Details

Autor(en) / Beteiligte

• Sinclair, Alyssa H
• Taylor, Morgan K
• Brandel-Tanis, Freyja
• Davidson, Audra
• Chande, Aroon T
• Rishishwar, Lavanya
• Andris, Clio
• Adcock, R Alison
• Weitz, Joshua S
• Samanez-Larkin, Gregory R
• Beckett, Stephen J
• Daoust, Jean-François

Titel

Communicating COVID-19 exposure risk with an interactive website counteracts risk misestimation

Ist Teil von

• PloS one, 2023-10, Vol.18 (10), p.e0290708

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2023

Quelle

MEDLINE

Beschreibungen/Notizen

• During the COVID-19 pandemic, individuals depended on risk information to make decisions about everyday behaviors and public policy. Here, we assessed whether an interactive website influenced individuals' risk tolerance to support public health goals. We collected data from 11,169 unique users who engaged with the online COVID-19 Event Risk Tool (https://covid19risk.biosci.gatech.edu/) between 9/22/21 and 1/22/22. The website featured interactive elements, including a dynamic risk map, survey questions, and a risk quiz with accuracy feedback. After learning about the risk of COVID-19 exposure, participants reported being less willing to participate in events that could spread COVID-19, especially for high-risk large events. We also uncovered a bias in risk estimation: Participants tended to overestimate the risk of small events but underestimate the risk of large events. Importantly, even participants who voluntarily sought information about COVID risks tended to misestimate exposure risk, demonstrating the need for intervention. Participants from liberal-leaning counties were more likely to use the website tools and more responsive to feedback about risk misestimation, indicating that political partisanship influences how individuals seek and engage with COVID-19 information. Lastly, we explored temporal dynamics and found that user engagement and risk estimation fluctuated over the course of the Omicron variant outbreak. Overall, we report an effective large-scale method for communicating viral exposure risk; our findings are relevant to broader research on risk communication, epidemiological modeling, and risky decision-making.