years and above), sex ratio over age 50, proportions of rural population, household overcrowding, materially deprived households, health facilities, and secondary school education.

RESULTS

Our analyses found a significant association between greenness and reduced risk of COVID-19 deaths. Compared to the districts with the lowest NDVI (quintile 1), districts within quintiles 3, 4, and 5 have respectively, around 32% [MRR = 0.68 (95% CI: 0.51, 0.88)], 39% [MRR = 0.61 (95% CI: 0.46, 0.80)], and 47% [MRR = 0.53 (95% CI: 0.40, 0.71)] reduced risk of COVID-19 deaths. The association remains consistent for analyses restricted to districts with a rather good overall death registration (>80%).

CONCLUSION

Though cause-of-death statistics are limited, we confirm that exposure to greenness was associated with reduced district-level COVID-19 deaths in India. However, material deprivation and air pollution modify this association.

An exploration of structural determinants driving racial disparities in COVID-19 deaths in Michigan

Aim

Racial disparities in COVID-19 death rates have largely been driven by structural racism in health, housing, and labor systems that place Black, Brown, and Indigenous populations at greater risk for COVID-19 exposure, transmission, and severe illness, compared to non-Hispanic White populations. Here we examine the association between taxable property values per capita, an indicator influenced by historical and contemporary housing policies that have disproportionately impacted people of color, and COVID-19 deaths.

Methods

Taxable values serve as a proxy for fiscal health providing insight on the county's ability to address imminent needs, including COVID-19 responses. Therefore, higher taxable values indicate local governments that are better equipped to deliver these public services. We used county-level data from the American Community Survey, the Michigan Community Financial Dashboard, The Atlantic's COVID Tracking Project, and the Community Health Rankings and Roadmap for this cross-sectional study. Maps were created to examine the geographic distribution of cumulative death rates and taxable values per capita, and regression models were used to examine the association between the two while controlling for population density, age, education, race, income, obesity, diabetes, and smoking rates.

Results

Seventy-five counties were included. The mean taxable value per capita was $43,764.50 and the mean cumulative death rate was 171.86. Findings from the regression analysis showed that counties with higher taxable values were associated with lower COVID-19 death rates (B = -2.45, P < 0.001).

Conclusion

Our findings reveal a need to reevaluate current policies surrounding taxable property values in the state of Michigan, not solely for their inequitable impact on local governments' financial solvency and service quality, but also for their negative consequences for population health and racial health equity.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10389-022-01817-w.

Time-series COVID-19 policymaker analysis of the UAE, Taiwan, New Zealand, Japan and Hungary

There are two types of policy analysis: socioeconomic analysis and public policy outcome analysis. The socioeconomic analysis is used for understanding the relationship between COVID-19 incident and mortality and building effective governance. There are two types of policy outcome analysis: general policy analysis and time series policy analysis. This paper is a policy outcome analysis of COVID-19, not a policy analysis. This paper examines COVID-19 policy outcome analysis of five countries such as the UAE, Taiwan, New Zealand, Japan and Hungary. Two policy outcome analysis tools are used in this paper such as scorecovid to generate a snapshot list of sorted scores and time-series hiscovid to identify when policymakers made mistakes for correcting mistakes in the near future policy update. Scores in both tools are based on the population mortality rate: dividing the number of COVID-19 deaths by the population in millions. The lower the score, the better the policy. The higher the score, the more deaths that make people unhappy. COVID-19 death is the most unfortunate event in life and is caused by policy. The introduced time-series policy analysis tool, hiscovid discovered ten facts of five countries. Discovered ten facts will be detailed in this paper. Visualization of policy outcomes over time will play an important role in mitigating the COVID-19 pandemic.

[Description of excess of overall and cause-specific mortality in the Agency for Health Protection of the Metropolitan Area of Milan (Lombardy Region, Northern Italy) in 2020]

BACKGROUND

as a result of the SARS-CoV-2 pandemic, a generalised mortality excess was recorded in 2020. However, the mortality for COVID-19 cannot fully explain the observed excesses. The analysis of cause-specific mortality could contribute to estimate the direct and indirect effects of the SARS-CoV-2 outbreak and to the monitoring mortality trends.

