A Web-Based Digital Contact Tracing Strategy Addresses Stigma Concerns Among Individuals Evaluated for COVID-19
Introduction
The novel coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 has over 100 million confirmed cases as of February 2021.1 As cumulative cases and mortality increased, public health authorities recognized the importance of implementing contact tracing programs to minimize viral transmission.2 Contact tracing is a key public health principle for containment of transmissible diseases as it provides recent data concerning the disease burden, which may then inform actions to safeguard the public.3
To leverage information technologies in the response to the COVID-19 pandemic, public health officials and technology companies debuted a multitude of digital contact tracing initiatives, such as Bluetooth-enabled mobile phone applications, in the hopes that the swift notification of close contacts would turn the tide in this pandemic.4 The advantages of digital contact tracing are particularly noteworthy in infectious diseases such as COVID-19 in which individuals are infectious 1 to 2 days before becoming symptomatic and close contacts generally become infectious 3 to 4 days after exposure.5 While digital contact tracing is well-suited for COVID-19 transmission dynamics, data privacy has been a major barrier in the adoption of digital contact tracing programs due to concerns of government surveillance and vulnerability to hackers.5
In addition to data privacy concerns, there is growing recognition that contact tracing efforts are hindered by COVID-19 stigma.6 A recent study showed that over half of the participants reported some level of concealment in regard to their positive COVID-19 status.7 Such behavior at a population level comes at the expense of public health efforts to contain the current pandemic.
To inform more effective strategies for contact tracing programs in the era of COVID-19, this study explores the recent experiences of individuals undergoing evaluations for COVID-19 as it pertains to perceived stigma surrounding disclosure of testing to close contacts, as well as attitudes toward existing digital contact tracing services and an alternative digital contact tracing avenue via website services.
Materials and Methods
Survey Design
This study is a cross-sectional, nonrepresentative, national survey of individuals who underwent recent COVID-19 testing in the United States. Participants were recruited via Amazon Mechanical Turk (MTurk), which is an online labor marketplace that crowdsources tasks to an estimated registered workforce of 150,000 individuals.8 Originally developed to outsource tasks such as market research and media transcription, MTurk has evolved into a recruitment channel for marketing and behavioral science research as evidenced by a study showing that a third of all MTurk tasks originated from academic research groups.9,10
We surveyed individuals with recent experiences obtaining COVID-19 testing to characterize their behavior related to the notification of testing results to close contacts, and receptiveness of digital contact tracing efforts. The survey inquired about the following: demographic data, details of COVID-19 testing, experiences regarding the notification of test results to close contacts, experiences with public health contact tracing efforts, and their opinions of digital contact tracing services.
Study Participants
Participants were recruited from December 23–28, 2020, on MTurk. Inclusion criteria included the following: residence in the United States, MTurk Human Intelligence Task approval rating greater than 90%, age older than 18 years, ability to speak English, and a COVID-19 evaluation involving a nasal swab test within the past 6 weeks. Participants were excluded from this study if responses met poor effort indicators such as failing 2 of 3 attention checks or a survey completion duration below the 2.5 percentile. Furthermore, if participants submitted multiple survey responses, only the initial survey submission was included in the analysis as is standard practice in behavioral research utilizing MTurk.11
Data Collection
The survey responses were collected using a Qualtrics® survey instrument.12 Participants who met the inclusion criteria were invited to participate in the full survey. Our initial goal was to collect 500 satisfactorily completed surveys; we did not calculate a sample size as this was a hypothesis-generating study.
Data Analysis
Continuous data were summarized with medians and interquartile ranges, and statistical comparisons were made using analysis of variance (ANOVA). Categorical data were summarized with proportions, and statistical comparisons were made using Pearson chi-squared testing. Data analysis was performed in R version 4.0.4.13
This study was approved by the George Washington University Institutional Review Board (IRB# NCR203122).
Results
Demographics
A total of 3,361 participants were screened and 668 (19.9%) participants met the inclusion criteria, provided consent, and completed the survey (Fig. 1). Participants resided in 49 U.S. states, the District of Columbia, and Puerto Rico (Alaska had no participants). Participants had a median age of 33 years, with a majority identifying as female (58.1%) and white (69.8%) (Table 1). A majority possessed health insurance (88.3%), were employed (68.4%), and owned a smartphone (98.2%).
