Abstract
The New York City Department of Health and Mental Hygiene (DOHMH) began to actively monitor people potentially exposed to Ebola virus on October 25, 2014. Active monitoring was critical to the Ebola virus disease (EVD) response and mitigated risk without restricting individual liberties. Noncompliance with active monitoring procedures has been reported. We conducted a survey of 4,075 eligible persons to evaluate (1) the frequency of reporting of false data during active monitoring, and (2) factors associated with reporting of false temperature data. A total of 393 persons (9.6%) responded to the survey. Fifty-five (14.0%) provided false temperature data, 5 (1.3%) did not report EVD-like symptoms that they had experienced, and 2 (0.5%) did not report a hospital or emergency room visit. Having visited Liberia (OR: 3.4, 95% CI: 1.4-7.9), Sierra Leone (OR: 3.4, 95% CI: 1.6-7.5), or multiple EVD-affected countries (OR: 12.9, 95% CI: 3.5-47.7); being aged <50 years (OR: 7.5, 95% CI: 1.7-33.1); and rating the importance of active monitoring as low (OR: 1.4, 95% CI: 1.1-1.8) were associated with increased odds of reporting false temperature data. Over 10% of respondents reported providing false data during EVD active monitoring. However, it remains unclear whether reporting of false data during active monitoring impedes the ability to rapidly identify EVD cases in settings with a low burden of EVD.
The New York City Department of Health and Mental Hygiene actively monitored people potentially exposed to Ebola virus, which was critical to the EVD response and mitigated risk without restricting individual liberties. Over 10% of respondents to a survey reported providing false data during EVD active monitoring, but it remains unclear whether this impeded the ability to rapidly identify EVD cases in settings with a low burden of EVD.
T
Active monitoring was critical to the Centers for Disease Control and Prevention's (CDC) EVD response and mitigated risk without restricting individual liberties. 5 Active monitoring relies on voluntary adherence, and other jurisdictions have reported occasional noncompliance among people being actively monitored.2,6-8 Noncompliance ranged from individuals sporadically not reporting their health status or travel plans, to reporting false data or withholding certain data altogether, to refusing completely to cooperate. It is unknown whether such noncompliance had serious public health ramifications and whether it undermined the ability to rapidly detect EVD cases in settings with a low burden of EVD, such as the United States.
Quarantine for EVD can result in social isolation, stress, and stigma, but few data exist on the psychosocial impact of active monitoring or factors related to reporting of false data—particularly whether such psychosocial factors are associated with noncompliance.4,9,10 Results from a survey of people under active monitoring for EVD in Washington, DC, indicated an overall positive experience, although some respondents reported experiencing stigma and discrimination as a result of active monitoring. 11
We conducted a survey to evaluate (1) the frequency of reporting of false data during EVD active monitoring, (2) factors associated with reporting of false temperature data, and (3) the psychosocial impact of and preferences during EVD active monitoring.
Methods
Survey
The DOHMH EVD active monitoring operation has been previously described. 1 People who underwent active monitoring were categorized into 1 of 3 EVD risk categories designated by CDC: “low (but not zero) risk,” “some risk,” or “high risk.” Those classified as “low (but not zero) risk” were asked to make contact with DOHMH once a day to report temperature readings (taken twice a day), presence of symptoms consistent with EVD, plans to travel overnight outside of NYC, and hospital or emergency room visits because of an illness. Those classified as “some risk” or “high risk” were asked to make contact with DOHMH twice a day (one contact entailed direct visualization by DOHMH, such as through video conferencing technology) to report temperature readings, presence of symptoms, travel, and hospital or emergency room visits; this heightened level of active monitoring was known as “direct active monitoring.” 1 In this article, the term “active monitoring” will refer to monitoring of any individual for EVD, regardless of EVD risk category.
