Posts written by Thomas Lumley (2534)

From David Hood on Twitter, this graph shows leaving-home-ness in Aotearoa and the West Island, based on Google’s phone mobility data

The most important point about the graph, to me, is that the black dots follow a horizontal line (and the blue dots mostly follow a set of three horizontal lines).  This says that level 4 restrictions (and level 3, in RoNZ) were not eroding over time.  People were staying home just as much at the end as the beginning, even after four weeks and a much reduced case load.

The second important point is that the cluster of blue dots in the middle is a bit below the rest of the middle. Level 3 is slightly more effective, in terms of people staying home, than the Victoria and NSW and ACT restrictions. Level 3 is still a risk: it relies on people being at least as careful about masks and distancing and not accidentally flying to Wanaka as in level 4. Experts seem to be worried that it might be a bad idea, but to pretty much agree it’s still an effort at elimination.

How is that possible, given all the news about level 4 breaks? Well, Auckland is a big place. If 1% of people committed some serious breach of the rules and 1% of that 1% were reported, you’d have 160 reports.

• Good Herald piece on the Covid network contagion model 
• Andrew Chen organised a bunch of people to write a letter about privacy for Covid location data. He’s also been saying the same things to journalists.  It’s not that we think the government has any intention of misusing the data or letting the private sector misuse it, but the protections aren’t all that strong, the data collection is not voluntary, and having high-quality data is very important.
• There’s an interesting poll on US vaccine attitudes from the Washington Post and ABC News. Highlights: 82% of unvaccinated people said the FDA full approval for the Pfizer vaccine won’t make any difference to their decision. Crosstabulations (don’t you love polls with actual detail) showed 18% of unvaccinated respondents were in favour of requiring vaccination for school teachers and staff, and 15% requiring vaccination for students when a vaccine is approved at their age.  72% of those employed by someone else and not vaccinated said they would resign if required by their employer to be vaccinated. Politics site The Hill headlined this as Over 70 percent of unvaccinated Americans in survey would quit their job if vaccines are mandated, which is unlikely to be true — it’s a lot easier to claim to a poller you’d quit than to actually do it.
• Derek Lowe writes about bad clinical trials in Covid “I’m all for trying out new ideas – that’s essential, in fact. But try them out for real. … If you’re going to do research on human beings, you owe it to the subjects of your trial and to the rest of the medical community – and to the rest of the world, in this case – to do it right. To ask solid questions and get solid data on them that will allow you to make a real decision at the end of it.”
• Animation of vaccination progress in NZ (from Jonathan Marshall)
  

There are different ways of testing for the SARS-Cov-2 virus that causes Covid-19.  Broadly speaking, there are three approaches to the actual measurement: amplifying and testing for the viral RNA, testing for viral proteins, and testing for antibodies against the virus.  On top of that, samples can be be taken in different places: way up in the back of your nose, less far up, saliva samples, blood.

These tests are useful for different purposes because they have different characteristics.  The viral RNA tests using a deep swab and PCR have essentially zero false positives if you can avoid contamination.  That’s important in New Zealand because we use positive PCR tests to lock down the whole country, at nine-digit costs, and because we use them to put people in non-voluntary medical isolation.

The swab/PCR tests also have reasonably low false negatives. Nowhere near as low as the false positives — the lab assay is incredibly sensitive, but sometimes the swab just doesn’t pick up virus.  Again, we know this from NZ data. We currently have tests as soon after exposure as possible, again at five days, and again at twelve days, and people do test positive at five days or twelve days for the first time.  The false negative rate is important in New Zealand because we don’t want to miss even one case and allow an outbreak to expand.

For the places where we use swab/PCR testing now, we don’t want to substitute anything else. It’s the best technology available. But there are limits. The swab is a bit uncomfortable and the PCR process is slow and requires lab equipment in limited supply. We couldn’t, for example, do daily testing of all customer-facing essential workers with swab/PCR: they’d hate it and the labs would struggle to keep up.

