Excess risk of SARS-CoV-2 infection among in-person nonhealthcare workers in six states, September 2020-June 2021.

BACKGROUND: While the occupational risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection for healthcare personnel in the United States has been relatively well characterized, less information is available on the occupational risk for workers employed in other settings. Even fewer studies have attempted to compare risks across occupations and industries. Using differential proportionate distribution as an approximation, we evaluated excess risk of SARS-CoV-2 infection by occupation and industry among non-healthcare workers in six states. METHODS: We analyzed data on occupation and industry of employment from a six-state callback survey of adult non-healthcare workers with confirmed SARS-CoV-2 infection and population-based reference data on employment patterns, adjusted for the effect of telework, from the U.S. Bureau of Labor Statistics. We estimated the differential proportionate distribution of SARS-CoV-2 infection by occupation and industry using the proportionate morbidity ratio (PMR). RESULTS: Among a sample of 1111 workers with confirmed SARS-CoV-2 infection, significantly higher-than-expected proportions of workers were employed in service occupations (PMR 1.3, 99% confidence interval [CI] 1.1-1.5) and in the transportation and utilities (PMR 1.4, 99% CI 1.1-1.8) and leisure and hospitality industries (PMR 1.5, 99% CI 1.2-1.9). CONCLUSIONS: We found evidence of significant differences in the proportionate distribution of SARS-CoV-2 infection by occupation and industry among respondents in a multistate, population-based survey, highlighting the excess risk of SARS-CoV-2 infection borne by some worker populations, particularly those whose jobs require frequent or prolonged close contact with other people.

Reported Exposures Among In-Person Workers With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection in 6 States, September 2020-June 2021.

BACKGROUND: Surveillance systems lack detailed occupational exposure information from workers with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The National Institute for Occupational Safety and Health partnered with 6 states to collect information from adults diagnosed with SARS-CoV-2 infection who worked in person (outside the home) in non-healthcare settings during the 2 weeks prior to illness onset. METHODS: The survey captured demographic, medical, and occupational characteristics and work- and non-work-related risk factors for SARS-CoV-2 infection. Reported close contact with a person known or suspected to have SARS-CoV-2 infection was categorized by setting as exposure at work, exposure outside of work only, or no known exposure/did not know. Frequencies and percentages of exposure types are compared by respondent characteristics and risk factors. RESULTS: Of 1111 respondents, 19.4% reported exposure at work, 23.4% reported exposure outside of work only, and 57.2% reported no known exposure/did not know. Workers in protective service occupations (48.8%) and public administration industries (35.6%) reported exposure at work most often. More than one third (33.7%) of respondents who experienced close contact with ≥10 coworkers per day and 28.8% of respondents who experienced close contact with ≥10 customers/clients per day reported exposures at work. CONCLUSIONS: Exposure to occupational SARS-CoV-2 was common among respondents. Examining differences in exposures among different worker groups can help identify populations with the greatest need for prevention interventions. The benefits of recording employment characteristics as standard demographic information will remain relevant as new and reemerging public health issues occur.

COVID-19 mortality among Amalgamated Transit Union (ATU) and Transport Workers Union (TWU) workers-March-July 2020, New York City metro area.

BACKGROUND: Transit workers have jobs requiring close public contact for extended periods of time, placing them at increased risk for severe acute respiratory syndrome coronavirus 2 infection and more likely to have risk factors for coronavirus disease 2019 (COVID-19)-related complications. Collecting timely occupational data can help inform public health guidance for transit workers; however, it is difficult to collect during a public health emergency. We used nontraditional epidemiological surveillance methods to report demographics and job characteristics of transit workers reported to have died from COVID-19. METHODS: We abstracted demographic and job characteristics from media scans on COVID-19 related deaths and reviewed COVID-19 memorial pages for the Amalgamated Transit Union (ATU) and Transport Workers Union (TWU). ATU and TWU provided a list of union members who died from COVID-19 between March 1-July 7, 2020 and a total count of NYC metro area union members. Peer-reviewed publications identified through a scientific literature search were used to compile comparison demographic statistics of NYC metro area transit workers. We analyzed and reported characteristics of ATU and TWU NYC metro area decedents. RESULTS: We identified 118 ATU and TWU NYC metro area transit worker COVID-19 decedents with an incidence proportion of 0.3%. Most decedents were male (83%); median age was 58 years (range: 39-71). Median professional tenure was 20 years (range: 2-41 years). Operator (46%) was the most reported job classification. More than half of the decedents (57%) worked in positions associated with close public contact. CONCLUSION: Data gathered through nontraditional epidemiological surveillance methods provided insight into risk factors among this workforce, demonstrating the need for mitigation plans for this workforce and informing transit worker COVID-19 guidance as the pandemic progressed.