OBJECTIVES

to describe the impact of the SARS-CoV-2 epidemic in overall and cause-specific mortality in population residing in the Agency for Health Protection (ATS) of Milan. Descriptive analysis of cause-specific mortality within thirty days of SARS-COV-2 infection.

DESIGN

descriptive analysis of overall and cause-specific mortality in the ATS of Milan area in 2020 and comparison with a reference period (2015-2019).

SETTING AND PARTICIPANTS

overall deaths in ATS of Milan in 2020 were collected, using the Local Registry of Causes of Death, and were classified according to the ICD-10 codes.

MAIN OUTCOME MEASURES

total and weekly overall and cause-specific mortality, by age.

RESULTS

in 2020, 44,757 deaths for all causes were observed in people residing in the ATS of Milan with percentage change of 35%. The leading cause of death in 2020 were cardiovascular disease and neoplasm; COVID-19 infection was the third cause. An excess of mortality was observed for most of all causes of deaths. Starting from 40-49-year age group, an increase of mortality was observed; the largest increase was observed in the group 70+ years. The largest increases were observed for endocrine, respiratory, and hypertensive diseases. On the contrary, for neoplasm, infectious (not COVID-19) diseases, traffic-related mortality, and cerebrovascular disease and ictus, a decrease of mortality was observed. The greater mortality increase was observed during the first pandemic wave. The leading cause of death after positive swab was COVID-19 infection, with little variation with age class. Other frequent causes of death were respiratory diseases, cardiovascular diseases, and neoplasm.

CONCLUSIONS

the study showed a generalised increase for most causes of death; observed mortality trends may indicate delay in access to health care system, in diagnosis and treatment.

Epidemiology and Response to the COVID-19 Pandemic in Kerala, India, 2020-2021: A Cross-Sectional Study

Kerala, a southern state in India, experienced a slightly different COVID-19 pandemic than the rest of India. Using data from daily COVID-19 bulletins and two other Kerala health information systems, this study reported on epidemiological characteristics and response measures of the COVID-19 pandemic between January 2020 and December 2021. After the first six months, Kerala experienced three distinct phases, with COVID-19 cases peaking in October 2020, May 2021, and August 2021. This contrasts with India, which experienced two main peaks in September 2020 and May 2021. The demographic profile of cases aligned with the national profile except for a slight increase of COVID-19 in persons aged ≥60 years. Monthly COVID-19 deaths increased dramatically from May 2021 onwards in line with case numbers but also reflecting changes in definitions of COVID-19 deaths. Case fatality for the two years was significantly higher in males than females, increased with increasing age groups, and varied between districts (p < 0.001). Trends in bed occupancy in field hospitals, hospitals for severe disease, intensive care units, and mechanical ventilation mirrored the different phases of the pandemic. The monitoring system in Kerala allowed certain aspects of the pandemic to be mapped, but it would benefit from further strengthening.

Association between immunosuppressive drugs and COVID-19 outcomes in patients with non-infectious uveitis in a large US claims database

Purpose

To determine the dose-dependent risk of systemic corticosteroids (SCs) and the risk of other immunosuppressive therapies on coronavirus disease 2019 (COVID-19) infection, hospitalization, and death in patients with noninfectious uveitis (NIU).

Design

A retrospective cohort study from January 20, 2020, to December 31, 2020 (an era before widespread COVID-19 vaccination), using the Optum Labs Data Warehouse, a US national de-identified claims database.

Participants

Patients who had at least 1 NIU diagnosis from January 1, 2017.

Methods

Unadjusted and adjusted hazard ratios (HRs) were estimated for each variable and COVID-19 outcome using Cox proportional hazards models, with time-updated dichotomous indicators for outpatient immunosuppressive medication exposure. To assess the dose-dependent effect of SC exposure, the average daily dose of prednisone over the exposed interval was included in the adjusted models as a continuous variable, in addition to the dichotomous variable.

Main Outcome Measures

Incidence rates of COVID-19 infection, COVID-19–related hospitalization, and COVID-19–related in-hospital death.

