Category: Covid-19

Vaccine roll out success, coupled with adherence to behavioural rules, has led to substantial declines of infections in the UK and Israel.  Increasing vaccine coverage in North America and Europe is seen also as the route back to normality.  Yet infectious disease epidemiologists are still worried about a third wave causing large numbers of severe cases.  Are they right to be worried?

Let’s start with the current success

• Excluding countries in the Far East and Australasia, globally most other countries have had substantial second peaks of infection
• I have plotted below the rates/million total population (including children) of new diagnosed infections in Israel and UK 

• The UK – with one of the most stringent and (probably) adhered to lockdown measures since the start of January – has seen a substantial fall in the rate of new cases.  Given that only around 10% of the population has had a second jab, then the decline in new cases is predominantly explained by the measures enforced
• Israel has a second jab rate of around 60% and epidemiological studies, examining the vaccination records of those who have become ill, by contrast, do point to vaccine roll out being the major explanation for the decline
• Indeed Israel began easing its lockdown rules in mid-February without seeing, so far, any rise in the rate of infection 

So what’s the worry?

• Worth repeating (and I have!), though obvious – if we all stayed at home then the infection would die out.  So whether the rates of new infection are going to remain controlled as lockdown is released depends on a number of factors
• I have illustrated these in the diagram below and will consider them all in turn

• The general point is that we need to consider a range of factors in order to achieve the elimination of the threat of Covid-19 

Vaccine effectiveness

• In terms of transmission we want the vaccines to stop people being able to pass on the infection those around them
• We know that the vaccines stop people getting ill, but it is still uncertain by how much the vaccines stop people transmitting the infection
• Here are some estimates from two epidemiology groups from the UK: Imperial College London and Warwick University
• ‘All infections’ includes those with and without symptoms 

• The rates of infection are following the second jab and assume no waning in immunity over time
• The assumption about waning immunity is probably reasonable over a short time frame, i.e. protection at least until the end of this year
• These figures are from the rolled out vaccination programmes rather than the earlier clinical trials and are estimates of the effects across all adult age groups 
• Pfizer probably stops 90% of transmissions and AstraZeneca around 60%
• A 60% reduction in transmission though is really good if the population rates of infection are low.  Conversely if the population rates of infection are high then, even with a 90% reduction, there is still scope for high numbers of new infections to be passed from vaccinated people

Vaccine coverage

• Thus far in Israel, UK and USA, the vaccine coverage has been higher than the pessimists feared
• Concerns about hazards and the roll out to younger populations less at-risk from severe infection might see a decline in take up, although restrictions on travel etc for those without a vaccine might encourage greater take up
• Based on different sources of data here are the projections (OK they are guesses!) of vaccine take up in the UK:

• Although these figures seem ‘very good’, as with the effectiveness data above, in periods of high infection even 10% of people who are not vaccinated could contribute to a large number of people being susceptible to infection

Speed of vaccine roll out

• Again obvious, but the longer it takes to vaccinate the population the greater the number of people who can transmit the infection
• This is because as mentioned above  vaccinated people, even with a pessimistic (AstraZeneca) protection, are 60% less likely to transmit the infection
• An interesting ethical issue is that younger people have more social contacts and currently in many countries contribute proportionately more cases of infection than older people
• Thus it could be argued that to prevent transmission alone, it might make some sense to focus vaccine efforts on those who are younger 
• Anecdotally this may be what is happening  in some countries in Eastern Europe

Seasonality

• As is well known, influenza pandemics tend to occur in winter
• Whether this is because in the summer there is reduced viral survival with the greater  sunlight and/or humidity, or we spend less time outdoors, is unknown
• The concern from some epidemiologists is that the decline observed now in countries such as the UK may represent a seasonal decline and that come winter there will be a bounce back 
• This is the effect of season from the Warwick and Imperial guesses

• These are not large differences but could tip the balance
• This underlines the importance of achieving high vaccine coverage before the autumn

Impact of new variants

• It is now well known that the current major variant in UK, USA, Israel and indeed the rest of Europe is the so-called English variant
• This variant does spread more easily
• The South African variant also spreads even more easily, but it seems that high rates of the English variant seem to reduce the South African (or indeed the Brazilian) variants from taking a major hold
• The epidemiologists have in their scenario planning assumed that no new nastier variant will take hold – this is probably reasonable but cannot be relied on absolutely

Social Behaviours 

• Clearly a return to normal social interchange increases the chances of transmission
• It was believed at the start of the pandemic that the natural R value, i.e. the average number of cases caused by one person passing it on to others, is around 2.5
• Countries with their various lockdowns are achieving rates of say between 0.8 and 1.5
• R values have to be considered against how many cases there are of course, but the worry is that releasing the brakes given all the other issues mentioned above could lead to a greater number of new transmissions.

Putting it altogether

• Complicated isn’t it!!
• This is just one model from Warwick attempting to predict the number of cases hospitalised in a third wave this summer: 

• To be honest they’ve brought so much together in that graph that I’m not going to even try and explain it all ! But there is an important message here
• The red line has allowed for all the things I have mentioned above (they call it the ‘central assumption’)
• An increase in R because of any of the issues mentioned would have major effects on the numbers of severe cases (in this graph shown as the how many beds in hospitals in the UK are occupied by Covid-19 patients) 
• We can’t easily change the effectiveness of the vaccines (they are pretty good), the seasonal impact or the possibility of new variants
• By contrast, we can ensure maximum and speedy vaccine coverage
• More importantly, it will be necessary to keep tabs on all the above, to ensure that any return to ‘normality’ is carefully monitored

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In my post earlier today, I stated that “it is possible that the risks of cerebral venous sinus thrombosis in younger women are greater than the risks from Covid-19 infection”.  This afternoon, the regulator in the UK announced the results of their detailed calculation addressing this question.  

