Talk:Lucy Letby
Oh come on ref
It is a common enough trajectory: we start with an instinct that, this popular, diligent, young, female nurse from a stable background is the last person you would expect to be a serial murderer. But since this kind of intuition is not scientific, let alone evidence, we must set it aside and consider the circumstantial evidence as it accumulates on its merits, and “without prejudice”.
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But hold on: if we regard purely circumstantial evidence as evidence that changes the prior likelihood of the event — that can change the inference we would otherwise draw from the baseline facts — then in as much as it reflects a basic statistical likelihood our baseline intuitions are a useful part of the story. We may not be able to assign precise probabilities to them, but we can legitimately ask, where there is no direct evidence of actual wrongdoing, what is the probability that a young female professional with a healthy social life, a stable and affluent background, a good circle of friends and no history of criminality, deprivation, instability or mental illness and no motivation — no “criminal propensity” at all, in other words — will, without warning, transform herself into a calculating serial murderer. We can see this probability is very, very low. Serial murderers are already very rare in the general population. Wikipedia lists 55 in Britain since 1255. Let’s conservatively put the total number of inhabitants in the UK since 1255 at 100m: this makes the incidence of any (known) serial murderer at something like one in 2 million.
concerning only probabilities, then there is a “mathematical” way of articulating what seem to be “biases” of our own:
, but has some basis in probabilities. She is the last person you would expect. The prior probability here is about as low as it could possibly be.
Then
The amateur expert serial murderer
The unit’s lead consultant Dr Stephen Brearey first raised concerns about Letby in October 2015.
No action was taken and she went on to attack five more babies, killing two.
On the face of it, the intensive care unit in a neonatal hospital — which must be as tightly controlled, monitored and overwatched as any place in Britain — is the last place you would embark on a regime of surreptitious serial murder. Better, surely to do it like Harold Shipman did, in the privacy of your consulting rooms, or better still, during a house call.
And once the hospital’s lead consultant had his own suspicions about the Nurse, you would think, she would be under even greater surveillance. Wouldn’t she? So does this not make the lack of direct evidence even more remarkable?
| Category | Daniela Poggiali | Lucia de Berk | Jane Bolding | Lucy Letby |
|---|---|---|---|---|
| “Incriminating” evidence |
|
Example | Example |
|
| Motive | “She must have just loved killing people” | Example | Example | Example |
| Actual evidence | Correlation between shifts and deaths | Example | Example | Correlation between shifts and deaths |
| Mitigants |
|
Example | Example | Example |
| Alleged Method | Pottassium Choloride | Example | Example | Several |
| Resources | Richard Gill blog | Example | Example | New Yorker article |
More Witches
Peasant 1: We have found a witch may we burn her?
Peasant 2: Burn her!
Bedevere: How do you know she is a witch?
Peasant 1: She looks like one
Bedevere: Bring her forward.
Woman: I am not a witch
Bedevere:But you are dressed as one
Woman: They dressed me up like this
Peasant 1: We didn't!
Woman: And this isn't my nose it's a false one
Bedevere:Well?
Peasant 1: Well, we did do the nose
Bedevere: The nose?
Peasant 2: And the hat but she is a witch
Peasant 1: Burn her!
Bedevere: Did you dress her up like this?
Peasant 1: No.
Peasant 2: Yes.
Peasant 3: Yes.
Peasant 3: A bit. She has got a wart.
Bedevere: What makes you think she is a witch?
Peasant 1: Well, she turned me into a newt.
Bedevere: A newt?
Peasant 1: I got better.
Peasant 2: Burn her anyway!
Peasant 1: Burn her!
Bedevere: Quiet! There are ways of telling whether she is a witch.
Peasant 1: Are there? What are they? Tell us.
Bedevere: Tell me, what do you do with witches?
Peasant 1: Burn them!
Bedevere: What do you burn apart from witches?
Peasant 1: More witches!
Peasant 2: Wood.
Bedevere: So, why do witches burn?
Peasant 1: Because they're made of wood?
Bedevere: Good!
Bedevere: So, how do we tell whether she is made of wood?
Peasant 1: Build a bridge out of her!
Bedevere: Can you not also make bridges of stone?
