Posts written by Thomas Lumley (2534)

• Siouxsie Wiles in Stuff today with a piece about different study designs in medical research and the hierarchy of evidence. Nice to see this from a lab scientist!
• Censuses: the data releases from the 2020 US Census showing changes in population and in race/ethnic composition: Washington Post, NY Times, LA Times
• Censuses: Australia is holding its census at the moment, which is not going to be good for data on commuting, but will be good for data on the pandemic
• Censuses: Australia has a very good statistical standard for sex and gender questions, but is strangely not using it for the census.
• It appears that machine learning systems can distinguish self-reported racial identity from x-ray images. People can’t, and it’s weird that it’s even possible. Blog post, twitter thread, research preprint. I’m not sure I believe this, but the research seems to have been fairly careful.
• Jonathan Marshall is doing graphs of vaccination in NZ. These show the data rounded to the nearest sixth of the population — having all the wedges filled means at least 92%ish vaccinated.
  

You might have seen, on social media (or asocial or antisocial media) claims that the Delta variant of Covid can be spread by vaccinated people just as easily as unvaccinated people.  It’s not true, but if you strip out the two big reasons it’s not true, what’s left is still worrying. Here’s two relatively careful stories: WaPo, NYTimes.

We know that vaccination dramatically reduces the chance that you’ll spread Covid to someone else by dramatically reducing the chance you’ll be infected if you’re exposed.  Vaccination of people you come into contact with also reduces the chance you’ll be exposed, because they are less likely to be infected.

If vaccination reduces your chance of infection with Delta by 80%, it’s going to reduce your chance of transmitting Delta by around 80%. Reducing the uncertainty on that number is important in public health planning: the chance of transmitting Delta affects how much community protection we get from a given vaccination rate, and so affects what other precautions (MIQ, lockdown, masks, etc) need to be taken to get to an acceptable level of risk.  For example, the modelling of community protection by researchers at Te Punaha Matatini had a baseline assumption that ‘breakthrough’ infections were half as likely to transmit the disease as infections in unvaccinated people (though they also used a lower estimate of vaccine effectiveness in preventing infection than I think we’d use now, so it cancels out to some extent).

Estimating ‘secondary transmission’ is hard. Ideally, you’d trace all the contacts of each infected person and determine how many people they actually transmitted the virus to.  In practice, that won’t work.  In countries like Australia and New Zealand we don’t have enough free-range infections (or vaccination) to get reliable quantitative estimates information. Somewhere like the US or Britain, where you can get a sample of hundreds of cases, you can’t easily track down who infected whom.  There’s some information from comparing high and low vaccination regions in a country such as Israel, and from cluster-randomised trials that vaccinate whole communities at once, but not enough.

Logically, breakthrough infections might be about the same as unvaccinated infections (an infection is an infection), or less transmissible (your immune system reduces the viral load) or even more transmissible (only the people who are especially susceptible get infected).  Reason unaided won’t get us any further; we need data.

One approach is to estimate the transmission from the amount of virus people are shedding.  This roughly works — viral load explains the extra transmissibility of Delta.  If we find that ‘breakthrough’ infections shed a lot less virus, they’re probably less transmissible; if they shed about the same, they’re probably about the same.  According to the CDC, they’re about the same.  This doesn’t mean the vaccine has no effect on viral load — it could easily be that the people who get breakthrough infections would have had higher than average viral load without the vaccine, and the vaccine has reduced it to only average. It doesn’t mean that vaccination isn’t preventing infections — vaccination absolutely is.  It does mean the relationship between number of cases walking  around in the population and risk of new infections is about the same.  Knowing this will allow better estimates of population risk and better choices of precautions.

A graph about the current salary negotiations for nurses, tweeted by Andrew Little, the Minister of Health:

There are many situations when it is entirely proper to draw a graph with a y-axis starting somewhere other than zero.  There are essentially no situations where a bar chart should have the axis starting somewhere other than zero (the very occasional exception is when ‘zero’ basically is a number other than zero).  There’s a reason for this: in a bar chart, the area (length) of the bar conveys the information, and cutting the feet out from under the bar changes the information.