In other countries, it’s much more valuable to have easy, rapid, and inexpensive tests even at a slight cost in sensitivity. There’s some risk of infection all the time; the consequences of a false positive or false negative are lower; there isn’t the same need to make sure all positive tests get reported. There’s a lot more scope for other tests to be helpful.

Even in NZ, though, there are gaps where other tests could be useful.  The obvious one is frequent testing of high-risk people. In normal times that would be people at the border; during an outbreak it might be essential workers whose job involves being exposed to customers or crossing the alert-level boundaries.  If we compare to swab/PCR the rapid antigen tests are not as good; but that’s not the right comparison. The rapid tests would be useful in settings where there isn’t going to be a swab/PCR. In those settings, the chance of detecting a case with swab/PCR is obviously zero, and the chance of detection with another test is actually pretty fair.

There’s a theoretical downside that negative rapid tests might slow someone with symptoms from getting a swab/PCR test until they get a positive.  If we were getting nearly 100% testing among people with symptoms, this would be a big concern. We probably aren’t anywhere near that; but it would need monitoring. There’s also a theoretical downside that false positive rapid tests might make people take positive results less seriously. I don’t think that’s plausible during lockdown, but again it would need monitoring. Somewhat more likely, it might turn out that there’s nothing actually wrong with the tests but that they don’t detect enough additional cases to be worth the cost and hassle. But that’s worth investigating, and where the realistic options are additional rapid tests or just the status quo, the effectiveness comparison should be between additional rapid tests and just the status quo.

The world’s Covid response has benefited from the twenty-odd years of large-scale genetics research that preceded it: inexpensive, widely-available PCR and sequencing; mRNA synthesis and delivery.  None of that was the plan, though.  Genomics was supposed to produce widely-applicable treatments for diverse medical problems, and revolutionise medical diagnosis and treatment. It didn’t: there have been genuine breakthroughs, but mostly in the  form of expensive treatments for rare diseases.

Today in Britain, there was definite progress.   NICE, who make recommendations for medication subsidy decisions, have pushed for the funding of inclisiran in people who have high cholesterol and who’ve already had a stroke or heart attack.  Inclisiran lowers LDL (‘bad’) cholesterol a long way, by a different mechanism from the current ‘statin’ drugs, and it can be given by twice-yearly injection at a GP’s office. The drug would usually cost more than it’s worth, but the NHS has a Pharmac-like secret deal to pay less than the £2,000 sticker price.

I’m not sure this is huge news from a public health point of view, but it’s interesting to someone who has worked in genetic epidemiology.  Inclisiran inhibits a gene called PCSK9.  The function of PCSK9 was originally fairly obscure; mutations in it were found by genetic linkage analysis to be related to familial high cholesterol in a group of families who didn’t have mutations in the known high-cholesterol genes.  Research in the Dallas Heart Study, a cohort study of risks for heart disease, found that several people with unusually low cholesterol also had mutations in PCSK9, suggesting that blocking the gene’s action would lower cholesterol.  Now, we actually need some cholesterol, so you’d worry that blocking the gene could be dangerous — but the Dallas Heart Study also found one woman who had natural mutations in both her copies of the gene, and who had extraordinarily low LDL cholesterol and no apparent adverse health effects.  All this came from largely correlational research that relied on inexpensive, large-scale gene sequencing — exactly what genomics had promised.

The other genetic aspect of the new treatment is that it works by silencing the gene, rather than the more-usual approach of blocking the activity of the enzyme after it has been produced.  Inclisiran is a ‘small interfering RNA’ molecule that binds to messenger RNA from the PCSK9 gene and triggers the cell’s recycling mechanisms to chop it up. The protein never gets produced.  This idea has been through hype and disappointment cycles — a small piece of RNA injected into the body looks remarkably like a virus, and the immune system tends to disapprove — but this time it seems to work, and to work on a common risk fact for a common disease.

The return on genetic ‘precision medicine’ has still been rather disappointing compared to the hype, but it’s nice to have the occasional example where it does basically work as promised.

