Improving COVID-19 vaccinations through contact tracking apps

In our latest interview, News-Medical spoke to Dr. Mark Penney on his research on the ongoing COVID-19 pandemic and how we can improve COVID-19 vaccinations through contact tracking apps.

What inspired your latest research on COVID-19?

I am a mathematical physicist by training and prior to the pandemic my research focused on the applications of topology to quantum field theory. During our first lockdown, I started talking to some colleagues at the Perimeter Institute for Theoretical Physics about how we could apply models from physics, particularly percolation theory, to understand COVID-19.

In the end, we formed an interdisciplinary team of physicists and experts in the modeling of infectious diseases and vaccinations. There is some classic research in percolation theory that shows that the rate of spread of an infectious disease increases when the population has more fluctuations in the number of contacts. Our initial motivation was to better understand how these heterogeneities in human contact patterns affect public health interventions.

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The COVID-19 pandemic has taught us that scientific progress can be made quickly by working together. How can this level of collaboration be implemented in COVID-19 vaccination programs?

This research was certainly the result of a collaboration. When we first thought about this project, our co-author Lee Smolin suggested that if we were to make a difference, we would have to work with infectious disease experts.

So we teamed up with Chris Bauch, Madhur Anand and Ed Thommes. We also added Lee’s then PhD student Yigit Yargic, who is the other lead author on the article and with whom I worked very closely.

Vaccines are in some ways collaborative in nature: they not only offer protection to the person who receives them, but often also to those who come in contact with them. More specifically, collaboration and resource sharing are certainly required to achieve equitable access to COVID-19 vaccines in all countries.

At the local level, vaccination campaigns can be hampered by a high level of preferential bonding between unvaccinated individuals, allowing the disease to spread more freely among unvaccinated individuals. Such preferential bonding could be a symptom of the rift within the community around vaccination.

How do COVID-19 contract tracking apps work?

Different countries have implemented different approaches to digital contact tracking. A popular approach uses Bluetooth to create a decentralized, encrypted contact log. The Google / Apple Exposure Notification API and BlueTrace are the two main implementations. The former is used in Canada, Europe, and some US states, while the latter is used in Singapore, New Zealand, and Australia.

The “decentralized contact log” mentioned above is, at least in my opinion, the most exciting part of these contract tracking apps. The basic idea is that whenever two people using the app are close to each other for some time, they exchange cryptographic tokens to record their contact. Each user’s device has a log of all the contacts they have had, except that the entries are encrypted, making it impossible to find out who that contact was.

When a person who tests positive for COVID-19 decides to upload it to the app, they will send a key that will allow all other app users to decrypt the exchanged tokens. This way, another user’s phone can alert them to the potential exposure.

It is important to note that in the Google / Apple framework there is no way for authorities or other people to access the encrypted contact log. These contact tracking systems work without the central collection of private information.

Contact tracking

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Can you describe how you did your latest research on COVID-19 vaccines and contact tracking apps?

The biggest technical challenge in this project was that our model was not just from how many Contacts that people had, but also on how long these contacts kept up. This is due to an important subtlety in how contact tracking apps record entries in the contact log.

If you spend a long time with the same person, the apps may be able to exchange tokens multiple times, with new entries being added roughly every 10-15 minutes. Since the tokens are encrypted, it is impossible to know whether two entries corresponded to contact with two different people or to prolonged or repeated contact with the same person.

The existing literature on the application of the percolation theory to infectious diseases had assumed, for the sake of simplicity, that the duration of contact has no influence on the probability of transmission. That’s not exactly a terrible assumption, but given how contact tracking apps work, it also took us time to get in the picture.

So, among other things, we had to include the duration in these models and derive the key formulas anew. In addition, we had to determine how a vaccination program, in which people were prioritized based on the number and duration of contacts, affected the rate of spread.

What did you discover

A vaccine strategy that prioritizes those with greater exposure to others has the potential to limit the spread of disease more effectively. This is because people who have more contacts are more likely to infect the disease and also more likely to spread it to others. This idea has been well researched in the literature and has even been put into practice.

However, its use in the real world is limited by the ability of health officials to actually identify those with more contacts. In practice, they typically use larger demographic factors. For example, during a lockdown in my area, COVID-19 vaccines were prioritized for those key workers who were unable to work from home due to their increased risk of transmission.

We suggested a way to leverage existing contact tracing apps to distribute vaccines more efficiently. The decentralized contact log created by contact tracing apps provides the ability to target public health strategies, especially vaccinations, to people with high exposure without the need for authorities to centralize information about population contacts. In our proposal, the app decides, based on the number of entries in the contact log, whether the app user is to be prioritized or not.

In the paper we modeled a scenario where the demand for vaccines is much higher than the supply and the goal is to reduce the transmission of disease as much as possible through a limited supply. We looked at an idealized scenario where someone would only get a vaccine if they were selected by the app.

Our modeling showed that our “hot spotting” strategy with contact tracking apps is very efficient at reducing the spread, which means that fewer vaccines can suppress the disease. In fact, herd immunity was achieved with about half as many doses for our model contact network.

Study results

Credit: 2021 Penney et al

How would this approach work for developing countries where few people use contact tracing apps?

The fewer people use the app, the fewer people could possibly even be prioritized by the app. So the overall reduction in disease spread that could be achieved depends on how many people are using the app. However, an interesting result of our work was that the Efficiency the strategy is still high even with a small number of users.

All vaccines assigned to people with high exposure have a relatively greater effect, and therefore the strategies are still able to achieve greater reductions from the vaccines they assigned using the hot-spotting strategy.

More research would need to be done before a country can decide whether using this technology is the right solution for them. The choice of priority for vaccination has social and health implications beyond transmission rate.

Were there any restrictions in your studies? If so, what were they?

It would be best to think of this study as a preliminary modeling of a proposal. As mentioned earlier, more detailed studies would need to be done to better understand the full effects. However, there is one important caveat worth pointing out. We analyzed the app-based vaccination strategies in isolation.

In more realistic scenarios, the app-based distribution would likely take place alongside other, more traditional systems. Indeed, to better understand the implications of the strategy it just needs to be viewed as part of a holistic vaccination approach.

What’s next with your research?

We have developed a model for a scenario that is more like a seasonal flu shot. The main reason for vaccination protection is no longer the provision of vaccines, but the individual decision to receive the vaccination. The contact tracking apps are no longer used to prioritize access to the vaccine.

Instead, when a user is selected by the app, they will receive a notification promoting that they will be vaccinated because of their high contact pattern. Our initial results suggest that the hot-spotting strategy could be a valuable tool to reduce the exposure to seasonal influenza, especially given the low implementation costs.

Where can readers find more information?

About Dr. Mark Penney

Mark Penney is a postdoctoral fellow at the University of Waterloo. He received his DPhil in Mathematics from the University of Oxford in 2017 for research at the intersection of topology and physics. Before moving to the University of Waterloo, Mark spent two years at the Max Planck Institute for Mathematics in Bonn.Dr.  Mark Penney

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