COVID-19: Genetic tests

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COVID-19 testing is very much in the news these days. Let’s take a look.

There are two main types of testing: detection of the pathogen (SARS-CoV-2) itself and antibody testing. In detective-speak, the first kind of testing looks for the perpetrator while the second kind of testing looks for the perpetrator’s footprints. The science and machinery are quite different. This article discusses the first kind of test: pathogen detection.

SARS-CoV-2 detection looks for the presence (or absence) of the pathogen’s genetic material. Genetic testing doesn’t try to match a sample against the entire SARS-CoV-2 genome. Instead, genetic tests target specific genes within the genome. It looks for specific sequences within SAR-CoV-2 genetic RNA. Unlike cells which store genetic information in DNA (deoxyribonucleic acid), the SARS-CoV-2 virus stores genetic information in RNA (ribonucleic acid).

The World Health Organization guidance recommends five target sequences which can be used to identify the presence of SARS-CoV-2:

  • Nucleocapsid gene (N)
  • Envelope gene (E)
  • Spike gene (S)
  • RNA-dependent RNA polymerase gene (RdRP)

The capsid and envelope genes code for the proteins forming the shell around the virus. The spikes are the proteins protruding from the shell and are the attachment points for cell infection. The RdRP gene codes for the chemical enzyme (polymerase) that assist the replication of virus RNA. The RdRP in this case is specific to SARS-CoV-2. All of these genes are SARS-CoV-2 fingerprints. (See “COVID-19: Know Your Foe.”)

The amount of RNA in a sample is very minute and is not sufficient for immediate chemical analysis. The sample RNA must be amplified, a fancy way of increasing the concentration (amount) of targeted RNA. These kinds of tests are called nucleic acid amplification tests (NAAT).

One form of NAAT is the reverse-transcription polymerase chain reaction (RT-PCR). You may have seen the term “RT-PCR” in the news. RT-PCR is a bread-and-butter technique in genetics research and drug development. Reverse transcrption (RT) turns the RNA into DNA which is amplified using polymerase chain reaction (PCR).

Without deep diving PCR (there are many good on-line tutorials), the term “chain reaction” hints at the technique. We know how an uncontrolled nuclear chain reaction leads to explosive fission. One nucleus splits causing two other nuclei to split and so on. PCR is a chain reaction in which DNA splits into two halves producing two new complete strands of DNA which split into four halves and so on. Each cycle doubles the concentration of the DNA in the sample. Eventually, enough DNA is available in the sample to reliably detect the presence of target genetic sequences.

Real time RT-PCR uses flourescent dyes to reveal the presence of targeted genetic material. Results are produced much faster than older methods employing radioactive isotope markers. Because speed matters, real time RT-PCR is widely used throughout the research and medical communities.

Real time RT-PCR is automated and many manufacturers, like Abbott Molecular, sell machines. Real time RT-PCR machines run a sample through multiple amplification cycles, typically, 30 to 40 cycles. Fluorescence is measured after each cycle. When fluorescence exceeds a threshold, the test is positive, confirming the presence of the targeted genetic sequence (and the pathogen). The machine counts the number of cycles needed to exceed the threshold. Severe infection (i.e., more pathogen RNA in the original sample) requires fewer cycles.

See “How is the COVID-19 Virus Detected using Real Time RT-PCR?”

Abbott M2000 RealTime System

The Abbott M2000 RealTime System is one example of a real time RT-PCR testing machine. The M2000 can test up to 96 samples in one run: 93 patient samples and 3 control samples. Control samples are required to assure valid results. Both positive and negative control samples are required.

Abbott M2000 RealTime System

The M2000 is a large machine suitable for a laboratory setting.

Like the RT-PCR machines from other vendors, the M2000 requires consumable supplies. Consumable supplies are usually machine-specific. If you own a laser or inkjet printer, you’re already familiar with this concept. 😉 The vendor develops and manufactures pathogen-specific test kits in the form of cartridges, etc. that are physically compatible with their machines.

The Abbott RealTime SARS-CoV-2 EUA test is Abbott’s COVID-19 test for the M2000. “EUA” means “Emergency Use Authorization.” Authorization is issued by the U.S. Food and Drug Administration (FDA). EUA limits the use of the SARS-CoV-2 EUA test and is not full FDA approval. The Abbott RealTime SARS-CoV-2 EUA test is designed specifically for the M2000 real time RT-PCR system for use by authorized laboratories in the U.S.

The M2000 can process up to 470 patient samples in 24 hours, roughly five runs per day, 93 patient samples per run. Abbott planned to ramp up U.S. production to one million tests per week by the end of March. This goal is far short of the millions of tests which experts believe are needed in order to re-open the economy.

Reagents are one of the consumables and you’ve probably heard the term “reagents” in the news as an item which is in short supply. Reagents are one of the main components of the Abbott SARS-CoV-2 test kit. The reagents break open the SAR-CoV-2 virus and release its genetic material (viral RNA). The reagents recognize targeted segments of the SARS-CoV-2 genome, ignoring genetic material from other viruses. The reagents select targeted genes for amplification. The Abbott RealTime SARS-CoV-2 test (assay) targets the RdRP and N genes.

