Tag: math

Math Time – Delta Edition

An update to my previous mathematical analysis of covid transmission now that I’ve seen R0 estimates for this delta variant …

The R0 value for the delta variant seems to be between 5 and 8. Looks like just over 46% of the US population is vaccinated. The vaccines are published as being 90-something percent effective. That makes an effective transmission rate between (5 * (1- (0.46 * 0.95))) and (8 * (1- (0.46 * 0.9))). Between 2.9 and 4.7 — somewhat surprising given the R0 of slightly under 3 that was published at the start of the SARS-CoV-2 outbreak. That means that, as health orders and mandates are lifted, we’re basically exactly where we were a year ago even though about half the population is vaccinated.

A mathematically interesting thing — if you could get the vaccine efficacy up to 100% (a third shot, a tenth shot, a different vaccine, whatever)? We’d still have an effective transmission rate between 2.7 and 4.3 — the value goes down, but not significantly. On the other hand, increasing the percentage of fully vaccinated individuals by 10% gives us an effective rate of transmission between 2.5 and 4.0. Having 70% of the population vaccinated would yield an effective rate of transmission between 1.8 and 3.0. We’d need to get somewhere between 90 and 98% of the population vaccinated to bring the delta variant’s effective rate down below 1 (the point where it would die out naturally)!

That tells me this virus is going to be around for a long time — especially since the R0 for some upcoming variants might be higher. Also, I’m curious to see if the government authorizes a third dose given the minimal impact increasing efficacy has on the effective rate of spread.

Math Time — COVID Edition

Scott’s dad gets on our cases about being paranoid hypochondriacs (or whatever) because we’re still wearing masks and have Anya in online school for another year. The governor dropped the health orders, after all. Anya is too young to be vaccinated, but he’s safe … and kids don’t get sick anyway. Now, I don’t believe the latter two “facts” — kids do get sick, even if it’s less virulent. And I’ve never seen anything published that indicates vaccinated individuals don’t spread the virus. Just that they don’t feel unwell (which, in my mind, makes them more likely to spread it ’cause they don’t know they are sick … the Yankees having so many vaccinated people test positive sticks in my mind. They wouldn’t have known they were sick if it weren’t for what I assume is routine team-wide testing). And it’s difficult to explain to someone who has already made a decision … but the math just doesn’t support the “it’s all good” attitude people are adopting. I’m not an epidemiologist — I went to school for theoretical physics and work in computer science. I have done a lot of data mining and analysis, so I’ve got a decent understanding of the math side of epidemiology without any of the “so what do we do about it” medical knowledge. That being said … the math side of it can be helpful.

There’s a rate of spread for infections — computer viruses or human, in fact. There’s an initial rate of spread when no one has any immunity / has patched their computer (R0 to epidemiologist). If one person gets the virus, they give it to x people over the course of their infection. This is where you either see the total number of infected people trend toward zero of infinity — that is, if one infected person infects 0.5 (i.e. for every two infected people, you get one more person infected) … eventually the virus dies out. If one infected person infects ten others? This is a ever increasing progression — those ten each infect ten more for 100 infected people. Who each infect 10 for 1000 infected people. Which doesn’t seem bad — but those each infect 10 for 10,000 infected. Then 100,000. For each iteration, the number of infected people is 10^n — 10,000,000,000 is ten iterations down.

But preventative measures get taken — in one case, a computer virus caused my employer to shut down the LAN facing ports on every router in the company. Techs had to walk around with a fix-it CD, clean up every computer on a subnet, and then request the subnet be returned to the network. And, if we saw the virus propagating from that subnet? It got locked down again. Highly disruptive, but effective. And that’s where we were last spring with stay-at-home orders.

There are less severe precautions — computers have anti-virus software that look for virus-like activity for day zero identification. In human terms, that means we’re washing our hands after coming home from an outing. Or, as of last spring, wearing masks. Any of these precautions reduce the R0 value — but it can be difficult to predict exactly how much these actions will reduce the rate of spread.

