Income inequality and the disease burden of COVID-19: Survival analysis of data from 74 countries

Epidemiology and risk factors for adult gliomas died by respiratory diseases during the COVID-19 pandemic: a population-based study

BACKGROUND

The research on epidemiology of gliomas died of respiratory diseases (RDs) is very scarce. The study aimed to explore the epidemiology and risk factors for adult gliomas death from respiratory diseases during the COVID-19 pandemic.

METHODS

Adult gliomas patients (age ≥ 18 years) diagnosed between 2020 and 2021 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching analysis was used to reduce confounding bias between gliomas died of respiratory diseases and died of gliomas directly. The Cox proportional hazards regression model and Kaplan-Meier (K-M) survival curves were used for survival analyses in the matched groups. Logistic regression analyses were conducted to identify risk factors for dying of respiratory diseases in the entire population.

RESULTS

Among 9315 eligible adult gliomas enrolled in the study, 39.4% died from gliomas, 1.0% from respiratory diseases, and 61.4% survived. Gliomas who died from respiratory diseases had a trend towards a higher risk of death (HR = 1.35, P = 0.031). Surgery did not increase the all-cause mortality risk (HR = 0.86, P = 0.327). The K-M survival curves suggested a worse prognosis for dying from respiratory diseases. Those who died from RDs had a shortened median survival (median 3 months) compared with those who died from gliomas directly (median 5 months). Multivariable logistic regression models indicated that those aged ≥ 65 years, with median household income < 75,000$/year, and not receiving surgery had a higher risk of dying from RDs.

CONCLUSIONS

RDs have become a crucial cause of death for gliomas. Those with advanced age and lower median household income have a higher risk of dying from respiratory diseases. Surgical treatment has been found to be safe for glioma patients and has been shown to reduce the risk of glioma patients dying from respiratory diseases. The study provides valuable insights for the perioperative management of gliomas patients in the post-pandemic era.

Determinants of differences in RT-PCR testing rates among Southeast Asian countries during the first six months of the COVID-19 pandemic

A positive correlation has been demonstrated between gross domestic product (GDP) per capita and COVID-19 tests per 1000 people. Although frequently used as an indicator of economic performance, GDP per capita does not directly reflect income distribution inequalities and imposed health costs. In this longitudinal ecological study, we aimed to determine if, besides GDP per capita, indicators relating to governance, public health measures enforcement, and health and research investment explain differences in RT-PCR testing rates among countries in Southeast Asia (SEA) during the first six months of the COVID-19 pandemic. Using open-access COVID-19 panel data, we estimated the effect of various indicators (GDP per capita, health expenditure per capita, number of researchers per one million population, corruption perceptions index, stringency index, regional authority index) on daily COVID-19 testing by performing fixed-effects negative binomial regression. After accounting for all indicators, the number of daily confirmed COVID-19 cases, and population density, the model provided a 2019 GDP per capita coefficient of 0.0046330 (95% CI: 0.0040171, 0.0052488; p <0.001), indicating that a rise in 2019 GDP per capita by 100 international dollars is associated with a 46.33% increase in the number of daily tests performed. Additionally, all indicators were significantly associated with the daily number of RT-PCR testing on multivariable analysis. In conclusion, we identified different country-level indicators significantly associated with differences in COVID-19 testing rates among SEA countries. Due to the study's ecological design, we caution on applying our results to the individual level given potential for systematic differences between the included countries. Additional investigation is likewise needed to understand how government expenditure on healthcare may have impacted COVID-19 testing capacity during the initial stages of the pandemic.

Income inequality and pandemics: insights from HIV/AIDS and COVID-19-a multicountry observational study

OBJECTIVES

Assess the relationship between income inequality and HIV incidence, AIDS mortality and COVID-19 mortality.

DESIGN

Multicountry observational study.

SETTING

217 countries for HIV/AIDS analysis, 151 countries for COVID-19 analysis.

PARTICIPANTS

Used three samples of national-level data: a sample of all countries with available data (global sample), a subsample of African countries (African sample) and a subsample excluding African countries (excluding African sample).

MAIN OUTCOME MEASURES

HIV incidence rate per 1000 people, AIDS mortality rate per 100 000 people and COVID-19 excess mortality rate per 100 000 people. The Gini index of income inequality was the primary explanatory variable.

RESULTS

A positive and significant relationship exists between the Gini index of income inequality and HIV incidence across all three samples (p<0.01), with the effect of income inequality on HIV incidence being higher in the African sample than in the rest of the world. Also, a statistically positive association exists for all samples between income inequality and the AIDS mortality rate, as higher income inequality increases AIDS mortality (p<0.01). For COVID-19 excess mortality rate, a positive and statistically significant relationship exists with the Gini index for the entire sample and the excluding African sample (p<0.05), but the African sample alone did not deliver significant results (p<0.1).

CONCLUSION

COVID-19 excess deaths, HIV incidence and AIDS mortality are significantly associated with income inequality globally-more unequal countries have a higher HIV incidence, AIDS mortality and COVID-19 excess deaths than their more equal counterparts. Income inequality undercuts effective pandemic response. There is an urgent need for concerted efforts to tackle income inequality and to build pandemic preparedness and responses that are adapted and responsive to highly unequal societies, prioritising income inequality among other social determinants of health.

Global Inequities in COVID-19 Vaccination: Associated Factors and Tools to Measure Inequality

INTRODUCTION

Socioeconomic factors have been recognized by the WHO as determinants of health, and it is important to consider these factors in decision making to curb existing inequality in vaccination for SARS-CoV-2, which causes COVID-19.

OBJECTIVE

We aimed to determine whether there is a correlation between socioeconomic factors and vaccination worldwide and measure inequality.

