Public Preferences for Pandemic Response Strategies: A Discrete Choice Experiment on Vaccination, Restrictions, and Risk Communication in a Hypothetical Hantavirus Outbreak

Last registered on June 29, 2026

Pre-Trial

General Information

Title

RCT ID

AEARCTR-0019055

Initial registration date

June 27, 2026

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

June 29, 2026, 9:40 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Name

Giuseppe Maggio

Affiliation

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Other Primary Investigator(s)

PI Name

Michele Battisti

PI Affiliation

Università degli Studi di Palermo

Contact Investigator

PI Name

Valentino Dardanoni

PI Affiliation

Università degli Studi di Palermo

Contact Investigator

PI Name

Emanuele Amodio

PI Affiliation

Università degli Studi di Palermo

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Additional Trial Information

Status

In development

Start date

2026-06-29

End date

2026-07-31

Keywords

Health

Additional Keywords

Discrete Choice Experiment (DCE); Hantavirus; Vaccination Preferences; Public Health Decision-Making

JEL code(s)

C25, D81, D91, I12, I18

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Public acceptance of public health interventions is critical for the effective management of future infectious disease outbreaks. This study investigates individual preferences for alternative pandemic response strategies using a discrete choice experiment (DCE) embedded in a large-scale online survey conducted in Italy and the United States. Respondents complete eight hypothetical choice tasks set in the context of a future hantavirus epidemic, selecting among three policy options: a vaccination program, non-pharmaceutical restrictions, or no additional public health measures. Alternatives vary in vaccine efficacy, risk of serious adverse events, regulatory approval status, recommending authority, type and duration of restrictions, economic and social burden, and projected hospitalizations and deaths. In addition to stated preferences, the survey collects information on respondents' experiences during the COVID-19 pandemic, vaccine attitudes, trust in institutions and information sources, risk literacy, political orientation, health status, and sociodemographic characteristics. Preference heterogeneity is analyzed using mixed logit models, with interaction terms examining how trust, prior pandemic experiences, and individual characteristics moderate policy preferences. The study also compares preference structures between Italian and U.S. respondents and estimates trade-offs individuals are willing to make between health outcomes and the social and economic costs of public health interventions. By identifying the factors that shape public support for vaccination, restrictions, and risk communication strategies, this research provides evidence to inform the design of pandemic preparedness policies that are both effective and socially acceptable.

External Link(s)

Registration Citation

Citation

Amodio, Emanuele et al. 2026. "Public Preferences for Pandemic Response Strategies: A Discrete Choice Experiment on Vaccination, Restrictions, and Risk Communication in a Hypothetical Hantavirus Outbreak." AEA RCT Registry. June 29. https://doi.org/10.1257/rct.19055-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Participants are presented with a hypothetical future hantavirus outbreak and complete a discrete choice experiment (DCE) consisting of eight randomized choice tasks. In each task, respondents choose their preferred public health response among three alternatives: (1) a vaccination strategy, (2) a restriction-based strategy, or (3) no new public health measures. The vaccination option varies in vaccine efficacy, risk of serious side effects, regulatory approval status, and recommending authority. The restriction option varies in the type, duration, and economic/social burden of non-pharmaceutical interventions. All alternatives are accompanied by projected numbers of hospitalizations and deaths per 100,000 population over the following six months. The order of the choice tasks is randomized across participants. The intervention is embedded within a broader online survey that also collects information on COVID-19 experiences, vaccine attitudes, trust in institutions, risk literacy, and sociodemographic characteristics.

Intervention Start Date

2026-07-02

Intervention End Date

2026-07-31

Primary Outcomes

Primary Outcomes (end points)

The primary outcome is the respondent's stated choice in each discrete choice experiment (DCE) task. Each participant completes eight choice tasks and, in each task, selects one of three alternative public health response strategies:

Vaccination strategy
Restriction-based strategy
No new public health measures

The outcome is recorded as a categorical choice variable at the respondent–choice task level (up to eight observations per participant). These repeated choices are used to estimate the marginal utility (preference weights) of the experimental attributes—including vaccine efficacy, side-effect risk, regulatory approval status, recommending authority, restriction type, restriction duration, economic/social burden, and projected hospitalizations and deaths—using mixed logit (random-parameters logit) models.

Primary Outcomes (explanation)

The primary outcome is the respondent's choice in each of the eight discrete choice experiment (DCE) tasks. For every task, respondents select one of three alternatives: (1) a vaccination strategy, (2) a restriction-based strategy, or (3) no new public health measures. This choice is recorded as a categorical variable at the respondent-task level.

The outcome itself is not constructed from multiple variables. However, the analysis estimates latent preference weights (marginal utilities) for each policy attribute by modeling the observed choices using mixed logit (random-parameters logit) models. These preference weights are inferred from repeated choices across the eight tasks rather than directly observed. Respondent-level variables, including COVID-19 experiences, vaccine attitudes, trust in institutions, political orientation, and risk literacy, are used as moderators in interaction analyses to explain heterogeneity in preferences.

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

This study employs a randomized, within-subject discrete choice experiment (DCE) embedded within a cross-sectional online survey administered to adult participants residing in Italy and the United States. The objective is to elicit stated preferences for alternative public health response strategies during a hypothetical future hantavirus outbreak.
Each participant completes eight discrete choice tasks. In every task, respondents are presented with three mutually exclusive public health strategies and are asked to select the option they would most prefer. The three alternatives consist of: (1) a vaccination strategy, (2) a restriction-based strategy, and (3) a no-new-measures strategy. The "no new measures" alternative serves as a constant reference option across all tasks, while the vaccination and restriction alternatives vary according to experimentally assigned attribute levels.
The vaccination strategy is characterized by vaccine efficacy, the probability of serious side effects, regulatory approval status, and the authority recommending vaccination. The restriction strategy varies according to the type of restriction implemented, its duration, and the associated economic and social burden. In every choice task, each alternative is also accompanied by projected numbers of hospitalizations and deaths per 100,000 population over the following six months. Attribute combinations are generated using an efficient fractional factorial design to maximize statistical efficiency while avoiding implausible or dominant profiles.

The order of the eight choice tasks is randomized across respondents to reduce potential order and fatigue effects. All participants receive the same overall survey structure, but the randomized presentation of the experimental tasks ensures variation in exposure to the choice scenarios.
The DCE is embedded within a broader questionnaire collecting information on demographic characteristics, health status, previous experiences during the COVID-19 pandemic, vaccine attitudes, trust in institutions and information sources, political orientation, and risk literacy. These variables are measured observationally and are not experimentally manipulated.
Each respondent contributes up to eight observations, one for each completed choice task, allowing estimation of preferences for alternative policy attributes and investigation of heterogeneity in preferences across individuals and between the Italian and U.S. samples.

Experimental Design Details

Not available

Randomization Method

Randomization was implemented automatically through the Qualtrics survey platform. Qualtrics randomized the order of presentation of the eight discrete choice experiment (DCE) tasks for each respondent using its built-in randomization functionality. The allocation of attribute combinations to choice tasks was predetermined by the experimental design, while the sequence in which the tasks were presented was randomized independently for every participant.

Randomization Unit

Individual respondent. Randomization occurs at the individual level through the Qualtrics platform, with each participant receiving a randomized order of the discrete choice experiment (DCE) tasks.

Was the treatment clustered?