Results

This study included 52 286 NIU patients of whom 12 000 (23.0%) were exposed to immunosuppressive medications during the risk period. In adjusted models, exposure to SCs was associated with increased risk of COVID-19 infection (HR, 2.66; 95% confidence interval [CI], 2.19–3.24; P < 0.001), hospitalization (HR, 3.26; 95% CI, 2.46–4.33; P < 0.001), and in-hospital death (HR, 1.99; 95% CI, 0.93–4.27; P = 0.08). Furthermore, incremental increases in the dosage of SCs were associated with a greater risk for these outcomes. Although tumor necrosis factor-α (TNF-α) inhibitors were associated with an increased risk of infection (HR, 1.48; 95% CI, 1.08–2.04; P = 0.02), other immunosuppressive treatments did not increase the risk of COVID-19 infection, hospitalization, or death.

Conclusions

This study from an era before widespread COVID-19 vaccination demonstrates that outpatient SC exposure is associated with greater risk of COVID-19 infection and severe outcomes in patients with NIU. Future studies should evaluate the impact of immunosuppression in vaccinated NIU patients. Limiting exposure to SCs and use of alternative therapies may be warranted.

Long-term commuting times and air quality relationship to COVID-19 in São Paulo

The Coronavirus Disease 2019 (COVID-19) epidemic is an unprecedented global health crisis and the effects may be related to environmental and socio-economic factors. In São Paulo, Brazil, the first death occurred in March 2020 and since then the numbers have grown to 175 new deaths per day in April 2021, positioning the city as the epicenter of the number of cases and deaths in Brazil. São Paulo is one of the largest cities in the world with more than 12 million inhabitants, a fleet of about 8 million vehicles and frequent pollutant concentrations above recommended values. Social inequalities are evident in the municipality, similarly to other cities in the world. This paper focuses on transportation activities related to air pollution and associated with cardiovascular and respiratory diseases especially on people who developed comorbidities during their whole life. This study relates travel trip data to air quality analysis and expanded to COVID-19 disease. This work studied the relationship of deaths in São Paulo due to COVID-19 with demographic density, with family income, with the use of public transport and with atmospheric pollution for the period between March 17th, 2020 and April 29th, 2021. The main results showed that generally passenger kilometers traveled, commuting times and air quality related diseases increase with residential distance from the city center, and thus, with decreasing residential density. PM_2.5 concentrations are positively correlated with COVID-19 deaths, regions with high urban densities have higher numbers of deaths and long-distance frequent trips can contribute to spread of the disease.

[Impact of the COVID-19 epidemic on total and cause-specific mortality in Rome (Italy) in 2020]

OBJECTIVES

to estimate the impact of the COVID-19 epidemic on total and cause-specific mortality in people residing and dead in the Municipality of Rome (Italy) in 2020, and to describe the causes of death of subjects with SARS-CoV-2 infection confirmed by molecular test.

DESIGN

descriptive analysis of total and cause-specific mortality in 2020 in Rome and comparison with a reference period (2015-2018 for total mortality and 2018 for cause-specific mortality); descriptive analysis of cause-specific mortality in the cohort of SARS-CoV-2 infected subjects.

SETTING AND PARTICIPANTS

27,471 deaths registered in the Lazio mortality-cause Registry, relating to people residing and died in the municipality of Rome in 2020, 2,374 of which died from COVID-19.MAIN OUCOME MEASURES: all-cause mortality by month, gender, age group and place of death, cause-specific mortality (ICD-10 codes).

RESULTS

in the municipality of Rome in 2020, an excess of mortality from all causes equal to +10% was observed, with a greater increase in the months of October-December (+27%, +56%, and +26%, respectively) in people aged 50+, with the greatest contribution from the oldest age groups (80+) who died in the nursing homes or at home. Lower mortality was observed in the age groups 0-29 years (-30%) and 40-49 years (-13%). In 2020, COVID-19 represents the fourth cause of death in Rome after malignant tumours, diseases of the circulatory system, and respiratory diseases. Excess mortality was observed from stroke and pneumonia (both in men and women), from respiratory diseases (in men), from diabetes, mental disorders, dementia and Parkinson's disease (in women). On the contrary, mortality is lower for all cancers, for diseases of the blood and haematopoietic organs and for the causes of the circulatory system. The follow-up analysis of SARS-CoV-2 positive subjects residing in Rome shows that a share of deaths (about 20%) reports other causes of death such as cardiovascular diseases, malignant tumours, and diseases of the respiratory system on the certificate collected by the Italian National Statistics Institute.

