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Preprint em Inglês | medRxiv | ID: ppmedrxiv-20112011

RESUMO

BackgroundIn the United States, Black Americans are suffering from significantly disproportionate incidence and mortality rates of COVID-19. The potential for racial-justice interventions, including reparations payments, to ameliorate these disparities has not been adequately explored. MethodsWe compared the COVID-19 time-varying Rt curves of relatively disparate polities in terms of social equity (South Korea vs. Louisiana). Next, we considered a range of reproductive ratios to back-calculate the transmission rates {beta}i[->]j for 4 cells of the simplified next-generation matrix (from which R0 is calculated for structured models) for the outbreak in Louisiana. Lastly, we modeled the effect that monetary payments as reparations for Black American descendants of persons enslaved in the U.S. would have had on pre-intervention {beta}i[->]j. ResultsOnce their respective epidemics begin to propagate, Louisiana displays Rt values with an absolute difference of 1.3 to 2.5 compared to South Korea. It also takes Louisiana more than twice as long to bring Rt below 1. We estimate that increased equity in transmission consistent with the benefits of a successful reparations program (reflected in the ratio {beta}b[->]b / {beta}w[->]w) could reduce R0 by 31 to 68%. DiscussionWhile there are compelling moral and historical arguments for racial injustice interventions such as reparations, our study describes potential health benefits in the form of reduced SARS-CoV-2 transmission risk. As we demonstrate, a restitutive program targeted towards Black individuals would not only decrease COVID-19 risk for recipients of the wealth redistribution; the mitigating effects would be distributed across racial groups, benefitting the population at large. FundingETR and LW are supported by NIGMS MIDAS grant R01 GM130900. ETR is also supported by NIAID K08 AI139361. WAD is supported by NIMHD R01 MD011606, NSF SES 1851845, and IES R305A190484. MMM is supported by the Ethics and Governance of Artificial Intelligence Fund.

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