If there is anything that is permeating the national conversation wholly and completely as of late, it’s a bunch of numbers and percentages tossed like spaghetti at a wall hoping something might stick.
And a lot of those same numbers and percentages are freaking a lot of people out.
So let’s get into what all these numerical shenanigans actually mean, and how you can parse through whatever data you’re looking at and determine how relevant it is for you.
Alex and I read this helpful set of articles from OurWorldInData.org that were incredibly enlightening to us, and we wanted to share the big takeaways we had from those and from our own experiences with how numbers are shared in the current crisis environment.
Mortality rate predictions are obviously a big deal, and a lot of people are paying attention to them, so they will obviously be a topic of discussion. However, another piece of data being thrown around that seems to have a lot of weight is the number of confirmed cases and number of confirmed non-cases (negative COVID-19 tests) in any given place.
We are going to dive into both.
Now, in our podcast this week, we talk A LOT about the mortality rate of COVID-19 in an attempt to provide a more personalized look at those numbers – what does that rate mean on an individual level?
Here, we’re going to talk more about which mortality rate and number of confirmed cases are likely most relevant on a person-to-person basis and why.
The good people at OurWorldInData.org were kind enough to parse this out for us in this very informative article, but we’re going to expound upon a few of their best points here to give you a look at what these data mean for more rural areas (since cities are getting a lot of love right now, and things seem to be heating up in some rural areas). After reading our take, definitely hop over to OurWorldInData.org and check out their hard work and useful explanations.
- The number of confirmed cases seems pretty easy on its face. We just have to count the number of people who have tested positive for the coronavirus, right?
Well, this number can be a bit more slippery than that. Lack of access to testing makes it incredibly difficult to determine just how many cases of COVID-19 there actually are in any given place, and it is a number that is constantly changing.
Poor reporting methods, low-symptom and asymptomatic cases that don’t get counted, and complex pre-existing conditions that could mask the true cause of death all combine to make it even harder to know how many people have actually been infected. New research has been coming out periodically that is making this count easier and more comprehensive over time, but remember that these numbers tend to be location-specific – different areas have different access to testing, and reporting may not be consistent across all cases. - Mortality (death) rates, according to Our World In Data, look at the somewhat simplified equation: (number of deaths/number of cases) x 100.
It seems pretty straightforward, right? What else could possibly matter in determining how deadly COVID-19 really is?
Well, we are making a lot of assumptions if we simplify the numbers this much, and that means significantly over- or underestimating the actual mortality rate. In simplifying these numbers, we aren’t considering how correct those numbers are – have these deaths been confirmed by testing or just symptomology as COVID-19 related? Is this confirmed number of COVID cases, or suspected? Is it deaths versus resolved (recovered and no longer sick) cases, or deaths versus all ongoing cases, which includes a lot of unknown potential outcomes? Are there patients getting infected and/or dying of COVID that are not being properly diagnosed or counted? Are the tests being used even that accurate? (You get the point. Statistics are hard.)
The reality of the situation is that it is incredibly difficult to determine highly accurate numbers, in large part because we are so far behind on testing (which has a lot to do with test accessibility, as well as physical supply chains and operational laboratories). Compounding these challenges is a distinct possibility that a significant number of patients are either low-symptom or entirely asymptomatic and not being counted.
What we’re really seeing here is that numbers without context are pretty useless, and can actually become misinformation more than anything. For example, the movement of coronavirus into more rural areas is a situation where numbers without good explanation and examination could either become frightening or create a false sense of security.
Applying the numbers we have now that are highly concentrated in urban areas could be problematic in truly understanding what is happening in rural areas, and a number of factors play into why that is:
- Distance between people and their local hospitals and healthcare centers is much greater in rural areas. Often, this means that people who live in rural areas are incredibly self-reliant and can figure quite a bit of shit out on their own. Unfortunately, it also means that a lot of people heading to hospitals in rural areas are in worse condition when they arrive, having traveled long distances and sometimes having waited longer periods before making the decision to go to the hospital in the first place due to transportation difficulties, economic concerns, or some other reason.
(Also note: suburban and sprawl areas often have diffuse, minimal public transit options, which can make the effective distance to medical care and other resources challenging for those without ready access to a private vehicle, even if the actual distance to a hospital isn’t that great.)
For COVID-19, that can mean more patients arriving in an advanced condition and needing more immediate and invasive treatment. It could mean more people needing to be intubated and put on a ventilator, which leads to our next point – a dearth of resource availability. - Overall, access to resources is much lower—or at least slower—in rural communities than in urban areas. Fewer people, fewer employment opportunities, less capital, etc mean there are fewer hospitals with less money and less access to all the fancy technology and tools that can be found in urban healthcare. This can mean fewer beds available in the intensive care unit (ICU) and emergency departments.
It is highly likely that it means fewer accessible ventilators on-hand with which to treat patients. In the case of COVID-19, this can easily mean a lack of ability to save patients in serious condition. This lack of resources also means a lack of access to testing kits, which leads to an inability to determine who has what and how to treat and quarantine them. And finally, it often means less robust disaster preparedness and smaller resource stockpiles, leading to less resiliency in an emergency. - A systematic concern with rural areas is the way a lot of resource-poor areas rely on nearby urban centers for larger response capabilities and more advanced care. Most rural hospitals (as mentioned above) don’t have the same access to resources (including doctors and specialists) as urban areas and often send more complex and severe cases to larger, urban hospitals that are more well-equipped to deal with them.
In the case of COVID-19, this relationship is a difficult one. Most urban areas were hit first, and a few of the urban hospitals out there that rural healthcare systems have relied on in the past have been overwhelmed or are at capacity. This leaves those groups of patients without anywhere to go when rural hospitals run out of resources and means resource-sharing is not much more than a pipe dream in places like New York. - Socioeconomic factors play into concerns about rural healthcare response in a number of ways in the current crisis. Rural areas tend to have less capital, fewer employment opportunities, and job sectors largely in the essential business realm. Many of those working in rural areas are doing so in closer contact (for instance in factory jobs), or with fewer benefits and resources (like agriculture and other industries), and often do not have the option or opportunity to work from home.
Combine those realities with the fact that the population tends to be older with more chronic health issues due to employment sectors and healthcare access, and you have the perfect microcosm for spreading the virus to vulnerable populations.
Other factors definitely play a role in how dangerous COVID-19 could become in rural areas, and its spread is obviously largely dependent on each community and how they are handling the situation. Unfortunately, a large number of rural communities (and even some states) across the country do not have (or have not had) mandatory stay-at-home orders, putting their communities at greater risk than they need to be.
As the virus moves into these communities, numbers could go flying. Everyone is going to discuss rural confirmed cases vs urban and what the mortality rates look like, and context is going to get blurred or be completely absent in some cases. Just remember, lack of access to sufficient test kits means that these numbers are going to be rough estimates at best. It’s impossible to confirm anything without a test, and mortality rates depend on confirmations to be accurate.
Look at this data with a grain of salt, and definitely check out OurWorldInData.org to get more information on how to get a better grasp of the context of all those numbers floating around out there.