Fig. 1. Recruitment of participants.
| OVERALL | |
|---|---|
| Age (years)a | 33 (26, 43) |
| Gender | |
| Male | 272 (40.7%) |
| Female | 388 (58.1%) |
| Prefer not to say | 3 (0.4%) |
| Other | 5 (0.7%) |
| Race or ethnicity | |
| White | 466 (69.8%) |
| Black or African American | 65 (9.7%) |
| Hispanic or Latino | 58 (8.7%) |
| Asian | 49 (7.3%) |
| American Indian or Alaska Native | 6 (0.9%) |
| Native Hawaiian or Pacific Islander | 2 (0.3%) |
| Prefer not to say | 5 (0.7%) |
| Other | 17 (2.5%) |
| Marital status | |
| Married | 265 (39.7%) |
| Divorced | 49 (7.3%) |
| Separated | 11 (1.6%) |
| Widowed | 11 (1.6%) |
| Never married | 332 (49.7%) |
| Health insurance | |
| Insured | 590 (88.3%) |
| Uninsured | 78 (11.7%) |
| Level of education | |
| Advanced degree (masters, professional, or doctorate) | 102 (15.3%) |
| Bachelor’s degree | 243 (36.4%) |
| Associate degree | 71 (10.6%) |
| High school graduate or GED | 70 (10.5%) |
| Some college (no degree) | 157 (23.5%) |
| Some high school (no diploma) | 6 (0.9%) |
| Trade/technical/vocational training | 19 (2.8%) |
| Employment status | |
| Employed | 457 (68.4%) |
| Self-employed | 58 (8.7%) |
| Student | 63 (9.4%) |
| Homemaker | 13 (1.9%) |
| Retired | 15 (2.2%) |
| Military | 3 (0.4%) |
| Unable to work | 13 (1.9%) |
| Unemployed | 46 (6.9%) |
| Annual household income | |
| <$25,000 | 123 (18.4%) |
| $25,000–$50,000 | 175 (26.2%) |
| $50,000–$100,000 | 246 (36.8%) |
| $100,000–$200,000 | 104 (15.6%) |
| >$200,000 | 20 (3.0%) |
| Type of cell phone | |
| Smartphone | 656 (98.2%) |
| Not a smartphone | 11 (1.6%) |
| I do not own a cell phone | 1 (0.1%) |
COVID-19 Testing Features
A minority of participants reported having positive test results (14.2%) and had undergone a median of 2 COVID-19 evaluations with a median wait time of 2 days before receiving results; 38.6% of participants were symptomatic at the time of testing (Table 2). Among participants who tested positive for COVID-19, 63.2% interacted with a contact tracing program a median of 2 days after receiving their test results (interquartile range 2–5 days). We compared regional aspects of COVID-19 testing and contact tracing by aggregating states according to Census Bureau regions and observed that there was a significant difference in participants who reported being symptomatic at the time of COVID-19 testing between regions. Otherwise, we did not observe additional significant differences between these groups. COVID-19 positivity ranged from 8.4% to 19.9% and the median wait time for results was 2 to 3 days. Participants who tested positive for COVID-19 and had not been contacted by contact tracing programs ranged from 18.5% to 50% of cases, and the median time between test result availability and outreach from contact tracing programs ranged from 2 to 5 days.