CONCLUSIONS

the 2020 mortality study highlighted excesses for acute and chronic pathologies, indicative of possible delays in the diagnosis or treatment of conditions indirectly caused by the pandemic, but also a share of misclassification of the cause of death that is recognized as COVID-19 death.

The Effect of the COVID-19 Vaccine on Daily Cases and Deaths Based on Global Vaccine Data

Background: Coronavirus disease 2019 (COVID-19), a global pandemic, has caused over 216 million cases and 4.50 million deaths as of 30 August 2021. Vaccines can be regarded as one of the most powerful weapons to eliminate the pandemic, but the impact of vaccines on daily COVID-19 cases and deaths by country is unclear. This study aimed to investigate the correlation between vaccines and daily newly confirmed cases and deaths of COVID-19 in each country worldwide. Methods: Daily data on firstly vaccinated people, fully vaccinated people, new cases and new deaths of COVID-19 were collected from 187 countries. First, we used a generalized additive model (GAM) to analyze the association between daily vaccinated people and daily new cases and deaths of COVID-19. Second, a random effects meta-analysis was conducted to calculate the global pooled results. Results: In total, 187 countries and regions were included in the study. During the study period, 1,011,918,763 doses of vaccine were administered, 540,623,907 people received at least one dose of vaccine, and 230,501,824 people received two doses. For the relationship between vaccination and daily increasing cases of COVID-19, the results showed that daily increasing cases of COVID-19 would be reduced by 24.43% [95% CI: 18.89, 29.59] and 7.50% [95% CI: 6.18, 8.80] with 10,000 fully vaccinated people per day and at least one dose of vaccine, respectively. Daily increasing deaths of COVID-19 would be reduced by 13.32% [95% CI: 3.81, 21.89] and 2.02% [95% CI: 0.18, 4.16] with 10,000 fully vaccinated people per day and at least one dose of vaccine, respectively. Conclusions: These findings showed that vaccination can effectively reduce the new cases and deaths of COVID-19, but vaccines are not distributed fairly worldwide. There is an urgent need to accelerate the speed of vaccination and promote its fair distribution across countries.

The Association between Noninfectious Uveitis and Coronavirus Disease 2019 Outcomes: An Analysis of United States Claims-Based Data

Purpose

To identify if noninfectious uveitis (NIU) is associated with a greater risk of Coronavirus Disease 2019 (COVID-19) infection, hospitalization, and death.

Design

A retrospective cohort study from January 20, 2020 to December 31, 2020, using a national claims-based database.

Participants

Enrollees who had continuous enrollment with both medical and pharmacy coverage for 3 years before January 20, 2020. Patients with an NIU diagnosis within 3 years of the start of the study were included in the NIU cohort. Those with infectious uveitis codes or new NIU diagnoses during the risk period were excluded.

Methods

Cox proportional hazard models were used to identify unadjusted hazard ratios (HRs) and adjusted HRs for all covariates for each outcome measure. Adjusted models accounted for patient demographics, health status, and immunosuppressive medication use during the risk period.

Main Outcome Measures

Rates of COVID-19 infection, COVID-19-related hospitalization, and COVID-19-related in-hospital death identified with International Classification of Disease 10^th revision codes.

Results

This study included 5 806 227 patients, of whom 29 869 (0.5%) had a diagnosis of NIU. On unadjusted analysis, patients with NIU had a higher rate of COVID-19 infection (5.7% vs. 4.5%, P < 0.001), COVID-19-related hospitalization (1.2% vs. 0.6%, P < 0.001), and COVID-19-related death (0.3% vs. 0.1%, P < 0.001). However, in adjusted models, NIU was not associated with a greater risk of COVID-19 infection (HR, 1.05; 95% confidence interval [CI], 1.00–1.10; P = 0.04), hospitalization (HR, 0.98; 95% CI, 0.88–1.09; P = 0.67), or death (HR, 0.90, 95% CI, 0.72–1.13, P = 0.37). Use of systemic corticosteroids was significantly associated with a higher risk of COVID-19 infection, hospitalization, and death.

