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The health and ecological harms created and spread by firms active in many unhealthy commodity industries (UCIs) have received considerable attention from the public health community. However, less focus has been paid to analysing the distribution of wealth and income – important social and economic determinants of health – by these industries. This study aimed to examine long-term trends in wealth and income distribution by publicly listed corporations active in four UCIs: fossil fuels; tobacco; ultra-processed foods; and alcohol. Quantitative analysis of a range of data was conducted for firms listed on stock exchanges in the United States (US). Wealth and income distribution metrics were analysed at the industry level, including effective corporate tax rates and shareholder value ratios. The equity ownership structures and investor location of 20 of the largest firms were also explored. Since the 1980s, US-listed firms in the examined UCIs have distributed much less of their wealth and income to governments and much more to shareholders and investors mostly based in high-income countries. The study provides evidence that firms active in UCIs create a 'double burden of maldistribution': their externalised social and ecological harms disproportionately affect disadvantaged population groups and governments in low- and middle-income countries; whilst, simultaneously, they are increasingly transferring wealth and income to a group over-represented by a small and privileged elite. The identified distributive injustice warrants increased policy attention. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the causal agent for COVID-19, is a communicable disease spread through close contact. It is known to disproportionately impact certain communities due to both biological susceptibility and inequitable exposure. In this study, we investigate the most important health, social, and environmental factors impacting the early phases (before July, 2020) of per capita COVID-19 transmission and per capita all-cause mortality in US counties. We aggregate county-level physical and mental health, environmental pollution, access to health care, demographic characteristics, vulnerable population scores, and other epidemiological data to create a large feature set to analyze per capita COVID-19 outcomes. Because of the high-dimensionality, multicollinearity, and unknown interactions of the data, we use ensemble machine learning and marginal prediction methods to identify the most salient factors associated with several COVID-19 outbreak measure. Our variable importance results show that measures of ethnicity, public transportation and preventable diseases are the strongest predictors for both per capita COVID-19 incidence and mortality. Specifically, the CDC measures for minority populations, CDC measures for limited English, and proportion of Black- and/or African-American individuals in a county were the most important features for per capita COVID-19 cases within a month after the pandemic started in a county and also at the latest date examined. For per capita all-cause mortality at day 100 and total to date, we find that public transportation use and proportion of Black- and/or African-American individuals in a county are the strongest predictors. The methods predict that, keeping all other factors fixed, a 10% increase in public transportation use, all other factors remaining fixed at the observed values, is associated with increases mortality at day 100 of 2012 individuals (95% CI [1972, 2356]) and likewise a 10% increase in the proportion of Black- and/or African-American individuals in a county is associated with increases total deaths at end of study of 2067 (95% CI [1189, 2654]). Using data until the end of study, the same metric suggests ethnicity has double the association as the next most important factors, which are location, disease prevalence, and transit factors. Our findings shed light on societal patterns that have been reported and experienced in the U.S. by using robust methods to understand the features most responsible for transmission and sectors of society most vulnerable to infection and mortality. In particular, our results provide evidence of the disproportionate impact of the COVID-19 pandemic on minority populations. Our results suggest that mitigation measures, including how vaccines are distributed, could have the greatest impact if they are given with priority to the highest risk communities.

The Bill & Melinda Gates Foundation is a major contributor to global health; its influence on international health policy and the design of global health programmes and initiatives is profound. Although the foundation's contribution to global health generally receives acclaim, fairly little is known about its grant-making programme. We undertook an analysis of 1094 global health grants awarded between January, 1998, and December, 2007. We found that the total value of these grants was US$8.95 billion, of which $5.82 billion (65%) was shared by only 20 organisations. Nevertheless, a wide range of global health organisations, such as WHO, the GAVI Alliance, the World Bank, the Global Fund to Fight AIDS, Tuberculosis and Malaria, prominent universities, and non-governmental organisations received grants. $3.62 billion (40% of all funding) was given to supranational organisations. Of the remaining amount, 82% went to recipients based in the USA. Just over a third ($3.27 billion) of funding was allocated to research and development (mainly for vaccines and microbicides), or to basic science research. The findings of this report raise several questions about the foundation's global health grant-making programme, which needs further research and assessment.