That’s all very well and good, you say, but is there empirical evidence that real people are misled by truncated bar charts? I’m glad you asked! Yes, there was a research paper published last year, titled “Truncating Bar Graphs Persistently Misleads Viewers”, which found …well, what it says on the label.  A truncated graph was misleading; it was still misleading for graphically-sophisticated nerds; and it was still misleading when accompanied by a warning. Truncated bar charts are bad. Don’t use them.

Sticking the missing $30,000 into the bottom of the Minister’s graph gives this:

• Queueing theory is a branch of applied probability and so is StatsChat relevant. Tava Olsen, a professor in the UoA business school, was interviewed on RadioNZ about the MIQ booking system and wrote for The Spinoff.   (disclaimer: I recommended her to RadioNZ)
• Matt Nippert writes in the Herald about Pharmac and — unusually for a story about Pharmac — looks at the tradeoffs involved in what they choose to fund.
• Via Axios: JAMA, the medical journal, requested revisions to the research paper with data supporting approval of aducanumab for Alzheimer’s disease. That’s pretty standard.  Apparently the company said “Nope” and will look for a different journal.  This isn’t unheard of — sometimes, reviewers are just wrong and you try another journal — but it is another unusual occurrence.
• Mediawatch reported that economic forecasts are often wrong.  That’s not really surprising: economics says that (a) recessions are unpredictable and (b) if economists benefit from their forecasts being mentioned in the news they will tend to produce newsworthy forecasts. I suggested that the forecasts should come with uncertainty intervals, so we have some ability to tell if they’re bad at forecasting or it’s just that the economy is uncertain.

• From Radio NZ: an exegesis of the non-quantitative weakly graph-like thing that accompanied information about NZ vaccine rollout plans in March.  This was unusually bad for a graph from the NZ public service, but I think the story is overthinking it.
• The FDA approval of aducanumab for Alzheimer’s disease seems may have been procedurally a bit dodgy as well as scientifically dubious. (STAT($), Washington Post)
• photochrome.io will take a word or phrase and give you a colour palette based on photos found using the word/phrase
• “Why are gamers so much better at catching fraud than scientists?”  (I don’t think they are; they just care about it more)
• The US is having problems getting new electorates laid out because of the Census delays.  In NZ, one of the constraints on the Census 2018 data quality improvement process was that it absolutely positively had to be done in time for the Representation Commission to make electorates.
• A twitter thread on finding evidence of secret US flights into Australia. Only not.
• Why housing costs aren’t in the Consumer Price Index (but are in other indexes, which you might want to use instead)

Q: Did you see that learning maths can affect your brain?

A: Well, yes. There wouldn’t be much point otherwise

Q: No, biochemically affect it

A: Yes, that’s how learning works

Q: But the researchers “can actually guess with a very good accuracy whether someone is continuing to study maths or not just based on the concentration of this chemical in their brain.”

A: How good is “very good”?

Q: I thought I was the one who asked those questions.

A:

Q: How good is “very good”?

A: The research paper doesn’t say

Q: Can you get their data?

A: <downloading and analysis noises>

A: Ok, so in their data you can get about 66% accuracy, 55 correct out of 83, using this brain chemical

Q: And just by guessing?

A: 56% (46 out of 83)

Q: Are these changes in the brain good? I mean, apart from learning maths being good for learning maths?

A: That seems to be assumed, but they don’t explain why

Q: And what about subjects other than maths?

A: The Herald piece says the differences they saw with maths don’t happen with any other subject, but the research paper doesn’t say they did the comparisons — in fact, it more or less denies that they did, because it talks about how many comparisons they did just in terms of two brain regions and two chemicals, not in terms of other subjects studied.

Q: But in any case, learning some other subject might still cause different changes in the brain

A: I think we can guarantee that it does, yes

Every two years, there’s a news story about how many condoms are being handed out at the Olympics.  I last wrote about it four years ago, when Rio planned to give away 450,000 condoms in the Olympic Village, compared to a mere 150,000 in London, and 90,000 in Sydney (initially 70,000, but they ran out).  The number was 110,000 in Pyeongyang, and the Guardian reports that it’s 160,000 for Tokyo.

It’s pretty clear that advertising for safe sex is a big part of these numbers. Which is a bit tricky this time around — the Tokyo Olympics has a serious problem with the risk of communicable disease, but it’s not one that condoms will fix. This year, according to the Guardian, the condoms are just intended as souvenirs, not as a way around social distancing rules.