Increases in Health-Related Workplace Absenteeism Among Workers in Essential Critical Infrastructure Occupations During the COVID-19 Pandemic - United States, March-April 2020.

During a pandemic, syndromic methods for monitoring illness outside of health care settings, such as tracking absenteeism trends in schools and workplaces, can be useful adjuncts to conventional disease reporting (1,2). Each month, CDC's National Institute for Occupational Safety and Health (NIOSH) monitors the prevalence of health-related workplace absenteeism among currently employed full-time workers in the United States, overall and by demographic and occupational subgroups, using data from the Current Population Survey (CPS).* This report describes trends in absenteeism during October 2019-April 2020, including March and April 2020, the period of rapidly accelerating transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). Overall, the prevalence of health-related workplace absenteeism in March and April 2020 were similar to their 5-year baselines. However, compared with occupation-specific baselines, absenteeism among workers in several occupational groups that define or contain essential critical infrastructure workforce† categories was significantly higher than expected in April. Significant increases in absenteeism were observed in personal care and service§ (includes child care workers and personal care aides); healthcare support¶; and production** (includes meat, poultry, and fish processing workers). Although health-related workplace absenteeism remained relatively unchanged or decreased in other groups, the increase in absenteeism among workers in occupational groups less able to avoid exposure to SARS-CoV-2 (3) highlights the potential impact of COVID-19 on the essential critical infrastructure workforce because of the risks and concerns of occupational transmission of SARS-CoV-2. More widespread and complete collection of occupational data in COVID-19 surveillance is required to fully understand workers' occupational risks and inform intervention strategies. Employers should follow available recommendations to protect workers' health.

Update: Characteristics of Health Care Personnel with COVID-19 - United States, February 12-July 16, 2020.

As of September 21, 2020, the coronavirus disease 2019 (COVID-19) pandemic had resulted in 6,786,352 cases and 199,024 deaths in the United States.* Health care personnel (HCP) are essential workers at risk for exposure to patients or infectious materials (1). The impact of COVID-19 on U.S. HCP was first described using national case surveillance data in April 2020 (2). Since then, the number of reported HCP with COVID-19 has increased tenfold. This update describes demographic characteristics, underlying medical conditions, hospitalizations, and intensive care unit (ICU) admissions, stratified by vital status, among 100,570 HCP with COVID-19 reported to CDC during February 12-July 16, 2020. HCP occupation type and job setting are newly reported. HCP status was available for 571,708 (22%) of 2,633,585 cases reported to CDC. Most HCP with COVID-19 were female (79%), aged 16-44 years (57%), not hospitalized (92%), and lacked all 10 underlying medical conditions specified on the case report form† (56%). Of HCP with COVID-19, 641 died. Compared with nonfatal COVID-19 HCP cases, a higher percentage of fatal cases occurred in males (38% versus 22%), persons aged ≥65 years (44% versus 4%), non-Hispanic Asians (Asians) (20% versus 9%), non-Hispanic Blacks (Blacks) (32% versus 25%), and persons with any of the 10 underlying medical conditions specified on the case report form (92% versus 41%). From a subset of jurisdictions reporting occupation type or job setting for HCP with COVID-19, nurses were the most frequently identified single occupation type (30%), and nursing and residential care facilities were the most common job setting (67%). Ensuring access to personal protective equipment (PPE) and training, and practices such as universal use of face masks at work, wearing masks in the community, and observing social distancing remain critical strategies to protect HCP and those they serve.

Health-Related Workplace Absenteeism Among Full-Time Workers - United States, 2017-18 Influenza Season.