The fine print notes “Negative results do not preclude SARS-CoV-2 infection and should not be used as the sole basis for patient management decisions. Negative results must be combined with clinical observations, patient history, and epidemiological information.” Thus, Abbott acknowledges that false negatives are possible.

The M2000 made the news in early April when Dr. Birx (White House coronavirus response coordinator) stated that 80% of the 175 Abbott machines in 120 laboratories across the U.S. were not being fully utilized. The machines are located in academic medical centers and hospital laboratories [Bloomberg News]. I suspect that the bottleneck is collecting samples and getting samples to the central laboratories. New York State plans to have pharmacies collect samples thereby increasing the number of tests per day and improving RT-PCR utilization.

Other big players in the market are Thermo Fisher Scientific (Applied Biosystems TaqPath), Roche )Cobas 6800/8800 System) and BD Molecular (BD MAX System). These tests target other SARS-CoV-2 genes like S and ORF-1AB in addition to N and RdRP.

Abbott ID Now

The Abbott ID NOWâ„¢ system is a small machine suitable for a doctor’s office or portable use (8.15″W x 5.7″H x 7.64″D). The Abbott machine was developed originally by Alere. (Abbott acquired Alere in October 2017.) The ID NOW is used to detect the influenza A and B2 viruses as well as COVID-19. ID NOW costs about $12,000USD.

Abbott ID NOWâ„¢ system

Multi-cycle RT-PCR tests raise and lower the sample temperature during each cycle. ID NOW operates at a single constant temperature, so-called isothermal chemistry. Thus, ID NOW can obtain results faster than conventional real time RT-PCR.

The overall test process is similar. Reagents break open viral RNA in the sample. The reagents recognize the target sequence in the pathogen. The isothermal amplification chemistry amplifies the selected genetic sequence. Fluorescent probes recognize and attach to each replicated sequence. The probe molecules fluoresce. The ID NOW hardware monitors fluorescence. When fluorescence exceeds a trigger threshold, a positive result is displayed.

Like the M2000, it uses consumable supplies like its reagent test cartridge, e.g., the ID NOW COVID-19 assay. A single test costs about $50USD.

The COVID-19 assay targets the SARS-CoV-2 RdRP gene. Results come fast — a positive result in 5 minutes (minimum) or a negative result in 13 minutes. The ID NOW COVID-19 assay is available for use under FDA EUA and is only available in the U.S. The ID NOW COVID-19 test is not yet approved or cleared by the U.S. FDA.

Machines like the Abbott ID NOWâ„¢ could greatly speed up COVID-19 testing. Big M2000 machines are centrally located and patient samples must be sent to the lab. The sample may await other samples for a full run. Then results must be reported back to the physician and patient. The round-trip takes too long; a delay of several days is not uncommon. The Abbott ID NOW can be located on site, potentially reducing the round-trip to an hour or two.

The chief disadvantage is cost. The ID NOW single test, cartiridge approach is nore expansive than M2000’s batch testing. ID NOW targets a single SARS-CoV-2 gene, RdRP, making it vulnerable to a mutation in this one gene. The M2000 targets three genes and is less vulnerable to a mutation.

Stay distant and stay healthy — P.J. Drongowski

COVID-19: Washington State April 15

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Time for this week’s Washington update. I’m tracking the daily positivity rate for Washington State using data from the Washington Department of Health, the University of Washington Virology Laboratory and the Snohomish Health District.

The daily positivity rate is the percentage of positive COVID-19 test results for each 24 hour period. The rate adjusts for the number of tests which varies from day to day.

The daily positivity rate is a useful metric, but an imperfect one. As I’ve said in previous posts, we need a proper epidemiologic study of COVID-19.

The first graph (below) is the daily positivity rate for Washington State though April 15. Why April 15 and not today, 24 April 2020? The Department of Health does not guarantee complete data for the most recent days. The data through April 15 is (nearly) complete although a few test results still trickle in.

Washington State daily positivity rate (April 15, 2020)

As noted in the graph posted last week, the state is past the peak and is in a slow decline. The peak occurred in late March. The daily positivity rate has declined to where it was in mid-March.

For comparison, here is the data from the UW Virology Lab. UW performs testing for and county and state health authorities. [Click images to enlarge.]

University of Washington positivity rate (April 23, 2020)

The shape of the graph is consistent with the overall state data. The Virology Lab data is up-to-date since they just report daily results for the lab itself (samples in, results out).

The Washington State epidemiologic curve (below) is informative, too. Known cases are tallied by the date of illness onset.

Washington State epidemiologic curve (April 22, 2020)

The epidemiologic curve shows a steady decline due to community mitigation, also known as “social distancing.” This is good news.

To complete the picture, here is the epidemiologic curve for Snohomish County, where I live.

Snohomish Country epidemiologic curve (April 15,2020)

Snohomish County shows a similar decline in new confirmed cases. Again, this is good news.

The big question for Governor Inslee and other decision makers is “How low is enough?” The answer to this question determines when social distancing can be relaxed. Currently, social distancing is expected to be in place until May 4th at the earliest. Hopefully, Washington will beef up contact tracing and isolation over the next two weeks. Then, it’s whack-a-mole.

