October 18: another day, another exceeding the expected number of cases
Daily Status, October 18
The trends over the last three weeks, now are showing a modest increase, at 2.6%/per day or 20% per week.
By combining our current regional trends with the typical reporting for the day of the week, I expect about 880 cases tomorrow (Monday) with a 90% chance of the numbers falling between 600 - 1298 cases. If tomorrow's numbers differer from that, we are having a very rare event. This is useful to consider if I am unable to report tomorrow, as you can compare the state reported numbers with this.
Regionally, all of the commonwealth are showing positive case growth. The testing numbers now show the percent positive to below the 5% metric over the last week (4.80%) that is often used to indicate sufficient testing (e.g., is is safe to reopen schools). Virginia is testing about 2.8% of the population every two weeks, which is about 1/4th the number of tests desired for random sampling, but most of the Commonwealth's testing is driven by medical needs and not surveillance. Surveillance would ideally test at least 5% of the population per week but the testing is somewhat invasive..
On one other front, over the last week, we well above 10 cases per 100,000 to enter states like NY without quarantine -- we are at nearly 12.7 cases per 100K. As expected NY added us back on the quarantine list.
When we look at the local/ZIPCode data, we see that the observed increases are almost universal across the Virginia. For comparison, I am comparing the current estimated % positive to that one month ago. Note that almost all is a warmer color (further from blue and closer to yellow). This is an indication of the uniformity of the increase. As a practice matter, it means to be safe and careful no matter where in Virginia you are at risk.
NOVA: 1.032 - GMU
Central VA: 1.033-- VCU
Hampton Roads/Eastern VA: 1.014-- W&M, CNU & ODU
SW VA: 1.028-- VT & Radford
NW VA: 0.998-- JMU & UVA
The state as a whole is is increasing with Rt=1.0215
The following table shows the number per 100k for each region. Again, NOVA and Eastern VA are doing the best, and the mountainous regions in NW & SW continue having more cases. The concerning aspect is in all regions, the numbers for last week are significantly higher than the prior 3 weeks. What is most concerning is SW &NW VA, where it is hitting very high numbers, inspite of VT and Radford doing better.
The following charts are for the 5 regions. in the chart that shows all regions, The individual line charts show the unfiltered data per day, coupled with the trend lines. The trend lines show the different periods of growth. Early in the pandemic, the different parts of Virginia were functioning largely independently, with NOVA mimicking the northern states, and Hampton Roads mimicking the southern states. But, since September 1, the regions have trended with each other. Starting in late Sept., NoVA and SWVA diverged from the rest of the state.
Note that the effects at both ends of the chart are probably an artifact of the 7-day polynomial filtering I use. For those not inclined, it means it does a bad job at the beginning and end of the data.
For those technically inclined, the filter is called a Savitzky-Golay filter, basically is a moving window polynomial filter. At the edge (first and last days of the time series), the filter will over compensate for the trend as it is unconstrained. I recommend the Wikipedia article if anyone is interested in more information, or contact me.
Growth rate (%/day)
5 0.00e+00 1.69e-07 1.52e-06 5.76e-06 1.52e-05 4.03e-05 9.18e-05 1.48e-04 2.77e-04
15 0.00e+00 5.05e-07 4.54e-06 1.72e-05 4.54e-05 1.20e-04 2.74e-04 4.43e-04 8.27e-04
50 0.00e+00 1.65e-06 1.48e-05 5.61e-05 1.48e-04 3.92e-04 8.94e-04 1.45e-03 2.70e-03
100 0.00e+00 3.20e-06 2.88e-05 1.09e-04 2.88e-04 7.62e-04 1.74e-03 2.81e-03 5.25e-03
500 0.00e+00 1.28e-05 1.15e-04 4.36e-04 1.15e-03 3.05e-03 6.94e-03 1.12e-02 2.10e-02
1000 0.00e+00 1.99e-05 1.79e-04 6.76e-04 1.79e-03 4.73e-03 1.08e-02 1.74e-02 3.26e-02
2000 0.00e+00 2.60e-05 2.34e-04 8.83e-04 2.34e-03 6.18e-03 1.41e-02 2.28e-02 4.25e-02
Last 10 days
% that had COVID***
* estimated from the number of cases in the zip codes associated with the university removing the pre-student arrival case rate
Large Scale Community Spread:
- People can test negative and still spread the disease.
- Even if everyone who interacts with you is tested immediately prior to the interaction, you can still get sick (see 1).
- If you have an event with hundreds of people, there is potential for it to be a super-spreader event, even if you test everyone at the event.
- If you do this frequently enough, you will get unlucky.
- A non-spaced, but outside event is still dangerous.
1) You can repost / share in the entirety by forwarding the link, 2) If you want share partial content, you must receive my permission – I need to make sure you understand what I am saying. If anyone sees this work being used without attribution, please let me know as soon as possible. I am willing to have an informed discussion / debate on my approach, but I want to make sure the proper context is captured.
Other Sites: John's Hopkins
Kids can pass covid to parents: Pediatric SARS-CoV-2: Clinical Presentation, Infectivity, and Immune Responses