People eligible for the survey were aged ≥18 years; underwent EVD active monitoring by DOHMH during January 1, 2015, to December 29, 2015; and had either an email address on file or a US-based mailing address. Surveys collected data on (1) whether false data had been reported during active monitoring, and (2) the psychosocial impact of active monitoring (for full survey, see Appendix at http://online.liebertpub.com/doi/suppl/10.1089/hs.2017.0020). Surveys were administered to eligible people from November 12, 2015, to January 21, 2016, with a median duration between completing EVD active monitoring and receiving the survey of 2 months (range: 0.5-8.5 months). People for whom we had an email address on record received an internet-based survey link via email; those who did not submit a survey after 3 weeks were sent a reminder email. We sent surveys using postal mail for people with a domestic address who either did not respond to the internet-based survey or who did not have an email address on record; we made up to 3 outreach attempts for each individual. Surveys were sent in either English or French based on a person's preference during active monitoring. The only identifying information on surveys was a unique 9-digit identifier that we could use to link respondents' survey responses to data collected during EVD active monitoring; respondents were asked not to enter their names or other identifying information anywhere on the survey forms.
Data Analysis
We calculated median and interquartile range (IQR) for numeric Likert scale–based (ie, 1 to 5) survey questions, and counts and percentages for questions that did not have a Likert scale. We assessed differences between respondents and nonrespondents with a chi-square test for the following variables: EVD-affected country visited, country of citizenship, preferred language, EVD risk category (“low [but not zero]” vs “some”), median age, and gender (see Appendix).
We performed a univariate logistic regression analysis to evaluate whether sociodemographic factors, travel-related factors, or psychosocial impact related to active monitoring were associated with reporting of false temperature data. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated.
To build our multiple logistic regression model, we included variables that were statistically significant (p < 0.05) in the univariate analysis. Stepwise model selection was conducted, and scale checking was performed for the linear variables under the assumption that log odds of outcome increases by the same fixed amount anywhere on the predictor scale. Associations among predictors were evaluated using Pearson's correlations for continuous variables (r was calculated) and Pearson's chi-squared statistic (Cramér's V was calculated). To avoid multicollinearity, variables highly statistically associated with each other were not included in the final multivariable analysis; the final multivariable logistic regression model contained only the variables that were significant in the model. Crude and adjusted odds ratios and 95% confidence intervals were calculated. Hosmer and Lemeshow Goodness-of-Fit test was performed. Analyses were conducted with SAS v. 9.2 (SAS Institute Inc., Cary, NC) and R v. 3.2.1 (R Development Core Team, Vienna, Austria).
DOHMH determined that this investigation is not human subjects research, and CDC determined that this investigation is public health nonresearch.
Results
There were 4,726 unique persons who underwent EVD active monitoring by DOHMH during January 1 to December 29, 2015, none of whom were classified as “high risk,” and 4,075 (86.2%) of whom met eligibility criteria and were sent the survey; a total of 393 persons (9.6%) returned the survey and were included for analysis. There were no significant differences between respondents and nonrespondents in age and gender, but there were significant differences in EVD-affected country visited, country of citizenship, preferred language, and risk category (see Appendix Table).
Frequency of Reporting of False Data
In all, 55 respondents (14.0%) reported providing false temperature data during active monitoring, of whom 14 (25.5%) said that they did this either often or always; the most commonly reported reason (out of 9 nonmutually exclusive responses) for providing false temperature data among these 55 respondents was not taking their temperature (n = 42; 76.4%), followed by feeling that they were healthy (n = 31; 56.4%). Five respondents (1.3%) reported having experienced EVD-like symptoms that they denied having experienced when asked while being actively monitored; all 5 reported that they did not think the symptoms were related to EVD. Two respondents (0.5%) reported having gone to a hospital or emergency room, which they had denied having done when asked while being actively monitored; 1 of the 2 (50%) reported the reason for providing the false data was not knowing that he or she was supposed to tell DOHMH about the healthcare visit, and the other did not provide a reason. Finally, 10 respondents (2.5%) reported having traveled overnight outside of NYC, which they denied having done when asked while being actively monitored; 5 of these 10 (50%) reported the reason for providing false travel data was that they were not traveling far from NYC (Table 1).
Reporting of false data during Ebola virus disease active monitoring—New York City, January 1, 2015 to December 29, 2015
Note: DOHMH = Department of Health and Mental Hygiene; EVD = Ebola virus disease; NYC = New York City.
Missing data are reflected in the denominator.