| NORTHEAST | SOUTH | MIDWEST | WEST | TOTAL | P | |
|---|---|---|---|---|---|---|
| Lifetime number of COVID-19 evaluationsa | 2 (1, 4) | 2 (1, 3) | 2 (1, 3) | 2 (1, 3) | 2 (1, 3) | 0.521b |
| COVID-19 result | 0.036c | |||||
| Positive—the laboratory test indicated I had COVID-19 | 10 (7.5%) | 33 (13.6%) | 25 (16.4%) | 27 (19.3%) | 95 (14.2%) | |
| Negative—the laboratory test indicated I did not have COVID-19 | 123 (92.5%) | 210 (86.4%) | 127 (83.6%) | 113 (80.7%) | 573 (85.8%) | |
| Symptomatic at time of testing | <0.001c | |||||
| Yes—I had symptoms | 28 (21.1%) | 105 (43.2%) | 67 (44.1%) | 58 (41.4%) | 258 (38.6%) | |
| No—I was asymptomatic | 105 (78.9%) | 138 (56.8%) | 85 (55.9%) | 82 (58.6%) | 410 (61.4%) | |
| Days elapsed before receiving COVID-19 test resulta | 3 (1, 4) | 2 (2, 3) | 3 (1, 3) | 3 (2, 4) | 2 (1, 3) | 0.670b |
| Contacted by contact tracing program | 0.343c | |||||
| Yes | 5 (50.0%) | 18 (54.5%) | 15 (60.0%) | 22 (81.5%) | 60 (63.2%) | |
| No | 5 (50.0%) | 14 (42.4%) | 9 (36.0%) | 5 (18.5%) | 33 (34.7%) | |
| I do not know | 0 (0.0%) | 1 (3.0%) | 1 (4.0%) | 0 (0.0%) | 2 (2.1%) | |
| Days elapsed before communication from contact tracing programa | 1 (1, 3) | 2 (2, 5) | 4 (2, 6) | 2 (1, 6) | 2 (2, 5) | 0.850b |
Close Contacts and Notification Behavior
Most participants (62.1%) had close contacts before their testing, as defined by the U.S. Centers for Disease Control and Prevention (CDC) as “any individual who was within 6 feet of an infected person [or person under investigation] for at least 15 min.”14 Of the participants who had close contacts, 58.1% of participants notified all of their close contacts of the recent COVID-19 evaluation, whereas 14.5% of participants did not notify any contacts, and 92.1% notified their close contacts within 24 h of receiving their test result (Table 3). The notification methods involved text message (36.9%), phone call (27.5%), in-person (26.3%), social media (4.2%), e-mail (3.8%), and other (1.2%).
| POSITIVE—THE LABORATORY TEST INDICATED I HAD COVID-19 | NEGATIVE—THE LABORATORY TEST INDICATED I DID NOT HAVE COVID-19 | TOTAL | P | |
|---|---|---|---|---|
| Had close contacts | 0.012a | |||
| Yes | 70 (73.7%) | 345 (60.2%) | 415 (62.1%) | |
| No | 25 (26.3%) | 228 (39.8%) | 253 (37.9%) | |
| Number of close contactsb | 5 (3, 10) | 4 (2, 10) | 4 (2, 10) | 0.089c |
| % close contacts notified of COVID-19 evaluation (baseline)d | 0.102a | |||
| 0% (I did not notify my close contacts of my COVID-19 testing results) | 4 (5.7%) | 56 (16.2%) | 60 (14.5%) | |
| 1–25% | 5 (7.1%) | 32 (9.3%) | 37 (8.9%) | |
| 26–50% | 8 (11.4%) | 17 (4.9%) | 25 (6.0%) | |
| 51–75% | 5 (7.1%) | 25 (7.2%) | 30 (7.2%) | |
| 76–99% | 4 (5.7%) | 18 (5.2%) | 22 (5.3%) | |
| 100% | 44 (62.9%) | 197 (57.1%) | 241 (58.1%) | |
| Time elapsed before notification of close contacts (baseline)d (hours) | 0.099a | |||
| <1 | 33 (50.0%) | 140 (48.4%) | 173 (48.7%) | |
| 1–6 | 18 (27.3%) | 75 (26.0%) | 93 (26.2%) | |
| 6–12 | 6 (9.1%) | 33 (11.4%) | 39 (11.0%) | |
| 12–24 | 8 (12.1%) | 14 (4.8%) | 22 (6.2%) | |
| 24–48 | 1 (1.5%) | 15 (5.2%) | 16 (4.5%) | |
| >48 | 0 (0.0%) | 12 (4.2%) | 12 (3.4%) |
Digital Contact Tracing
When asked about mobile applications that provide automated and anonymous contact tracing services, 16.9% of all participants reported the prior adoption of such a service. When grouped by COVID-19 test result, a smaller proportion of participants with a negative result reported the adoption of such a mobile application compared with participants with a positive test result (15.2% vs. 27.4%, respectively; p = 0.012). Of participants who had not previously downloaded a mobile application for contact tracing, there were a greater proportion of participants who indicated interest in doing so among those with a negative test result compared with those with a positive test result (31.1% vs. 23.2%, respectively; p = 0.049). Of participants who reported not having interest in downloading a mobile application for contact tracing, only 20.9% reported they would download this service if a health care provider made this recommendation.