Stay distant and stay healthy. Science works — P.J. Drongowski

COVID-19: Washington State April 8

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My weekly chart showing the positivity rate for Washington State is a tad late. The Washington Department of Health (DOH) has been busy fixing and upgrading its web site. The new site is a quite an improvement with informative charts, graphs and tables.

Looking at their data, I can appreciate the depth of their collection and reporting problems. Their old database was a “peacetime” tool, collecting positive results from a few of Washington’s many counties. In the fight against COVID-19, all counties are reporting at once and epidemiologists and decision makers want and need additional data about the number of tests, sex, age, etc. Of course, doing all of this work in the middle of a crisis must raise the IT stress level!

The state DOH site now reports detailed testing information in the form of a bar chart. The bar chart shows the number of positive and negative tests each day based on specimen date. This is a meaningful time base as it allows a snapshot of the positivity rate on a given day. It’s much harder to organize test data in this way than just lumping test results willy-nilly as they come in. (See “stress level” above.)

Because all test results for a given specimen day do not arrive at once, the DOH doesn’t guarantee complete results for the days just past. In keeping with their approach, my graph shows the Washington State positivity rate through April 8, 2020. [Click to enlarge graph.]

Washington State Positivity Rate (Through April 8, 2020)

The true peak in the rate occurred on March 28-29, 2020 when it hit 14.49%. The positivity rate has been slowly declining since then. The peak rate was more than double the 5% to 6% rate established around March 10. The new chart agrees reasonably well with raw statistics from the University of Washington Virology Laboratory. UW results, of course, are large portion of the State’s results. A back-of-the-envelope estimate shows that the rate has improved after April 8. Stay tuned.

So, what about those high rates in early March?

The positivity rate is a rather poor indicator which is subject to bias. COVID-19 tests are only administered under certain specific conditions because testing is rationed. Criteria include COVID-19 symptoms (fever, cough, tiredness, difficulty breathing) or contact with a known infected person. Properly, first responders may be given preference since they are most likely to come into contact with infectious people who may or may not be symptomatic. Further, COVID-19 hits nursing homes with vulnerable residents early and hard.

The general public has not been tested in a systematic epidemiological study, i.e., a random sampling of the population at large. Thus, the positivity rate as measured here is imperfect and may not accurately represent what the disease itself is doing in the overall community.

Contact is an important biasing factor and it is why I do not consider results in early March to be baseline. Public health authorities were actively pursuing contacts in early March after the first case of community spread was detected. The number of daily tests ranged from 74 to 500 — small numbers which are easily skewed.

As I’ve mentioned in earlier posts, today’s statistics tell us what the disease was doing 10 to 14 days ago due to the time required for incubation, development of symptoms, clinical presentation, and testing. Washington’s first community mitigation measures went into effect on March 11, with home-stay recommended on March 16 and home-stay ordered on March 16. I think we can safely say “Community mitigation works.”

Now we need the patience to finish the job and win the fight.

Stay distant and stay healthy — P.J. Drongowski

COVID-19: Know Your Foe

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OK, that’s a little bit over the top. I was trying to find a way to work NPH into this post. 🙂

Viruses are the simplest biological forms. Viruses are obligate parasites. A virus must invade a host cell in order to reproduce. Viruses contain genetic material, but do not have ribosomes which replicate the genetic material. Viruses use ribosomes in the host cell for replication.

Since a virus cannot reproduce on its own, one may ask if a virus is alive. The question “What is life?” is non-trivial and is not as easy to answer as you may think. Another interesting question to consider is “How did viruses and life begin?”

Please note the term “genetic material.” Viruses are exceptionally diverse. Some viruses are DNA-based, some are RNA-based. Further, the genetic material may be single-stranded or double-stranded. On top of these characteristics, the material may have a linear or a circular structure, or be segmented or non-segmented. Amazing.

RNA-based retroviruses are a huge exception to Francis Crick’s central dogma: DNA makes RNA and RNA makes protein. In a retrovirus, reverse transcriptase (a chemical enzyme/catalyst) synthesizes a DNA copy from viral RNA. The DNA copy integrates into the host genome (in eukaryotic cells). Then, the cell’s protein and replication factory takes over. Eventually, the cell bursts or otherwise expunges the particles and a new cells are infected.

Both ribonucleic acid (RNA) and deoxyribonucleic acid (DNA) are large molecules (polymers) — chains of nucleic acid molecules. Genetic material (RNA or DNA) is rather fragile. Strong UV light or heat causes the chemical bonds in RNA and DNA to break. Whether it’s a cell or a virus, genetic material needs to be protected. A virus typically has a hard protein “shell”, called a “capsid,” that surrounds and protects the genetic material inside.

At this point, I recommend the NOVA Labs and Khan Academy tutorial about RNA before reading on. They do quite a decent job of describing RNA, transcription (copying), and protein synthesis. If you want to cut to the chase, jump to the Virus Wars section of the tutorial.

SARS-CoV-2

SARS-CoV-2 is the virus which causes COVID-19, the disease. It is a type of coronavirus. Calling SARS-CoV-2 “coronavirus” is really refering to this specific type of virus by a generic name. (Not quite correct semantically.)

