Covid 19 coronavirus: What you need to know about models and herd immunity

The more people are vaccinated against Covid-19, and the more quickly this happens, the higher the chance we have of achieving population immunity. Photo / ODT

Kiwis have been hearing some worrying predictions around achieving herd immunity against the pandemic coronavirus and its growing number of variants. But what are the missing pieces of the picture we don't have yet? University of Auckland vaccine experts Associate Professor Helen Petousis-Harris and Dr Janine Paynter offer a quick recap to Herald science reporter Jamie Morton.

We've been hearing much about herd immunity again: can we quickly recap what this is?

Dr Janine Paynter (JP): Population or community immunity, as we call it, is when the number of people who are not susceptible to an infectious disease - usually because they've had a vaccine - is high enough to prevent an infection occurring people who are still susceptible to the disease.

In particular, that includes infants, immune-compromised people, such as those undergoing cancer treatment, or those who just haven't been vaccinated.

When enough people are immune, the disease doesn't move through the population very effectively.

But herd immunity also isn't as simple as vaccinating a certain proportion of a population. What are the other factors at play behind it?

JP: That's correct – there isn't a fixed proportion, as it depends very much on vaccine characteristics and the type of virus or bacteria that we want to stop.

One of the most important characteristics used to estimate herd immunity or how many people need to be vaccinated is the "R" value; which is how many susceptible people who encounter an infected person get infected with the disease.

The R value itself depends on a range of things, such as how many people an infected person usually encounters, and how well, or quickly, the disease organism moves to the uninfected person.

Associate Professor Helen Petousis-Harris (HPH): The more people we vaccinated, then the more we reduce the "R" value.

The overall effectiveness of a vaccine depends on how well it reduces or prevents transmission, the duration of protection it provides, and the protection people get from having the natural disease, and how long it lasts.

There's also the infectiousness of the disease, and the proportion of people vaccinated.

As you can see there are quite a few things that go into the pot: some of these things we know, and others we have to guess at a bit.

Scientists and mathematicians from around the world have tried to estimate what proportion of the population need to be vaccinated with the current vaccines to reduce this R value to one or lower. That's because this is important for helping to decide whether countries lift restrictions on borders and allow travel and in doing so allow the virus to travel. How reliable are these estimates now?

JP: At present, the estimates are generally relying on measures of vaccine effectiveness or efficacy as a starting point, to estimate how much transmission can occur if someone is vaccinated.

Vaccine effectiveness or efficacy relies on classifying someone as a case or not, and being a case of Covid-19 relies on having a positive PCR test.

Here's where the trouble begins, because infectiousness or the ability to transmit is not tightly or neatly related to being a PCR positive case.

This is because the PCR test detects fragments of virus, regardless of whether the virus is intact and able to infect another person, or is a broken piece of virus - the result of an unsuccessful battle with our immune system.

There has been some nice work that's tried to understand the relationship between how much virus fragment has been found on a swab using PCR, and the level of infectiousness.

However, the modelling work that's been done so far - including work done here and by US epidemiologist Professor Marc Lipsitch's team at Harvard University - hasn't used that relationship to modify their estimate of transmission based on positive PCR.

Even if they had, it is likely that this relationship would be different for a vaccinated person being PCR positive, and an unvaccinated person. As far as I'm aware, that study hasn't been done.

What are we learning about herd immunity currently, as more vaccination data from around the world comes back?

JP: We are in a lucky position in New Zealand, because we can use data from other countries, such as the UK, to improve our modelling.

As long as UK or other countries keep collecting good data on who has been vaccinated and basic contact tracing data, we should continue to have a good picture.

For example, we can look at vaccinated people, and the unlucky 5 per cent of them or so who still get sick from Covid-19, find out who they encountered, and then ask how many of those people got sick.

So far, what do you think are the biggest positives around vaccination and immunity, or optimistic signs that we can take away?

JP: The modelling to date has sensibly been very conservative in assumptions about vaccine effect on transmission.

However, I always like throwing real world data at models and see how they measure up.

We had a glimpse at what is a plausible R value for someone who has been vaccinated with our recent unfortunate Australian tourist.

He'd had the more transmissible delta variant, but had received one dose of the AstraZeneca vaccine.

As far as we know, only one of his close contacts were also infected.

This is an R of one, and it's also possible they picked the virus up from the source who infected the tourist, and not him.

Obviously, it would be mad to rely heavily on one data point, however I think it gives us room to be more optimistic and more sceptical of recent modelling estimates for herd immunity.

HPH: I agree. Also, we see these kinds of things play out in other real-world examples with other diseases.

Often, the overall effectiveness of vaccines ends up higher than predictions and these slightly more indirect effects - some which can be quite subtle.

Generally, what remain the big unknowns, where we urgently need more data?

JP: Some of the big questions I have, are long will the vaccine protect us for? How long will people who have had the disease be protected for?

Will we need top-up doses if the virus is still circulating in the population at low levels, or will it change such that the vaccine is less effective?

Nonetheless, is it fair to say that the longer we take to vaccinate as much of the population, the more opportunity the virus will have to mutate into new variants, and thus prove harder to eliminate?

JP: Absolutely. I'm still waiting for my first dose of vaccine – I'm in Group 4 - and I get fleeting pangs of jealousy when other people tell me they've had their vaccine, but the more the merrier.

HPH: Yes, the more human incubators, the more chance for mutation, and the harder it will be to beat this back.

We need as many people on the planet protected as soon as possible, or this is going to drag on.

How long might it drag on? Could it be possible the long-term picture could prove permanent circulation and evolution of the virus - like influenza - requiring ongoing vaccine updates and interventions?

JP: It's looking increasingly likely that this will be the future - and this coronavirus isn't the first coronavirus to have made a jump from animals to humans and stayed.

What is certain, is that humans and the virus will continue to adapt and change.