Peasant 1: Oh, yeah.
Bedevere: Does wood sink in water?
Peasant 1: No. It floats! Throw her into the pond!
Bedevere: What also floats in water?
Peasant 1: Bread.
Peasant 2: Apples.
Peasant 3: Very small rocks.
Peasant 4: Cider.
Peasant 5: Cherries.
Peasant 6: Gravy.
Peasant 7: Mud.
Peasant 8: Churches.
Peasant 9: Lead.
Arthur: A duck!
Bedevere: Exactly. So, logically —
Peasant 1: If she weighs the same as a duck, she's made of wood.
Bedevere: And, therefore?
Peasant 1: A witch!
Peasant 1: A witch!
David Holmes
JHB: what could have been the tell-tale signs that this woman was a danger? Was there anything that could have given us forewarning? Holmes: “Well, it may not give forewarning but generally speaking, [with] a serial killer of this stature really it’s almost obligatory to have psychopathic traits and they will often show themselves in various ways. ... she was very controlled. She was trying to give the image of a very responsible, caring nurse who would be there in a crisis to save babies and so on and so forth. So she is playing the role of someone who would not be suspected other than the correlation between her and the babies’ deaths.”
“It’s a situation where you have not got any really concrete evidence: one piece, like a CCTV camera footage or a witness, etc, all you’ve got is an accumulation of basically very low-level evidence — coincidences, etc — but when you actually accumulate a large number of these [using] something called a Bayesian analysis, it’s actually more statistically sound to have 100 little arrows pointing towards Lucy and none pointing away from her, and I think that’s how justice was actually reached.”
- —Criminologist David Holmes on Sky News, 18 August 2023
Well, to a point. Bayesian analysis starts with a “prior probability” — an initial estimate of the likelihood that “Lucy Letby murdered multiple neonatal infants with no motive, no psychiatric history and no prior tendency” — which is extremely low — and adjusts it to a “posterior probability” on the cumulative effect of the “little arrows” to revise the likelihood of it being true. An accumulation of even weak “little arrows” can increase the “posterior” probability of the hypothesis, but if all the arrows are also consistent with another explanation, their contribution to updating a Bayesian analysis may be modest. There is significant potential for false positives when dealing with rare events and weak evidence. (Compare this with David Bain’s case, where the prior probability that he was the culprit was already high (the event was certainly murder, and he was one of only two plausible suspects), and the circumstantial evidence against him was strong, and Lindy Chamberlain, where the prior probability was very low, and the circumstantial evidence weak).
| Case | There was a Murder | Suspect responsible | Another person responsible | |||
|---|---|---|---|---|---|---|
| Prior | Posterior | Prior | Posterior | Prior | Posterior | |
| OJ Simpson | Certain | Unchanged | Very likely | Greatly increased | Fairly unlikely | Unchanged |
| David Bain | Certain | Unchanged | Fairly likely | Greatly increased | Fairly likely | Greatly decreased |
| Peter Ellis | Very unlikely | Mildly increased | Extremely unlikely | Mildly increased | Extremely unlikely | Unchanged |
| Lindy Chamberlain | Very unlikely | Mildly increased | Extremely unlikely | Mildly increased | Extremely unlikely | Unchanged |
| Lucy Letby | Very unlikely | Mildly increased | Extremely unlikely | Mildly increased | Extremely unlikely | Unchanged |
The question, then, is how many of the “little arrows” are inconsistent with another explanation. Here there are two categories of alternative explanation: that someone else was responsible, or that no-one was criminally responsible: the event would have happened anyway.
The prior probability of there being a different murderer on the ward is the same for any other nurse as for Lucy Letby: extremely unlikely. No suggestion was made that any other person was involved, so we can assume two alternatives: either an innocent explanation or Letby was the culprit.