This is the result of their calculation and I have adapted their slide for this post

• This is how they did their calculation
• First they obtained the current rate of new Covid-19 infections in the population.
• They then identified how likely it was that someone with a new infection would be admitted to an intensive care unit (ICU)
• They analysed these data by age
• They then calculated how many people per 100,000 in each 10 year age group would be admitted to an ICU in a 16 week period  at that rate of infection
• These rates (the blue boxes) were very low for those age under 30 at less than 1/100,000,  but were much higher for those aged 60-69 at 14/100,000
• They then calculated what the rates of serious harms would be in those who were vaccinated based on the numbers and ages of the cases reported to date
• They then estimated how many people per 100,000 who had been vaccinated with one dose would have a serious clotting problem
• They estimated these rates separately for each 10 year age group would
• The rates of vaccine problems were highest – at 1/100,000 in those under 30 and lowest at 0.2/100,000 in those 60-69
• Putting all this together the conclusion is that
  • In those aged 20-29, the risks from the virus and those from the vaccine were similar
  • In those aged 60-69, the risks from the virus were 70 times (ie 14.1 divided by 0.2) higher than those from the vaccine
• In most other European countries the rate of infection is much higher than in the UK
• The higher the rate of infection and the more the number of people get infected then more get admitted to ICU, whereas the risks from the vaccine remain the same
• The consequence is that as the incidence of infection rises, (it is obvious really), the benefits from the vaccine relative to the harms becomes more favourable 

My conclusion:

• Given the low rates of current infection in the UK it makes sense to use alternative vaccines in those aged under 30
• The European Medicines Agency has not issued the same advice, they may do so of course in the near future, but with the higher infection rates in EU countries, the benefits from the vaccine are still present for all age groups 

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In my post on March 16, I considered the evolving information on rare blood clotting events in relation to the AstraZeneca vaccine.  I concluded that the risk of pulmonary embolism, although higher with the AstraZeneca than the Pfizer vaccine, was no higher than that in the general population.  Attention recently has focused on the rarer brain clotting disorder: cerebral venous sinus thrombosis. More cases of this disorder have been reported in the past few weeks and in this post I review the new data and discuss the link to the AstraZeneca vaccine and the nature of any risk.

How many cases of cerebral venous sinus thrombosis (CVST) have there been following vaccination?

• Obviously the numbers are changing and different reports give different numbers
• Credible rates of CVST in UK and the rest of Europe are as follows:
  • 62 cases have been reported in the European Union from around 9 million vaccinated
  • Half of these were reported in Germany from around 3.4 million vaccinated
  • 79 cases have been reported in the UK from around 20 million vaccinated
• The numbers of cases are higher in younger people (aged under 50)
• Approximately a third of those with CVST have died
• I have not been able to find any reports of this disorder following the Pfizer or Moderna vaccines 

What is the exact nature of this brain disorder?

• The disorder reported in people following the AstraZeneca vaccine is an unusual one – it is actually combination of two separate disorders

• The second abnormality seen in the CVST patients following vaccination is the development of antibodies against their own platelets
  • There are a number of other causes of having low platelets, for example it can be a complication of some prescribed drugs
  • We need enough platelets to help us clot normally and stop bleeding
  • Having a low platelet count is actually quite common and indeed it is known that many cases are due to people developing antibodies against their own platelets – although this is normally an easily treated disorder
  • What is weird about the loss of platelets in the post-vaccine patients is that, instead of increasing the risk of bleeding, it increases the risk of clotting

How common is this combination in the general population?

The combination of a low platelet count and CVST is so rare we do not know how common this combination is in the general population

If we look at the two parts separately:

1. CVST

• CVST is very rare and accurate figures of the incidence are difficult to obtain
  • My reading suggests that a rate of 2-4/million per year is a reasonable estimate
  • Most cases of CVST in the population are due to infection

2. Low platelet count and increased risk of clotting:

• The overall incidence of a low platelet count with thrombosis (which has been reported in many different blood vessels – both arteries and veins)  is also around 2/million/year
  • It is mainly seen in people aged under 45
  • Most cases have occurred as a strange reaction to the anticoagulant injection heparin
  • In such cases, there is also both a low platelet count and a blood clot – the latter can be in either an artery or a vein
• The combination seems very rare
• This headline from an article published in January last year showed the disorder is so unusual that the existence of a single case is enough for it to warrant publication in the medical press

Do these data prove that there is a link?

• Proving cause and effect is almost impossible with such a rare disorder
• It is also difficult to compare the numbers in the short period after being vaccinated with general population rates that are calculated over a year
• I think that the chances of these cases being random is small and that the points below all point to the link being causal:
  • the number of cases
  • the timing in relation to the vaccine
  • the immune nature of the likely cause
• Unlike the situation I discussed a few weeks ago in relation to pulmonary embolism, where the data did not prove the rate of that disorder post-vaccine was greater than the underlying risk, my take on CVST is that all cases need to be considered as a consequence of the AstraZeneca vaccine 

What then is the risk of CVST in people who have had the vaccine?

• The question then is not “is there an increased risk of CVST compared to ‘normal’?” but rather
  • “what is the size of the risk?”
  • “does this risk vary in particular sub-groups of the population?”
• From the available information, which is limited, the German data suggests an incidence of around 1/100,000 vaccinated 
• The UK data suggests a lower rate of around 1/250,000
• BUT although I have not seen a detailed breakdown by age and gender, about 2/3 of the cases of CVST are reported to be in women and more in those under the age of 55
• Given that most of the vaccine programmes have been focussed above the age of 50, the overall rates of CVST in younger women could be even higher

Could this problem have been identified earlier?

• I cannot see how this could have been foreseen
• I am not aware of any other vaccines that have been linked to this complication
• Even if the incidence is as frequent as 1/100,000, then the clinical trials of the vaccines, which studied around 30,000 subjects, would have been too small to detect any cases

How does this risk compare with risks of other rare severe medical events?

• In thinking about a risk that say lies between 1/100,000 and 1/250,000, a frame of reference is the risk of other severe medical events in previously healthy people 
• I have taken two comparisons:
  • Deaths in pregnancy and childbirth
  • Deaths and severe complications from having an anaesthetic in people with no prior health problems 
• The results are shown below:

• The results show that for these two comparators, which most would consider non-risky (getting pregnant or having an elective operation), the rates of CVST – even taking the most pessimistic (German) data – are lower

What can happen now?