Factors Associated with Reporting of False Temperature Data
Results of the univariate logistic regression analysis showed statistically significant positive associations between reporting of false temperature data and (1) having visited Liberia, Sierra Leone, or multiple EVD-affected countries (vs visiting Guinea); (2) female sex (vs male sex); (3) being aged <50 years (vs being aged 50 to 60 years); (4) among US residents (defined as people who reported living in the United States for the majority of the past year), having traveled for business- or service-related reasons (vs having traveled to visit friends or relatives); 12 (5) experiencing frustration (vs not experiencing frustration) and annoyance (vs not experiencing annoyance) as a result of being actively monitored; and (6) rating the importance of active monitoring as 1 or 2 (vs 4 or 5) on a scale of 1 (not important) to 5 (very important). These statistically significant (p < 0.05) variables were considered for the multivariable logistic regression analysis. Because “frustration” and “annoyance” were significantly associated with each other, only 1 of these variables (“annoyance”) was included in the final model (Table 2).
Factors related to reporting of false temperature data during Ebola virus disease active monitoring during univariate analysis—New York City, January 1, 2015 to December 29, 2015
Note: CI = confidence interval; DOHMH = Department of Health and Mental Hygiene; EVD = Ebola virus disease; OR = odds ratio.
Percentages are calculated for each row. Missing data are reflected in the denominator. Bold indicates statistically significant associations in which the CI does not include 1.
This question was asked only of those who were classified as United States residents.
Treated as a linear variable (ie, 1-5).
Each variable was referenced against its inverse (ie, not experiencing feelings as a result of being actively monitored).
After the stepwise multivariable logistic regression model selection was conducted, the final model included only the variables that were significant in the multivariable analysis (Table 3). The outcome variable was reporting of false temperature data. The final multivariable analysis demonstrated positive statistically significant independent associations with (1) having visited Liberia (vs Guinea: OR: 3.4, 95% CI: 1.4-7.9, p < 0.01), having visited Sierra Leone (vs Guinea: OR: 3.4, 95% CI: 1.6-7.5, p < 0.01), and having visited multiple EVD-affected countries (vs Guinea: OR: 12.9, 95% CI: 3.5-47.7, p < 0.001); (2) being aged <50 years (vs being aged 50 to 60 years: OR: 7.5, 95% CI: 1.7-33.1, p < 0.01); and (3) rating the importance of active monitoring as low (vs rating the importance as high: OR: 1.4, 95% CI: 1.1-1.8, p < 0.01). Hosmer and Lemeshow Goodness-of-Fit test showed an acceptable model fit (p > 0.05) (Table 3).
Independent factors related to reporting of false temperature data during Ebola virus disease active monitoring during multivariate analysis —New York City, January 1, 2015 to December 29, 2015
Note: CI = confidence interval; EVD = Ebola virus disease; OR = odds ratio. Only explanatory variables associated with reporting false temperature data during active monitoring significant at p < 0.05 in the univariate analysis were included in the model. Bold indicates statistically significant associations in which the CI does not include 1.
Treated as a linear variable (ie, 1-5).
Psychosocial Impact and Preferences During Active Monitoring
Respondents rated both their overall active monitoring experience and interactions with DOHMH staff as positive. They also reported being minimally worried about getting sick with EVD and minimal disruption to daily life. Annoyance, frustration, and stress were the feelings most frequently reported as a result of active monitoring. Respondents rated the prepaid cellular telephone they received on arrival in the United States as useful, and more than twice as many respondents preferred conducting active monitoring over telephone rather than via the internet. 13 When asked what respondents found useful in helping to cope with being actively monitored for EVD, the top 2 reported answers were the DOHMH active monitoring staff and support from family or friends (Table 4).
Psychosocial impact of Ebola virus disease active monitoring — New York City, January 1, 2015 to December 29, 2015
Note: DOHMH = Department of Health and Mental Hygiene; EVD = Ebola virus disease; IQR = interquartile range.
Missing data are reflected in the denominator.
Of a series of 8 reactions to the stress of EVD active monitoring that respondents were asked about, the top 3 reactions reported most frequently as occurring either “sometimes” or “often” (compared with either “not at all” or “rarely”) were (1) thinking about active monitoring when they did not want to, (2) trying not to talk about active monitoring, and (3) having waves of strong feelings about active monitoring.
