Comparing reports of flu symptoms with Covid testing rates provides a critical insight. We can’t let it slip over summer, writes Siouxsie Wiles.
For almost two years, my family and I have been taking part in the FluTracking project. This fantastic initiative started in Australia in 2006 to use the power of the internet to track flu and flu-like symptoms. It expanded to include New Zealand in 2018 with support from the Ministry of Health.
Here’s how it works. When you sign up you are asked for a little bit of demographic information, like how old you are and where you live. Then once a week you are sent a short online survey. And when I say short, I mean short. It only takes about 15 seconds to fill out. Originally, the survey started by asking whether anyone in your household had experienced a fever or cough over the last week. If you answered yes to either of those questions, then you were asked a few more. Have they also had a sore throat, taken any time off work, or seen a doctor or other healthcare provider. Because FluTracking started as a way to track seasonal influenza, the survey used to only run over winter.
Since the pandemic began upending our lives, the FluTracking project has been expanded to help track Covid-19 symptoms too. The survey still takes seconds to complete but now asks about a wider range of symptoms and whether you’ve had a Covid-19 test. Over winter almost 50,000 people in New Zealand have been regularly doing the survey. Because we’re moving into summer and the normal flu season is over, this week participants were asked whether they would like to keep doing the surveys over summer or opt out till next winter. Last year this saw the number of people filling out the survey drop dramatically to around 20,000.
Here’s why it’s important. With the delta variant now spreading in the community in New Zealand, we need as many people as possible to do the FluTracking survey over summer. If you’ve been a FluTracker over winter, please click the link in your next survey to keep going. If you’ve opted out already, please opt back in again. And if you aren’t a FluTracker yet, then please sign up.
Let me explain why.
How FluTracking data helps keep tabs on Covid
While physicist Shaun Hendy and mathematician Mike Plank have become household names in New Zealand for their Covid-19 modelling work, they are just two of the many members of Te Pūnaha Matatini (TPM) working on aiding the country’s pandemic response. If you aren’t familiar with TPM, it’s a Centre of Research Excellence with people all over the country working to understand and solve complex problems. For full transparency, I’m a member of TPM too and for the last few years was one of the centre’s deputy directors. What I love about being part of TPM is the centre’s focus not just on doing excellent research but on building diverse, creative, kind, and excellent research teams that work collaboratively and respectfully to tackle big problems. Its creating a very different research culture from the norm.
TPM researchers Emily Harvey and Dion O’Neale and their team have been using the weekly FluTracking survey to help understand the risk of undetected or unconfirmed Covid-19 spread around New Zealand. You can read some of their work here and here. Using the data on how many people have new onset of symptoms and combining that with the Ministry of Health’s testing numbers allows the team to estimate roughly how many people who became symptomatic within the last week didn’t go and get a Covid test. Obviously the more symptomatic people that don’t go and get tested, the longer it could take an outbreak to be picked up. I often wonder how the current delta outbreak would have played out if someone had got tested in the week before the first identified case took themselves off for a swab.
So, what does the FluTracking data tell us about the current delta outbreak? The graphs below show the symptomatic testing rates (in the grey bars) for different age groups by District Health Board alongside the team’s estimates from the FluTracking data. Compare the grey bars to the estimates of the number of people with new onset of two or more Covid-like symptoms (dark blue lines). The red lines are the estimates for the people who became symptomatic and didn’t get tested and are likely a little bit of an overestimate. We want to see those red lines as low as possible which is what happens when testing rates are high.
In response to the first community case of delta, the whole country moved into alert level level at 11:59 pm on August 17. As you can see from the grey bars, that coincided with a big rise in people being tested in Auckland, though less so in older Aucklanders, and hence a big drop in the red lines. Compare that with the testing rates in the wider Wellington region, which never got as high as they should have been, given the number of people with new symptoms. It does look though like people of working age in Capital and Coast District Health Board were good about getting tested at the start of the outbreak but then fell back on old habits once the region started moving down the alert levels.
We can also see the effect of people staying home in their bubbles on the spread of all the microbes that cause Covid-like symptoms. Check out the sharp drop in the number of people with new onset of Covid-like symptoms (blue line) when the country was in alert levels four and three. In the Auckland Region, this line has stayed low, but in other parts of the country we see it climbing up when they shifted to alert level 2 and schools went back, then dropping again in the school holidays. The FluTracking survey data also shows that schools being open or closed drives a lot of illness in adults. As a parent myself, I’ll never forget all the colds my daughter brought home from day care and primary school.
Using the FluTracking data to track our Covid control measures
The other thing the FluTracking data is really good for is looking to see how our control measures are impacting on Covid-like symptoms. Take the graph below. The shaded areas are when either the whole country (grey) or Auckland (green) were at alert levels two or three. The estimates for the percentage of people with Covid-like symptoms in Auckland is shown in orange and for the rest of New Zealand in blue. See how levels drop when we enter alert level three? And then rise again as we move down the alert levels? As we switch from the alert level system to the traffic light system, graphs like this are going to be really valuable.
With Covid-19 now in the community, the FluTracking data is more important than ever. We need to keep tabs on whether testing rates are high enough not just in Auckland but all around the country. While our vaccination rates are rising, we aren’t all protected yet so identifying people with Covid-19 is still an important way to stop the spread of the virus.
Emily and Dion and their team, working with Dr Oliver Maclaren, have also created a model of New Zealand that represents just how connected we all are, through schools, workplaces, and our communities. Called the Populated Aotearoa Interaction Network (PAIN), the model can be used to predict how Covid-19 will spread from suburb to suburb and city to city as well as the impact of things like vaccination. Models like these need good data, and the FluTracking project is one such source of data.
Initiatives like FluTracking work at their best the more of us take part. So please, sign up today and let’s keep track of Covid-19 in New Zealand.