Conclusions

Patients with NIU were significantly more likely to be infected with COVID-19 and experience severe disease outcomes. However, this association was due to the demographics, comorbidities, and medications of patients with NIU, rather than NIU alone. Patients using systemic corticosteroids were significantly more likely to be infected with COVID-19 and were at greater risk of hospitalization and in-hospital death. Additional investigation is necessary to identify the impact of corticosteroid exposure on COVID-19-related outcomes.

Mapping the geodemographics of racial, economic, health, and COVID-19 deaths inequalities in the conterminous US

A large number of studies have examined individual-level factors that increase COVID-19 fatalities. However, no research has focused on the geodemographic classification of the most susceptible communities to COVID-19. In this cross-sectional ecological study, we used local fuzzy geographically-weighted clustering to create the socioeconomic profile of the US counties in relation to COVID-19 death rates. We demonstrate that living in a county which has households with lower income, people with a lack of health insurance, a high African-American percentage, and lower education level, lead to 27.12% higher COVID-19 death rates than the national median, and 72.56% higher compared to the least vulnerable counties. Compared to counties with a high COVID-19 death rate, counties with a low COVID-19 death rate have 44.90% higher annual median household income and nearly double house worth (89.51% more). Results show that the effects of the COVID-19 pandemic are not universal and that the minoritised and impoverished populations suffer more. Our analysis can effectively pinpoint the most vulnerable counties and importantly allows for understanding the socioeconomic context in which tailored interventions can be applied to mitigate COVID-19 deaths.

International Council of Nurses representing nursing at the World Health Organization: COVID-19, policy and holding politicians to account

The International Council of Nurses is in a unique position to represent nurses at the World Health Organization, and its task has never been more urgent than this year. Amid the global COVID‐19 pandemic, the death rates of nurses and other health care workers are truly shocking, with around 115 000 deaths. However, many countries do not collect statistics on health and care workers’ deaths and infections from COVID‐19, so the full extent of this awful situation is not known.

At this year's World Health Assembly, the body that sets the World Health Organization's agenda for the following year, the International Council of Nurses’ 50‐strong delegation voiced the concerns of nurses and ensured that the views and advice of nurses were heard by the World Health Organization's 194 member states’ delegates. Here, the International Council of Nurses’ Chief Executive Officer Howard Catton describes how the Council is influencing health and care policy worldwide. He urges nurses everywhere to hold their politicians to account.

[COVID-19 deaths among residents of inpatient nursing homes in Munich-causes and places of death]

INTRODUCTION

The new infectious disease COVID-19 first appeared in China in December 2019. So far, a systematic evaluation of death certificates of COVID-19-associated deaths of residents in inpatient nursing homes has not been presented.

METHODS

Death certificates of all deaths in Munich in the death period from 1 March to 31 July 2020 were analyzed. Inclusion criteria were the presence of "Corona, COVID-19, SARS-CoV-2" on the death certificates. Standardized, anonymized data entry was performed. The collected data were analyzed descriptively.

RESULTS

During the study period, a total of 5840 persons died, 281 (4.8%) of whom died of confirmed COVID-19 disease. Of those, 72 deaths involved residents of Munich nursing facilities. The most frequent causes of death were respiratory insufficiency (54 cases) and multiple organ failure (9 cases). On the death certificates, an average of two preexisting diseases had been reported; the average age at death was 88 years. All deaths of nursing home residents occurred in association with nosocomial COVID-19 outbreaks, which affected one-third of the facilities. The vast majority of these homes did not have a COVID-19 hygiene plan in place at the time.

DISCUSSION

One quarter of all COVID-19 deaths in Munich occurred in the context of nosocomial outbreaks in elderly, chronically ill residents of nursing facilities. Evidence of inadequate risk assessment and inadequate hygiene management emerged. In the opinion of the authors, the appropriate structures for adequate hygiene management must be created and a hygiene regulation must be issued in which the tasks and responsibilities of the facility operators are defined.