• More intensive analysis of the cases of CVST that have happened will quantify a more accurate risk in the different age and gender groups 
• The risk of dying or having a serious complication from contracting Covid-19 in younger people is small (and indeed women do not have as many  serious complications as men) 
• Thus it is possible that the risks of CVST in younger women are greater than the risks from Covid-19 infection 
• My view is that regulators should be open and accept:
  • that it is highly probable there is a link
  • the issue has only come to light because of the many millions who have been vaccinated
  • the absolute risk to those most at risk of the serious consequences from Covid-19 is far greater than the risk of CVST from the AstraZeneca vaccine; the same may not be true for younger people
• I have to accept that regulators’ views on ‘who to vaccinate and with what’ may need to change to allow public confidence 

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STOP PRESS:

• Since posting this at 12:30 UK time today, the UK regulator has just announced that people aged under 30 will be offered another vaccine to the AstraZeneca
• I provide details of the data behind this decision in a new post https://makingsenseofcovid19withs.com/2021/04/07/new-calculation-risks-from-astrazeneca-vaccine-exceed-benefits-in-people-under-30/

• This is a sensible move both from an epidemiological perspective and reducing vaccine hesitancy in those at lower risk from the effects of Covid-19.

Two recent  studies, one from the UK and the other  from Denmark, have addressed the question as to how likely is it that having been infected with Covid-19 once, you can catch it again.  The hope is that a previous infection would give sufficient immunity to protect against a second infection.  How far is this the case?

What did we know before these studies?

• If infected with Covid-19, most people will develop some immunity 
• The level of the immunity has been measured by the level of antibodies produced
• Immunity might be less strong:
  • In those who had a very mild infection
  • (Rarely) in those who had a very severe infection (which paradoxically dampens the effectiveness of the immune system)
• But we know the level of antibodies:
  • Is not the same in everyone who has been infected and is lower, for example, in older people
  • Does tend to fall over time following the infection and may even disappear within 6 months 
•  But we also know that when faced with another infection
  • Previous low levels of antibodies (even if they’ve fallen to zero) can rise again in response to a new infection
  • Antibodies are not the only defence we have: there are our T cells as well
  • As explained before in this blog*, when faced with a second infection, our T cells can also be woken up and attack and destroy the virus

What we didn’t know?

• Despite the data about antibodies, we didn’t know for certain if they would be enough
• Indeed, even if our level of antibody response after a first infection was not that high, the only important statistic is how much less likely is it that they would prevent us getting a second infection 

What about the new variants? 

• We do know, for example, that the Brazilian variant is not such a great respecter of antibodies from a previous infection as we would like.
• The new UK (Kent) variant though, which is the main variant in much of the world currently, should be covered by previous antibodies; although the UK variant passes more easily from person to person than the original strains
• Thus, there is no reason to believe that there would be any difference in the protection resulting from a previous infection – whether this was the original or the new UK strain

Why answering the question about re-infection is not that easy?

• The obvious question is (as my title suggests): “I have had Covid-19 once, how likely will I get it again?”
• It is obvious that the answer is that reinfection:
  • is not “impossible” 
  • and must be related to how many people around you have the infection
  • and how careful you are
  • and if you’ve had the vaccine
  • and how successful the vaccine is
• The question we now have some answer to is:

• The answer has therefore required some careful monitoring of large populations to make those comparisons; in the UK we have ad the Siren study

• Let me help in interpreting this graph!
  • Look at the dashed line, this is what happened to those workers who had not had any infection first time round
  • By the end of the next 6 months, around 5% of them had evidence of a new infection
  • Now look at the continuous line, which is what happened to the workers who had a previous infection
  • By the end of the next 6 months only around 1% of them had evidence of a new infection
  • This is a reduction of 80%
• Of course, we don’t know if the two groups had the same exposure to new infections they were all continuing their roles  in the NHS
  • Perhaps those with a previous infection were more careful, hence their lower rate
  • Equally, they may have been less careful, thinking that they were less at risk because of their immunity
• The conclusion was that previous infection did not take away the risk of a second infection completely but did reduce it (as expected) by a large amount up to 6 months later

The Danish Study

• This was a very similar study 
• The headline result was identical: an 80% reduction in the risk of a second infection 

• The study also showed that the relative size of this  reduction did not go down with time:

• The result thus suggests our immunity can burst back into action
• What was a bit worrying, but not entirely unexpected, was the protection from a previous infection was less in those aged over 65
  • The elderly with a previous infection had a much lower rate of protection  against a second infection compared to those younger age groups  

What does 80% protection mean?

• It is probably worth saying that the absolute risk of having a second infection will still depend on how common the infection is in the general population 
• Look at this diagram below, which shows how likely it is someone with a previous infection will get an infection in a second (or say third) wave*
• The different sizes of the pies illustrate the overall number of cases occurring depending on how widespread the infection is
• The orange slice shows that the number of people with a second infection will vary depending on how widespread the virus is
• Although the absolute numbers in the orange slice vary accordingly, their proportion remains the same

What’s the impact of vaccination on interpreting these results?

• Firstly, across all ages a previous infection does not give complete protection against a second infection
• Next, that is more true for people aged over 65, reinforcing the need to have the jab even if you have had a previous infection
• We know that vaccines work, giving at least 80% protection in those over 65, much higher in those who are younger.
• I conclude that vaccines do then give a higher level of protection than natural infection
• What we don’t know is whether a previous infection plus being vaccinated gives more protection than just being vaccinated – I suspect not, but let’s see as the results come in over the next few months 

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The last week has seen headlines across the world concerning both the supply and uptake of vaccines.  The AstraZeneca vaccine has been the subject of twin concerns: not enough is being produced and – in some countries – hesitancy in accepting this (or indeed any other) vaccine.  Aside from worries about exceptionally rare health hazards, the hesitancy in large part reflects anxieties about the high prevalence of short term side effects and questions about the benefits in the face of new variants.  In this post I look into the very near future and review how some exciting new approaches to vaccines could address many of the issues of supply, side effects and indeed efficacy.

What are the plusses and minuses of vaccines given by injection?

• The short answer is that by injecting into muscle – with its good blood supply – the vaccine can rapidly be recognised by the immune system which can then start producing its response
• Vaccines given by mouth or inhaled have to combat the body’s immediate defence mechanisms which are designed to protect us against the effects of infecting organisms in  what we eat or breath in – which then turn against the vaccines 

There are a lot of minuses with injectable vaccines summarised in the Table below:

Before Covid-19 what vaccines were given without injection?

1. By Mouth

2. By inhalation

What about oral vaccines for Covid-19?  