Newshub has a commendably restrained story about some biochemical research into possible starting points for Covid treatment

Brazilian researchers have found that a molecule in the venom of a type of snake inhibited coronavirus reproduction in monkey cells, a possible first step toward a drug to combat the virus causing COVID-19.

Not everyone is so calm about it: The Hill says Brazilian viper venom shows promise as drug to combat COVID-19, the Daily Express says Covid breakthrough as deadly Brazilian snake venom 75% effective in stopping virus, and Indian site Zee News says Jararacussu pit viper, found in Brazil, can be the answer to Coronavirus, says study.

The research paper is here.

Researchers in Brazil were already studying the properties of a fragment of a protein from the venom of the jararacussu, a South American pit viper. This fragment blocks a protease, a protein-snipping enzyme, that is needed by the SARS-Cov-2 virus.  The protein fragment isn’t a drug on its own — and the protein it comes from definitely isn’t; it’s in the snake venom for a reason, and that reason isn’t to benefit animals that get bitten. However, this genuinely is one of the ways we get new drugs. A protein fragment from the venom of a related South America pit viper, which blocked a human protease enzyme,  was the starting point for developing ACE inhibitors, an important class of medications for high blood pressure and heart failure.

A few more things to  point out, though. First, the research paper is studying the ability of the SARS-Cov-2 virus to infect lab-grown hamster kidney cells in a Petri dish. These aren’t particularly realistic targets; they’re just convenient. The paper describes the use of a ‘positive control’, a chemical that they know is effective at stopping infection of these hamster cells under lab conditions. You might have heard of this chemical; it’s called chloroquine.  And finally, the tweet from The Hill that pushed me to write this post has a picture of a pretty green snake. It’s not the jararacussu. It’s an African snake that’s not especially closely related and whose venom hasn’t been studied all that much. They have the picture handy because a snake of that species bit a handler at the San Diego zoo in April. Zee News also use a pretty green snake picture, and it’s even less closely related.

This graphic, in a tweet by @heyblake, struck a chord in a lot of people. On the one hand, data together with stories that personalise the statistics can be a very powerful way to communicate.

On the other hand, this story is a lot whiter and greener than the data, and that’s definitely a thing that can happen.

Having been exposed for the past year and half to stories about the ‘basic reproduction number’ and ‘effective reproduction number’ of Covid, you might ask ‘what is R_eff at the moment?’

It’s hard to say. Firstly, it’s not really Covid that has an effective reproduction number but SARS-Cov-2; not the disease, but the virus.  The reproduction number is a feature of models for infection, not models for illness or even for confirmed cases.  Trends in illness or in the number of confirmed cases are important, but they are separated from trends in infection by the whole process of diagnosis, testing, and tracing. Right now, testing is on overdrive: people with minor symptoms are tesing (yay them!) and people with no symptoms but even minor contact with a case are testing (yay them, too!). As a result, cases are much more likely to be diagnosed than they were, say, two weeks ago.

In the long run, under constant conditions, the outbreak will have exponential growth or decay. In the long run, even quite large changes in the diagnosis, testing, and tracing process will be swamped by the much larger changes in the underlying infection rates. In the long run it will be obvious if total infections are going up or down and the rate can be estimated fairly well from confirmed cases. But in the long run we are all in level 1, so that’s not very satisfying.

At the moment, we have a reasonable hope that the population is effectively partitioned into bubbles, with much lower spread between bubbles than within bubbles.  If so, new confirmed cases will mostly either be new diagnoses of cases infected a while ago, or cases who got it from someone in their bubble.  For example, a lot of people who work in the same building as the Stats Department were being tested yesterday, in case they had been infected on August 17.

The number of cases like these is important, because we care about their health, but doesn’t really tell us about the effectiveness of level 4 lockdown, which is about the relatively small number of new between-bubble transmissions from people who were not yet diagnosed.  Calculating effective reproduction numbers from the number of observed cases isn’t going to be very accurate.

All this goes to say that, yes, we have good reason to hope the out-of-bubble reproduction number is well under 1, but the actual value genuinely is hard to estimate — and it’s particularly hard to estimate just from public data on numbers of newly confirmed cases.