Vaccines, on the other hand, have a quantified (and published) impact on spread. That efficacy and the percentage of the population that has been vaccinated scale the R0 value. The effective rate of spread is R0 * (1 – ( (vaccine efficacy) * (% of population that is vaccinated) ) ). If a vaccine prevents infection for half of the people who are exposed, then the effective rate of spread after vaccination is R0 * (1 – 0.5 * % of population that is vaccinated)). If a vaccine can prevent 90% of infections from occurring, the effective rate of spread after vaccination is R0 * (1 – 0.9 * % of population that is vaccinated)).

For convenience, I am going to ignore partially vaccinated individuals because I don’t know how effective a partial dose is at preventing transmission. The R0 published last year was around 3 — with about 40% of the population vaccinated with a 95% effective vaccine, that’s an effective rate of spread around 1.86 without other precautions being taken.

Now my numbers aren’t perfect — but this is almost a best-case effective rate of transmission. Another ten percent or so of the population is half-way vaccinated even if I don’t want to get that granular with my maths. But plenty of people got a 80-something percent effective vaccine, too. And the efficacy of each vaccine is reduced against variants. Having an effective transmission rate hovering around 2 seems, to me, like a premature time to cease taking other precautions.

Card Game: Sum War

Anya and I came up with a new card game — sum war. It’s a bit like war, but you throw two cards. The person with the higher sum wins all of the cards & puts them on the bottom of their stack. Keep going until someone has all of the cards. There’s obviously lots of addition involved, but the game uses estimation too (I have a 5 and a 7, you have a 5 and a 9 … you win without actually adding anything).

Equations: The Card Game

We came up with a new card game today — something to practice adding and subtracting (and mathematical thinking). Deal x cards (we’ve had five and seven to start). The remaining cards are the ‘draw’ pile. Flip one card over. Try to come up with an equation using the cards in your hand that combine with the flipped card to make an equation. Aces are 1, jacks are 11, queens are 12, and kings are 13.

There’s a King up — you’ve got 2, 5, 8, 9, and Q. 12(Q) + 9 – 8 = 13(K). You select one of the cards in your equation to place on the top of the face-up pile. The next person then tries to create an equation using the card you laid down.

Zero is a little special — there’s a some card up, x. If you have two cards of the same value, y. X plus Y minus Y equals X … and you can discard one of the cards you used in your equation.

If you cannot form an equation, you draw a card. The game ends when the face-down pile is exhausted. Add the values of the cards in your hand, and the person with the lowest value hand wins. This means you probably want to discard the highest value card in your equation (unless there’s a strategy to having the card — if I have an equation with 5 and 10, but have another 10 in my hand … I might want to hold on to the ten because the two tens are a 0 and are a guaranteed play).

Sometimes, math *is* hard

A recent meeting included a call back to “math is hard barbie” — back in 1992, Mattel produced a ‘talking’ Barbie that (among other phrases) said “math class is tough”. They ended up recalling the doll – a process which I assume cost the company quite a bit of money. And bad press. As a sophomore in high school, I didn’t understand the controversy. I was concurrently taking both Algebra 2 and Geometry (allowing me to complete two years of Calculus at graduation), so I had some experience with math classes.

The thing that struck me — the actual phrase is not untrue. Sometimes math class was hard. As someone with hand-eye coordination issues, art class was hard too. As someone who is tone deaf, music class was really hard. People who take offense at someone declaring something to be ‘hard’ have themselves declared difficult things as somehow negative. Not worth doing. I understand that the offense was people familiar with existing stereotypes extrapolating the statement to mean “girls think math is hard and girls avoid difficult academic subjects” or “females think math is hard because their brains don’t work that way and males have an innate advantage”.

I worry that we’re selling people false hope by refusing to tell them that something is hard. At some point, you’re going to encounter reality. I studied theoretical physics – gravitation, specifically gravitational phenomenon brought about during binary black hole collisions. Had someone told me it was going to be a super easy way to earn money – head into a computer lab for a few hours a day, drink some coffee, do a little typing, and head home … wow, what a shock my first day would have been. Why don’t we work on teaching people that a lot of things are hard. And each person makes their own effort:reward analysis. Raising chickens is a lot harder than picking a carton up at the grocery store; but if you like fresh eggs, or if you like to ensure the welfare of the animals providing your eggs, if you want to avoid using fossil fuels to transport your food, or if you just want to be involved in the process of generating your food … you decide to get some chickens. If you want to understand the mechanisms of the universe, you learn the math and physics. You do the research.