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Collaboration, cardiology, and COVID-19: An interview with Anoop Shah

Dr Anoop Shah recently joined CGCC as Deputy Director. Born in Nairobi, raised in Kenya, now based in Scotland working as a cardiologist and researcher (with a PhD in Cardiovascular Epidemiology and MSc in Public Health under his belt), Anoop has been an energising addition to the team. His most recent publication provides the first empirical evidence that vaccinating healthcare workers at high risk of COVID-19 reduces risk to their household members. We caught up with him to find out more...
Anoop Shah completing zoom interview. He's sat on a computer chair wearing dark clothes and headphones.

Q: OK, so firstly, can you summarise in one sentence?

Vaccinating health care workers who generally work in a field that is at a high risk of exposure to COVID-19, was associated with a reduced risk in their household members for COVID-19.

Q: Let's start with your background - how did you come to be involved in this particular work?

So actually, my expertise is not in infectious disease and certainly not COVID- 19. I'm actually a clinical cardiologist and I did my PhD in epidemiology. However, my entire previous work was predominately based on large scale data science, using national administrative datasets in Scotland – a envious research and clinical resource in Scotland.

When COVID-19 hit the infrastructure was already there to link large scale datasets from vaccinations, admissions, and COVID-19 mortality and morbidity.

And that data science element with clinical epidemiology and a bit of clinical medicine effectively put us in a position to be able to answer these questions.

Q: This was an observational study? Can you briefly explain what that means?

This is an interesting question, actually. Usually, we think of explaining observational studies in technical terms. And I was thinking, ‘what does it mean in simple terms?’.

Well, as the name suggests, you're observing something rather than manipulating something. If you compare it to a clinical trial where you either give a medicine or intervene with some kind of treatment, that treatment, or the actual act of giving medicine, is under the control of the researcher. Whereas in an observational study, it's not. That treatment or that intervention is happening anyway. And you’re just looking from the top above, observing what the impact of that is going to be on the public or on that population where that treatment or intervention is being administered to.

Q: So where exactly did the data come from for this study?

Scotland holds a very, very comprehensive national administrative dataset infrastructure from multiple sources. These include microbiology datasets including COVID-19 tests, patient prescriptions, what patients present with in hospital and why, and the cause of death for the patients who don't survive.

We used this comprehensive infrastructure that's already present. Our study involved linking all these datasets to healthcare workers who were vaccinated. And then asking, ‘what was the risk of them having subsequent COVID-19, being hospitalised with COVID-19, or dying from COVID-19?’.

And then we did something interesting - we could actually locate where the healthcare worker stayed. So we linked that data to other household members of the healthcare worker and then looked at what their risk was of COVID-19 infection or worsening infection.

"We noticed an 80 percent reduction in risk of hospitalisation in health care workers following vaccination."

Q: When linking the household members, were they tested?

The household members weren't systematically tested. But we looked at the rate of positivity when they did go for a test.

What we showed was that if you vaccinate the health care worker, COVID-19 cases in household members fell by 30 percent.

More interestingly, we also showed that the hospitalisation rates in the household members also fell. This wasn't statistically significant in our study, but it still went in the same direction as that for all COVID cases

Q: And was that outcome found with just one dose? Or were both doses of the vaccine required?

This is one of the rare times we could test this strategy because vaccinations in Scotland started on the 8th of December. And obviously, health care workers were the first group to be vaccinated as the highest priority category.

Now, initially, the strategy was that everybody will end up with a two-dose strategy as per the trials – a 21-day gap between them. At the end of December, the UK government introduced a different strategy where they wanted to vaccinate as many people as possible with the first dose and therefore increased the time interval between the first and second dose to 12 weeks from 3 weeks.

So a portion of the health care workers were vaccinated with both doses and a portion weren't. And we saw a signal that the infection rates in those getting two doses of the vaccine was lower than those getting just the first dose.

"From a personal point, a major concern for me when I was working at the hospital was going back to my parents' house. And actually, I really tried to avoid that because they're in their late 70s, and you definitely don't want to bring something from work back home."

Q: Interesting – great to have some positive news. Overall, what are the take-home messages from this paper?

I think there are two take-home messages, two big ones.

First, vaccinating index cases (in this case, healthcare workers) who are of an occupation that is at high risk of exposure was associated with a reduced infection rate in their respective households.

Second, vaccination of the healthcare workers themselves was associated with a reduced risk of infection and a much larger reduction in hospitalisation. In fact, we noticed an 80 percent reduction in risk of hospitalisation in health care workers following vaccination.

Q: It's interesting as a recent paper from MARCH researchers showed that 85% of healthcare workers feared for their own safety during the pandemic. So perhaps data like this can provide some reassurance moving forward?

Yup, I think personal safety, and also fear for family is a real concern.

From a personal point, a major concern for me when I was working at the hospital was going back to my parents' house. And actually, I really tried to avoid that because they're in their late 70s, and you definitely don't want to bring something from work back home.

Q: And is the data applicable beyond healthcare workers into a wider population?

This all depends on your initial risk of getting COVID-19 in the first place, which in turn is proportional to your risk of exposure.

So, you can easily see this kind of a strategy being applied to occupational groups or population groups where the risk of exposure remains high. For example, in crowded places or where you are having quite a lot of adult-to-adult interactions.