• The second was announced yesterday between an Israeli Biotech company (Oramed) and the Indian pharmaceutical company (Premas) to develop a capsule for oral immunization against Covid-19 
• Despite the press release, given the above it was not a world first!

• What do we know about this vaccine
  • So far only tested in animals
  • In a single dose gave excellent antibody response
  • Active against multiple parts of the CoVid-19 virus (not just the spike protein) and could protect against mutations
  • A clinical study of 35 people completed recruitment in December and we await the results (though I gather that the antibody response may not be as good as the T cell response) 
  • My guess is though that the results are looking sufficiently good hence the announcement of the Israel/India tie up two days ago

My conclusion about oral vaccines?

• Theoretically it should be possible to achieve sufficient immunity with an oral capsule.  
• We should have a first  answer about how effective this will be in real life in say a couple of months and could possibly be available by the end of the year 

What about inhaled vaccines for Covid-a9?

• Like with the oral vaccines there are two approaches that are being tried
• The first is a version of the AstraZeneca vaccine and works in the same way (spike protein bolted onto a harmless virus)
• This has only been tried in Macaque monkeys so far but did prove to produce a strong immune response
• Infected  monkeys also had a rapid loss of the virus 
• Testing in humans is awaited  

• The second is a different type of vaccine to all the other Covid-19 vaccines 
• It is based on a weakened form of the Covid-19 virus, indeed like many conventional vaccines for non-Covid disorders 
• Because of this  it will create an immune response against all the bits of the virus and thus be more resilient to new variants

My conclusion?

• The inhaled version of the AstraZeneca approach looks OK so far and should be safe
• Obviously early days but using a weakened form of the virus seems to me to be a risk that it could mutate.

Making your own vaccine at home!

• Is this Star Wars or a genuine possibility?
• The essence is to use 3D printing (also called additive manufacture)
• For those of you not familiar with this amazing technological advance very briefly the steps are:
  • Develop a computer programme to build anything you want from basic ingredients
  • Allow the programme to access those ingredients and then the technology will physically make the desired object
  • The software can be downloaded and the object ‘printed’ locally
• Although it is mainly used to build inanimate objects such as car parts, it has been used to create artificial bits of human tissue like skin, bone etc
• The big advantage of the system is that the clever bit (the software) can be remote and provided you have the ingredients locally you can then make whatever you want where you want
• The guy in the picture printed his own virus!

• In theory therefore adopting the same approach one can 3D print a vaccine 
• This is most useful for mRNA vaccines (like Pfizer’s) and a company CureVac is working on this

• If it works then it could be of enormous benefit for vaccine supply and distribution especially to poorer parts of the world

My conclusion?

• I won’t dismiss the concept
• Certainly 3D printing is being used to produce vaccine administration systems (like very fine needles) which could reduce the amount of vaccine required 

Final words

• The pace of even more novel vaccine development globally has been breath-taking over the past 12 months. 
• We will need such advances to enhance vaccine production, vaccine acceptance and resilience to mutations

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My headline conclusion from yesterday’s post was that, compared to the general population, there was no increased risk of pulmonary embolism following the AstraZeneca vaccine: indeed, the published general population rate was about 6 times that following the AstraZeneca vaccine. More than one reader has commented that far from showing that the vaccine increased the risk of embolism, the reverse seemed to be the case and that the vaccine gave substantial protection against this disorder.  I do not believe protection is a logical conclusion and in this post I will explain why the data are problematic. 

Is there any plausibility that vaccines are protective?

• The short answer – it does not make sense that vaccines provide short term protection against the occurrence of embolism  
  • Vaccines do not have any anticoagulant properties that would provide the protection
  • Vaccines do not have anything that would protect the walls of veins from clots
• If the above are true, then what are the explanations for what would appear to be a false suggestion of a level of protection?
• Thinking about the calculation I posted; there are number of possible sources of error inherent in the available data

1. Was the quoted background population rate of pulmonary embolism inaccurate?

• I quoted the figure of 8/10,000 (800/million) provided in a  UK official guidance document on the prevention of this disorder*
• The accuracy of this  figure is reinforced by other data I have examined**
• Thus the estimate is as good as we can have

*https://www.nice.org.uk/guidance/ta287/documents/pulmonary-embolism-acute-treatment-vte-prevention-rivaroxaban-appendix-b-final-scope **https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3718593/ 

2. What is the correct time interval following vaccination that should be considered relevant in counting a pulmonary embolism?

• I made a guess at one month, to allow time for a clot to have developed in the legs and then pass to the lungs
• From the publicly available data on AstraZeneca’s embolism cases though we don’t know the interval between vaccine and diagnosis
• If all occurred within a week then the apparent reduction in incidence is only 1.5 times, compared to 6 times, background risk by allowing 4 weeks for cases to be included

3. Could there be under-reporting of the  number of cases of pulmonary embolism following vaccination?

• The short answer is yes, but we ‘don’t know what we don’t know’
• I would have expected that something serious like pulmonary embolism occurring within a short time after vaccination would have been reported
• We might expect because of the publicity more cases will be reported in the future

4. Is like being compared with like?

• The regulators like the European Medicines Agency will have done a similar task to my own calculation
• Essentially two separate rates are being compared though the data are gathered in very different ways

• Perhaps the biggest difference is how pulmonary embolism is diagnosed
  • The general population cases will include the hospital cases that will have been picked up incidentally, for example as an unexpected finding on an X-ray 
  • By contrast, cases of pulmonary embolism following vaccines, would not have been detected if they had been mild, with only minor symptoms
• As mentioned yesterday many cases of pulmonary embolism occur as a complication of surgery and it is not easily possible to identify the rate of ‘underlying natural cases’
• Probably not a major issue, but any analysis needs to take account of age, gender and other factors such as ethnicity which might affect the overall rates 

Conclusion

• I do not think it is likely that any of the vaccines protect against pulmonary embolism – though calculations based on the limited available data could give that misleading impression
• There are many ways in which feeding the limitations of the available data into these calculations could distort the results 
• These comments only refer to the data on pulmonary embolism and do not address the other concern about thrombosis in the veins in the brain
• None of the above explain what appears to be lower rates of embolism from the Pfizer vaccine 

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News internationally has been dominated in the past two days by a string of European countries pausing their use of the AstraZeneca vaccine, due to reports of a possible increased risk of blood clots.  European regulators are not concerned, citing that the rates of these disorders just reflect the background population rates.  I have taken a deeper look at the figures and the issue is perhaps more complex than we are led to believe. 