When asked about a website service that could provide anonymous contact tracing services, 40.3% of all participants reported they would be interested in using such a service. Of those who reported not having interest in using a website service for contact tracing, 24.1% reported they would use this service if a health care provider made this recommendation. When grouped by COVID-19 test result, a smaller proportion of participants with a positive result reported receptiveness to such a website service recommended by a health care provider compared with those with a negative test result (13.5% vs. 25.6%, respectively; p = 0.052).
In terms of overlapping interest in mobile application and website contact tracing services, 24.5% of participants reported interest in both forms of digital contact tracing, whereas 16.1% reported interest in a mobile application service but not a website service, and conversely, 14.5% reported interest in a website service but not a mobile application service (Fig. 2).
Fig. 2. Participant interest in digital contact tracing approaches.
COVID-19 Stigma
When notifying close contacts of COVID-19 test results, 30.7% reported concern about negative reactions from the recipients of their notification. When grouped by COVID-19 test result, a greater proportion of participants with a positive test result reported concern of negative reactions compared with those with a negative test result (43.9% vs. 27.7%, respectively; p = 0.01).
Of participants who reported concern about negative reactions when notifying close contacts of COVID-19 test results, 58.7% stated that an anonymous website service would decrease their concerns for negative reactions. When grouped by COVID-19 test result, a greater proportion of those with a positive test result reported decreased concerns of negative reactions with the use of a website service compared with those with a negative test result (79.3% vs. 51.2%, respectively; p = 0.028).
Effect of an Anonymous Contact Tracing Website on COVID-19 Close Contact Notifications
Participants were asked if an anonymous contact tracing website would have affected the communications of their test results to close contacts in terms of the proportion of notified close contacts and the speed of these notifications. Had an anonymous website service been available, participants reported a net increase in the proportion of close contacts who would have been notified of testing results and a net decrease in the time it would have taken to notify close contacts of testing results (Table 4).
| POTENTIAL IMPACT OF WEBSITE SERVICE | |||
|---|---|---|---|
| % NOTIFIED, BASELINE REPORT | NO CHANGE | INCREASED NOTIFICATIONS | DECREASED NOTIFICATIONS |
| 0% | 31 (52%) | 29 (48%) | NA |
| 1–25% | 24 (65%) | 10 (27%) | 3 (8%) |
| 26–50% | 17 (68%) | 8 (32%) | 0 (0%) |
| 51–75% | 16 (53%) | 10 (33%) | 4 (14%) |
| 76–99% | 14 (64%) | 6 (27%) | 2 (9%) |
| 100% | 211 (88%) | NA | 30 (12%) |
| NOTIFICATION DELAY, BASELINE REPORT (HOURS) | NO CHANGE | FASTER NOTIFICATIONS | SLOWER NOTIFICATIONS |
| <1 | 154 (89%) | NA | 19 (11%) |
| 1–6 | 48 (52%) | 38 (41%) | 7 (7%) |
| 6–12 | 21 (54%) | 14 (36%) | 4 (10%) |
| 12–24 | 7 (32%) | 15 (68%) | 0 (0%) |
| 24–48 | 6 (38%) | 9 (56%) | 1 (6%) |
Discussion
Throughout the beginning of the COVID-19 pandemic, traditional contact tracing has been relied upon as a method of close contact disclosure. In this study, 34.7% of participants diagnosed with COVID-19 were not approached by contact tracing programs. Moreover, of those who were contacted, there was a median delay of approximately 2 days (interquartile range 2–5). While the original intention of contact tracing is to minimize disease transmission, the performance of this conventional method documented in our survey falls short of expectations especially when considering the prodromal infectivity of COVID-19.15 The lack of comprehensive and timely follow-up reveals a systemic incongruity in the capacity of contact tracing programs and the caseload of positive individuals requiring counseling for containment measures.16 This becomes germane when considering that 62.1% of participants indicated they had close contacts and the median number of contacts was 4 (interquartile range 2–10). By these results, for every person who goes unnotified by contact tracing, there is an exponential uptick in the number of exposed persons who may then unknowingly expose others. This reiterates the need for contact tracing and underscores the need for alternative methods to yield more effective results.
Digital contact tracing and COVID-19 case surveillance are intended to provide real-time assessments of disease progression, although these methods have been called into question by the public, given privacy concerns.17 Among the participants in this survey, 81.3% had not downloaded mobile contact tracing applications and ∼58% of them were not interested or were reluctant to do so. However, when participants of this study were recommended to download a contact tracing mobile application by a health care provider, there was an increase in willingness of almost 20%. This demonstrates the vital public health role that health care providers can play and the importance of counseling patients on the availability of benefits of digital public health resources.
