key: cord-0950171-xmyestai authors: Smith, Aaron A.; Akerson, Joie; Danahey, James; Dinh, Tam N.M.; Porter, Paul S. title: COVID‐19 drive‐through testing survey: Measuring the burden on healthcare workers date: 2020-10-15 journal: J Am Coll Emerg Physicians Open DOI: 10.1002/emp2.12286 sha: e6857593ccedabff251f02ab32d96d0d092a3832 doc_id: 950171 cord_uid: xmyestai OBJECTIVE: To survey individuals who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) at 1 of 4 Trinity Health of New England drive‐through testing centers to assess their demographic information, hospitalization rate, preexisting conditions, possible routes of exposures, duration of symptoms, and subsequent household infections of healthcare workers (HCWs) when compared to non‐HCWs. METHODS: Data were collected via a telephone survey using a standardized script. Between March 1, 2020 and June 17, 2020, 28,903 people were tested at 4 Connecticut drive‐through testing centers. Individuals who tested positive between March 16 and April 21, 2020 were randomly contacted. Of those individuals, 100 people agreed to complete the survey. Bivariate analysis and logistic regression were performed. RESULTS: HCWs comprised 46% of the 100 survey respondents during the study period. Similarly, HCWs comprised 42.1% of all individuals who tested positive and listed an employer between March 1 and June 17, 2020. HCWs reported a longer duration of symptoms (17.39 vs 13.44 days) and were more likely to report work as their route of exposure (80.4% vs 27.8%) than non‐HCWs. CONCLUSIONS: HCWs may face a disproportionate risk of contracting COVID‐19 and self‐report a longer duration of symptoms than the general public. The data suggest a need for an increased recovery time away from work than is currently recommended by the Centers for Disease Control and Prevention, as well as an increase in infection precautions for HCWs. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19), first described in Wuhan, China in December 2019. As of August 21, 2020, there have been 22.9 million confirmed cases of COVID-19 worldwide and nearly 800,000 deaths. 1 Connecticut has seen 51,519 total confirmed cases in the same period. 2 As the prevalence of COVID-19 rises, patient-facing healthcare workers (HCWs) are at a heightened risk of exposure. It has been estimated that HCWs comprised up to 19% of all COVID-19 cases in the United States. 3 A few factors contribute to the increased physical health risks HCWs assume when working with patients during the COVID-19 pandemic: asymptomatic individuals can transmit the virus, standard face masks provide insufficient protection, and at various times there were critical shortages of personal protective equipment (PPE). 4 Despite this increased risk, information on HCW infection rates and disease burden remains limited. Epidemiological and demographic information on HCWs who test positive for COVID-19 is essential for informing policies to protect those who are most vulnerable and ensure adequate sick leave and recovery time following infection, yet the current literature is lacking. Data on HCWs who are patient facing, but not on the frontline, is even scarcer. Thus, we conducted a follow-up survey of individuals who tested positive at drive-through testing centers to compare the disease burden and demographic information of HCWs when compared to the general population. This study aims to survey individuals who tested positive at 4 Trinity Health of New England drive-through testing centers to assess their demographic information, hospitalization rate, preexisting conditions, possible routes of exposures, duration of symptoms, and subsequent household infections of HCWs when compared to the general public. The Data were collected using a telephone survey tool and from Trinity Health medical records. This study focused on a predefined cohort of potential responders. Given this, the method used for selecting potential participants most closely resembled registration-based sampling (RBS), a method for conducting election polls employing a list of registered individuals that acts as a representative sample. 5 For random sampling, the phone numbers listed on medical records were exported to Microsoft Excel, and their order was randomized before calls were made. To ensure that a maximal number of potential responders were contacted, both landline and cellphone numbers were used if listed on the records. Using the study population of 1,607 individuals mentioned previously, calls were made until a sample of 100 surveys had been conducted. Only one attempt was made to call each patient, unless they answered and requested a callback. Phone calls were conducted by 5 researchers, all of whom received the same training prior to their engagement in the study. All researchers used a preapproved script for making calls and were encouraged not to deviate from the script. The survey is included in the appendix (Supporting Information). Survey respondents were asked about demographic information (sex, race, and ethnicity) as well as comorbidities, hospitalizations, subsequent household infections, and number of people who share their dwelling. Respondents were asked to identify where they believe they were exposed to COVID-19 and their answers were categorized as "Work," "Home," or "Other." Answers were categorized under the "Other" label if the location of suspected exposure was outside of the workplace and their home, such as the grocery store, a friend's house, or school, or if the location of exposure was unknown. The study classified participants as HCWs or non-HCWs based on self-identification. No distinction was made in terms of the healthcare settings (inpatient, outpatient, or private practice), interaction with patients (direct or indirect contact), or roles of participants (delivering care directly, administration, or hospitality services). Individuals who were not surveyed were also classified as HCWs or non-HCWs based on the employer listed on their records at the time of testing, if the employer was listed. To test the bivariate relationship between risk factors and HCW status, the Fisher's exact test was utilized to compare all categorical variables, and an independent samples t test was used for the continuous variables. A model of HCW-status was made using a binary logistic regression analysis. A backward stepwise elimination approach was used to Between March 1 and June 17, 2020, there were a total of 28,903 tests administered at Connecticut-based Trinity Health of New England sites. Of the study population of the 1,607 (5.6%) individuals who tested positive between March 16 and April 21, 2020, 462 (28.7%) people were called, of whom 100 (21.6%) answered and completed the survey (see Figure 1 ). Of the 100 individuals interviewed, 46 (46.0%) of respondents were HCWs, and 54 (54.0%) were non-HCWs. Fifty-four (54%) of participants were white and non-Hispanic. Of the HCWs, certified nursing assistants (CNAs) and medical assistants (MAs) constituted the largest single group, followed by registered nurses (RNs), as seen in Table 1 . There are some limitations to this study. In addition, there is the possibility of recall bias, given that participants were asked to recall details of their illness that had occurred prior to the date of the survey. In this study of 100 individuals who tested positive for SARS-CoV-2 at drive-through testing centers, almost half of the survey respondents identified as HCWs. Despite HCWs citing a longer duration of symptoms and a higher average number of household members, HCWs infected fewer people in their household after receiving their positive result than non-HCWs, as seen in Table 2 . This is not necessarily a contradiction but rather might be explained by HCWs having a higher degree of medical literacy and a better understanding of COVID-19, leading to better adherence to standard precautions and self-quarantine. Though the difference between subsequent household infections in HCWs and non-HCWs is statistically significant, the magnitude of the difference is relatively small, as is the sample size. Although it is difficult to conclude the clinical significance of this finding, it raises a question that might be worth examining in future studies. The logistic regression analysis supports the findings of the bivariate analysis, as duration of symptoms was found to be a statistically significant predictor of HCW-status. Moreover, the duration of symptoms reported by HCWs is longer than the return-to-work criteria of the CDC. At the time of writing this manuscript, the CDC recommended that HCWs with confirmed or suspected COVID-19 infections should be excluded from work for at least 3 days after recovery. 15 In this case, recovery includes resolution of fever without the use of antipyretic medications, improvement in respiratory symptoms, and a duration of at least 10 days after symptoms first appeared. This study suggests that infected HCWs may be symptomatic for longer than the minimum 10day period. Therefore, a longer minimum period of recovery time away from work may be necessary to ease the physical health burden of the pandemic on HCWs. Overall, the results from this study suggest that HCWs faced an None. Cumulative cases Connecticut COVID-19 data tracker Response Team CDC COVID-19 Response Team. Characteristics of health care personnel with COVID-19-United States Protecting health-care workers from subclinical coronavirus infection In: Lavrakas P, ed. Encyclopedia of Survey Research Methods A simulation study of the number of events per variable in logistic regression analysis Investigating selection bias of online surveys on coronavirus-related behavioral outcomes Your health care is in women's hands COVID-19 in health care workers-a systematic review and metaanalysis Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study Personal protective equipment needs in the USA during the COVID-19 pandemic Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019 Perceived infection transmission routes, infection control practices, psychosocial changes, and management of COVID-19 infected healthcare workers in a tertiary acute care hospital in Wuhan: a cross-sectional survey Criteria for return to work for healthcare personnel with suspected or confirmed COVID-19 AAS and PSP conceived the study. AAS designed the survey. AAS, JA, JD, and TNMD conducted the phone calls and collected data.AAS conducted statistical analysis. AAS, JA, JD, and TNMD wrote the manuscript. All authors contributed to editing the manuscript. PSP takes responsibility for the paper as a whole.