What are the new data that have filled the news?

• The new data come from reports received both from companies and national drug safety agencies* on the numbers of cases with one of the above disorders
• What especially precipitated the current concern seems to have been:
  • 7 reported cases of ‘cavernous sinus thrombosis’ in 1.5 million Germans given the AstraZeneca vaccine
  • 4 cases in Norway of clotting problems, although 3 of these were too little clotting due to thrombocytopenia
• In response to this news AstraZeneca said they were aware from their data of about 40 cases of clotting problems:
  • 15 deep vein thromboses
  • 22 pulmonary embolisms
  • (they haven’t publicly mentioned thrombocytopenia)

*I did discuss in a previous post how these data are obtained
https://makingsenseofcovid19withs.com/2020/12/04/how-will-we-know-about-long-term-side-effects-of-vaccines-learnings-from-thalidomide-swine-flu-and-donald-rumsfeld/

What information regulators need to collect when checking such reports

• Before reaching any conclusions on the numbers, the quality of the diagnoses in the cases reported have to be checked
• These case reports to regulators come from many sources and diagnostic accuracy cannot be assumed 
• Companies and regulators would thus seek the following confirmatory information from relevant health records 

• Information on the risk factors in the table above may be used to identify specific subgroups for whom a warning may be required

What did I find in the UK?

• I have reviewed the data published on the MHRA ( the UK regulator) website for reports of all clotting events up to the end of February
• I cannot find exactly how many doses of AstraZeneca vaccine had been administered  by the end of February but
  •  There had been 1.5 million doses by early February
  •  I therefore have guessed 3 million by end of February 
• I searched through the list of the 200,000 reported side effects to the AstraZeneca vaccine published on 9 March (most were trivial like arm soreness) for any mention of thrombosis or pulmonary embolism – 
• This is what I found

• There are also rarer reports on clots at other sites in the body
• I suspect AstraZeneca’s figure publicised yesterday of just 40 cases in total worldwide is an under-estimate
• I cannot emphasise enough times that these cases may, or may not be, related to the vaccine
• A rate of 4/million for pulmonary embolus is also a very low risk 

What about data from other vaccines? 

• I searched the same UK database for reports of the same disorders from the Pfizer vaccine
  • Similar data from other countries on their licensed vaccines are likely to become available 
• When the UK database was updated my estimate is that there had been  3 times the number of Pfizer doses given compared to AstraZeneca 
• The table below therefore adds the column for the Pfizer vaccine 

• I could find no reports of pulmonary embolism from the Pfizer vaccine
• Whatever the inaccuracies, the rates of all these reports are much greater for AstraZeneca than for Pfizer 
•  Combining all reports that mentioned a clotting problem, the rate/million vaccinated (orange bars) was five times that for AstraZeneca than for Pfizer vaccine
• I have also displayed the key results on a graph

What about the background population risk of these events

• As readers of my previous blogposts on the topic of vaccine safety may remember we have to compare the rates of reports of disorders, such as clotting, to the occurrence of these in the general population
• I must emphasise that accurate data on the occurrence of these conditions in the general population is not easy to find 
• There are no population registers, as there are for some disorders such as cancers
• So we are reliant for serious clotting problem such as pulmonary embolism  on the number of cases recorded from hospital databases
• The number of such cases from hospitals with DVT or pulmonary emboli can be misleading as a source of the underlying population rate:
• Why: because 60% of these disorders are  the result of being in hospital – especially following an operation!
• For what it is worth, given this bias, I have taken one report suggesting that 800/million in the UK are diagnosed with a pulmonary embolism each year*
• I have therefore attempted to do my own calculation on the true background population rate of pulmonary embolism 
• I am assuming that pulmonary embolism is likely to be reported as a possible side effect of vaccination within 4 weeks of the vaccine  
• So I have estimated the background monthly incidence of new cases 
• This is my calculation:

• This rate of 25/million is around 6.5 times the rate of embolism even in the AstraZeneca vaccinated cases 
• This might suggest that the AstraZeneca vaccine might even by protective. I think that is very unlikely and that we need to very cautious in interpreting such data
• I have given further commentary on this is a new post published today (17 March): https://makingsenseofcovid19withs.com/2021/03/17/could-vaccines-actually-protect-against-pulmonary-embolus/

*https://www.nice.org.uk/guidance/ta287/documents/pulmonary-embolism-acute-treatment-vte-prevention-rivaroxaban-appendix-b-final-scope2

Are patients with Covid-19 infection at risk of clots?

• If we are interested in the risks of clots following the vaccine we should also look at the risk of clots following the infection!
• We have known for some time that patients admitted to hospital with severe Covid-19 are at risk of having blood clots
• Indeed clots are one of the major reasons for serious complications following Covid-19
• Perhaps 30% of Covid-19 patients admitted to hospital either have direct evidence of a clot or their blood tests suggest they are at risk
• I can only find a very few reports of severe clotting problems from mild Covid-19, but in those patients too the consequences can be substantial

Is it biologically likely that the vaccine could cause blood clots?

• The story linking AstraZeneca vaccine would be compelling if there was a biological explanation
• There are coherent pathways of how natural Covid-19 infection can lead to clotting
  • These are mainly as a consequence of the body’s overactive immune response to the virus  damaging the walls of blood vessels
  • Other suggestions are that there is an increase of clotting proteins in the blood
• I guess it is just possible that in some people there is an overactive immune response to the vaccine which could have the same effect
• This is pure conjecture (!) but some people do have very severe responses to the vaccines and just possibly a small subset of these have the same potential for damage to the walls of blood vessels to increase the risk of clotting

Conclusion

• Honestly this is a difficult one!
• I accept, though allowing for all the possible inaccuracies, that the rate of events such as pulmonary embolism following the AstraZeneca vaccine is much lower than the expected rate in the general population 
• The data though, again with all their inaccuracies, suggest that rates of all these events of concern are greater with the AstraZeneca vaccine than with Pfizer- for reasons that are not easily explained
• It may be that with closer examination of the cases who have reported these problems will identify a group of people who may be at particular high risk of clotting and possibly should not have the AstraZeneca vaccine.  We should keep an open mind on this
• Let me finish by emphasising that the risks of having a serious clotting  problem are much higher from a bad attack of Covid-19 than from the vaccine

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As the concerns about the life-threatening risks from CoVid-19 are beginning to recede, so there is growing interest in the long-term effects following infection.  Whereas it might be expected that those who had suffered severe complications and been hospitalised would have continuing health issues, the concern now is that those with mild, or even asymptomatic, infection would have continuing symptoms over several months.  In this post I consider the evidence. 