During an influenza pandemic and during seasonal epidemics, more persons have symptomatic illness without seeking medical care than seek treatment at doctor's offices, clinics, and hospitals (1). Consequently, surveillance based on mortality, health care encounters, and laboratory data does not reflect the full extent of influenza morbidity. CDC uses a mathematical model to estimate the total number of influenza illnesses in the United States (1). In addition, syndromic methods for monitoring illness outside health care settings, such as tracking absenteeism trends in schools and workplaces, are important adjuncts to conventional disease reporting (2). Every month, CDC's National Institute for Occupational Safety and Health (NIOSH) monitors the prevalence of health-related workplace absenteeism among full-time workers in the United States using data from the Current Population Survey (CPS) (3). This report describes the results of workplace absenteeism surveillance analyses conducted during the high-severity 2017-18 influenza season (October 2017-September 2018) (4). Absenteeism increased sharply in November, peaked in January and, at its peak, was significantly higher than the average during the previous five seasons. Persons especially affected included male workers, workers aged 45-64 years, workers living in U.S. Department of Health and Human Services (HHS) Region 6* and Region 9,† and those working in management, business, and financial; installation, maintenance, and repair; and production and related occupations. Public health authorities and employers might consider results from relevant absenteeism surveillance analyses when developing prevention messages and in pandemic preparedness planning. The most effective ways to prevent influenza transmission in the workplace include vaccination and nonpharmaceutical interventions, such as staying home when sick, covering coughs and sneezes, washing hands frequently, and routinely cleaning frequently touched surfaces (5).

Insights Into the National Institute for Occupational Safety and Health's Emergency Preparedness and Response Program.

NEHA strives to provide up-to-date and relevant information on environmental health and to build partnerships in the profession. In pursuit of these goals, we feature this column on environmental health services from the Centers for Disease Control and Prevention (CDC) in every issue of the Journal. In these columns, authors from CDC's Water, Food, and Environmental Health Services Branch, as well as guest authors, will share insights and information about environmental health programs, trends, issues, and resources. The conclusions in these columns are those of the author(s) and do not necessarily represent the official position of CDC. Kerton Victory is an environmental health specialist and emergency coordinator with the National Institute for Occupational Safety and Health's (NIOSH) Emergency Preparedness and Response Office (EPRO). Jill Shugart is a senior environmental health specialist and the Emergency Responder Health Monitoring and Surveillance coordinator with NIOSH EPRO. Sherry Burrer is a senior epidemiologist and emergency coordinator with NIOSH EPRO. Chad Dowell is the NIOSH deputy associate director for emergency preparedness and response. Lisa Delaney is the NIOSH associate director for emergency preparedness and response.

Use of Community Assessments for Public Health Emergency Response (CASPERs) to Rapidly Assess Public Health Issues - United States, 2003-2012.

INTRODUCTION: Community Assessment for Public Health Emergency Response (CASPER) is an epidemiologic technique designed to provide quick, inexpensive, accurate, and reliable household-based public health information about a community's emergency response needs. The Health Studies Branch at the Centers for Disease Control and Prevention (CDC) provides in-field assistance and technical support to state, local, tribal, and territorial (SLTT) health departments in conducting CASPERs during a disaster response and in non-emergency settings. Data from CASPERs conducted from 2003 through 2012 were reviewed to describe uses of CASPER, ascertain strengths of the CASPER methodology, and highlight significant findings. METHODS: Through an assessment of the CDC's CASPER metadatabase, all CASPERs that involved CDC support performed in US states and territories from 2003 through 2012 were reviewed and compared descriptively for differences in geographic distribution, sampling methodology, mapping tool, assessment settings, and result and action taken by decision makers. RESULTS: For the study period, 53 CASPERs were conducted in 13 states and one US territory. Among the 53 CASPERS, 38 (71.6%) used the traditional 2-stage cluster sampling methodology, 10 (18.8%) used a 3-stage cluster sampling, and two (3.7%) used a simple random sampling methodology. Among the CASPERs, 37 (69.9%) were conducted in response to specific natural or human-induced disasters, including 14 (37.8%) for hurricanes. The remaining 16 (30.1%) CASPERS were conducted in non-disaster settings to assess household preparedness levels or potential effects of a proposed plan or program. The most common recommendations resulting from a disaster-related CASPER were to educate the community on available resources (27; 72.9%) and provide services (18; 48.6%) such as debris removals and refills of medications. In preparedness CASPERs, the most common recommendations were to educate the community in disaster preparedness (5; 31.2%) and to revise or improve preparedness plans (5; 31.2%). Twenty-five (47.1%) CASPERs documented on the report or publications the public health action has taken based on the result or recommendations. Findings from 27 (50.9%) of the CASPERs conducted with CDC assistance were published in peer-reviewed journals or elsewhere. CONCLUSION: The number of CASPERs conducted with CDC assistance has increased and diversified over the past decade. The CASPERs' results and recommendations supported the public health decisions that benefitted the community. Overall, the findings suggest that the CASPER is a useful tool for collecting household-level disaster preparedness and response data and generating information to support public health action.