There are two basic ways a government can put downwards pressure on carbon emissions and let consumers find the best ways to adapt. One is to charge a fixed tax per kg of CO₂ equivalent, the other is to fix a total cap on emissions and let consumers bid for the rights to use it.  There’s a sense in which these are equivalent: if the price in a cap-and-trade system ends up being $X per kg, the emissions will be the same as if the government charged $X per kg and didn’t have a cap. A sufficiently flexible and adaptive version of either one could match the other.  In reality they aren’t quite the same because governments want a simple and relatively predictable price or cap.

We’ve got a cap (more or less). One of the non-intuitive aspects of having a cap rather than a fixed price is that parallel efforts to reduce carbon emission don’t work the way you’d expect them to. If I replace my gas stove with an electric one, my kitchen will emit less carbon (modulo the impacts of making the new equipment).  If everyone did it, everyone’s kitchen would emit less carbon (again, ignoring the impacts of making the new equipment).  What would happen to NZ’s total carbon emissions? Nothing. We have a cap.  Less of the cap would go on carbon coupons for burning natural gas; more of it would be available for cars or trucks or coal-fired power stations.  The impact of our kitchen-renovation decisions would be cheaper emissions rights for other polluters, not lower emissions.

In principle, I could keep buying emissions rights for the natural gas I wasn’t using. That would turn my lower emissions into reductions for NZ as a whole. Or, the government could monitor the sales of induction cooktops and withdraw emissions rights to compensate (or, more realistically, track kitchen conversions through some sort of subsidy).  But if nothing happens to the total ETS carbon budget, nothing will happen to total emissions. A big enough change in demand could change emissions — if cars were suddenly banned, the government might not be able to sell all its ETS coupons — but a modest change won’t.

When the government says that new subsidies for low-emissions cars will reduce carbon emissions by some large number, there’s a gap in the explanation.  Having more low-emissions cars will lower carbon emissions by cars, but unless the government withdraws the corresponding emissions rights from the carbon budget, it won’t reduce carbon emissions in total. The reduction will go to lowering carbon costs for other polluters.

This, in itself, doesn’t mean the policy is bad; it just means the policy needs to be evaluated in some other way.  Maybe subsidising electric cars will lower the cost of future emissions reductions. Maybe it will improve the political feasibility of reducing the total emissions budget. Maybe there’s some other big benefit that I haven’t seen. But it is a problem that the policy is being sold on emissions reductions and that there doesn’t seem to be media or political reaction asking exactly where these reductions are coming from given the ETS cap.

The US Food and Drug Administration has approved a new treatment, aducanumab for Alzheimer’s Disease. The Chief Executive of Alzheimers NZ was quoted by  TVNZ

She said people living with dementia often ride a rollercoaster of emotion when it comes to new drugs being announced.

One way not to track vaccine attitudes, which I’ve already covered briefly, is to ask people if some piece of news, such as the rare blood clots with the AZ and J&J vaccine, has made them less likely to get vaccinated.  People who always supported vaccination will say “no”; people who always didn’t will say “yes”.  It’s like if you ask people whether Judith Collins’s speech in Christchurch yesterday made them less likely to vote National. National supporters will say “no”; Labour and Green supporters will  say “yes”, and that’s regardless of whether she actually was in Christchurch or gave a speech.

The Sydney Morning Herald has another way not to do it (via David Hood)

The story says

The exclusive survey, an initiative of The Sydney Morning Herald and The Age with research company Resolve Strategic, found vaccine doubts were stronger than in Ipsos polls carried out in February and September, before an official ruling in April about blood clots linked to AstraZeneca doses for people under 50.

It’s possible that’s true, but we’re not given any reason to believe it. We aren’t told what the figures were in February and September, and the new figures exclude the 15% of Australians who are the most likely to get at least one shot of the vaccine, because they already have.

Also, the numbers in the bar chart add up to 64%, with no explanation of where the missing 36% are. Perhaps the 15% already vaccinated are part of that, and the statement about excluding them is untrue. Perhaps 36% said they didn’t know and that wasn’t thought to be worth mentioning. Perhaps they were eaten by drop bears. We can’t tell.

Attitudes to vaccination actually matter, and it’s plausibly a topic where knowing what other people believe will affect your beliefs, so it’s worth doing better than this.