Changes in public preferences for technologically enhanced surveillance following the COVID-19 pandemic: a discrete choice experiment

An Overview of Data Collection in Health Preference Research

This paper focuses on survey administration and data collection methods employed for stated-preference studies in health applications. First, it describes different types of survey administration methods, encompassing web-based surveys, face-to-face (in-person) surveys, and mail surveys. Second, the concept of sampling frames is introduced, clarifying distinctions between the target population and survey frame population. The discussion then extends to different types of sampling methods, such as probability and non-probability sampling, along with an evaluation of potential issues associated with different sampling methods within the context of health preference research. Third, the paper provides information about different recruitment methods, including web-surveys, leveraging patient groups, and in-clinic recruitment. Fourth, a crucial aspect addressed is the calculation of response rate, with insights into determining an adequate response rate and strategies to improve response rates in stated-preference surveys. Lastly, the paper concludes by discussing data management plans and suggesting insights for future research in this field. In summary, this paper examines the nuanced aspects of survey administration and data collection methods in stated-preference studies, offering valuable guidance for researchers and practitioners in the health domain.

Digital public health leadership in the global fight for health security

The COVID-19 pandemic highlighted the need to prioritise mature digital health and data governance at both national and supranational levels to guarantee future health security. The Riyadh Declaration on Digital Health was a call to action to create the infrastructure needed to share effective digital health evidence-based practices and high-quality, real-time data locally and globally to provide actionable information to more health systems and countries. The declaration proposed nine key recommendations for data and digital health that need to be adopted by the global health community to address future pandemics and health threats. Here, we expand on each recommendation and provide an evidence-based roadmap for their implementation. This policy document serves as a resource and toolkit that all stakeholders in digital health and disaster preparedness can follow to develop digital infrastructure and protocols in readiness for future health threats through robust digital public health leadership.

Primary Care Physicians' and Patients' Perspectives on Equity and Health Security of Infectious Disease Digital Surveillance

PURPOSE

The coronavirus disease 2019 (COVID-19) pandemic facilitated the rapid development of digital detection surveillance (DDS) for outbreaks. This qualitative study examined how DDS for infectious diseases (ID) was perceived and experienced by primary care physicians and patients in order to highlight ethical considerations for promoting patients' autonomy and health care rights.

METHODS

In-depth interviews were conducted with a purposefully selected group of 16 primary care physicians and 24 of their patients. The group was reflective of a range of ages, educational attainment, and clinical experiences from urban areas in northern and southern China. Interviews were audio recorded, transcribed, and translated. Two researchers coded data and organized it into themes. A third researcher reviewed 15% of the data and discussed findings with the other researchers to assure accuracy.

RESULTS

Five themes were identified: ambiguity around the need for informed consent with usage of DDS; importance of autonomous decision making; potential for discrimination against vulnerable users of DDS for ID; risk of social inequity and disparate care outcomes; and authoritarian institutions' responsibility for maintaining health data security. The adoption of DDS meant some patients would be reluctant to go to the hospital for fear of either being discriminated against or forced into quarantine. Certain groups (older people and children) were thought to be vulnerable to DDS misappropriation.

CONCLUSIONS

These findings indicate the paramount importance of establishing national and international ethical frameworks for DDS implementation. Frameworks should guide all aspects of ID surveillance, addressing privacy protection and health security, and underscored by principles of social equity and accountability.Annals "Online First" article.

Population preferences for non-pharmaceutical interventions to control the SARS-CoV-2 pandemic: trade-offs among public health, individual rights, and economics

PROBLEM

Policymakers must decide on interventions to control the pandemic. These decisions are driven by weighing the risks and benefits of various non-pharmaceutical intervention alternatives. Due to the nature of the pandemic, these decisions are not based on sufficient evidence regarding the effects, nor are decision-makers informed about the willingness of populations to accept the economic and health risks associated with different policy options. This empirical study seeks to reduce uncertainty by measuring population preferences for non-pharmaceutical interventions.

METHODS

An online-based discrete choice experiment (DCE) was conducted to elicit population preferences. Respondents were asked to choose between three pandemic scenarios with different interventions and impacts of the Corona pandemic. In addition, Best-worst scaling (BWS) was used to analyze the impact of the duration of individual interventions on people's acceptance. The marginal rate of substitution was applied to estimate willingness-to-accept (WTA) for each intervention and effect by risk of infection.