Before Covid-19……

This banner headline from Medical News Today was from an article written in October 2019  just before the pandemic (how coincidental was that!)

• It acts as a reminder that following the recovery from the acute stage after any viral infection, a proportion of patients continue with symptoms, most specifically:
  • Fatigue
  • Lack of energy
  • ‘Brain fog’ 
• Post-viral fatigue/syndrome was a helpful term in describing this experience

• The relationship with a prior viral infection is not clear, as many suffer the same symptoms without evidence of a proven prior virus  – leading to the non-specific term chronic fatigue syndrome (CFS) *
• The proportion of people who have continuing symptoms, following flu for example,  does vary between reports – depending on how the cases were recruited – but there is no debate that the continuing fatigue can occur in some people and last for a long time
• A more potent viral infection causing long-term fatigue is glandular fever (infectious mononucleosis).  This infection has a predilection for young people and many students have had their university courses seriously affected by the long-term effects following this 

*I do not wish to get into the debate about the name ME – myalgic encephalomyelitis – just to say that I do not find it helpful as whilst the ‘myalgic’ bit, meaning muscle ache, may be descriptive, the ‘encephalomyelitis’ term is misleading – and should be reserved for the specific and severe acute brain infection, which is exceptionally rare in individuals with CFS 

Theories about the cause of post viral fatigue

• There are many theories and this post is not the place to discuss the hundreds of studies that have proposed or disproved various biological explanations
• Of relevance to Long CoVid is the observation in some studies that it is the body’s own immune system that goes into overdrive in some people, that explains the continuation of symptoms

What is Long CoVid?

• It is one thing to say that some people have continuing symptoms, it is another to have a definition that can be used as a label
• That’s important as it is impossible for example to compare between studies, or to consider who should have specific treatments, unless there is a common rule for saying ‘this is a case of Long CoVid’
• The problem is there is no simple agreed definition:
  • The UK’s: National Institute for Health and Clinical Excellence – NICE- came up with this scheme which separates out short-term and longer-term problems
  • How useful they are is debated and not agreed internationally

• At the moment therefore, rather than use Long CoVid as a term describing a specific focused disorder, it is used as an umbrella term to cover all the people with continuing problems
• Thus, the focus has been on attempting to identify how often this happens, what are the symptoms and who is at risk 

How often do symptoms persist?

• As mentioned at the beginning of this post, the key question for me is not about the continuation of symptoms in people who have been in hospital, but what happens to people in the community who have been tested positive
• I am going to give the results of the UK’s population survey (Office of National Statistics – ONS study) which followed up 9063 people between April and December last year, who had tested positive in their ongoing population surveys to find out if they were unwell at 5 and then 12 weeks after the positive test.
• They asked about 5 symptoms:
  • Fatigue
  • Cough
  • Headache
  • Loss of taste and smell
  • Muscle aches
• This what they found in terms of one or more of these  symptoms:

• A word of caution of course: these are common symptoms, even without the virus. Thus the people in the ONS survey who tested negative for CoVid-19 may have had the same symptoms but they were not followed up.
• The ZOE-Kings College App, used by millions in the UK and USA, has been tracking symptoms in people with and without CoVid-19 to provide a suitable comparison 
  • People were asked about symptoms 28 days after a positive test
  • A comparison group (same age, gender etc)  who never tested positive were asked about symptoms at a random time 
  • The CoVid positive group had 6 times the rate of these symptoms

Which specific symptoms persist?

• The ONS survey showed that most people who reported symptoms had 2 or 3 of the 5 symptoms above, with no single symptom being the more common

What are the risk factors?

• Role of gender
  • What is a little interesting from the data above is that the rates of reporting were slightly higher in women then in men 
  • Remember it is men who are more likely to be hospitalised from the CoVid
• Role of age
  • Older people were more likely to report continuing symptoms
  • Unlike the risk of life-threatening complications, the proportion with symptoms did not change that much across the adult age span
• Also note that children who test positive are not free of long term symptoms Indeed, children commonly report other long-term symptoms including:
  • Sore throats
  • Mood changes (I assume more than normal!)
  • Rashes

• There are other groups of people who are more at risk of Long CoVid.  These include those who:
  • Are obese
  • Have pre-existing conditions such as asthma
  • Have specific Covid-19 symptoms such as loss of sense of taste and smell

Does it all sound rather minor?

• At first glance the persistence of these symptoms may be considered, because they are not life threatening, as not too worrisome
• That of course underplays the impact on individuals of the persistence of feeling unwell
• There is another side to the Long CoVid story, which is the risk of new serious health problems
• Although it is difficult to put numbers on what are quite small risks, there are a number of serious late effects with CoVid-19 

• Many of the more serious consequences are thought to be due to blood clots and scarring of major organs including:
  • Lungs
  • Heart
  • Kidneys
  • Liver
  • Gut
  • Brain
• Plus some patients have reported the development of other diseases associated with the body’s immune system attacking itself
• Perhaps less expected is the possibility that CoVid-19 could lead to the development of diabetes

• Although many CoVid-19 patients with new diabetes are those who had been hospitalised with severe infection, this is not always the case
• I am going to be cautious again though in giving conclusions about these serious consequences – why?
  • The numbers for each of these complications are very small
  • Given the millions affected by CoVid-19, some of these severe problems might have arisen by chance, independent of the CoVid-19 
• But they should not, and are not, being ignored and more research is ongoing

Why CoVid-19 might be different from other viruses in its long-term complications?

