Covid-19: Droplets (Sep 25)

A couple weeks ago, Cornell University had over 80 active infections, and it was looking pretty dire. Then, the students got scared, and more careful. Last week there were 29 new cases. This week only 5. Someone was hospitalized for a few days last week, but it’s down to zero again. Still no local deaths.

Cornell has already run about 90,000 PCR tests since classes started. Students are tested twice weekly, and staff once. It’s probably not cheap. But, there’s a lot to be said for testing everyone: it nips outbreaks in the bud, and also acts as a reminder that the situation is serious. Having same-day turnaround also helps.

Meanwhile, I’m still doing research for a Coronavirus risk estimator. The consensus now seems to be that most infections happen through the air, so I’ve read a few dozen research publications about droplets and aerosols. The best is a 1934 paper by W. F. Wells. Here are a couple of its charts:

The first shows what happens to droplets that leave a person from talking, coughing or sneezing. Anything smaller than about 140 microns (.14 mm) evaporates, and turns into a floating aerosol. Anything bigger falls to the ground within a few seconds. What that means for Covid-19 is that there are three basic risks:

  1. if you are close enough to someone, you may inhale one of those bigger droplets while it’s still falling. That’s what the 6-foot rule is all about, and the advice to cough into your elbow.
  2. After the big droplets land, you can touch that surface, then transfer virus into your eyes, nose or mouth. It’s the reason for washing hands, and not touching your face.
  3. If you breathe air, you may inhale those small dried-up droplets, which gradually mix into the entire room volume. This is where HVAC comes in. The risk for any space depends on the number of infected people inside and what they are doing, minus air changes and filtration. It’s also why masks are so effective: they block droplets both coming and going.

The second chart from the Wells paper explains why respiratory diseases are more common in winter. People are indoors more, which is half the problem. Even worse, the air is heated and dry, so more droplets evaporate, float around, and end up in noses and lungs.

When working with droplets and aerosols, it’s easiest to do everything in microns (symbol ┬Ám, aka micrometers). A micron is one thousandth of a millimeter. It’s about the size of the biggest tobacco smoke particles, a medium-sized bacteria, or the smallest pollen grains. PM2.5 pollution is 2.5 microns and smaller (the most dangerous size because it gets into your lungs easily). N95 masks filter 95% at 1/3 micron size. They hit 99% for both smaller and larger particles. 3M says that’s because the bigger particles are heavy, and ram into a fiber. Smaller ones are extremely light, so the fibers suck them in by electrostatic attraction. 1/3 micron is the sour spot in between. A coronavirus is about 1/10 of a micron.

A few researchers have measured the amount of Coronavirus in mucus and saliva: results range from 12 million to 36 billion virions per cc. It’s simple math to translate that to the amount of virus in droplets of different sizes. As it turns out, a one-micron exhaled particle only has a 2% chance of containing a virus, even at the maximum rate. The bigger droplets that dry up and then float are worse. The maximum size that evaporates in humid air (97 microns) will contain somewhere between 3 and 17,000 virions. The maximum in dry air (172 microns) has 16 to 96,000.

As those droplets lose water, they shrink down to roughly 10 microns diameter (about average pollen size). They become a tiny glob of mucus proteins and passengers, light enough to float for hours, easy to inhale. By the math, those are probably the most dangerous.

Dennis Kolva
Programming Director
TurtleSoft.com

Goldenseal Pro Progress (Sept 14)

Our staff is gradually getting Goldenseal Pro to run, using the QT framework. Right now the app launches, opens files, and fills in a list of accounts and transaction types on the left side of the main window. Next step is to get it to load layouts into tabs on the right. That’s the most important part of the interface for Goldenseal Pro.

Back when we attempted to use Apple’s Cocoa framework, it took two or three months to get this far. So far, progress seems faster with QT, despite spending fewer hours per week. Some of speed increase is because we can reuse previous programming, or at least the logic behind it. Some is because we don’t have to futz with two different programming languages.

We currently are working mostly on Macs, but the same code also runs on Windows. Most likely we will alternate between them.

People warned us that QT is bloated, and they weren’t kidding. I found a list of all the QT classes: there are 1,718 of them. In comparison, Apple’s Cocoa has 654 classes, and Microsoft’s MFC has 475. I put all the QT stuff into a spreadsheet and narrowed it down to things that we might actually use. That gets it to a couple hundred.

In the past few years we used both Cocoa and MFC to build Goldenseal Pro, and failed completely. Not the first time we’ve had to toss months or years of work. Since 1987, our staff has tried about 20 different frameworks for building desktop apps. Only three resulted in actual apps: Microsoft Excel (MacNail), Apple HyperCard (BidMagic), and Metrowerks PowerPlant (the current Goldenseal). All three of them were productive right from the start. So far, QT feels the same way. Despite the bloat, it works. It’s not painful to use. Success is not guaranteed, but I’m more optimistic that we will finish this time.

The real test will be breakdown tables. If necessary we can use the work-arounds already developed for Cocoa, but it would be better if we can have something closer to the current interface. It probably will be 2 or 3 months until we get that far.

Dennis Kolva
Programming Director
TurtleSoft.com

Covid-19 in New York #4 (Sept 5)

There are two colleges here in Ithaca. Both planned to have classes on campus. Ithaca College (the smaller one) changed their mind a few weeks ago. They will be online-only for the Fall semester. Cornell went ahead with their reopening plans, and classes started on Wednesday. The Vet School laboratories are testing all undergraduates twice a week, which sounds great in theory.

Three weeks ago, there were 7 active cases of Covid-19 in the county. A week ago there were 19. Yesterday, there were 70. Most cases happened because students had parties without masks or social distancing. Who could possibly have suspected that might happen? /s

Maybe everyone will get scared, and change their behavior. More likely, there will be enough cases to trigger an automatic shut-down, per NYS regulations. We’ll see.

Meanwhile in the rest of the US, the State Rt tracker shows wavy curves for every single state. Today the majority of states are positive. Sometimes the majority are negative. It seems to vary on a few-week cycle. Back in April I compared state responses to skidding on icy roads. Because of the feedback delay, it’s easy to lose control and end up in a ditch.

Luckily, that isn’t happening with Covid-19. Most states seem to be converging on a Rt value close to 1. That’s probably the ideal growth rate, as long as the case count is low: the best balance between health and economic activity. I guess it also applies to ice and snow: most drivers in the North eventually figure out how to slow down the feedback cycle and stay on the road.

Globally, infections are also at a steady state, with about a million new infections every 4 days. Much of Europe is starting to see early stages of exponential growth, again. It’s going to be a long haul.

I’m still working on an Excel spreadsheet that calculates Covid-19 risk. There are many studies with useful info, but nothing that translates directly into hourly risk. It will require some assumptions and guesswork to get it calculating accurately.

Covid-19 risk is mostly a matter of HVAC. The amount of virus you inhale is equal to the number of people nearby, times the % that are infected, then divided by the volume of air and the number of air changes per hour.

At least a dozen case studies have been published: cruise ships, a Seattle choir practice, a Maine wedding, church events. I have been using Google maps and other sources to estimate building sizes. Air changes is totally a guess.

The biggest uncertainty was expressed best by Dr. Gregory House: “everybody lies”. Folks don’t want to miss work, or they really need a pack of cigs, so they get into public space even though they are shedding virus into the air. Odds are good that they don’t wear a mask. They avoid testing and don’t get into the official data, so the math is more difficult. Everyone’s lives are more difficult.

Dennis Kolva
Programming Director
TurtleSoft.com