The results of this survey strongly demonstrate the need for alternative digital contact tracing strategies other than mobile applications. Considering that participants recruited on MTurk tend to be more technologically forward-leaning, the fact that only 18.7% of participants reported the adoption of mobile applications for digital contact tracing highlights the necessity for public health organizations to develop and operate a diversified portfolio of digital contact tracing services.18,19 Borrowing from the work in partner notification of sexually transmitted infections, anonymous website services that facilitate notification of COVID-19 close contacts could address the perceived privacy issues inherent in mobile applications since a website service would not require the installation of software on a personal mobile device.20 Our results showed that the availability of an anonymous website service for contact tracing would broaden the reach of digital contact tracing programs as a website service appealed to a subset of participants who were not interested in a mobile application service.
While privacy is a major barrier to contact tracing, another important barrier to address involves the stigma surrounding status disclosure. Among all participants, 30.7% reported they were concerned about negative reactions that could arise from notifying close contacts of their recent COVID-19 evaluation, and this proportion was even greater among participants who tested positive for COVID-19. Interestingly, an anonymous website service for contact tracing could effectively counter the perceived stigma surrounding the notification of close contacts of COVID-19 testing based on our findings that 58.7% of individuals who experienced stigma related to their COVID-19 evaluation stated that a website service would decrease their concern for stigma.
Lastly, our findings propose that a website service could enhance the effectiveness of contact tracing efforts as participants reported such a service would increase the proportion of close contacts notified and decrease the time to make these notifications compared with existing approaches. In light of research that suggests delays in testing and contact tracing of more than 2 days may result in COVID-19 reproduction numbers of greater than one, alternative contact tracing strategies that enable broader and more expedient forms of outreach are critically needed and anonymous website services may hold the promise improve society’s ability to contain COVID-19 and future pandemics.21
Limitations
A limitation of this study was the use of MTurk to collect online survey data. MTurk participants tend to have lower annual incomes, are younger, and are more educated, reducing the ability to obtain survey samples that are nationally representative.22 Given that all information is provided by self-report, participants may misrepresent themselves to qualify for more surveys. In addition, as participants are compensated per survey completion, participants may rush through surveys and generate poor quality data. To avoid misrepresentation, this study implemented a two-staged survey with the initial survey serving as a screener that discreetly ascertained whether participants met the inclusion criteria. To address issues of poor effort, this study implemented attention checks throughout the survey, and failure to adhere to the attention check instructions was construed as poor effort or lack of attention and resulted in discarding those submissions. Since participants self-reported their COVID-19 testing and results, we limited recruitment to individuals who underwent nasal swab testing to reduce the diagnostic uncertainties surrounding clinical and serologic antibody testing; in addition, to reduce recall bias, we limited recruitment to individuals with testing within the past 6 weeks.
Lastly, this study limited the collection of location data to the level of state of residence to avoid issues of personally identifiable information; therefore, we cannot compare the experiences of participants between urban and rural environments.
Conclusion
Contact tracing in the COVID-19 pandemic has fallen short of expectations specifically in terms of comprehensive and timely notifications of close contacts and is therefore an aspect of our public health response that requires attention. Mobile contact tracing applications and/or anonymous websites are two innovations in contact tracing that could improve close contact notification while mitigating the fear of reproach that many individuals face when dealt their COVID-19 status.
This study found that the addition of anonymous website services for contact tracing purposes has the potential to address the adoption deficiencies plaguing mobile application contact tracing services, patients under investigation are receptive to an anonymous website for close contact notification, and such website services may decrease the perceptions of stigma inherent in the disclosure of their COVID-19 status to close contacts.
Authors’ Contributions
The authors all made substantial contributions to the design, data collection, and analysis of this work; drafting of work; and final approval of the version to be published. The authors agree to be accountable for all aspects of the work.
Acknowledgment
We thank Isabel Villamor Martin for her guidance on the implementation of best practices in MTurk survey methodology.
Disclosure Statement
No competing financial interests exist.
Funding Information
The George Washington University Medical Faculty Associates provided an internal grant to support the data collection in this research study and did not have any further role in this investigation.
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