We went for a health care worker population because we know that they work in a high exposure area. In theory, there’s no reason why you wouldn’t see similar trends when you vaccinate other occupations who also work in high exposure areas.

Q:  So, in your opinion, that this would make that case, that people who are at high risk – eg. teachers - should be getting vaccinated?

I suppose the question is whether we can quantify that risk in the first place? Has the questions been asked: ‘Are teachers actually high risk of exposure or not?’. And as they work with children and adolescents: ‘Is COVID-19 easily transmissible from child to adult?’.

I’m not an expert, but I’m not currently aware of any significant data that shows that.

However, we do know from a previous data that household members of healthcare workers were at a two-fold higher risk of getting infection compared to the general population, and that was during lockdown settings. So one assumes that this is most likely, household transmission originating from the healthcare worker.

Q: To be a cynic, my next question is why is it important study this? Do we not already know that the vaccine works?

Well, look, we know three things so far.

Firstly, we know that vaccines work to prevent Covid-19 in clinical trials. That's been shown across three large scale phase 3 clinical trials and many of the clinical trials that are still ongoing are likely to show similar results. Its therefore not surprising at all why vaccines have been fast tracked into clinical approval.

Secondly, we also know from real world studies, both from Israel and one recently from Scotland, that vaccinating populations in the real world also have decent vaccine effectiveness and prevents vaccinated people from getting Covid-19.

And finally, we know from the AstraZeneca study that vaccinations reduced asymptomatic carrying of the virus in the index participants.

So, sticking to the last point, one would assume that if you can't carry the virus, you can't transmit it. And that's a theoretical association.

Our study, I think, provides the first empirical evidence that suggests: If you stay with a health care worker who is working in a high exposure area, and they get vaccinated, you as a family member or a household contact are at a lower risk of getting COVID-19.

Q: What is the action you hope people will take as a result of this data?

These estimates could be used for modelling studies on how vaccine effectiveness can impact on infection rates. And as a direct result of that, governments can then decide when to restrict or dampen down societal restrictions that are currently in place.

Additionally, it does give a bit more clinical evidence in terms of policy into which occupational groups we should target for vaccination, that might actually reduce transmission to the household members.

Finally, our results may have important implications for people who are shielding because they are immunocompromised or don't have a great immune system, and where we don't  have definite vaccine effectiveness data. There may be a role in vaccinating their household contacts instead.

Q: So say, hypothetically, we get a new variant this winter that required a whole new vaccination schedule. Would this be the start of a journey to a more targeted vaccination approach to prioritise those people who are most likely to be spreading it?

Really, it comes back to what the strategy is. And the goal of the strategy initially was to take the pressure off the NHS, and prevent people who are elderly and who have co-morbidities from being admitted into hospital.

The strategy is now likely changing and in addition to protecting the NHS to try and restrict or dampen down transmission so that we can lift societal restrictions.

And that's where I think this data probably does help.

Q: And on a note of collaboration. Science is often seen as a competitive industry. We've certainly seen this race to the first vaccine from pharmaceuticals. How important is collaborative work versus competition in tracking research forward?

In my experience, I think competition is in some ways is quite destructive to research. Whereas collaboration always results in better research, better translation of research into practise and in the generalisability of those research findings to much wider settings.

Just taking this paper as an example, this was a massive collaborative effort between epidemiologists, clinicians, infectious disease specialists and data scientists. Each piece of that cog is vital to delivering this research. If one-piece fails, the whole research project goes.

"We need to think of a patient as a whole. Infectious disease and chronic disease coexist and treating these conditions in silos is unhelpful."

Q: Working as a cardiologist and researcher, what are your personal reflections on the impact of COVID-19 on global health?

For me, the last year has put a spotlight on the interplay between infectious disease and non-communicable disease.

People with diabetes, heart disease, obesity and hypertension are at higher risk of severe COVID and these conditions don't work in silos. We've seen that those co-morbidities really affect how you survive an infectious disease pandemic.

Covid-19 affects more adversely in patients who have chronic conditions and vice versa. It is those patients with the non-communicable disease that probably have the largest burden on the healthcare system. In normal times, and probably even more so during the pandemic.

Thinking of the patient as ‘a whole’ is probably more important now than ever.

Q: Did you notice any changes in your clinical work?

So during the first wave, I was working in a district general hospital in Scotland.

And one of the most striking observation was the reduction in cardiac admissions. From having about ten to twelve admissions a day that I would see, I would see about two or three.

The first thing you think is, 'that can't be right… heart disease hasn't just gone away in a short period, it's a chronic condition.'

I think fear played a huge part, so during the second wave it was hopefully made clear to tell patients that if they are feeling unwell, they should still seek medical help.

Q: And, finally, as we begin to recover from a pandemic, in your opinion, which areas of global health are most vital to focus on to ‘build back better’?

I'm going to be extremely biased here. Given my given my clinical background.

Non-communicable diseases have been going up and up. And as low- and middle- income countries develop, the burden of chronic conditions, such as diabetes and hypertension are only going to rise. In these settings, there is already a high burden of infectious diseases, both acute and chronic, like HIV, tuberculosis, malaria, and enteric viruses.

So, going back to my point earlier, we need to think of a patient as a whole. Infectious disease and chronic disease coexist and treating these conditions in silos is unhelpful.

I think the next global health hurdle to from a clinical perspective will be to try and adapt health systems to tackle all diseases in patients rather than single conditions.

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