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BMJ Glob Health ; 6(5)2021 05.
Artículo en Inglés | MEDLINE | ID: mdl-34039588

RESUMEN

BACKGROUND: Policy makers need to be rapidly informed about the potential equity consequences of different COVID-19 strategies, alongside their broader health and economic impacts. While there are complex models to inform both potential health and macro-economic impact, there are few tools available to rapidly assess potential equity impacts of interventions. METHODS: We created an economic model to simulate the impact of lockdown measures in Pakistan, Georgia, Chile, UK, the Philippines and South Africa. We consider impact of lockdown in terms of ability to socially distance, and income loss during lockdown, and tested the impact of assumptions on social protection coverage in a scenario analysis. RESULTS: In all examined countries, socioeconomic status (SES) quintiles 1-3 were disproportionately more likely to experience income loss (70% of people) and inability to socially distance (68% of people) than higher SES quintiles. Improving social protection increased the percentage of the workforce able to socially distance from 48% (33%-60%) to 66% (44%-71%). We estimate the cost of this social protection would be equivalent to an average of 0.6% gross domestic product (0.1% Pakistan-1.1% Chile). CONCLUSIONS: We illustrate the potential for using publicly available data to rapidly assess the equity implications of social protection and non-pharmaceutical intervention policy. Social protection is likely to mitigate inequitable health and economic impacts of lockdown. Although social protection is usually targeted to the poorest, middle quintiles will likely also need support as they are most likely to suffer income losses and are disproportionately more exposed.


Asunto(s)
COVID-19 , Control de Enfermedades Transmisibles , Equidad en Salud , Pobreza , COVID-19/epidemiología , COVID-19/prevención & control , Chile/epidemiología , Control de Enfermedades Transmisibles/métodos , Georgia/epidemiología , Equidad en Salud/estadística & datos numéricos , Humanos , Modelos Económicos , Pakistán/epidemiología , Filipinas/epidemiología , Pobreza/estadística & datos numéricos , Sudáfrica/epidemiología , Estados Unidos/epidemiología
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