I think until this current outbreak slows that I’ll continue to do weekly data dumps for people who need to see the latest data in a unvarnished, non-manipulated form. Again, I’ll have better data for Arizona since I live in that state and have collected data from the state Dept. of Health Services for much of 2020. Of course, they don’t make it easy to collect the data in any form except the current day, so I have to go back every day and capture the latest. However, by doing so, I feel like I have insights that many don’t have. One of my reasons showing the Arizona data in such detail is that I feel that the behavior of the virus is similar in all regions and perhaps the Arizona results can provide insight into COVID activity in other states.
Zip Code Data
I feel that the Zip Code case data (wish I had deaths/hospitalizations by zip code too, but that is not provided) is valuable at understanding how the outbreaks are trending. For instance, we continue to see the largest case growth for this current Arizona winter outbreak in areas that weren’t hit very hard by COVID during the spring or the summer. This raises a couple of questions… 1) Why is it just hitting these regions now? Some of them are places that people from Tucson or Phoenix travel for vacation. I would have expected the case growth to have occurred along with the big outbreak in Arizona over the summer. The second question this raises is if this is an indicator that we’re seeing the effect of immunity in the areas that were hit hard over the summer (Yuma, SW Phoenix, S. Tucson, Nogales). See the latest charts below on the case growth in the last week across Arizona. Note in the table that there aren’t any obvious patterns in this wave (see my zip code correlation study from July here which demonstrated a number of patterns in the summer outbreaks)
Deaths Per Day
I think a lot of people are fairly aware that deaths have decreased in count since the big COVID waves in the Northeast this spring. I was curious how the “Daily Death” count in Arizona compared between the over 65 and the under 65 age demographics through the big summer outbreak and now in the winter outbreak. The plots below that perform this comparison are stacked bar plots. You can see three things in each bar, the under 65 deaths that day (the height of the blue bar on the Y-axis), the over 65 deaths that day (the difference between the height of the red bar and the blue bar), and the total deaths (the height of the stacked blue-red bar for the day). Hopefully that’s clear enough. But it’s a pretty useful chart, especially for visualizing differences between 2 or 3 groups.
The first plot shows raw numbers of deaths (blue is under 65, red is over 65). Therefore you can see that on the highest day for deaths during July we saw somewhere over 50 deaths in the under 65 demographic, around 120 deaths in the over 65 group, and about 170 deaths total. This is a good way to view the data and it reveals that on most days, there are many more deaths in people over 65. However, this isn’t that informative of a visualization, because the blue bars represent 87% of the state’s population. Therefore the second graph shows the death data normalized by the population of the group. I’m representing it as deaths per 100,000 people in the age grouping so the numbers aren’t too small to be meaningful. Therefore, now you can see that on the same day that we saw the 170 deaths, on the chart with normalized data, this represented about 13 deaths per 100,000 persons over age 65 and just under 1 death per 100,000 persons under age 65. This is a good way to visualize the true impact across age groups. If I separated the age groups under 65 it would be evident that the deaths are far more rare under age 45.
Cases
Now that I’ve demonstrated normalizing by population, here is how the cumulative case curve looks when normalized by the population of each age grouping. You can read this as that the 55-64, the 20-44, and the 45-54 groups all currently have cumulatively reached 45 cases per 1000 persons in their group. Note that this is just the cumulative count, not the number of cases currently active! What this shows us is that case growth for the three groups above has tracked almost identically since June. The interesting points to note, however, is that the over 65 case count when normalized by the over 65 population numbers is much lower (even though their deaths are much higher) and the under 20 normalized case counts is even lower. This tells us a few things. Cases are rarer in the 65+ population and even rarer in the under 20 population. The fact that 65+ deaths have been so much higher on a smaller number of cases shows that getting COVID is much more deadly proposition for this age group.
Hospitalization
A while back, the Arizona DHS improved their hospitalization status chart by adding the COVID cases in. Here’s an example of the ICU bed usage across the state. The other types of hospital bed usage charts look basically the same, but you can find them by following the link above. We see the peak from the summer hitting and the non-COVID ICU patients were squeezed out. Utilization never really went over 90% because of the hospitals’ ability to manage their beds. Then as the hospitalizations from COVID crashed in late July, new patients flooded into the ICU beds to keep the overall utilization around 80%. Now it’s creeping up again due to an uptick of COVID patients. I’m curious (and hopeful!) if the increase in COVID hospitalizations will be more gradual during this outbreak. It seems likely to me, but we’ll have to watch.
COVID-19 US State Table
The below is sorted by the “acceleration” of cases per day. Therefore, North Dakota is seeing an increase of 0.0388 cases per 1000 persons every single day. Therefore their case velocity (IROC_confirmed) of .9640 cases per 1000 persons will likely increase to around 1.03 cases per 1000 per day tomorrow and 1.0688 the following day. This acceleration metric (dIROC_confirmed) is a useful indicator to determine when an outbreak is slowing in a state. When Arizona was number one on this list last summer this metric is exactly where we first noticed the change.
As you can see, the midwestern states are currently seeing the largest case growth, but right behind them are the Northeastern states. I’m hoping and praying that the daily Delta_Deaths metric in all of these regions remains lower than it tended to be during the spring.