• Having read thus far, you might feel that I have not made a case that there is an undoubted issue with Long CoVid that is different from the problems people report following flu
• The numbers of those with continuing disabling symptoms are higher – although the quality of data from other common viruses is poor
• I am however persuaded that this virus is different because of some special features that I have mentioned in previous blogposts
  • The virus locks onto a protein found on the surfaces of cells of many of our organs called the ACE receptor and this can explain why organs such as the lungs, kidneys and heart could be damaged
  • As part of the body’s response to this virus, the immune system does sometimes go into overdrive – indeed this unwanted response is the cause of many of the deaths of patients in intensive care units
  • This overdrive caused by the body producing too many nasty proteins called cytokines can damage the walls of our small blood vessels, which makes them more likely to allow clots to form

My take home message

• We need to think about the long-term consequences of CoVid-19 seriously
• There can be long-term symptoms even in those who had mild infections or even were asymptomatic
• The overwhelming majority do recover but a significant minority have continuing health challenges to their everyday life for some months
• This includes people of all ages including children
• It is difficult to put numbers on the level of these risks and serious long-term effects will still be the exception 
• The diabetes story is intriguing
• And my answer to my opening question: I think this is different from the issues seen in recovery from other viruses, especially flu 

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The rolling out of national vaccination programmes on their own will not completely eradicate the virus, because even the most successful vaccines cannot prevent some transmission.  Interest is now focusing on the possible role of ‘super-spreaders’ in maintaining the pandemic.  In this post I review some very recent data on what makes a super-spreader and what influence they might have on the future number of cases.

Apologies but I do have to mention R!

• As a concept R (more correctly referred to as R₀) _– the transmissibility of a viral infection – is helpful:  the greater it is, the more quickly an infection will spread 
• R is the average number of new cases infected from one existing case
• Here are the R  values for some common infections that, like Covid-19, are transmitted from person to person in the same ways:

• No surprises perhaps, although interestingly seasonal flu might have an R below 1, which is why even without social distancing a flu epidemic can die out 
• Note that these are the values in “normal times”, when there are no preventive measures in place (masks/distancing etc), but of course there will be a range of values depending on how much social contact there is between cases
• The common-sense conclusion is that these R values are helpful in comparing between viruses, but the precise values are wobbly at best

R  and Coronavirus infections

• In this pandemic there has been a considerable focus on how transmissible the infection is, for good reasons
• One major reason is that unlike the infections above, there was no prior disease-acquired or vaccine-induced immunity, so the infection could spread at its ‘natural’ rate
• So what is our estimate of the ‘natural’ value of R?  In this table I have compiled experts’ best estimates and have compared these with estimates for the other major SARS pandemics and also for the most recent variants 

• Thus Covid-19 is very similar to the other coronaviruses
• It is interesting, though, to see how small changes in R can have a major influence on the rate of cases
• In the figure below, as an example, I used the estimate that in the UK, by the time we got round to doing anything serious about controlling the spread, there were 30,000 cases dotted around the country
• (for non-UK readers the principles are identical!)
• I have made a series of assumptions about the period of infectivity, but I have calculated the speed of growth/decline for various values of R₀ from a high of 2.5 to a low of 0.7, over a 12 month period
• The red dotted line is for R of 1, so the number of cases (in this example 30,000) stays the same over the year

• The graph clearly shows that with an R value of 2.5, after 6 months the original 30,000 cases would grow to around 10 million
• Similarly, with an R value of 0.9, even after 12 months there would still be around 8000 cases: enough to cause problems
• Getting R to 0.7 though could eliminate the infection (from my calculations!) in 7 months
• If the R value was indeed  as high as 3.6, or we needed to allow for greater transmissibility of the new variants, then the growth would be even greater

How do super-spreaders change the picture?

• An R value is an average and would conceal the fact that some people spread to no-one and others to several 
• There have been some infamous cases, most notably a Santa Claus visit to an old people’s home in Belgium delivered more than they were expecting!

• This is not an isolated incident but one that, given the circumstances, was easy to track down
• How much do super-spreaders contribute to the overall number of cases in a population?
• There has been an interesting analysis from China, which charted the paths by which individual cases in 8 areas caught the infection
• This is best illustrated in the figure below:
  • In very simple terms, the dots with no lines show cases with no spread, whereas there are some cases who pass on to several others (eg shown by the red arrow)
  • The bar graph shows what proportion of cases passed the infection on to one or more others
  • 80% of cases spread to nobody else
  • Thus just 20% of cases are responsible for the spread of the virus 
  • This highlights the need to consider the role of super-spreaders 

What makes a super-spreader?

• One question is whether it is there are differences in the virus in people who are super-spreaders
• The short answer is – very unlikely
• For sure some new variants show greater powers of transmissibility (see Table above) but:
  • There are super-spreaders with none of the variants
  • The increase in R is modest (less than 1.0)
  • The thought is that people infected with these variants transmit more virus because the mutations allow the virus to replicate more easily and thus infected people breathe out more virus
• Thus, the answer to ‘why super-spreaders’ must lie within the person.  What are the options?
• Super-spreaders have more social contacts
  • This is unlikely and did not explain the super-spreading events which had been traced to specific individuals 
• Super-spreaders generally breathe out more stuff
  • Unlikely as it sounds, this actually may be true
  • We know from experiments that different activities such as singing, shouting etc are associated with breathing out more virus in those who are infected
  • What appears to be the case is that there are some individuals who normally (ie when not infected) breathe out more droplets (which in an infected person could contain the virus)
  • Look at this data from a non-per-reviewed publication of 2 weeks ago
  • In this study 74 volunteers had their breath examined for the number of droplets they breathed out

• This shows dramatically that there are 1000-fold differences between normal people in the amount of droplets that they breathe out
• Is there anything different about people who breathe out more droplets?
  • The same study showed that older people breathe out much more than younger people
  • (This might explain the lower transmissibility in children)
  • People who are more obese breathe out more droplets than leaner folk
  • Adding age and obesity together, as these researchers in the USA did, showed that indeed super-spreaders 
    • did breathe out more droplets and
    • were much more likely to be older and fatter
  • This is illustrated in the graph below 

Conclusions

• Even with the current reduction in transmissibility (as a consequence of the lockdowns in different countries), the infection will still take several months to essentially stop being a public health problem 
• Super-spreaders could make an important dent in the success rate
• These preliminary results suggest that it would be helpful for efforts encouraging mask-wearing to focus on those most at risk of exhaling large amounts of droplets
• It would be a shame to constrain the obvious success of the vaccines in substantially reducing the severity of Covid-19 by not considering this issue

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The number one question that people in the UK when chatting to each other in the past few weeks is “Which vaccine did you have?”!