Global Temporal Patterns of Age Group and Sex Distributions of COVID-19

Since the beginning of 2020, COVID-19 has been the biggest public health crisis in the world. To help develop appropriate public health measures and deploy corresponding resources, many governments have been actively tracking COVID-19 in real time within their jurisdictions. However, one of the key unresolved issues is whether COVID-19 was distributed differently among different age groups and between the two sexes in the ongoing pandemic. The objectives of this study were to use publicly available data to investigate the relative distributions of COVID-19 cases, hospitalizations, and deaths among age groups and between the sexes throughout 2020; and to analyze temporal changes in the relative frequencies of COVID-19 for each age group and each sex. Fifteen countries reported age group and/or sex data of patients with COVID-19. Our analyses revealed that different age groups and sexes were distributed differently in COVID-19 cases, hospitalizations, and deaths. However, there were differences among countries in both their age group and sex distributions. Though there was no consistent temporal change across all countries for any age group or either sex in COVID-19 cases, hospitalizations, and deaths, several countries showed statistically significant patterns. We discuss the potential mechanisms for these observations, the limitations of this study, and the implications of our results on the management of this ongoing pandemic.

The predictors of COVID-19 mortality in a nationwide cohort of Turkish patients

The COVID-19-related death rate varies between countries and is affected by various risk factors. This multicenter registry study was designed to evaluate the mortality rate and the related risk factors in Turkey. We retrospectively evaluated 1500 adults with COVID-19 from 26 centers who were hospitalized between March 11 and July 31, 2020. In the study group, 1041 and 459 cases were diagnosed as definite and highly probable cases, respectively. There were 993 PCR-positive cases (66.2%). Among all cases, 1144 (76.3%) were diagnosed with non-severe pneumonia, whereas 212 (14.1%) had severe pneumonia. Death occurred in 67 patients, corresponding to a mortality rate of 4.5% (95% CI:3.5–5.6). The univariate analysis demonstrated that various factors, including male sex, age ≥65 years and the presence of dyspnea or confusion, malignity, chronic obstructive lung disease, interstitial lung disease, immunosuppressive conditions, severe pneumonia, multiorgan dysfunction, and sepsis, were positively associated with mortality. Favipiravir, hydroxychloroquine and azithromycin were not associated with survival. Following multivariate analysis, male sex, severe pneumonia, multiorgan dysfunction, malignancy, sepsis and interstitial lung diseases were found to be independent risk factors for mortality. Among the biomarkers, procalcitonin levels on the 3rd-5th days of admission showed the strongest associations with mortality (OR: 6.18; 1.6–23.93). This study demonstrated that the mortality rate in hospitalized patients in the early phase of the COVID-19 pandemic was a serious threat and that those patients with male sex, severe pneumonia, multiorgan dysfunction, malignancy, sepsis and interstitial lung diseases were at increased risk of mortality; therefore, such patients should be closely monitored.

COVID-19 modelling in the Caribbean: Spatial and statistical assessments

The novel COVID-19 disease has highlighted the vulnerability of small and developing economies in managing what is now a global health crisis. This study presents the preliminary overview of the dynamics of the spread and expansion of COVID-19 as the disease takes its footprint in the Caribbean. The study explored the spatial clusters of the disease and its variations in the Caribbean region. Data was gathered from the World Health Organization reports and collated into a cross sectional data set. Spatial mapping and spatial lag analysis were conducted to identify spread patterns and statistical relationships with several relevant socioeconomic variables. Models showed the prominence of cases and deaths in the Caribbean region have a spatial connection with mainland countries. The models also show the connection between COVID-19 cases and deaths and the availability of medical services within the country. Results also showed similar social distancing policies adopted in the region and the possible connection between prevalence of diabetes and hypertension regionally impacted the number of deaths. It is hoped that the findings presented here will be useful in planning for an epidemiological response for the region based on the differences in the patterns for possible interventions and actions.

Geographic disparities in COVID-19 infections and deaths: The role of transportation

The US government imposed two travel restriction policies to prevent the spread of the COVID-19 but may have funneled asymptomatic air travelers to selected major airports and transportation hubs. Using the most recent JHU COVID-19 database, American Community Survey, Airport and Amtrak data form Bureau of Transportation Statistics from 3132 US counties we ran negative binomial regressions and Cox regression models to explore the associations between COVID-19 cases and death rates and proximity to airports, train stations, and public transportation. Counties within 25 miles of an airport had 1.392 times the rate of COVID-19 cases and 1.545 times the rate of COVID-19 deaths in comparison to counties that are more than 50 miles from an airport. More effective policies to detect and isolate infected travelers are needed. Policymakers and officials in transportation and public health should collaborate to promulgate policies and procedures to protect travelers and transportation workers from COVID-19.