It is worth also looking at the categories of circumstantial evidence in each case and associating it with one or other of those probabilities. Does it make it more likely that There was criminality involved in the deaths, or that, Assuming there was criminality, Letby was the culprit.
| Evidence | Criminality | Letby was the culprit | ||
|---|---|---|---|---|
| Relevance | Posterior value | Relevance | Posterior value | |
| Ward roster | No | N/A | Yes | Contested |
| Post-it Note | No | N/A | Yes | Weak |
| Editing nursing notes to “cover tracks” | Yes | Weak | Yes | Contested |
| Post-event internet activity | No | N/A | Yes | Weak |
| “Trophy” handover notes | No | N/A | Yes | Weak |
| Bubbly personality | No | N/A | No | N/A |
| Obsession with a married doctor | No | N/A | No | N/A |
| Unexpected collapse | Yes | Weak | No | N/A |
| Insulin levels | Yes | Weak | No | N/A |
| Skin discolouration | Yes | Weak | No | N/A |
| Liver damage | Yes | Weak | No | N/A |
| Evidence of air in blood and brain | Yes | Weak | No | N/A |
Interestingly, bar for the alleged editing of nursing notes, which case been oddly under-reported, none of the “small arrows” point to both the presence of criminality and Letby’s particular involvement. It is worth reviewing the published pieces of the chief “public prosecutors” who make the case for Letby’s guilt. Among these are the expert witness Dr Dewi Morris, Daily Mail Journalist Liz Hull,[1] BBC Journalist Judith Moritz and the frequently interviewed Criminologist David Holmes. They are emphatic in their dismissal of the “yellow butterfly gang” — in Hull’s words, “diverse band of fanatics and pseudo-scientists” (later upgraded to a “strange band of misfits and ghouls”) coming from all “walks of society: well-to-do pensioners, middle-aged women, and the unemployed” and who, er, “counted scientists, neo-natal nurses, doctors and statisticians among their members” — so I was curious to see what they brought out as their clinchers.
Lizz Hull
Hull, on the New Yorker piece:
I’ve read the article and now the retrial is over I can write about it. And while there’s no doubting the author, who says she obtained full transcripts of the ten-month trial at huge cost, has researched the case thoroughly, it contains errors and cherry-picks evidence, omitting large parts of the prosecution case which was pivotal in reaching a conviction.
For example, it makes no mention of the 250 confidential “trophy” handover notes, blood test results and resuscitation notes relating to the babies police found at Letby’s home; it does not try to explain the Facebook searches that she made for the parents of her victims, years after she harmed their children.
Letby’s abnormal, animated behaviour in front of grieving parents after a baby died and pictures of cards she sent or received from parents of babies she murdered that were stored on her mobile phone, are also ignored, as is her obsession with a married doctor and her deliberate editing of nursing notes to make it seem like a baby was on the verge of collapse to cover her tracks.[2]
In a later article on 24 July 2024 — the first one evidently not having the desired effect — Hull sets out the overlooked evidence that proves the conspiracy theorists (although they are better described as “no conspiracy theorists”) wrong.
Star witness Dr Dewi Evans
Uncalled defence expert Mike Hall
Sewage and insulin
- No evidence was presented to show any of the infants contracted bacterial or parasitic infections linked to dirty water caused by drainage problems.
- Though journalists have since queried the suitability of the insulin tests for use in a criminal prosecution, the defence team did not.
Concession that the insulin was deliberate
The Court reporting suggests this was less emphatic than it has been made out to be:[3]
Letby is asked if Child E was poisoned with insulin.
“Yes I agree that he had insulin.”
“Do you believe that somebody gave it to him unlawfully?”
“Yes.”
“Do you believe that someone targeted him?”
“No.”
“It was a random act?”
“Yes...I don't know where the insulin came from.”
“Do you agree [Child L] was poisoned with insulin?”
“From the blood results, yes.”
“Do you agree that someone targeted him specifically?”
“No...I don't know how the insulin got there.”
Letby adds: “I don’t believe that any member of staff on the unit would make a mistake in giving insulin.”
Liver injury
One of the babies suffered significant liver trauma. The post-mortem said the bleed was due to vigorous CPR, but a forensic pathologist from told the jury he’d only ever seen this type of extensive internal injury in children involved in road, trampolines cycling accidents, or who had been deliberately assaulted.
Letby accepted in evidence that the injury took place “on her watch”.
Air in stomachs
The Guardian reported that seven anonymous neonatologists called Dr Evans’ theory about the injection of air into the stomach via nasal feeding tubes “ridiculous”.