Reducing Public Health Risk During Disasters: Identifying Social Vulnerabilities.

All regions of the US experience disasters which result in a number of negative public health consequences. Some populations have higher levels of social vulnerability and, thus, are more likely to experience negative impacts of disasters including emotional distress, loss of property, illness, and death. To mitigate the impact of disasters on at-risk populations, emergency managers must be aware of the social vulnerabilities within their community. This paper describes a qualitative study which aimed to understand how emergency managers identify social vulnerabilities, also referred to as at-risk populations, in their populations and barriers and facilitators to current approaches. Findings suggest that although public health tools have been developed to aid emergency managers in identifying at-risk populations, they are not being used consistently. Emergency managers requested more information on the availability of tools as well as guidance on how to increase ability to identify at-risk populations.

Emergency department visit data for rapid detection and monitoring of norovirus activity, United States.

Noroviruses are the leading cause of gastroenteritis in the United States, but timely measures of disease are lacking. BioSense, a national-level electronic surveillance system, assigns data on chief complaints (patient symptoms) collected during emergency department (ED) visits to 78 subsyndromes in near real-time. In a series of linear regression models, BioSense visits mapped by chief complaints of diarrhea and nausea/vomiting subsyndromes as a monthly proportion of all visits correlated strongly with reported norovirus outbreaks from 6 states during 2007-2010. Higher correlations were seen for diarrhea (R = 0.828-0.926) than for nausea/vomiting (R = 0.729-0.866) across multiple age groups. Diarrhea ED visit proportions exhibited winter seasonality attributable to norovirus; rotavirus contributed substantially for children <5 years of age. Diarrhea ED visit data estimated the onset, peak, and end of norovirus season within 4 weeks of observed dates and could be reliable, timely indicators of norovirus activity.

Media Reports as a Tool for Timely Monitoring of COVID-19-Related Deaths Among First Responders-United States, April 2020.

We aimed to describe coronavirus disease 2019 (COVID-19) deaths among first responders early in the COVID-19 pandemic. We used media reports to gather timely information about COVID-19-related deaths among first responders during March 30-April 30, 2020, and evaluated the sensitivity of media scanning compared with traditional surveillance. We abstracted information about demographic characteristics, occupation, underlying conditions, and exposure source. Twelve of 19 US public health jurisdictions with data on reported deaths provided verification, and 7 jurisdictions reported whether additional deaths had occurred; we calculated the sensitivity of media scanning among these 7 jurisdictions. We identified 97 COVID-19-related first-responder deaths during the study period through media and jurisdiction reports. Participating jurisdictions reported 5 deaths not reported by the media. Sixty-six decedents worked in law enforcement, and 31 decedents worked in fire/emergency medical services. Media reports rarely noted underlying conditions. The media scan sensitivity was 88% (95% CI, 73%-96%) in the subset of 7 jurisdictions. Media reports demonstrated high sensitivity in documenting COVID-19-related deaths among first responders; however, information on risk factors was scarce. Routine collection of data on industry and occupation could improve understanding of COVID-19 morbidity and mortality among all workers.

Likely transmission of norovirus on an airplane, October 2008.