Fifty-three (13.5%) respondents reported noticing a change in behavior (whether positive or negative) among noncohabiters (someone with whom they did not live). Of these 53 respondents, 19 (35.8%) reported that a noncohabiter avoided them, and 13 (24.5%) reported that a noncohabiter did not include them in or invite them to social events. In contrast, 22 (41.5%) respondents reported that noncohabiters were more supportive after learning that the respondent was being monitored for EVD, and 14 (26.4%) reported that noncohabiters helped them cope better with being monitored. Behavior changes were also perceived at the workplace, with 19 (4.8%) respondents reporting noticing a behavior change in someone at their place of employment; 15 of the 19 (78.9%) reported being told by someone at their place of employment not to come to work (Table 4).
Discussion
We report the frequency of reporting of false data during EVD active monitoring, factors related to reporting of false temperature data while being actively monitored for EVD, and the psychosocial impact of being actively monitored for EVD. The most compelling and robust finding was that more than 10% of respondents admitted to providing false data of some sort. Specifically, 14.0% of respondents admitted to having provided false temperature data during active monitoring, more than a quarter of whom reported false temperature data often or always. Others admitted to having not reported during active monitoring when they experienced EVD-like symptoms, traveled overnight outside of NYC, or went to a hospital or emergency room. It is possible that these instances of false data reporting occurred because people self-screened their risk of EVD: They believed that they did not have EVD and therefore reported false data to prevent a public health investigation. In a setting with extremely low EVD incidence, such as NYC, such self-screening will likely not threaten the overall effectiveness of active monitoring. However, increased communication to people undergoing active monitoring regarding what to expect when they report an illness might help to promote compliance with active monitoring and reduce self-screening.
Results of the multivariable analysis indicate that EVD-affected country visited, age, and rating the importance of active monitoring as low were independently associated with reporting false temperature data. It is unclear exactly why these factors may be associated with noncompliance. Regardless, these data point to an opportunity for intervention during future active monitoring operations, such as targeting communication efforts specifically toward people who have traveled to multiple EVD-affected countries and people under age 50. To promote compliance, it may also be useful to remind all people under active monitoring about the importance of active monitoring and the potential ramifications of falsifying data.
Interestingly, results of the univariate analysis indicate that the odds of reporting of false temperature data were higher among those traveling for business- or service-related reasons compared with those who traveled to visit friends or relatives. This finding is paradoxical given that some of these people who traveled for business- or service-related reasons were likely involved in some aspect of the EVD response, and one would expect them to be relatively well informed about the importance of adhering to public health recommendations; of note, this relationship lost significance after multivariable adjustment.
Another notable finding was the number of respondents who experienced workplace discrimination, with approximately 5% reporting being treated differently by someone at work, more than three-quarters of whom were told they could not come to work at all. This finding is alarming, considering that each person we monitored was told at the time of enrollment in our active monitoring program that they could continue to work even while being actively monitored (assuming they had no illness). Starting in April 2015, each person was also mailed a flyer that outlined employment rights and obligations pertaining to EVD. 14 These findings underscore that during future active monitoring operations, public health agencies could routinely inquire about workplace discrimination and help to address the situation promptly. They also highlight the dilemma for health departments of needing to educate supervisors and co-workers without infringing on the confidentiality of those under active monitoring and without inciting worry in the workplace. One potential solution is for health departments to proactively prepare informational handouts for people undergoing active monitoring to provide to their colleagues that helps reassure colleagues that the health department is working closely with them to verify that they are noninfectious.
Similarly, approximately 13% of respondents reported experiencing a behavior change among noncohabitors, corroborating results from a survey of people under EVD active monitoring in Washington, DC. 11 As with workplace discrimination due to being monitored for EVD, perceived behavior changes by noncohabitors has potential implications for the mental health of people undergoing EVD monitoring. To help reassure noncohabitors, health departments could proactively prepare informational handouts that people undergoing active montioring could distribute as needed.
An unexpected finding was that more than twice as many respondents preferred to be monitored by telephone compared with the internet. Respondents also rated the cellular telephone they received at the airport on arrival to NYC as useful. This may have been influenced by respondents' overall positive ratings of their interactions with DOHMH staff and their familiarity with DOHMH EVD active monitoring procedures, given that DOHMH conducted EVD active monitoring entirely over the telephone. While some health departments have reported positive experiences using internet or short message service–based reporting, there are inherent advantages to both methods. Given respondents' preference to be monitored by telephone and the rating of the cellular telephone they received as useful, it may be beneficial for future active monitoring programs to use both options.6,8,11,15
Overall, respondents rated their monitoring experience and interactions with DOHMH staff as positive, citing little disruption posed by active monitoring to their daily life and reporting low levels of worry about getting sick with EVD. A notable finding is the large number of respondents (39%) who cited DOHMH as helping them cope with being actively monitored, underscoring the importance of effective communication and support between those undergoing active monitoring and trained public health staff. Many respondents also rated the importance of active monitoring as high, suggesting that they heeded the messages relayed by airport-based staff and DOHMH staff. That said, some respondents also reported experiencing the negative psychological impact of being actively monitored, with more than a quarter of respondents reporting experiencing annoyance and approximately 15% reporting experiencing frustration and stress.
