Hastings Center Report 2020
4 Pages Posted: 11 May 2020 Last revised: 18 May 2020
Date Written: May 1, 2020
The vast health inequalities in the United States and beyond that COVID-19 makes glaringly evident are frequently masked by aggregate statistics, which for years had been showing health improvements. Yet these improvements were inequitably distributed, with benefits disproportionately going to wealthier – and in the United States, white – populations. Globally, vast health inequities also exist among and within countries. The inequalities, which have also helped fuel the rise of populism, extend far beyond health care, including to wealth and income. Disaggregated, granular data is critical to understanding these inequalities.
Addressing health inequities must extend far beyond universal access to quality health service to under-funded population-based public health interventions. Meanwhile, as any epidemiologist will tell you, the single biggest predictor of health outcomes is a person’s zip code, indicative of social determinants outside the health sector, including employment, education, housing, and transportation. Without explicit attention to these determinants, and the systematic, structural factors like racism that underlie their inequitable distribution, we can make little progress towards health equity, and will fail to meet the UN Sustainable Development Agenda pledge of leaving no one behind.
Equity solutions require dedicated, systematic, systemic, well-resourced plans – health equity programs of action. These would include explicit targets, costed actions, rigorous measurement, and accountability through a comprehensive national effort. The United States could choose to lead, which would be a powerful political commitment to health equity and justice. And an intangible yet powerful benefit would be to restore a sense of dignity for all of society and, in turn, act collectively to elect truthful, compassionate leaders who bring us together as a nation.
Keywords: health disparities, global health, health inequality, populism, global health data, data collection, public health, social determinants, rural health
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