BACKGROUND: On 8 October 2008, members of a tour group experienced diarrhea and vomiting throughout an airplane flight from Boston, Massachusetts, to Los Angeles, California, resulting in an emergency diversion 3 h after takeoff. An investigation was conducted to determine the cause of the outbreak, assess whether transmission occurred on the airplane, and describe risk factors for transmission. METHODS: Passengers and crew were contacted to obtain information about demographics, symptoms, locations on the airplane, and possible risk factors for transmission. Case patients were defined as passengers with vomiting or diarrhea (> or =3 loose stools in 24 h) and were asked to submit stool samples for norovirus testing by real-time reverse-transcription polymerase chain reaction. RESULTS: Thirty-six (88%) of 41 tour group members were interviewed, and 15 (41%) met the case definition (peak date of illness onset, 8 October 2008). Of 106 passengers who were not tour group members, 85 (80%) were interviewed, and 7 (8%) met the case definition after the flight (peak date of illness onset, 10 October 2008). Multivariate logistic regression analysis showed that sitting in an aisle seat (adjusted relative risk, 11.0; 95% confidence interval, 1.4-84.9) and sitting near any tour group member (adjusted relative risk, 7.5; 95% confidence interval, 1.7-33.6) were associated with the development of illness. Norovirus genotype II was detected by reverse-transcription polymerase chain reaction in stool samples from case patients in both groups. CONCLUSIONS: Despite the short duration, transmission of norovirus likely occurred during the flight.

Assessment of Behavioral Health Concerns in the Community Affected by the Flint Water Crisis - Michigan (USA) 2016.

OBJECTIVES: The Flint Community Resilience Group (Flint, Michigan USA) and the Centers for Disease Control and Prevention (CDC; Atlanta, Georgia USA) assessed behavioral health concerns among community members to determine the impact of lead contamination of the Flint, Michigan water supply. METHODS: A Community Assessment for Public Health Emergency Response (CASPER) was conducted from May 17 through May 19, 2016 using a multi-stage cluster sampling design to select households and individuals to interview. RESULTS: One-half of households felt overlooked by decision makers. The majority of households self-reported that at least one member experienced more behavioral health concerns than usual. The prevalence of negative quality of life indicators and financial concerns in Flint was higher than previously reported in the Michigan 2012 and 2014 Behavioral Risk Factor Surveillance System (BRFSS) survey. CONCLUSIONS: The following can be considered to guide recovery efforts in Flint: identifying additional resources for behavioral health interventions and conducting follow-up behavioral health assessments to evaluate changes in behavioral health concerns over time; considering the impact of household economic factors when implementing behavioral health interventions; and ensuring community involvement and engagement in recovery efforts to ease community stress and anxiety. FortenberryGZ, ReynoldsP, BurrerSL, Johnson-LawrenceV, WangA, SchnallA, PullinsP, KieszakS, BayleyegnT, WolkinA. Assessment of behavioral health concerns in the community affected by the Flint water crisis - Michigan (USA) 2016. Prehosp Disaster Med. 2018;33(3):256-265.

Assessment of Impact and Recovery Needs in Communities Affected by the Elk River Chemical Spill, West Virginia, April 2014.

OBJECTIVES: In January 2014, 4-methylcyclohexanemethanol spilled into the Elk River near Charleston, West Virginia, contaminating the water supply for about 120 000 households. The West Virginia American Water Company (WVAWC) issued a "do not use" water order for 9 counties. After the order was lifted (10 days after the spill), the communities' use of public water systems, information sources, alternative sources of water, and perceived impact of the spill on households were unclear to public health officials. To assist in recovery efforts, the West Virginia Bureau for Public Health and the Centers for Disease Control and Prevention conducted a Community Assessment for Public Health Emergency Response (CASPER). METHODS: We used the CASPER 2-stage cluster sampling design to select a representative sample of households to interview, and we conducted interviews in 171 households in April 2014. We used a weighted cluster analysis to generate population estimates in the sampling frame. RESULTS: Before the spill, 74.4% of households did not have a 3-day alternative water supply for each household member and pet. Although 83.6% of households obtained an alternative water source within 1 day of the "do not use" order, 37.4% of households reportedly used WVAWC water for any purpose. Nearly 3 months after the spill, 36.1% of households believed that their WVAWC water was safe, and 33.5% reported using their household water for drinking. CONCLUSIONS: CASPER results identified the need to focus on basic public health messaging and household preparedness efforts. Recommendations included (1) encouraging households to maintain a 3-day emergency water supply, (2) identifying additional alternative sources of water for future emergencies, and (3) increasing community education to address ongoing concerns about water.