Coronaviruses contain positive-stranded RNA. The RNA is surrounded by an envelope with spike glycoproteins on the envelope. Without a doubt, you’ve seen the SARS-CoV-2 protein model on television — a grey envelope with red spikes. The spikey glycoproteins are composed of two subunits (S1 and S2). The spikes assist binding to a host cell and injection.

SARS-CoV-2 protein model (CDC)

SARS-CoV-2 is approximately 60 to 140 nm in diameter. That’s darned small. A human hair has a diameter of 15 to 181 um, 1000 times larger. The bactrium E. coli is 1 to 2 um in length, still much larger than SARS-CoV-2. Viruses are exceptionally small; they must be small enough to invade host cells like E.coli.

SARS-CoV-2 has a single-stranded RNA genome. Its RNA strand contains 29891 nucleotides and encodes for 9860 amino acids. In biology-speak, that’s almost 30 kb (kilobases, not kilobytes). AS RNA-based viruses go, that’s a fairly large genome.

The folks at Fusion Medical Animation have produced a new SARS-CoV-2 animation. The image below is taken from their animation.

Credit: Fusion Medical Animation

A tour of the genome

The New York Times published an excellent tour of the SARS-CoV-2 genome — Bad News Wrapped in Protein: Inside the Coronavirus Genome .

The Nucleocapsid gene (N), Envelope gene (E), Spike gene (S) and RNA-dependent RNA polymerase (RdRP) genes are important for testing. The WHO and CDC have developed nucleic acid amplification tests (NAAT) via reverse-transcription polymerase chain reaction (RT-PCR). Targeted genes include the N, E, S, and RdRP genes in the SARS-CoV-2 genome (WHO guidance). RT-PCR amplifies minute quantities of extracted SARS-CoV-2 RNA in a sample (if present) making it possible to assay one or more of the targeted subsequences (genes).

By now, you’ve come a long way along the journey and are ready for the summit. In closing, I recommend Features, Evaluation and Treatment Coronavirus (COVID-19) by Marco Cascella, et al. from the Istituto Nazionale Tumori – IRCCS – Fondazione Pascale. This paper is published by the National Center for Biotechnology Information (NCBI), a part of the U.S. National Institutes of Health (NIH).

If you would like to try your hand at sequencing, you can download the SARS-CoV-2 genome from NCBI. Don’t forget to snag a copy of BLAST. “BLAST finds regions of similarity between biological sequences. The program compares nucleotide or protein sequences to sequence databases and calculates the statistical significance.” STEM teachers, please take note of these resources. NCBI has many other genomes available for download.

Stay healthy, friends — P.J. Drongowski

COVID-19: Washington April 6

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Another week has past and it’s time for new charts. I’ve been tracking the daily positivity rate for Washington State. The “positivity rate” is the percentage of positive test results for each 24 hour period. Dividing by the number of tests each day adjusts for variations in daily testing throughput, i.e., the number of tests performed each day is different.

First, here is the chart using test results from the Washington State Department of Health (DOH). [Click to enlarge.]

Daily positivity rate (Washington State, April 3, 2020)

The gaps in the data are due to database issues at DOH. DOH receives and integrates test reports from around the state. Their database has been stressed and has not been tallying negative test results from which one can compute the number of tests per day (i.e., the sum of positive and negative results). Thus, I wasn’t able to compute a daily positivity rate for certain days.

Fortunately, I have the University of Washington Virology Laboratory as back-up. The UW Virology Lab is performing a large portion of tests in Washington. The Lab maintains a dashboard showing the number of tests they performed, the positives, negatives and inconclusives. Inconclusive tests are presumed positive. So, the daily positivity rate is the sum of the positive and inconclusive tests divided by the number of tests performed that day.

Daily positivity rate (UW Virology Lab, April 6, 2020)

Both graphs have a similar shape which shouldn’t be surprising as the UW Virology Lab is a major component in the DOH results. The positivity rate has more than doubled since early March. As of today (April 6), the positivity rate appears to be at a plateau and may show the beginning of a downturn. That’s good news and we need to remain committed to social distancing and other community mitigation measures.

Washington State recommended home-stay on March 16 and closed some businesses (e.g., hair salons, gyms, churches, etc.) I regard these measures as “social distancing lite.” On March 24, the State imposed a stay-at-home order. Given the time lag (10 to 14 days), the turn in the positivity rate is most likely due to the full stay-at-home order.

Fortunately, Governor Inslee has not declared victory. Instead, social distancing measures have been extended to May 4. Further, school has been cancelled through the end of the Spring term.

From my own observations, people in our part of Snohomish County (near Bothell and Everett) are treating COVID-19 seriously and are complying with the stay-at-home order. If a state, county or city is waiting for signs of an outbreak, don’t wait to issue a stay-at-home order. Response now will keep the size of your problem manageable. An ounce of prevention is worth a pound of cure.

Cleveland, OH

I keep an eye on the old hometown for no other reason than the Cavs and Browns. Cleveland.com published a few useful looking charts and graphs.

As we all go forward, we need to know when our communities have turned the corner and, importantly, when we can restart some business activities. The Ohio Department Health tracks the percentage increase in confirmed cases day-over-day.

