When tackling #COVID19, why is #intersectionality important?

Looking only at associations between deprivation & mortality OR gender and mortality, you miss the steep inequalities experienced by poor women. Perhaps even worse for women from black & minority ethnic communities. https://twitter.com/HealthFdn/status/1263721264952348672
. @AAPolicyForum primer: "...race, gender, sexual identity & class work together to limit access to...employment, fair immigration, healthcare... it is essential that....interventions be grounded in an understanding of how these factors operate together" http://static.squarespace.com/static/53f20d90e4b0b80451158d8c/53f399a5e4b029c2ffbe26cc/53f399c8e4b029c2ffbe2b28/1408473544947/59819079-Intersectionality-Primer.pdf?format=original
To tackle #COVID19 we need to use data (in all forms including experience and stories, not just numbers) to understand the circumstances that drive these inequalities. First step - individual level health data w/ good recording of gender, ethnicity, occupation etc.
Data isn't enough, we need need a response that acts on this information, and tailors action so that it reduces the steepest inequalities we see.
I'm no expert on #intersectionality theory and practice , so I'd recommend listening to Kimberlé Crenshaw speak on #intersectionality, the concept/theory she coined/founded.
Finally, just a friendly reminder that datasets we use can be biased reflecting the structural inequalities in our system: they might fail to recognise the (unpaid) work of women, reflect structural inequalities in health treatment, or record ethnicity poorly.
To illustrate this, working age women were less likely to have an 'occupation' listed in the ONS dataset than working age men. The majority of women with no occupation listed, were full time unpaid carers or volunteers. But were not included in the analysis of occupations.
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