RESULTS

Data from 3006 respondents were included in the analysis. The DCE showed, economic effect of non-pharmaceutical measures had a large impact on choice decisions for or against specific lockdown scenarios. Individual income decreases had the most impact. Excess mortality and individual risk of infection were also important factors influencing choice decisions. Curfews, contact restrictions, facility closures, personal data transmissions, and mandatory masking in public had a lesser impact. However, significant standard deviations in the random parameter logit model (RPL) indicated heterogeneities in the study population. The BWS results showed that short-term restrictions were more likely to be accepted than long-term restrictions. According to WTA estimates, people would be willing to accept a greater risk of infection to avoid loss of income.

DISCUSSION

The results can be used to determine which consequences of pandemic measures would be more severe for the population. For example, the results show that citizens want to limit the decline in individual income during pandemic measures. Participation in preference studies can also inform citizens about potential tradeoffs that decision-makers face in current and future decisions during a pandemic. Knowledge of the population's preferences will help inform decisions that consider people's perspectives and expectations for the future. Survey results can inform decision-makers about the extent to which the population is willing to accept certain lockdown measures, such as curfews, contact restrictions, lockdowns, or mandatory masks.

Applications of discrete choice experiments in COVID-19 research: Disparity in survey qualities between health and transport fields

Published choice experiments linked to various aspects of the COVID-19 pandemic are analysed in a rapid review. The aim is to (i) document the diversity of topics as well as their temporal and geographical patterns of emergence, (ii) compare various elements of design quality across different sectors of applied economics, and (iii) identify potential signs of convergent validity across findings of comparable experiments. Of the N = 43 published choice experiments during the first two years of the pandemic, the majority identifies with health applications (n = 30), followed by transport-related applications (n = 10). Nearly 100,000 people across the world responded to pandemic-related discrete choice surveys. Within health applications, while the dominant theme, up until June 2020, was lockdown relaxation and tracing measures, the focus shifted abruptly to vaccine preference since then. Geographical origins of the health surveys were not diverse. Nearly 50% of all health surveys were conducted in only three countries, namely US, China and The Netherlands. Health applications exhibited stronger pre-testing and larger sample sizes compared to transport applications. Limited signs of convergent validity were identifiable. Within some applications, issues of temporal instability as well as hypothetical bias attributable to social desirability, protest response or policy consequentiality seemed likely to have affected the findings. Nevertheless, very few of the experiments implemented measures of hypothetical bias mitigation and those were limited to health studies. Our main conclusion is that swift administration of pandemic-related choice experiments has overall resulted in certain degrees of compromise in study quality, but this has been more so the case in relation to transport topics than health topics.

The value of social interactions and incentives on the use of a digital contact tracing tool post COVID-19 lockdown in Singapore

We assessed the preferences and trade-offs for social interactions, incentives, and being traced by a digital contact tracing (DCT) tool post lockdown in Singapore by a discrete choice experiment (DCE) among 3839 visitors of a large public hospital in Singapore between July 2020 – February 2021. Respondents were sampled proportionately by gender and four age categories (21 – 80 years). The DCE questionnaire had three attributes (1. Social interactions, 2. Being traced by a DCT tool, 3. Incentives to use a DCT tool) and two levels each. Panel fixed conditional logit model was used to analyse the data. Respondents were more willing to trade being traced by a DCT tool for social interactions than incentives and unwilling to trade social interactions for incentives. The proportion of respondents preferring no incentives and could only be influenced by their family members increases with age. Among proponents of monetary incentives, the preferred median value for a month’s usage of DCT tools amounted to S$10 (USD7.25) and S$50 (USD36.20) for subsidies and lucky draw. In conclusion, DCE can be used to elicit profile-specific preferences to optimize the uptake of DCT tools during a pandemic. Social interactions are highly valued by the population, who are willing to trade them for being traced by a DCT tool during the COVID-19 pandemic. Although a small amount of incentive is sufficient to increase the satisfaction of using a DCT tool, incentives alone may not increase DCT tool uptake.

Learning From the Past to Improve the Future

Contact tracing apps were considered among the first tools to control the spread of COVID-19 and ease lockdown measures. While these apps can be very effective at stopping transmission and saving lives, the level of adoption remains significantly below the expected critical mass. The public debate as well as academic research about contact tracing apps emphasizes general concerns about privacy (and the associated risks) but often disregards the value-added services, as well as benefits, that can result from a larger user base. To address this gap, the study analyzes goal-congruent features as drivers for user adoption. It uses market research techniques – specifically, conjoint analysis – to study individual and group preferences and gain insights into the prescriptive design. While the results confirm the privacy-preserving design of most European contact tracing apps, they emphasize the role of value-added services in addressing heterogeneous user segments to drive user adoption. The findings thereby are of relevance for designing effective contact tracing apps, but also inform the user-oriented design of apps for health and crisis management that rely on sharing sensitive information.