Credit: Cleveland.com

Like Washington, Ohio has not hesitated to issue a stay-at-home order and to implement other forms of community mitigation. Gov. Mike DeWine, like Gov. Inslee, may not be the most dynamic individual, but he, too, is leading his state effectively in this crisis. I’m pulling for the folks at home!

Credit: Cleveland.com

This is another Ohio DOH chart which caught my eye. It plots confirmed cases by the onset of symptoms. This chart better aligns case count with the actual time frame in which a patient was infected.

NYT: What’s next?

The New York Times published two good articles on community mitigation and the next phase in our battle against SAR-CoV-2 (COVID-19) — cycles of “suppress and lift” as restrictions are applied and relaxed, so-called waves.

These articles are flying by so fast and so thick that you’ll miss them if you blink.

Stay 2 meters apart and stay healthy — P.J. Drongowski

COVID-19 Numeracy: Round-up

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Time for what’s known in the journalism biz as a “round-up.”

I started blogging about COVID-19 numeracy (AKA “by the numbers”) as a way to get my head around all of the data thrown at us by media outlets. Blogging also gave me a way to have the illusion of control over that which I cannot control, namely, the spread of COVID-19.

I hope that my blog posts are a resource for math and science teachers. (I try to keep these posts free of politics, BTW.) If there is a silver lining in all of this, what an opportune time to teach critical thinking and numeracy! I tried to collect the best and most useful examples of data presentation and, I collected a few stinkers, too.

So, here they are, links to my blog posts about COVID-19 numeracy:

If you’re a regular reader, you know that I usually deep-dive music technology and electronics. Fear not, I have been plugging away on music projects, too: Blokas MidiBoy, Toontrack EZKeys, recording demos with Genos, and more. All the projects for which I didn’t have time. Guess I’ve got the time now, just like everyone else. 🙂

I hope to blog about music-related topics as I’m not sure how much value I can add to the on-going COVID-19 discussion. I will continue to track the positivity rate for Washington State since this is my home with family and friends nearby. Plus, there are always subjects (e.g., reverse transcription polymerase chain reaction/RT-PCR testing) that pique my scientific interest.

Washington Post: Bending the curve

Here’s a quick hit from the Washington Post. It’s a set of graphs illustrating the effect of social distancing for select U.S. cities.

Source: Washington Post (April 2, 2020)

With respect to Washington State (Seattle), it’s still early days, really. I think my original guidance holds — we won’t really see a bend from another 7 to 14 days out from this point (April 2). Washington State imposed its first social distancing on March 16 followed by a stay-at-home order on March 23. With the delay due to SARS-CoV-2 incubation, development of symptoms, clinical presentation and testing (10 to 14 days according to medical experts), we should just now be seeing a bend in the curve.

The Washington State Department of Health (WADOH) has had technical issues with its disease reporting database. The original database could not handle the incoming stream of reports including negative test reports. So, the WADOH database went dark for a few days recently and is just now coming back. Due to these technical glitches, we need a little extra time to see the effect of social distancing in Washington.

Stay apart and keep all of us healthy — P.J. Drongowski

COVID-19 Numeracy: Seattle scene

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A New York Times article (March 29) suggests that social distancing is beginning to pay off in the Seattle area. The NYT article refers to work performed at the Institute for Disease Modeling in Bellevue, WA. The authors are cautious saying that data is preliminary and unpublished.

Quoting the IDM web site:

IDM shapes global efforts to eradicate infectious diseases and to achieve permanent improvements in the health of those most in need. By developing, using, and freely sharing computational modeling tools, we advise policymakers, promote quantitative decision-making and advance scientific methodologies.

IDM is an institute within the Global Good Fund, a collaboration between Intellectual Ventures and Bill and Melinda Gates.

Currently, IDM is working on disease transmission dynamics for malaria, polio, tuberculosis, HIV, pneumonia, typhoid, and more.

Personal thanks to Bill and Melinda Gates for their philanthropic work.

IDM has a COVID-19 InfoHub. For the latest results, I recommend the IDM InfoHub Research and Reports page. This is the real deal.

IDM published a report (as of March 29) on the effects of social distancing and mobility reductions on COVID-19 in King County, WA. Quoting the report:

Still, based on this data for King County, the trend clearly shows Re decreasing from about 2.7 in late February to roughly 1.4 on March 18th. These estimates come with high uncertainty, and while the trend is encouraging, it remains unlikely that COVID transmission in King County was below the 1.0 threshold on the 18th.

[We] cannot say with confidence if Re is below or above the critical threshold of 1 today.

Re is the effective reproductive number for COVID-19.

Thank goodness, Governor Inslee is not declaring victory either. Community mitigation measures remain in place and likely will be extended. (The federal guideline is currently April 30.) In his interview on CNN’s “State of the Union” on Sunday, the Governor cited shortfalls in testing supplies (swabs, vials, etc.) which are limiting the number of tests performed daily. As I’ve said before, we need community-wide epidemiological studies to get ahead of the disease. We cannot perform epidemiological tests (surveillance testing) when we can barely perform diagnostic testing for symptomatic patients.

