How to Make COVID-19 Contact Tracing Apps work: Insights from Behavioral Economics (Preprint)
Authors: Ayres Ian , Romano Alessandro , Sotis Chiara 
Published: January 2021

BACKGROUND

Due to network effects, Contact Tracing Apps (CTAs) are only effective if many people download them. However, the response to CTAs has been tepid. For example, in France less than 2 million people (roughly 3% of the population) downloaded the CTA. Consequently, CTAs need to be fundamentally rethought to increase their effectiveness.

OBJECTIVE

This study aimed to show that CTAs can still play a key role in containing the pandemic, provided that they take into account insights from behavioral sciences. Moreover, we study whether emphasizing the virtues of CTA to induce people to download them makes app users engage in more risky behaviors (risk compensation theory) and whether feedback on a user’s behavior affects future behaviors.

METHODS

We perform a double-blind online experiment (n=1500) divided in two phases. In Phase I respondents are randomly assigned to one of three different groups: Pros of the app, Pros and Cons of the app and Control I. Respondents in the Pros group were shown information on the advantages of CTAs. Participants in the Pros and Cons group were shown information on both the advantages and the problems that characterize CTAs. Last, respondents in the Control I group were not given any information on CTAs. All participants are then asked how worried they are about the pandemic, how likely they are to download the app, and on how they intend to behave (e.g. attend small and large gathering, wear a mask, etc.). A week later we carried out Phase II. Participants in Phase II were randomly assigned to different in-app notifications in which they were informed on how much risk they were taking compared to the average user. We then ask participants their intentions for future behaviors to investigate whether these notifications were effective in making respondents more prudent.

RESULTS

All 1500 participants completed phase I of the experiment, whereas 1303 (86.9%) completed also phase 2. The main findings are: i) informing people on the pros of the app make them less worried about the pandemic (p=.004), ii) informing people about both the pros and the cons of the app makes them more likely to download the app (p=.07); iii) carefully devised in-app notification induce people to state that they will: attend less large gatherings (p= .05) and less small gatherings (p= .001), see less people at risk (p=.004), that they stay more at home (p=.006) and wear more often the mask (p=.09). We do not find support for the risk-compensation theory.

CONCLUSIONS

we suggest that CTAs should be re-framed as Behavioral Feedback Apps (BFAs). The main function of BFAs would be providing users with information on how to minimize the risk of contracting COVID-19, e.g. to provide information on how crowded a store is likely to be at a given time of the day. Moreover, the BFA could have a rating system that allows users to flag stores that do not respect safety norms, such as mandating customers to wear a mask or not respecting social distancing. These functions can inform the behavior of app users, thus playing a key role in containing the spread of the virus even if a small percentage of people download the BFA. While effective contact tracing is impossible when only 3% of the population downloads the app, less risk taking by small portions of the population can produce large benefits. BFAs can be programmed so that users can also activate a tracing function akin to the one currently carried out by CTAs. Making contact tracing an ancillary, opt-in function might facilitate a wider acceptance of BFAs.