So yes, I do believe death counts are being intentionally under-reported, and that shit Florida pulled is deplorable. However, when it comes to statistics in general, I think skewing statistics isn't that widespread, nor is it very intentional. Deaths yeah probably. Overall cases? Much less likely. I think it can moreso be attributed to the sheer amount of uncertainty and incompetence than intentional misleading.
Let's rip apart the case definition game, shall we?
I want to start off by saying it took me months to wrap my head around the concept of case definitions as a thing. I mean, if a doctor says this person has [disease], and they have symptoms, why does it matter if the tests aren't the required tests and the symptoms aren't the required symptoms? I remember in my first few days all that time ago first starting disease investigation, my boss at the time was talking about how that person clearly had a disease, but it had to be counted as not a case, and I was so confused. Then a few days later he was doing it the opposite way, classifying someone as a case when the doctor said it wasn't, solely due to symptoms and tests. That man was not and is not a medical doctor. But you don't have to be for disease investigation. We take data, we compare data, and we classify data. That's it. And for that data, we need a standard. Even if the standard isn't great, we need a standard so everyone is doing the same thing. That way, at least it can be adjusted later on assuming everyone is doing the same thing. I know the assholes at the state watch and audit what we enter to make sure cases of various conditions are classified correctly.
COVID-19 case definition from CSTE was released a few weeks ago. Actually, looking for an exact date, I found CDC finally adopted CSTE's definition for interim guidance. that page gives April 5th. So before April 5th, there wasn't necessarily a coherent definition for all people to follow. And that's okay. We lacked data. We needed to say - Here are the positive people, Here are the symptoms we see in positive people, Here are the common ones, how can we make it so we capture accurate-ish numbers for those who aren't tested?
Okay, so I like CDC's layout a lot better than the PDF above, so I'm going to use that for quick reference. It's the same definition, but just different pages.
So take Johnny. Johnny is some dude living in a nursing home. Poor Johnny lives in a unit with a few cases. Guidance from my department has been once there are a few cases, assume an epidemiological link, don't necessarily test everyone. There's a 30% false negative anyway and we'd hate for you to cohort a negative test who is truly positive with true negatives and then expose a completely clean population. So poor Johnny is chilling in his room, doing his thing. Unfortunately, he starts with diarrhea. Dealing with this a lot, I can say yeah, diarrhea is a common first symptom in the elderly. Then Johnny pops a fever and has a lot of fatigue, and a hint of confusion. Johnny goes suffers a heart attack and dies. Poor Johnny. Did he have COVID-19? Clinically, I sure hope he was put on precautions and treated as a positive. Will he be counted in the state's system? Let's look at that case definition. He never got tested and we assume epi link. So no test is being done, he can either be Probable or Not a Case. So now we have to look at the symptoms. Did he have two of the following: fever (measured or subjective), chills, rigors, myalgia, headache, sore throat, new olfactory and taste disorder(s)? Nope, just Fever on that list. At least one of the following symptoms: cough, shortness of breath, or difficulty breathing? Nope, he was breathing as well as he ever did. No low pulse O2, no shortness of breath beyond what he as an elderly person in a nursing home already had, and no coughing. Then did he have severe respiratory illness with at least one of the following Clinical or radiographic evidence of pneumonia, OR Acute respiratory distress syndrome (ARDS)? Nope, again his lungs were fine. This guy would be classified as not a case.
Now you have Rico. Rico is Johnny's roommate. Rico, like Johnny, went untested. Rico was entirely afebrile. No diarrhea, weakness, or confusion like his roommate. But he had a dry cough going for a week or so with a runny nose before recovering and living a few more years in quiet comfort. Using that same case definition, Rico is a probable case.
So the benefit is not that that keeps case counts low. It's that we have a clearly defined "not a case" vs "probable case" vs "confirmed case." There's no question as to whether or not Johnny should be counted as a case or not a case in the same way there's no question Rico is Probable. It's clear. It leads to even reporting which is better in the long-term for statistics. Yeah, might Johnny have been positive? Sure. And did Rico just get a cold and recover? It's certainly possible. Might the case definition be capturing too few people or the wrong people? Yeah. But when we go back ten, fifteen years down the road, we can adjust for these. I wouldn't be surprised if we had more case definitions by the end of this, and we will be able to analyze them and say when we changed the definition, probables went up x%, so we can raise the earlier case definition x% as well. With aggregate data, we can pull both these cases, see there's someone who is not a case with diarrhea, fever, and other (the system my state uses does not have symptom options for fatigue or confusion but I see those often), and a probable case with dry cough and runny nose. We can adjust these based on future definitions. So I don't think it's so much incentivizing inaccurate reporting as it is standardizing even if that standardization is far from perfect.