The Fine Print

Let’s get nerdy. How do IDM define R0 and Re. Quoting the IDM glossary:

R0 (R Naught, Basic reproductive number): The average number of secondary cases a typical infectious individual will generate without any interventions in place to reduce transmission. The number of secondary cases per source is expected to change over time and space with different interventions and as the proportion of the population with immunity grows (REff).

REff (R Effective) or Re: The number of secondary cases each infectious individual will generate, on average, after interventions are in place and/or part of the population is immune. We would expect REff to be less than R0.

Washington Department of Health

The Washington State Department of Health upgraded COVID-19 reporting on their web site. They are publishing better graphs and data, especially data about testing. I’d like to see graphs for the posivity rate over time since the ratio of daily positive tests divided by the daily number of tests adjusts for day-to-day variations in testing. (“Daily” means for each 24 hour period.)

Positivity Rate

Governor Inslee referred to this ratio as the “Positivity Rate” and I like that term. It’s more concise than “Percentage of positive tests per day.”

Below is my plot of the Washington State positivity rate starting March 12 to March 29. Although the press is optimistic, The positivity rate has doubled over the time period. [Click image to enlarge.]

Washington State Positivity Rate (March 12 to March 29)

The gap in the graph is due to missing data from the Washington State Department of Health. They ran into database glitches March 24 and 25. The March 26 data point aggregates positive cases and tests across the gap.

There are several factors that affect the positivity rate. First off, this is not a random sample of the population at large. People are tested only if they satisfy a protocol, that is, satisfy a set of criteria. Criteria include presence of COVID-19 symptoms (fever, cough, shortness of breath), contact with a known infected COVID-19 patient, or in-coming travel from a known COVID-19 hot-spot (e.g., China, Italy, New York City metro, etc.) No doubt, some of the tests are due to contact tracing as officials try to identify possible carriers in order to isolate them. Bottom line, the positivity rate is far from a controlled epidemiological study (surveillance).

Please remember that any measurements we take today show what the virus (SARS-CoV-2) was doing 10 to 14 days ago. The delay is due to incubation, development of symptoms, clinical presentation and testing.

At this point in time (March 30), I’m glad that Washington State is staying the course and is looking at additional restrictions.

BTW, I’m still trying to absorb the changes to the Washington State Department of Health site. Their graphs don’t always jibe with my table of previously published data.

Cautionary tale

Here is a cautionary tale from The Seattle Times.

At the beginning of March, The Skagit Valley Chorale discussed weekly rehearsals and whether they should go ahead. Skagit County had not yet reported any cases of COVID-19. On March 6, they decided to go ahead with rehearsal on March 10. The chorale members used hand sanitizer and minimized contact during rehearsal.

None of those precautions, however, prevented an outbreak. Three weeks later, 45 members have been diagnosed with COVID-19 or have had symptoms. At least three members were hospitalized and two are dead.

Fortunately, our own church group passed on rehearsal during the same time frame.

This tale should be a warning to any community that feels safe because they have not yet experienced the disease. Please pay attention to our public health officials who predict eventual outbreak everywhere. Start social distancing and isolation now.

    Car crash fatalities (2019)    38,800 people 
    Vietnam War fatal casualties   58,220 people 
    Hiroshima fatal casualties     90,000 to 146,000 people 
    Nagasaki fatal casualties      39,000 to 80,000 people 
    COVID-19                       ?

— P.J. Drongowski

COVID-19 Numeracy: Epidemiologic Testing

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Epidemiologic testing

Yesterday, CNN carried interviews with Dr. Anthony Fauci and Bill Gates. Both gentlemen called for community-wide epidemiological studies of COVID-19. We need to know the prevelance of the disease in our communities in order to assess the effectiveness of community mitigation (i.e., social distancing).

Broadly speaking, there are two kinds of COVID-19 testing:

  1. Diagnostic testing
  2. Epidemiologic testing

Diagnostic testing is patient-focused. It determines if the tested individual is infected with SARS-CoV-2 (the virus which causes disease COVID-19) in order to isolate and treat the patient. Due to limited test capacity, all testing to date is diagnostic in purpose.

There are variants of diagnostic testing on the horizon such as a test to determine if an individual has acquired immunity to COVID-19 or not (antibody testing).

Epidemiologic testing is like a political poll. People are selected at random from the community, statistically called the “population.” The selected people are tested for SARS-CoV-2 infection using the same kind of medical test employed in diagnostic testing. Personal information is also collected such as age, sex, presence of underlying medical conditions, previous COVID-19 diagnosis, and so forth. Statistics are tallied and summarized such as the percentage infected, susceptible (not yet infected) and immunity. Like a political poll, the statistics are broken out by age, sex and so forth.

We have not yet performed a single community-wide epidemiological study of COVID-19. This leaves us blind to one important segment in the community — people in the community who are infected and are asymptomatic. We know that asymptomatic people are a significant factor in the spread of SARS-CoV-2 and COVID-19.

Impatient people are already chomping at the bit to restart the American economy. Given that we are only 2 weeks (at best) into community mitigation, this is preposterous. [Some communities have not even started social distancing and they are late.] At some point, though, we must restart the economy. Epidemiological studies will help us to decide if it is safe to reduce community mitigation and allow the free flow of commerce again.