Acute Health Effects After the Elk River Chemical Spill, West Virginia, January 2014.

OBJECTIVES: On January 9, 2014, approximately 10 000 gallons of a mixture of 4-methylcyclohexanemethanol and propylene glycol phenyl ether spilled into West Virginia's Elk River, contaminating the potable water supply of about 300 000 West Virginia residents. This study sought to describe acute health effects after the chemical spill. METHODS: We conducted a descriptive analysis using 3 complementary data sources: (1) medical records of patients who visited an emergency department during January 9-23, 2014, with illness potentially related to the spill; (2) West Virginia Poison Center caller records coded as "contaminated water" during January 9-23, 2014; and (3) answers to household surveys about health effects from a Community Assessment for Public Health Emergency Response (CASPER) questionnaire administered 3 months after the spill. RESULTS: In the 2 weeks after the spill, 2000 people called the poison center reporting exposure to contaminated water, and 369 people visited emergency departments in the affected area with reports of exposure and symptoms potentially related to the spill. According to CASPER weighted cluster analyses, an estimated 25 623 households (21.7%; 95% confidence interval [CI], 14.4%-28.9%) had ≥1 person with symptoms who felt that they were related to the spill in the 3 months after it. Reported health effects across all 3 data sources included mild skin, respiratory, and gastrointestinal symptoms that resolved with no or minimal treatment. CONCLUSIONS: Medical records, poison center data, and CASPER household surveys were inexact but useful data sources to describe overall community health effects after a large-scale chemical spill. Analyzing multiple data sources could inform epidemiologic investigations of similar events.

Coding of Electronic Laboratory Reports for Biosurveillance, Selected United States Hospitals, 2011.

Objective Electronic laboratory reporting has been promoted as a public health priority. The Office of the U.S. National Coordinator for Health Information Technology has endorsed two coding systems: Logical Observation Identifiers Names and Codes (LOINC) for laboratory test orders and Systemized Nomenclature of Medicine-Clinical Terms (SNOMED CT) for test results. Materials and Methods We examined LOINC and SNOMED CT code use in electronic laboratory data reported in 2011 by 63 non-federal hospitals to BioSense electronic syndromic surveillance system. We analyzed the frequencies, characteristics, and code concepts of test orders and results. Results A total of 14,028,774 laboratory test orders or results were reported. No test orders used SNOMED CT codes. To describe test orders, 77% used a LOINC code, 17% had no value, and 6% had a non-informative value, "OTH". Thirty-three percent (33%) of test results had missing or non-informative codes. For test results with at least one informative value, 91.8% had only LOINC codes, 0.7% had only SNOMED codes, and 7.4% had both. Of 108 SNOMED CT codes reported without LOINC codes, 45% could be matched to at least one LOINC code. Conclusion Missing or non-informative codes comprised almost a quarter of laboratory test orders and a third of test results reported to BioSense by non-federal hospitals. Use of LOINC codes for laboratory test results was more common than use of SNOMED CT. Complete and standardized coding could improve the usefulness of laboratory data for public health surveillance and response.

Specificity of the tuberculin skin test and the T-SPOT.TB assay among students in a low-tuberculosis incidence setting.

OBJECTIVE: Interferon-γ release assays (IGRAs) are an important tool for detecting latent Mycobacterium tuberculosis infection (LTBI). Insufficient data exist about IGRA specificity in college health centers, most of which screen students for LTBI using the tuberculin skin test (TST). PARTICIPANTS: Students at a low-TB incidence college health center. METHODS: TST and T-SPOT.TB were performed on prospectively recruited students. TB exposure risk was assessed using a questionnaire: Those at low risk were assumed to not have LTBI in order to calculate test specificity. RESULTS: Of 184 students enrolled, 143 had results available for both TST and T-SPOT.TB. Agreement of the tests was 97% (kappa statistic 0.717; 95% confidence interval, 0.399-1.00). Among 124 low-risk students, specificity for TST and T-SPOT.TB were 98.4% and 100%, respectively. CONCLUSIONS: T-SPOT.TB specificity was high among low-risk students. Additional studies such as cost-effectiveness analyses using T-SPOT.TB as a single or confirmatory test to TST are needed to contribute to LTBI screening policy decisions.