Expectations, reference points, and compliance with COVID-19 social distancing measures

Briscese, Guglielmo; Lacetera, Nicola; Macis, Mario; Tonin, Mirco

doi:10.1016/j.socec.2023.101983

Cited by 19 publications

(7 citation statements)

References 46 publications

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“…BCT approaches may be sub-optimal for COVID-19 control for the following reasons: First, BCT treats all recorded contacts of an index case as equally infectious; i.e., it does not use contacts' own information (e.g., symptoms, proximity and duration of encounters) to evaluate their likelihood of being infected or infecting others, thereby recommending quarantine to many more people than are infectious [12,13]. Such overly restrictive notifications can contribute to "pandemic fatigue," leading to reduced compliance [14]. Second, people who never develop symptoms or experience mild symptoms may nevertheless be infectious.…”

Section: Introductionmentioning

confidence: 99%

Proactive Contact Tracing

et al. 2023

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The COVID-19 pandemic has spurred an unprecedented demand for interventions that can reduce disease spread without excessively restricting daily activity, given negative impacts on mental health and economic outcomes. Digital contact tracing (DCT) apps have emerged as a component of the epidemic management toolkit. Existing DCT apps typically recommend quarantine to all digitally-recorded contacts of test-confirmed cases. Over-reliance on testing may, however, impede the effectiveness of such apps, since by the time cases are confirmed through testing, onward transmissions are likely to have occurred. Furthermore, most cases are infectious over a short period; only a subset of their contacts are likely to become infected. These apps do not fully utilize data sources to base their predictions of transmission risk during an encounter, leading to recommendations of quarantine to many uninfected people and associated slowdowns in economic activity. This phenomenon, commonly termed as “pingdemic,” may additionally contribute to reduced compliance to public health measures. In this work, we propose a novel DCT framework, Proactive Contact Tracing (PCT), which uses multiple sources of information (e.g. self-reported symptoms, received messages from contacts) to estimate app users’ infectiousness histories and provide behavioral recommendations. PCT methods are by design proactive, predicting spread before it occurs. We present an interpretable instance of this framework, the Rule-based PCT algorithm, designed via a multi-disciplinary collaboration among epidemiologists, computer scientists, and behavior experts. Finally, we develop an agent-based model that allows us to compare different DCT methods and evaluate their performance in negotiating the trade-off between epidemic control and restricting population mobility. Performing extensive sensitivity analysis across user behavior, public health policy, and virological parameters, we compare Rule-based PCT to i) binary contact tracing (BCT), which exclusively relies on test results and recommends a fixed-duration quarantine, and ii) household quarantine (HQ). Our results suggest that both BCT and Rule-based PCT improve upon HQ, however, Rule-based PCT is more efficient at controlling spread of disease than BCT across a range of scenarios. In terms of cost-effectiveness, we show that Rule-based PCT pareto-dominates BCT, as demonstrated by a decrease in Disability Adjusted Life Years, as well as Temporary Productivity Loss. Overall, we find that Rule-based PCT outperforms existing approaches across a varying range of parameters. By leveraging anonymized infectiousness estimates received from digitally-recorded contacts, PCT is able to notify potentially infected users earlier than BCT methods and prevent onward transmissions. Our results suggest that PCT-based applications could be a useful tool in managing future epidemics.

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Section: Introductionmentioning

confidence: 99%

Proactive Contact Tracing

et al. 2023

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“…Second, we contribute to the rapidly growing literature using aggregate GPS data to study the effect of policies trying to contain the spread of COVID‐19 on mobility patterns (Allcott et al, 2020; Dasgupta et al, 2020; Dave et al, 2020; Schlosser et al, 2020; Nguyen et al, 2021; Wellenius et al, 2021; Breidenbach and Mitze, 2022). The use of GPS data is one of the main alternatives to using surveys (Jørgensen et al, 2021; Briscese et al, 2023), which likely do not provide reliable data on mobility due to social desirability bias (Daoust et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

The effect of compulsory face mask policies on community mobility in Germany^*

Kovacs

Dunaiski

Tukiainen

2023

Scandinavian J Economics

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There is an ongoing debate about making face masks compulsory in public spaces to contain COVID‐19. A key concern is that such policies could undermine efforts to maintain social distancing and reduce mobility. We provide first evidence on the impact of compulsory face mask policies on community mobility. We exploit the staggered implementation of policies by German states during the first wave of the pandemic and measure mobility using geo‐located smartphone data. We find that compulsory masking policies led to a short‐term reduction in community mobility, with no significant medium‐term effects. We can rule out even small increases in mobility.This article is protected by copyright. All rights reserved.