One important factor in the decision to reduce mitigration is the degree of immunity in the community, the so-called “herd immunity.” The community (the herd) becomes protected from a disease when a large portion of the population (typically, 60%) is immune to infection. Infected individuals often become immune when they successfully fight off and recover from the disease (acquired immunity). Better yet, individuals can be made immune through vaccination.

Acquired COVID-19 immunity has not been confirmed by scientific study at this time. Based on prior experience with other coronaviruses, medical experts believe that recovered individuals will be immune to SARS-CoV-2.

“Flattening the curve” has two benefits. First, it reduces the strain on the health care system (hospitals, doctors, nurses and other caregivers). Second, it buys us the necessary time to develop a safe vaccine and to get a vaccination program ramped up and put in place. In some sense, developing the vaccine is the easy part. The time-consuming part is the medical trials and studies needed to assume safety and efficacy.

The Seattle Flu Study

During the Bill Gates interview, he mentioned The Seattle Flu Study.

The Seattle Flu Study was initially started to detect, monitor and control influenza outbreaks in Seattle using rapid virus genetic sequencing and mapping chains of transmission. The study is led by the Brotman Baty Institute, in collaboration with UW Medicine, The Fred Hutchinson Cancer Research Center, and Seattle Children’s.

With the outbreak of COVID-19, the Seattle Flu Study was “repurposed” to COVID-19. Quoting:

We are partnering with Public Health — Seattle & King County to launch the greater Seattle Coronavirus Assessment Network — or SCAN for short.

To track the spread of COVID-19, SCAN will collect nasal swabs from a sample of people across Seattle and King County, working to mirror the area’s population as closely as possible. We’ll collect swabs from both those who are healthy and those who feel sick and will also test de-identified clinical residual samples (these are left-over samples from tests performed for other reasons at clinical laboratories). The results of these tests will help us understand the outbreak more completely and, along with other data sources, help inform public health decisions. SCAN is not able to offer testing to every individual but the whole community will benefit from the program.

I look forward to the results of the SCAN study since we live a stone’s throw away from King County, Washington. This is our ‘hood.

Logarithmic graphs

Logarithmic graphs are good tools when analyzing phenomena with exponential growth. At this point, we’ve all seen linear scale graphs showing the steep rise of COVID-19 cases. Each tick in a linear scale graph has the same statistical weight, e.g., 100, 200, 300, 400, etc.

A logarithmic graph has a logarithmic scale. Each tick increases by a power of 10, e.g., 100, 1,000, 10,000, 100,000, etc. An exponential trend appears as a straight line in a logarithmic graph. Here is a logarithmic graph (from The Guardian, March 27).

Source: The Guardian (March 27)

Sadly, the United States is on an exponential trajectory. China and South Korea, in particular, have asymptotic curves, showing successul COVID-19 community mitigation. Those two countries are “flattening the curve.”

New York State Hospitalizations

Gov. Andrew Cuomo of New York presented an important and useful graph during his briefing this morning.

New York State COVID-19 Hospitalizations Through March 26

This chart shows the number of hospitalizations per day. Please note that the number of hospitalizations is increasing by almost 1,200 new patients per day. No health care system can sustain this kind of growth. New York State expects the apex of hospitalizations in 21 days, adding a further 25,200 hospitalized patients, if the current rate continues.

COVID-19 Numeracy: More NYT

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As I mentioned earlier today, The New York Times staff has published some excellent maps, charts and interactive simulations.

Their latest interactive simulation illustrates the effect of community mitigation (i.e., social distancing) for varying periods of time. I took snapshots at weekly intervals (social distancing for 7 days, 14 days, 21 days, etc.) [Click to enlarge.]

Effect of community mitigation for different time periods (NYT)

The curve in the lightest shade is the number of infected people. The middle shade curve is the number of people hospitalized and the darkest shade curve is the number of deaths. Each tick in the vertical scale is 10 million. Yes, millions. I recommend reading the article itself for assumptions and caveats on the mathematical model.

From this time series, it’s easy to see that two weeks (14 days) of community mitigation is wholly inadequate for suppressing the disease, let alone stopping it. To my eye, the shortest reasonable duration is 42 days (6 weeks).

Here is the latest NYT map (March 26, 2020) depicting the spread of COVID-19 across the United States. [Click to enlarge.]

Spread of COVID-19 (The New York Times, March 26, 2020)

Dedicated to Edward Tufte, who is still kicking around, thank goodness.

COVID-19 Numeracy: Geography

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Updated March 26, 2020.

State-by-state

Governor Cuomo, in his briefing today, asked why New York State is leading the United States in positive COVID-19 cases. Let’s compare the top four states:

                     Total   Total   Percent    
    State            Tests   Cases  Positive  Date 
    -------------   ------  ------  --------  ---- 
    New York        38,390  14,904     38.8%  3/24 
    Massachusetts   13,749   1,159      8.4%  3/24 
    California      27,650   2,102      7.6%  3/24 
    Washington      33,933   2,221      6.5%  3/23

Indeed, New York State has the highest percentage of positive tests — substantially higher. There must be a factor in play. Could there be a difference in testing (i.e., difference in the test kits? different test protocol?) Did SARS-CoV-2 hit New York State sooner? Is COVID-19 more prevalent due to the population density in the New York City region, as the Governor speculated?