The Herald had a story and headline based on a bogus online clicky poll today: Covid 19 coronavirus Delta outbreak: Majority vote for South Island alert level change

As we’ve seen in the past, bogus online polls can be very misleading. That last link, for example, compares three bogus polls from the same time period on the same question, whose results differed by more than you’d expect for random samples of only ten people.

The Herald does try to wiggle a bit on interpretation; the story starts “The votes are in and it is clear whether or not Herald readers think the South Island should stay in lockdown after Friday”. But the 70,000-odd votes are a tiny proportion of what the Herald claims as its readership: in January, they reported 610,000 daily print subscribers, 1.9 million monthly unique viewers on the blog, and a weekly ‘brand audience’ of over two million. There’s no reason to expect the poll responses are representative of any of those Herald readerships, either.

Usually one could argue that the bogus polls don’t do any major harm; they just amount to pissing in the swimming pool of public discourse. Usually they don’t get headlines. Usually they aren’t about a sensitive policy question in the middle of a pandemic. If the accuracy of the  numbers matters, you don’t want a bogus poll; if the accuracy doesn’t matter they shouldn’t be the basis for a lockdown-related headline

Not news-related, but just an observation from today while I was working on real-time bus data

At 1:30pm, just over 80% of buses were on time (by my fairly stringent metric of all buses; all stops).

That was just before a band of strong wind and moderately heavy rain. Afterwards, at 3:15pm, we’re down to about 70% of buses on time

Update: 4pm: — 53% on time

Rain messes up Auckland traffic, so it will inevitably mess up buses to some extent– bus lanes help, but even with bus lanes, they are affected by other traffic at most intersections.  There isn’t any straightforward solution; making buses allow lots of extra time and take regular naps along the route might fix the on-time metric, but it wouldn’t fix the problem.

PS: The interactive map –when it’s working — is here; the corresponding Wellington one is here

PPS: Bus performance has continued to deteriorate, but now it’s probably down to the likely coming Covid lockdown. Masks on public transport, folks. It’s not just the law, it’s a good idea

Q: Did you see more than 90% of LGBTQ adults in the US have had the Covid vaccine?

A: How could you even know that?

Q: From Twitter. And! Yahoo! News!

A: But…

Q: It makes sense, right? LGBTQ+ people are less likely to be on the anti-vaccine side of US culture wars, and there’s community experience with health activism

A: But there are queer and trans people in Alabama, not just in San Francisco. And a significant homeless population

Q: But that’s what the survey says

A: Two words: sampling frame

Q: Ok, what’s a sampling frame?

A: It’s the list you work from when you sample people: a list of phone numbers or houses or email addresses or workplaces or whatever. It defines the population you’re going to end up estimating

Q: So they’d just need a list of all the LGBTQ+ people in the US

A:

Q: Ok, yes, that would be scary. How did they really do it?

A: They had a list of some of the LGBTQ+ people in the US (press release, PDF report)

Q: Where did they get the list?

A: “Research participants were recruited through CMI’s proprietary LGBTQ research panel and through our partnerships with over 100 LGBTQ media, events, and organizations.”

Q: That sounds like it might not be very representative

A:  “Because CMI has little control over the sample or response of the widely-distributed LGBTQ Community Survey, we do not profess that the results are representative of the “entire LGBTQ community.””

Q: Exactly.  It might be useful for marketing, but it seems like it’s not going to be representative. They’ll miss some big groups of people

A: “Instead, readers of this report should view results as a market study on LGBTQ community members who interact with LGBTQ media and organizations. CMI views these results as most helpful to readers who want to reach the community through LGBTQ advertising, marketing, events, and sponsorship outreach. Results do not reflect community members who are more closeted or do not interact much with LGBTQ community organizations. More than likely, bisexual community members are also underrepresented in the results.”

Q: When you’re talking in italics like that, does it mean you’re quoting the report?

A: It does. Or the press release

Q: Sounds like they have all the right disclaimers

A: The disclaimers fell off on the way to Yahoo! News! and Twitter, though.