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COVID-19 in South Dakota: What’s My Risk?

Photo by Artem Beliaikin on

No matter what your political leanings may be, I think everyone can agree COVID-19 is often very confusing.  In the course of the pandemic so far, governments, private businesses, and individuals are being forced to make decisions about how to balance COVID risks vs non-COVID risks.  Most recently, everyone is struggling to make decisions about how to facilitate learning (in-person with masks? Distance learning? Business as usual?).  While two people may look at the same data and make different decisions, as a country we’re still trying to agree on what data to even look at.  And, on a personal level, it is difficult to reconcile the data debate with my personal experiences taking care of COVID-19 patients. 

                At the crux of the issue for many people is the question, how likely am I to get sick and die? People have tried to use mortality rates for different age groups to answer that question, but given concerns about access to testing especially early-on, it isn’t quite as useful as we might like.  It may be simpler to break it down into three questions: How likely am I to get infected?  If I do get infected, how likely am I to get very sick? If I do get very sick, how likely am I to die?

                While COVID-19 and Influenza A/B are NOT the same, I do think putting COVID-19 numbers next to Influenza numbers is helpful to give a sense of context.  The below chart compares COVID-19 so far vs the most recent Influenza season.

 DeathsEver HospitalizedTotal cases
COVID-19 (7/19/20)1167717862
Influenza A/B            (19-20 season)3256614776

In South Dakota, we have had 7862 positive cases.  (This is cases or individual people, not tests.  Even if you tested someone with COVID-19 five times, they’d still only be ONE case.).  Of those cases, 771 of those people ended up in the hospital at some point in their disease course.  Our total death count from COVID-19 is 116.  Inability to test people who may be ill but without severe symptoms requiring hospital-level care impacts the last column with the total number of positive cases.  However, even early on, people who were hospitalized were being tested so that number is a bit more reliable. 

Back to the questions!

Question 1- How likely am I to get infected?  At this point, it’s a bit unknowable.  This kind of information really requires going into a population and testing everyone which we haven’t done consistently except for small pockets (nursing homes, etc). 

                Question 2- If I get infected, how likely am I to get very sick?  This is not perfect data since we don’t know the total who had any infections.  However, if we look at people who were sick enough to be tested vs the people who were so ill they required hospital level care we do see that the rate of ever hospitalized vs total infection is 0.098 for COVID-19 to 0.038 for Influenza.  So, while the data looks like getting infected may mean you’re more likely to require hospitalization, there are too many caveats to consider that data ready for publication.

                Question 3- If I have a severe infection, how likely am I to die?  This is a pretty good apples to apples comparison.  771 people hospitalized vs 116 deaths is a rate 0.15 in COVID-19.  566 people hospitalized vs 32 deaths is a rate of 0.056 in Influenza.  This is roughly a three-fold increase. 

                For those of us in healthcare, these numbers appear consistent with our experiences.  I have taken care of numerous people with Influenza over the years and many of the COVID-19 patients we’ve seen in this state.  If you are sick enough to walk through my doors into the hospital, if you have COVID-19 you’re less likely to walk back out than if you had Influenza.  This is further risk-stratified by how healthy you were to begin with and your age, but that’s a breakdown for another time. 

                This also explains the disconnect between the numbers debate happening on a large scale to the personal experiences of healthcare workers at the frontlines.  The public is very vocal that they don’t understand what their personal risk is.  This is a fair concern, the numbers are incomplete and we don’t understand how many people may get infected with only mild to no symptoms.  At the same time, healthcare workers are seeing large numbers of COVID-19 patients who are very ill and may ultimately die which contributes to both physical and mental fatigue. 
                So, while the data isn’t perfect to address the question of individual risk, it does validate the feelings of many healthcare workers that treating people with COVID-19 is not like treating Influenza or other respiratory viruses.  I’ve struggled with trying to explain why I have a healthy respect for novel Coronavirus because I can’t share what I’ve seen because of HIPPA.  This data comes closest to painting the picture of the increased burden of illness we’re seeing in the people we take care of.

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