Only a good epidemiological study could really measure the prevalence of SAR-CoV-2 in the community. As to timing, I don’t think we will ever know when SARS-CoV-2 hit our shores. New York City is a major global transportation hub. Even so, Washington and California have strong business and family ties across the Pacific and Pacific rim and have major transportation hubs (Los Angeles, San Francisco, San Diego, Seattle).

If I get a chance today, I’m going to look into our neighbor to the north, Vancouver. Vancouver is also quite connected with Asia and the Pacific rim.

The Washington Department of Health has had difficulties with its COVID-19 database. Although they posted a new number of positive cases, 2,469 as of March 24, the number of negative cases was not updated, showing the same total negative test count as of March 23.

The national picture

The New York Times has published many informative graphs and simulations during the COVID-19 crisis. The chart below shows the spread of SARS-CoV-2 (the virus) and COVID-19 (the disease caused by SARS-CoV-2) across the United States as of March 19, 2020.

Source: The New York Times

The chart illustrates how population density affects the number of COVID-19 cases. [Click to enlarge.] The biggest circles coincide with the major urban centers in the United States. On the west coast are Seattle-Tacoma-Washington, the San Francisco Bay area, and Los Angeles, for example.

The chart demonstrates why it isn’t appropriate to think numerically about the country as a whole. Sure, Americans want to know how the U.S. is doing overall. However, when it comes to actual COVID-19 containment and mitigation, it’s a local, regional problem. That’s why our county and municipal health departments are so important and local statistics are the most meaningful and practical.

All is not local, however. The urban centers are connected by highways and air routes, giving SARS-CoV-2 passage. As the disease plays out, the coastal urban centers with the greatest population and density will likely succumb first, followed by so-called second tier cities. When the disease subsides in major urban centers, the second tier will maintain active reservoirs of SARS-CoV-2. If major urban centers drop community mitigation (e.g., social distancing) too soon, the active pools in the second tier will cause COVID-19 flare-ups in any major urban center that drops its mitigration too early.

Major urban centers are more tightly connected to global business and commerce than the second tier. SARS-CoV-2 likely arrived much earlier than the second tier and SARS-CoV-2 has probably been circulating in the first tier population for a longer time.

Italy

Media outlets have drawn many comparisons between the Unitet States and Italy. Let’s consider a few facts about Italy from the CIA World Factbook.

Italy’s land area is 294,140 sq km (square kilometers), roughly the size of Arizona (294,207 sq km). Italy’s population is estimated to be 62,402,659 people (July 2020). California is the most populous state with 39,512,223 residents (July 2019). Overall, Italy has as many people as California and New York State combined in a smaller land mass (Arizona).

Italy’s Lombardy region is, arguably, the Italian region most severely affected by COVID-19. Lombardy is located in northern Italy with the major urban center Milan as its capital.

Lombardy has 10,078,012 people (August 2019). It is the most populated region in Italy. It’s population is roughly the size of Michigan (or North Carolina, or Georgia). Lombardy, by population, would be the tenth largest state in the U.S. Lombardy is 23,844 sq km, roughly the size of West Virginia. Lombardy has a population density of 420 people per sq km.

The city of Milan has 1.369 million people. (The World Fact Book claims 3.140 million people, but it depends on how one draws boundaries.) Milan has a population density of 7,572 people per sq km (2019). That’s roughly the same density as Huntington Park (Los Angeles metro) or Somerville (Boston metro). New York City has a population density of 10,431 people per sq km. [I taught in Somerville; it’s dense.]

Lombardy accounts for 68% of COVID-19 fatalities in Italy. 23% of Italians are 65 or older, making it the second oldest population in the world. (Japan is first.) Age and underlying health conditions are known COVID-19 vulnerabilities. High population density and more elderly people (with existing health issues) are a fatal combination of factors.

Temperature

One final observation because it involves maps. The Kinsa US Health Weather Map has received media attention including MSNBC’s The Rachel Maddow Show. (Hi, Rachel.)

The Health Weather Map is a visualization of seasonal illness linked to fever as measured by Kinsa Smart Thermometers. The Kinsa Thermometer connects to your device (and the Kinsa App) via Bluetooth. The Kinsa Thermometer costs about $20-$25 USD retail and requires the Kinsa App for Web communication.

Here is today’s map (March 26). [Click to enlarge.]

Kinsa US Health Weather Map (March 26, 2020)

I look at the Health Weather Map with interest, but take it with a grain of salt. There are two factors to consider.

  • Although the Kinsa Thermometer is inexpensive, it needs an expensive smart device in order to communicate results via the Web.
  • It’s not clear how people use the thermometer, i.e., do they take their temperature every day? When they feel sick?

Given the need for a smart device and Internet connection, I’m not sure if Kinsa users represent the population at large. Use of the device may bias results, too. If users take their temperature only when they are sick, then the map will show more high temperatures. Ah, well, I need to dig into their study. [Thank you, Kinsa, for posting your methodology.]

Stay apart, mate, and we’ll both be healthy — P.J. Drongowski