Mitigating the Risk of COVID-19 Deaths in Cardiovascular Disease Patients in Africa Resource Poor Communities

The novel coronavirus disease 2019 (Covid-19) pandemic has affected millions of patients in almost all countries with over one million cases recorded in Africa where it is a major health challenge. Covid-19 is known to have significant implications for those with pre-existing cardiovascular disease (CVD) and their cardiologists. Patients with pre-existing CVD are at increased risk of morbidity and mortality from Covid-19 due to associated direct and indirect life threatening cardiovascular (CV) complications. Mitigating the risk of such Covid-19 deaths in resource poor communities requires the institution of preventive measures at the primary, secondary and tertiary levels of preventive phenomenon with emphasis at the first two levels. General preventive measures, screening and monitoring of CVD patients for complications and modification of drug treatment and other treatment methods will need to be implemented. Health policy makers and manager should provide required training and retraining of CV health care workers managing Covid-19 patients with CVD, provision of health education, personal protective equipment (PPE), and diagnostic kits.

The Age Structure, Stringency Policy, Income, and Spread of Coronavirus Disease 2019: Evidence From 209 Countries

This article aims at answering the following questions: (1) What is the influence of age structure on the spread of coronavirus disease 2019 (COVID-19)? (2) What can be the impact of stringency policy (policy responses to the coronavirus pandemic) on the spread of COVID-19? (3) What might be the quantitative effect of development levelincome and number of hospital beds on the number of deaths due to the COVID-19 epidemic? By employing the methodologies of generalized linear model, generalized moments method, and quantile regression models, this article reveals that the shares of median age, age 65, and age 70 and older population have significant positive impacts on the spread of COVID-19 and that the share of age 70 and older people in the population has a relatively greater influence on the spread of the pandemic. The second output of this research is the significant impact of stringency policy on diminishing COVID-19 total cases. The third finding of this paper reveals that the number of hospital beds appears to be vital in reducing the total number of COVID-19 deaths, while GDP per capita does not affect much the level of deaths of the COVID-19 pandemic. Finally, this article suggests some governmental health policies to control and decrease the spread of COVID-19.

Underreporting of Death by COVID-19 in Brazil's Second Most Populous State

The COVID-19 pandemic brings to light the reality of the Brazilian health system. The underreporting of COVID-19 deaths in the state of Minas Gerais (MG), where the second largest population of the country is concentrated, reveals government unpreparedness, as there is a low capacity of testing in the population, which prevents the real understanding of the general panorama of SARS-CoV-2 dissemination. The goals of this research are to analyze the causes of deaths in different Brazilian government databases (Civil Registry Transparency Portal and InfoGripe) and to assess whether there are sub-records showing an unexpected increase in the frequency of deaths from causes clinically similar to COVID-19. A descriptive and quantitative analysis of the number of deaths by COVID-19 and similar causes was performed in different databases. Our results demonstrate that different official sources had a discrepancy of 109.45% between these data referring to the same period. There was also a 758.57% increase in SARI deaths in 2020, when compared to the average of previous years. Finally, it was shown that there was an increase in the rate of pneumonia and respiratory insufficiency (RI) by 6.34 and 6.25%, respectively. In conclusion, there is an underreporting of COVID-19 deaths in MG due to the unexplained excess of deaths caused by SARI, respiratory insufficiency, and pneumonia compared to previous years.

Overcoming COVID-19 in West African countries: is herd immunity an option?

The coronavirus infection (COVID-19) to date has no vaccine or effective treatment. Herd immunity offers indirect protection to susceptible members of the population. If the acquired immunity of a community rises above 67%, then a gradual decline in the number of incident cases is recorded. How many deaths would have occurred in the West African countries by the time at least 67% of our people are infected with the present case fatality rate (CFR)? The objective of this study was to develop a forecast of the number of COVID-19 deaths that would be recorded to attain herd immunity for each country in West-Africa. We predicted the numbers of deaths using publicly available demographic and COVID-19 data. To attain herd immunity in West Africa 5.2 million COVID-19 deaths would have occurred assuming the CFR is maintained at the current rates in the region. Attention should be focused on strategies that would limit the spread of infection and protect the most vulnerable population groups while the race to develop an effective vaccine should be hastened.