Dr Evans admitted to me that injecting air in a nasogastric tube is “utterly bizarre” and something he’d never heard of before. But he added: “That doesn't mean it can’t exist.”
The shift rota
The infamous shift rota chart was not created after the fact, so the “Texas sharpshooter” argument falls over. Dr Evans reviewed all cases bar one were looked at “blind” months, before Letby’s name was disclosed to him.
Dr Evans says Cheshire police did not put together the shift graph until he had identified suspected cases. Only when officers cross-checked those events with staff on duty did the striking pattern of Letby’s presence emerge.
The rash
The argument that prosecution expert witnesses misdiagnosed a rash based on misreading Dr Shoo Lee’s 1989 report on the air embolism phenomenon. Dr Lee told Letby’s appeal he believed the rashes were not diagnostic of the condition.
But Dr Lee did not have access to the medical notes or witness statements when making this assessment and his evidence was ruled inadmissible.
The screaming
Hull describes “harrowing testimony of parents, doctors and nurses” of uncharacteristic “screaming” from several of the premature babies, who likely suffered extreme pain.
Letby, the Prosecution said, had rammed a medical instrument down the boy's throat moments earlier, causing internal bleeding. She later injected him with air to kill him.
Letby’s behaviour
On one occasion Letby told a colleague a baby “looked pale” when no lights were on in the nursery, and her face was obscured by a canopy. That child had stopped breathing but was resuscitated only to die by alleged air injection the next day.
The cards, googling and condolences.
Bayesian probabilities applied to other questions
As Tom Chivers notes in his excellent Everything Is Predictable: How Bayes’ Remarkable Theorem Explains the World, a fellow newly armed with Bayesian techniques is the proverbial “man with a hammer”: once you learn how to do it, it is hard to resist applying it to all kinds of questions not usually seen as the domain of statistics.
For example: miscarriages of justice are, as far as we know, extremely rare: those in the population of murder convicts across history — which surely numbers in the millions — who were justly convicted enormously outweigh those who were unjustly convicted, which we can put in the hundreds or thousands (Wikipedia lists just fifty-four). This might lead to the conclusion that a person who has been convicted by a jury is, ipso facto, highly unlikely to be innocent: that is, after all, the fundamental design goal of the justice system.
But the number convicted of “medical carer serial murders” in history is also small. According to Wikipedia, of nearly 800 serial killers fewer than 60 were medical carers, of whom two-thirds admitted their crimes. Serial murder is rare. Medical carer serial murder is even rarer.
But amongst Healthcare serial murder cases, miscarriages of justice are comparatively common. There are at least five recent examples, all strikingly similar:
- Lucia de Berk: A Dutch nurse wrongly convicted of multiple murders due to statistical errors and misinterpretation of medical evidence. Her conviction was later overturned.
- Susan Nelles: A Canadian nurse accused of murdering infants; charges were dropped due to lack of evidence.
- Ben Geen: A British nurse whose conviction for murdering patients by inducing respiratory arrests was quashed on appeal due to unreliable evidence.
- Colin Norris: A British nurse convicted of murdering patients by insulin injection; his conviction was later overturned due to flawed medical evidence.
- Daniela Poggiali: An Italian nurse accused of murdering patients in a hospital. She was initially convicted but later acquitted on appeal due to a lack of conclusive evidence.
- Jane Bolding: A British nurse accused of murdering patients in her care. She was acquitted after a retrial due to lack of evidence.
The relatively high proportion of miscarriages of justice among “hospital carer” cases raises the “posterior probability” that a given conviction of this type might be wrongful by comparison with other types of murder case where such errors are historically less common.
The multiple modus operandi
An unusual feature, compared with even other hospital carer serial killer cases is the variety of ways by which Letby is alleged to have murdered, or attempted to murder, the children.
- Insulin in intravenous bags
- Injection of air into bloodstream
- Injection of air into stomach via gastric tube
- Dislodging feeding tube
- Liver trauma
- Overfeeding by milk
Two points of significance here: first, serial killers generally develop and stick with a single modus operandi, refining a technique that “works” and avoids leaving evidence or allowing for detection. Leaving no evidence is hard. Second, the more different routes one uses, the more scope there is for evidence or detection.