Crisis and tragedy have a way of pulling us together.
Or so it is generally believed – the pandemic being a glaring example against this belief.
Yet in watching America’s response to the recent pandemic surge in India, you would hardly believe this is the country that went to war with itself over wearing masks or maintaining social distancing parameters. Yet this is the contradiction that defines present day America.
We have the best technology in the world, yet we are average at best in providing access to that technology.
We have some of the finest internet startups in the world, yet digital inequality runs rampant across parts of the country.
We unite against a common cause externally, but wage bitter wars among ourselves on issues that divide us internally.
Our ability to unite in support for India exemplifies a very American value of service and dedication, but reveals another very American value of internal discord, something that seems forever baked into the ethos of America – not being able to see in ourselves what we see in others.
This is a contradiction that has defined America since its original sin of slavery. Ta Nehisi Coates wrote in his novel, The Water Dancer, that American abolitionists love to fight against slavery, but hate to support the slave.
Which may portend trouble as a post-pandemic America comes to terms with the many inequities unveiled over the past year – healthcare inequity being among them.
A decidedly complex inequity, healthcare inequity is not obvious and apparent like other forms of inequity. There is no urban-rural divide. There are no skin tones to divide.
Instead we have complex inequities that fails to adhere to any simple line of logic as other forms of inequity have, manifesting in unforeseen ways, such as variations in the vaccination rates.
Kaiser Permanente Foundation analyzed county variations in COVID-19 vaccination rates and found a myriad of factors contributed to the overall decision to receive a vaccine – often with different counties determining whether to receive the vaccine on decidedly different reasons.
Across the 2,247 counties, the average vaccination rate is 15.8% for the total population and 46.7% for the population 65 and older. Seven of the top ten counties with the highest vaccination rates are in Alaska, where 21.9% of the population is fully vaccinated as of March 28, 2021.
More importantly, county vaccination rates do not correlate with COVID-19 impact. Counties with low scores for community transmission of COVID-19, as well as lower COVID-19 deaths per 100,000 people, have higher vaccination rates than counties with high community transmission scores and death rates.
In counties with high shares of Black people, the vaccination rate is 13.7% compared to 16.4% in counties with low shares of Black people. There is a smaller difference in vaccination rates among counties with high versus low shares of Hispanic people, with the vaccination rate in counties with higher shares of Hispanic people 15.0% versus 15.9% in counties with low shares of Hispanic people.
However, while the gap in vaccination rates for Hispanic people disappears in the population 65 and older, it remains for Black people.
As commonly displayed in the news, higher county uninsured rates and poverty rates are associated with lower vaccination rates. The average vaccination rate in counties with relatively high uninsured rates is 15.3% compared to 17.1% in counties with lower uninsured rates.
Yet, urban counties have lower vaccination rates for the total population than non-urban counties and the divide among counties is greater in states that voted for Trump compared to those that voted for Biden.
However, the share of the population 65 and older vaccinated is higher in urban counties, 47.5% versus 46.3% in non-urban counties.
The numbers are varied and inconsistent because the behavior is complex and unpredictable, not easily defined by a single trend or easily explainable concept.
America is truly a diverse nation, and while our diversity is seen as an asset, it becomes a liability when addressing inequities – as the perceived diversity forms the basis for our differences.
We find strife instead of accord, and we attribute blame to others for things we should all be accountability for together.
And the more complex the differences, the more easily we find divisions – which makes healthcare inequity one of the more divisive topics in today’s polarizing world of perpetual news cycles – healthcare inequity is mercilessly complex.
Just look at the variations in vaccination rates. There are no obvious trends or patterns we can trace to predict behavior. Any potential trend falls apart upon closer scrutiny or refutes itself when additional data is introduced.
In many ways, we do not even understand how we should conceptualize healthcare inequity – what is the frame of reference by which we compare those disadvantaged, those bear disproportionate burdens of healthcare?
Some have developed complex metrics like vulnerability index to create some standardized frame of reference, but the more complex the metric, the less relatable or applicable it becomes. We can relate to sexism because we see the oppression women face – and women are easily distinguished from me. It becomes difficult to relate to communities with high vulnerability indices because we likely do not even understand what that metric even means, or how to even apply the characteristics of a community that has high healthcare vulnerability.
Healthcare inequity, the ability to address healthcare disparities within our own communities is largely a matter of perspective, as many of the metrics that define this inequity are inherently subjective.
When we see an obese, Hispanic diabetic woman struggling to pay for her diabetes medications, we condemn her lifestyle choices and focus on her bad eating habits. When we see a thin, Caucasian diabetic man struggling to pay for his diabetes medications, we condemn the pharmaceutical industry’s profit driven motives and focus on the price of drugs.
Yet who is to say which of the two have better eating habits?
Instead of defaulting to the complex thought patterns we use to create associations – forming the biases we all hold – we must train our minds to see in others what we see in ourselves.
When we struggle to maintain a diabetic diet, we justify the difficulties we face. When we see others struggling, we attack their presumed lack of will power.
This perceptual contradiction is the deciding force limiting our ability to address healthcare inequity.
Not because we do not know how to fix it, but because we do not know how to see it. The problem is not external, but very much internal – in how we see ourselves.
Association between COVID-19 outcomes and mask mandates, adherence, and attitudes
Using an event study design, authors estimate the treatment effect of the introduction of mask mandates (shown on the vertical red line) on Z-scored population-normalized COVID-19 daily new confirmed cases, daily new hospitalization admissions proportion, and deaths across all 50 states and D.C. over the time period between February 1 and September 27, 2020.
Source: Dhaval Adjodah, Karthik Dinakar, Matteo Chinazzi, Samuel P. Fraiberger, Alex Pentland, Samantha Bates, Kyle Staller, Alex Vespignani, Deepak L. Bhatt. Association between COVID-19 Outcomes and Mask Mandates, Adherence, and Attitudes.