The higher odds of reporting of false temperature data among those indicating that they did not think it was very important to actively monitor people who recently returned from EVD-affected countries, as well as among those who reported experiencing frustration and annoyance as a result of being actively monitored, suggests that the psychosocial impact of active monitoring should be considered during future operations. Even before administering this survey, DOHMH recognized the possibility that people under active monitoring could experience stress, anxiety, or a more significant mental health emergency. Thus, we developed a protocol to refer individuals under active monitoring in need of help to a free, confidential mental health service; ultimately, we did not identify any individuals who required referral. 16 Future active monitoring programs in other jurisdictions could consider developing similar protocols to refer individuals under active monitoring to mental health services. Another possibility is to inform all individuals at the time of enrollment about the anticipated stress and anxiety of being monitored and to provide information about mental health support services.
There are several limitations inherent in our survey design. Perhaps the most significant limitation is our low response rate of 9.4%; caution should be used when interpreting our data or when making generalizations about the entire population that underwent EVD active monitoring, particularly when interpreting the findings related to psychosocial impact. Relatedly, the survey was likely prone to nonresponse bias, as those who felt compelled to complete and return the survey may have generally been more compliant with active monitoring. Moreover, the sensitive nature of the survey questions likely elicited response bias, which could mean that our results actually underrepresent frequency of reporting of false data. Also, due to data limitations, we excluded people monitored during October to December 2014, which was shortly after CDC's release of interim EVD guidance for monitoring and movement of individuals with potential exposure to EVD and which was during the height of fear in the United States, potentially biasing our results.5,17,18 Additionally, particularly for respondents who experienced an 8-month lapse between completing active monitoring and receiving the survey, recall bias is possible. Selection bias was also likely a limitation, as some groups either were less likely to receive and complete the survey (eg, people with limited access to email or who do not speak English or French) or were not sent the survey at all (eg, people residing outside of the United States). This limitation is evident in the comparison between respondents and nonrespondents, which shows significant differences between the 2 groups in EVD-country visited, citizenship, preferred language, and risk assessment.
Active monitoring was a critical component of the domestic and global EVD response and risk management framework, helping to safeguard the public while minimizing the restriction of individual liberties: Nearly 30,000 persons were actively monitored for EVD in the United States, none of whom received an EVD diagnosis, and no cases of community transmission occurred.3,5,17,18 The benefits of EVD active monitoring extend beyond a health department's ability to maximize public health by rapidly identifying imported cases. The centralization and interagency collaboration inherent in active monitoring allows health departments to monitor discreetly (rather than in a quarantine setting), to use trained public health physicians for clinical consultation (rather than primary care physicians evaluating patients in their office or in an urgent care setting), and to facilitate safe, efficient access, when appropriate, to healthcare facilities competent in managing EVD. It is possible that active monitoring will be needed for future infectious disease threats. As such, evaluating the factors related to reporting of false data and the psychosocial impact of active monitoring, as we did here, could potentially enhance the effectiveness of such programs in the future. While this survey provides definitive evidence confirming that people under active monitoring occasionally report false data, it remains unknown whether reporting of false data during active monitoring in low EVD-burden settings actually threatens the effectiveness of this countermeasure.
Footnotes
Acknowledgments
We thank the individuals who underwent active monitoring and who completed the survey, as well as all DOHMH staff involved with EVD active monitoring. We thank David Wu and Sameh Sertial for their assistance with database creation and Myla Harrison and Donald Decker for their consultation. This publication was supported by the Grant or Cooperative Agreement Number 3U90TP000546-03S2, funded by the Centers for Disease Control and Prevention. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention or the NYC Department of Health and Mental Hygiene. Use of trade names is for identification only and does not imply endorsement by any of the groups named above.
References
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