Should Digital Contact Tracing Technologies be used to Control COVID-19? Perspectives from an Australian Public Deliberation

Mobile phone-based applications (apps) can promote faster targeted actions to control COVID-19. However, digital contact tracing systems raise concerns about data security, system effectiveness, and their potential to normalise privacy-invasive surveillance technologies. In the absence of mandates, public uptake depends on the acceptability and perceived legitimacy of using technologies that log interactions between individuals to build public health capacity. We report on six online deliberative workshops convened in New South Wales to consider the appropriateness of using the COVIDSafe app to enhance Australian contact tracing systems. All groups took the position (by majority) that the protections enacted in the app design and supporting legislation were appropriate. This support is contingent on several system attributes including: the voluntariness of the COVIDSafe app; that the system relies on proximity rather than location tracking; and, that data access is restricted to local public health practitioners undertaking contact tracing. Despite sustained scepticism in media coverage, there was an underlying willingness to trust Australian governing institutions such that in principle acceptance of the new contact tracing technology was easy to obtain. However, tensions between the need to prove system effectiveness through operational transparency and requirements for privacy protections could be limiting public uptake. Our study shows that informed citizens are willing to trade their privacy for common goods such as COVID-19 suppression. But low case numbers and cautionary public discourses can make trustworthiness difficult to establish because some will only do so when it can be demonstrated that the benefits justify the costs to individuals.

Ethics, Integrity, and Retributions of Digital Detection Surveillance Systems for Infectious Diseases: Systematic Literature Review

Background

The COVID-19 pandemic has increased the importance of the deployment of digital detection surveillance systems to support early warning and monitoring of infectious diseases. These opportunities create a “double-edge sword,” as the ethical governance of such approaches often lags behind technological achievements.

Objective

The aim was to investigate ethical issues identified from utilizing artificial intelligence–augmented surveillance or early warning systems to monitor and detect common or novel infectious disease outbreaks.

Methods

In a number of databases, we searched relevant articles that addressed ethical issues of using artificial intelligence, digital surveillance systems, early warning systems, and/or big data analytics technology for detecting, monitoring, or tracing infectious diseases according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, and further identified and analyzed them with a theoretical framework.

Results

This systematic review identified 29 articles presented in 6 major themes clustered under individual, organizational, and societal levels, including awareness of implementing digital surveillance, digital integrity, trust, privacy and confidentiality, civil rights, and governance. While these measures were understandable during a pandemic, the public had concerns about receiving inadequate information; unclear governance frameworks; and lack of privacy protection, data integrity, and autonomy when utilizing infectious disease digital surveillance. The barriers to engagement could widen existing health care disparities or digital divides by underrepresenting vulnerable and at-risk populations, and patients’ highly sensitive data, such as their movements and contacts, could be exposed to outside sources, impinging significantly upon basic human and civil rights.

Conclusions

Our findings inform ethical considerations for service delivery models for medical practitioners and policymakers involved in the use of digital surveillance for infectious disease spread, and provide a basis for a global governance structure.

Trial Registration

PROSPERO CRD42021259180; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=259180

United States COVID-19 Vaccination Preferences (CVP): 2020 Hindsight

Background

Shortly after the 2020 US election, initial evidence on first-generation COVID-19 vaccines showed 70–95% efficacy and minimal risks. Yet, many US adults expressed reluctance.

Aims

The aim of this study was to compare persons willing and unwilling to be vaccinated against COVID-19 and to estimate the effects of vaccination attributes on uptake: proof of vaccination, vaccination setting, effectiveness, duration of immunity, and risk of severe side effects.

Method

Between 9 and 11 November 2020, 1153 US adults completed a discrete choice experiment (DCE) on Phase 2 of the CDC Vaccination Program (August 2021). Each of its eight choice tasks had three vaccination alternatives and “no vaccination for 6 months.” An opt-out inflated logit model was estimated to test for respondent differences and attribute effects.

Results

Respondent demographics were unrelated to one’s willingness to be vaccinated (p value 0.533), but those with less education were more likely to be unwilling (p < 0.001). Among those willing, uptake ranged from 61.70 to 97.75%, depending on the vaccination attributes. Effectiveness and safety had the largest effects. Offering proof of vaccination and a choice of setting increased uptake as much as increasing immunity from 3 to 6 months.

Conclusions

To maximize uptake, the CDC Program should standardize proof of vaccination and offer a choice of setting, instead of a one-size-fits-all approach. If the first-generation vaccines are efficacious, widely available, and free, overall predicted uptake is 68.81% by the end of Phase 2 (August 2021), which is well below the 75–90% needed for herd immunity. Further health preference research is necessary to uncover and address unwillingness and reluctance to vaccinate against COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40271-021-00508-0.