Last data update: May 13, 2024. (Total: 46773 publications since 2009)
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Query Trace: Richard DM[original query] |
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What's next: using infectious disease mathematical modelling to address health disparities
Richard DM , Lipsitch M . Int J Epidemiol 2023 Before and during the COVID-19 pandemic, an individual’s age and race/ethnicity have been highly predictive of their risk of infectious diseases and their health consequences. Disparities were evidenced in COVID-19 incidence rates and in hospitalization, severity and mortality metrics in the USA1 and in other countries.2,3 Identifying these disparate outcomes associated with demographic variables is valuable mainly if it prompts investigation into what mechanisms generate the disparities and inform how they can be reduced.4 A prominent report from the UK succinctly outlined that social determinants such as occupation, household characteristics, surrounding population density, urbanicity and social deprivation were all associated with increased risk of COVID-19 infection.3 Others have noted that social determinants can play a role in all stages of an outbreak, providing pathways for unequal exposure, transmission, susceptibility and treatment that produce and escalate disparities in health outcomes.5 |
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