METHOD

A study of secondary sources was carried out to assess inequality in vaccination against COVID-19 worldwide and its association with socioeconomic factors. For this assessment, 169 countries were chosen from January 2020 to March 2022 using LibreOffice and JASP 0.16.1.10. Several mathematical models and statistical tests were used, including a normality test, an analysis of frequencies and proportions, a Kruskal-Wallis test, Spearman's correlations, a Lorenz curve, a Concentration Index, and a slope.

RESULTS

Correlations were found between socioeconomic factors and vaccination with one, two, and three doses. As the GDP showed correlations of 0.71 for one dose and 0.82 for three doses, we found that the greater the competitiveness of the countries, the higher the percentage of vaccinated individuals in their populations. According to the Concentration Index, there was greater inequality in vaccination with regard to receiving a higher number of doses, as reflected in the life expectancy indices of 0.16-0.19 and 0.50. The continent with the highest degree of inequality was Africa, and the continent with the lowest degree was America. South Americans were vaccinated with two doses at a rate of 6.19%/month, which was 4.3 times faster than Africans, with 72% of the population being vaccinated in South America, compared to only 16% in Africa.

CONCLUSION

There is inequality in vaccination against COVID-19 with one, two, and three doses, which is associated with socioeconomic factors.

The impact of COVID-19 on economy, air pollution and income: evidence from China

The global pandemic caused by the outbreak of COVID-19 has posed significant risks to our health. Preventive measures such as closed management have greatly affected the economies, environments and societies of various countries. Economy, air pollution and income are three important interconnected aspects of sustainable development. However, current research lacks systematic quantitative analysis of their relationships. To fill the gap, this study adopts monthly data from January 2016 to April 2022 and constructs both a Simultaneous Equation Model (SEM) and a Time Varying Parameter Stochastic Volatility Vector Autoregressive (TVP-SV-VAR) model to empirically analyze the impact of COVID-19 on China's economy, air pollution and income. This study finds that the COVID-19 has a negative impact on China's economy and income, and a positive impact on air pollution, and the impact of the COVID-19 is systematic. In addition, there is an inverted-U shaped relationship between air pollution and economics, and a positive correlation between economic and income. The impact of COVID-19 on the economy, air pollution and income show a process of sharp fluctuations to gradual stabilization that gradually stabilized over time. This process is time-varying in the short-term, medium-term and long-term. The impacts are persistent at three different time points (before, during and after the outbreak of COVID-19), but the negative impact on the economy and income is persistent, while the positive impact on air pollution is limited. This study provides a more systematic and dynamic understanding of the COVID-19 preventive and mitigation measures in China and even the world, which helps to provide insights into the formulation of more comprehensive planning strategies in the future.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00477-023-02450-z.

Individual and neighborhood risk factors of hospital admission and death during the COVID-19 pandemic: a population-based cohort study

BACKGROUND

The coronavirus disease 2019 (COVID-19) disproportionately affects minority populations in the USA. Sweden - like other Nordic countries - have less income and wealth inequality but lacks data on the socioeconomic impact on the risk of adverse outcomes due to COVID-19.

METHODS

This population-wide study from March 2020 to March 2022 included all adults in Stockholm, except those in nursing homes or receiving in-home care. Data sources include hospitals, primary care (individual diagnoses), the Swedish National Tax Agency (death dates), the Total Population Register "RTB" (sex, age, birth country), the Household Register (size of household), the Integrated Database For Labor Market Research "LISA" (educational level, income, and occupation), and SmiNet (COVID data). Individual exposures include education, income, type of work and ability to work from home, living area and living conditions as well as the individual country of origin and co-morbidities. Additionally, we have data on the risks associated with living areas. We used a Cox proportional hazards model and logistic regression to estimate associations. Area-level covariates were used in a principal component analysis to generate a measurement of neighborhood deprivation. As outcomes, we used hospitalization and death due to COVID-19.

RESULTS

Among the 1,782,125 persons, male sex, comorbidities, higher age, and not being born in Sweden increase the risk of hospitalization and death. So does lower education and lower income, the lowest incomes doubled the risk of death from COVID-19. Area estimates, where the model includes individual risks, show that high population density and a high percentage of foreign-born inhabitants increased the risk of hospitalization.

CONCLUSIONS

Segregation and deprivation are public health issues elucidated by COVID-19. Neighborhood deprivation, prevalent in Stockholm, adds to individual risks and is associated with hospitalization and death. This finding is paramount for governments, agencies, and healthcare institutions interested in targeted interventions.

Differences in mortality in Switzerland by citizenship during the first and second COVID-19 waves: Analysis of death statistics

Background

Early in the COVID-19 pandemic, it became apparent that members of marginalized populations and immigrants were also at risk of being hospitalized and dying more frequently from COVID-19. To examine how the pandemic affected underserved and marginalized populations, we analyzed data on changes in the number of deaths among people with and without Swiss citizenship during the first and second SARS-CoV-2 waves.

Method

We analyzed the annual number of deaths from the Swiss Federal Statistical Office from 2015 to 2020, and weekly data from January 2020 to May 2021 on deaths of permanent residents with and without Swiss citizenship, and we differentiated the data through subdivision into age groups.

Results

People without Swiss citizenship show a higher increase in the number of deaths in 2020 than those who were Swiss citizens. The increase in deaths compared to the previous year was almost twice as high for people without Swiss citizenship (21.8%) as for those with it (11.4%). The breakdown by age group indicates that among people between the ages of 64 and 75, those without Swiss citizenship exhibited an increase in mortality (21.6%) that was four times higher than that for people with Swiss citizenship (4.7%).

Conclusion

This study confirms that a highly specialized health care system, as is found in Switzerland, does not sufficiently guarantee that all parts of the population will be equally protected in a health crisis such as COVID-19.