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“…For instance, Brodeur et al (2021) provide the first review of the economics of COVID-19, with over 700 citations on Google Scholar; Blundell et al (2021) provide a review on the COVID-19 crisis in the UK. Many studies have elicited and analyzed beliefs and expectations related to the Coronavirus and the COVID-19, including Adams-Prassl et al (2020), Akesson et al (2022), Altig et al (2020), Aucejo et al (2020), Belot et al (2021Belot et al ( , 2020, Briscese et al (2023), Bordalo et al (2022Bordalo et al ( , 2020, Bruine de Bruin and Bennett (2020), Ciancio et al (2020), Collis et al (2022), Delavande, Bono and Holford (2021), Kröger, Bellemare and de Marcellis-Warin (2020), Bravo and Sanz (2022), Papageorge et al (2021), Savadoria and Lauriola (2022), Smith et al (2020), Wise et al (2020), among others. Differently from these (and other) studies, we connect subjective expectations on Coronavirus-and lockdown-related risks to compliance decisions (plans) in a formal model of discrete choice, in order to quantify the role of expectations and preferences in determining compliance.…”

Section: Introductionmentioning

confidence: 99%

For better or worse? Subjective expectations and cost-benefit trade-offs in health behavior-offs in health behaviour-offs in health behaviour

Conti¹,

Giustinelli²

2023

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We provide a framework to disentangle the role of preferences and beliefs in health behavior, and we apply it to compliance behavior during the acute phase of the COVID-19 pandemic. Using rich data on subjective expectations collected during the spring 2020 lockdown in the UK, we estimate a simple model of compliance behavior with uncertain costs and benefits, which we employ to quantify the utility trade-offs underlying compliance, to decompose group differences in compliance plans, and to compute the monetary compensation required for people to comply. We find that, on average, individuals assign the largest disutility to passing away from COVID-19 and being caught transgressing, and the largest utility to preserving their mental health. But we also document substantial heterogeneity in preferences and/or expectations by vulnerability status, gender, and other individual characteristics. In our data, both preferences and expectations matter for explaining gender differences in compliance, whereas compliance differences by vulnerability status are mainly driven by heterogeneity in preferences. We also investigate the relationship between own and others' compliance. When others fail to comply and trust breaks down, individuals respond heterogeneously depending on their own circumstances and characteristics. When others around them comply less, those with higher risk tolerance and those without prior COVID-19 experience plan to comply less themselves, while the vulnerables plan to comply more. When a high-level public figure breaches the rules, supporters of the opposing political party plan to comply less. These findings emphasize the need for public health policies to account for heterogenous beliefs, preferences, and responses to others in citizens' health behaviors.

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Expectations, reference points, and compliance with COVID-19 social distancing measures

Cited by 19 publications

References 46 publications

Proactive Contact Tracing

Proactive Contact Tracing

The effect of compulsory face mask policies on community mobility in Germany^*

For better or worse? Subjective expectations and cost-benefit trade-offs in health behavior-offs in health behaviour-offs in health behaviour

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Expectations, reference points, and compliance with COVID-19 social distancing measures

Cited by 19 publications

References 46 publications

Proactive Contact Tracing

Proactive Contact Tracing

The effect of compulsory face mask policies on community mobility in Germany*

For better or worse? Subjective expectations and cost-benefit trade-offs in health behavior-offs in health behaviour-offs in health behaviour

Contact Info

Product

Resources

About

The effect of compulsory face mask policies on community mobility in Germany^*