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Humankind’s main defence against the virus that cuases COVID-19 (SARS-CoV-2), besides vaccine development, was co-ordinated behaviour change. In many countries, co-ordination was assisted by tracking surveys designed to measure self-reported behaviour and attitudes. This paper describes an alternative, complementary approach, which was undertaken in close collaboration with officials in the Department of the Taoiseach (Irish Prime Minister). We adapted the Day Reconstruction Method (DRM) to develop the ‘Social Activity Measure’ (SAM). The study was conducted fortnightly for 18 months, with findings delivered directly to the Department. This paper describes the method and shows how SAM generated a detailed picture of where and why transmission risk occurred. By using the DRM, we built aggregate measures from narrative accounts of how individuals spent their previous day. SAM recorded the amount, location and type of social activity, including the incidence of close contact and mask-wearing, as well as compliance with public health restrictions by shops and businesses. The method also permitted a detailed analysis of how public perceptions and comprehension are related to behaviour. The results informed government communications and strategies for lifting public health restrictions. The method could be applied to other future situations that might require co-ordinated public behaviour over an extended period.

People have limited capacity to process and integrate multiple sources of information, so how do they integrate multiple contextual risk factors for Coronavirus disease (COVID-19) infection? In June 2020, we elicited risk perceptions from a nationally representative sample of the public (N = 800) using three psychologically-distinct tasks. Responses were compared to a sample of medical experts who completed the same tasks. Relative to experts, the public perceived lower risk associated with environmental factors (such as whether a gathering takes place indoors or outdoors) and were less inclined to treat risk factors as multiplicative. Our results are consistent with a heuristic simply to “avoid people” and with a coarse (e.g., “safe or unsafe”) classification of social settings. A further task, completed only by the general public sample, generated novel evidence that when infection risk competes with risk in another domain (e.g., a different medical risk), people perceive a lower likelihood of contracting the virus. These results inform the policy response to the pandemic and have implications for understanding differences between expert and lay perception of risk

Contact-tracing mobile phone apps can play a role in controlling the spread of COVID-19, but their success hinges on widespread public acceptance, uptake and use, which are difficult for public administrators to foresee. We report on a rapid behavioral pre-test of COVID Tracker, Ireland’s contact-tracing app, prior to its launch. A large sample of participants were randomized to receive different versions of a trial app. They responded to an online survey while downloading and using the app on their phones in real time. Experimental manipulations focused on: (i) the level of privacy assurance provided in the app, (ii) the goal-framing of the purpose of the app and (iii) the structuring of the exposure notification. Almost one in five participants mentioned privacy concerns in relation to their likelihood of downloading the app, but concerns were lower and engagement stronger in a condition that included additional assurances regarding the privacy of users’ data in the app. This finding informed the final version of the app. Overall, our results demonstrate the value and feasibility of pre-testing digital interfaces to improve public administration.

Objective: Self-isolation is a vital element of efforts to contain COVID-19. We set out to test whether decision aids can support self-isolation. Design: We conducted a pre-registered online experiment with a nationally representative sample (n = 500). Three stages tested: (i) whether decision trees help people to decide whether they need to self-isolate; (ii) whether an online planning tool increases people’s confidence in their ability to self-isolate; and (iii) whether infographics help people to absorb advice on managing a household in which someone must self-isolate. Main Outcome Measures: (i) Accuracy of matching symptom patterns to a response scale for the need to self-isolate; (ii) self-reported confidence in coping with self-isolation; (iii) objective tests of recall and comprehension. Results: Decision trees improved decisions about when self-isolation was necessary, although participants systematically underestimated the need to self-isolate with less common COVID-19 symptoms (e.g. sore throat, fatigue). The online planning tool increased confidence about coping with self-isolation only among the adults aged under 40. Infographics improved recall and comprehension of how to manage self-isolation. Conclusion: Decision aids can be used to support self-isolation during COVID-19. The study also demonstrates how even an emergency public health response can benefit from rapid experimental pre-testing of interventions.

Rationale: Maintaining social distance during the COVID-19 pandemic can save lives. We therefore set out to test communication strategies to promote social distancing. Objective: We aimed to test two novel public health messages against a control message. The first was designed to exploit the “identifiable victim” effect by highlighting the risk of transmission to identifiable vulnerable persons. The second sought to counteract intuitive underestimation of exponential transmission. Method: In total, 500 Irish adults undertook a pre-registered, online experiment. They were randomly assigned to a control group or one of two treatment groups. The control group viewed a current poster that encouraged a 2-m separation between people. The two treatment groups saw posters of similar design, but with narrative messages describing how an individual had infected a specific vulnerable person or multiple other people. Later questions measured intentions to undertake three specific types of social interaction over the coming days and the stated acceptability of three other types of social interaction. Pilot work had identified these six behaviors as “marginal” – people were unsure whether they were advisable. Results: Participants in the treatment conditions were more cautious about undertaking the behaviors and less accepting of them. This positive effect occurred despite participants rating the treatment posters as likely to be less effective and memorable than the control poster. Conclusions: Messages that invoke thoughts of infecting vulnerable people or large numbers of people can motivate social distancing and, hence, help to limit the spread of COVID-19. Stated public evaluations (obtained via focus groups or surveys) may underestimate the actual effectiveness of such emotional messages.