Yesterday (22^nd February) the Scottish Government published preliminary data from their first 1.1 million people who had been enrolled in the national vaccine roll out programme.  This programme, like the rest of the UK, involved using both the Pfizer and AstraZeneca vaccines.  These data are the first real world information on whether there are any differences between the success rates from these 2 vaccines. 

What did we know before this Scottish Study

• Both vaccines target the spike protein of the virus
• They do this in slightly different ways*:
  • Pfizer by providing the genetic instructions – mRNA – to make the spike protein 
  • AstraZeneca by providing an earlier stage of the same genetic instructions which are bolted onto to a harmless virus to then make the spike protein
• By targeting the same spike protein, indeed the same genetic version of the spike protein, in theory both vaccines should be equally successful
• The key clinical trials before the vaccines were licensed however showed that
  • Pfizer gave 95% protection against being ill with 2 doses 3 weeks apart
  • AstraZeneca gave a lower protection but this could reach 85% with 2 doses 3 months apart

*See post: https://makingsenseofcovid19withs.com/2020/11/22/how-do-dna-and-rna-vaccines-work/

Other challenging news for AstraZeneca 

• These headline differences in the results between these trials seemed to suggest that Pfizer might be superior 
• It is not possible to compare the results of two trials done in different populations at different times – why not?
  • Because the overall background infection risk may have been different in the volunteers in the trials
  • The way that the 2 studies were designed meant that they had different ways of identifying the cases of Covid-19 that emerged during the follow up
• Nonetheless further support for Pfizer’s success came from the results from Moderna vaccine – an almost identical vaccine to the Pfizer – which produced the same very impressive reduction  
• AstraZeneca also had not included many elderly people (aged over 65) in their trial, and this lack of data – in the population most at risk of serious consequences from the infection – raised concerns that the AstraZeneca vaccine might not be effective in older people
• On the back of that concern, many European countries in high profile declarations, suggested they would not be using the AstraZeneca vaccine

• Further, recent data from a study in young South Africans showed the AstraZeneca vaccine did not reduce mild to moderate infection: the trial was abandoned and the South African government threatened to return their supply of the AstraZeneca vaccine
• This concern was fuelled by the emergence of the new South African variant, which was responsible for the cases in that study

• The UK is currently the only country routinely using both the Pfizer and AstraZeneca vaccines in any number
• In all 4 nations of the UK, who receives which vaccine is determined by logistics issues and vaccine availability and patients have no choice 
• (For interest my wife and I had our first doses just 3 days apart at the same centre, she had Pfizer, I had AstraZeneca!)
• Thus, the first data on the relative success of these two vaccines is of substantial interest as many people in the UK ask – although they have no choice – ‘which should I have?’

The Scottish Study published yesterday

• As with all these studies, although this is a publication from the government agency – Public Health Scotland (PHS) – it has not been peer reviewed and we should treat the results as preliminary
• To be honest, the report I have seen is not well written and I have a number of questions about the data. I accept that their headline results are probably accurate.
• The question they asked was a simple one:“How much do the vaccines reduce the risk of being admitted to hospital with Covid-19”
• Unlike the recently published preliminary studies from Israel, this study was based on a stronger epidemiological approach
  • They studied data from the entire Scottish population
  • They linked these 3 national databases

• It is having access to the whole population that makes this study so powerful
• This is how they analysed their data

• Their access to general practice data allowed them to identify individuals who had, and who had not, been vaccinated – the dark green boxes
• They identified all people who had been in hospital with Covid-19, but only included those cases who had a positive PCR test – the light green boxes
• They then compared the rates of being admitted between people who had and had not been vaccinated – the red and purple bordered light green boxes
• The most impressive part of their study was that having access to these data, especially the computerised primary care records, they were able to account for the fact that people who were vaccinated may be different from those who were not vaccinated in these ways:
  • Age
  • Gender
  • The area where they lived in terms of deprivation 
  • Their background health disorders
• Plus they were able to allow in part for the fact that those who were vaccinated were more likely to be health or care workers and hence more exposed to becoming infected 

• They then determined the success of the vaccine programme by working out how far fewer were the number of cases who had been vaccinated compared to the non-vaccinated
  • They compared the numbers in the red bordered boxes with those in the purple bordered boxes
  • Thus, if there were only half the risk of PCR positive hospitalised cases in the vaccinated group to that in the vaccinated group, this was a vaccine efficacy of 50%
• In doing these calculations they took into account the other differences between the 2 vaccine groups listed above (eg age etc)
• As the research assumed vaccine efficacy would increase with the more days after the first dose, they compared the efficacy of the vaccines at the different time periods
• All the data refer to the success of the vaccine in terms of days after the first dose
• This is what they found

• Compared to those who had not been vaccinated,  there was a reduction of around 40% in those who had Pfizer and 70% in those who had had AstraZeneca in the second week (7-13 days) after the first dose
• By 5 weeks (28-34 days) both vaccines were increasingly effective at reducing the number of cases – by over 85% in those who had the Pfizer and 94% in those who had the AstraZeneca 

Cautions

• As mentioned above, these are preliminary data and have not been peer reviewed
• Both vaccines, as everyone knows, are designed to be given as 2 doses, but that will only increase their success
• The data refer to hospitalised cases only and may not reflect how the vaccines work at preventing mild or asymptomatic infection

But on the positive side:

• Two thirds of those vaccinated were over 65 and almost 20% over 80, so answering the question about success in the elderly
• Most cases were of the new ‘English’ variant* whereas the trial data were collected before this variant was widespread
• Who got which vaccine was likely to be random, as this was determined by the logistics of the vaccination programme
• They could take into account the background differences in risk of severe Covid-19 between those in Scotland who had or had not been vaccinated by the time of this analysis

*There are too few cases so far of the other variants for any of the vaccines to provide robust data

Conclusion:

At this stage there is strong reassurance that the two vaccines are both very effective at preventing serious infection after one dose and no suggestion that the AstraZeneca vaccine is any less effective

As many readers might be aware I work at Oxford University but trust this has not coloured my judgement as to the relative value of the different vaccines!

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