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. 2021 May 3;4(5):e2110918.
doi: 10.1001/jamanetworkopen.2021.10918.

Consumer Views on Using Digital Data for COVID-19 Control in the United States

David Grande  1   2 , Nandita Mitra  3 , Xochitl Luna Marti  2 , Raina Merchant  4   5 , David Asch  2   6 , Abby Dolan  4 , Meghana Sharma  2 , Carolyn Cannuscio  7
Affiliations

Consumer Views on Using Digital Data for COVID-19 Control in the United States

David Grande et al. JAMA Netw Open. .

Abstract

Importance: Curbing COVID-19 transmission is currently the greatest global public health challenge. Consumer digital tools used to collect data, such as the Apple-Google digital contact tracing program, offer opportunities to reduce COVID-19 transmission but introduce privacy concerns.

Objective: To assess uses of consumer digital information for COVID-19 control that US adults find acceptable and the factors associated with higher or lower approval of use of this information.

Design, setting, and participants: This cross-sectional survey study obtained data from a nationally representative sample of 6284 US adults recruited by email from the web-based Ipsos KnowledgePanel in July 2020. Respondents evaluated scenarios reflecting uses of digital data for COVID-19 control (case identification, digital contact tracing, policy setting, and enforcement of quarantines).

Main outcomes and measures: Levels of support for use of personal digital data in 9 scenarios to mitigate the spread of COVID-19 infection, rated on a Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Multivariable linear regression models were fitted for each scenario and included factors hypothesized to be associated with views about digital data use for COVID-19 mitigation measures. Black and Hispanic survey respondents were oversampled; thus, poststratification weights were used so that results are representative of the general US population.

Results: Of 6284 individuals invited to participate in the study, 3547 responded, for a completion rate of 56%. A total of 1762 participants (52%) were female, 715 (21%) identified as Black, 790 (23%) identified as Hispanic, and 1224 (36%) were 60 years or older; mean (SD) age was 51.7 (16.6) years. Approval of scenarios was low, ranging from 28% to 43% (52%-67% when neutral responses were included). Differences were found based on digital data source (smartphone vs social media: coefficient, 0.29 [95% CI, 0.23-0.35]; P < .001; smart thermometer vs social media: coefficient, 0.09 [95% CI, 0.03-0.16]; P = .004). County COVID-19 rates (coefficient, -0.02; 95% CI, -0.16 to 0.13 for quartile 4 compared with quartile 1) and prior family diagnosis of COVID-19 (coefficient, 0.00; 95% CI, -0.25 to 0.25) were not associated with support. Compared with self-described liberal individuals, conservative (coefficient, -0.81; 95% CI, -0.96 to -0.66; P < .001) and moderate (coefficient, -0.52; 95% CI, -0.67 to -0.38; P < .001) individuals were less likely to support the scenarios. Similarly, large political differences were observed in support of the Apple-Google digital contact tracing program, with less support from conservative (coefficient, -0.99; 95% CI, -1.11 to -0.87; P < .001) and moderate (coefficient, -0.59; 95% CI, -0.69 to -0.48; P < .001) individuals compared with liberal individuals. Respondents from racial/ethnic minority groups were more supportive of the scenarios than were White, non-Hispanic respondents. For example, compared with White respondents, Black respondents were more supportive of the Apple-Google contact tracing program (coefficient, 0.20; 95% CI, 0.07-0.32; P = .002).

Conclusions and relevance: In this survey study of US adults, many were averse to their information being used on digital platforms to mitigate transmission of COVID-19. These findings suggest that in current and future pandemics, public health departments should use multiple strategies to gain public trust and accelerate adoption of tools such as digital contact tracing applications.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Grande reported receiving grants from the National Human Genome Research Institute (NHGRI), National Institutes of Health (NIH) during the conduct of the study and receiving grants from the Robert Wood Johnson Foundation, the Patient-Centered Outcomes Research Institute, and the National Heart, Lung, and Blood Institute outside the submitted work. Dr Mitra reported receiving grants from the NIH during the conduct of the study. Ms Luna Marti reported receiving grants from the NHGRI during the conduct of the study. Dr Merchant reported receiving grants from the NIH during the conduct of the study. Dr Asch reported receiving grants from the NIH during the conduct of the study and receiving personal fees from VAL Health, Healthcare Financial Management Association, National Alliance of Health Care Purchasing Coalitions, Alliance for Continuing Education in the Health Professions, Deloitte, the American Association for Physician Leadership, and the North American Center for Continuing Medical Education outside the submitted work. Ms Dolan reported receiving grants from the NHGRI, NIH during the conduct of the study. Ms Sharma reported receiving grants from the NHGRI, NIH during the conduct of the study. Dr Cannuscio reported receiving grants from the NIH during the conduct of the study.

Figures

Figure 1.
Figure 1.. Approval for COVID-19 Digital Data Use Scenarios
The weighted distribution of responses to the 9 COVID-19 digital data use scenarios is shown.
Figure 2.
Figure 2.. Support for Apple-Google Contact Tracing Program
Adjusted probabilities of support for 3 possible variations of the Apple-Google digital contact tracing program are shown.
See this image and copyright information in PMC

References

    1. Tau B. Government tracking how people move around in coronavirus pandemic. Wall Street Journal. Published March 28, 2020. Accessed March 29, 2020. https://www.wsj.com/articles/government-tracking-how-people-move-around-...
    1. Wang CJ, Ng CY, Brook RH. Response to COVID-19 in Taiwan: big data analytics, new technology, and proactive testing. JAMA. 2020;323(14):1341-1342. doi:10.1001/jama.2020.3151 - DOI - PubMed
    1. Onishi N, Méheut C. France weighs its love of liberty in fight against coronavirus. New York Times. Published April 17, 2020. Accessed April 19, 2020. https://www.nytimes.com/2020/04/17/world/europe/coronavirus-france-digit...
    1. Mozur P, Zhong R, Krolik A. In coronavirus fight, China gives citizens a color code, with red flags. New York Times. Published March 2, 2020. Accessed April 19, 2020. https://www.nytimes.com/2020/03/01/business/china-coronavirus-surveillan...
    1. Sonn JW. Coronavirus: South Korea’s success in controlling disease is due to its acceptance of surveillance. The Conversation. Published March 19, 2020. Accessed April 16, 2020. https://theconversation.com/coronavirus-south-koreas-success-in-controll...

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