Risk Factors for SARS-CoV-2 Infection Among US Healthcare Personnel, May–December 2020

Abstract Background In 2018 we experienced a nosocomial outbreak due to vancomycin-resistant enterococci (VRE) in our hospital network. Our goals were to characterize risk factors for VRE acquisition, elicit potential hot spots of transmission, and delineate an optimized approach to tracing contacts. Methods We assembled diverse datasets of variable quality and covering different aspects of care from electronic medical records generated during the outbreak period (1/2018–9/2018). Patients who tested VRE-positive during this period were compared with controls with up to 3 negative screenings. First, we identified risk factors for VRE colonization by means of uni- and multivariate analyses. Next, we elicited transmission pathways by detecting commonalities between VRE cases, and determined whether patients with characteristics and connections similar to VRE cases were missed by our current contact tracing strategy. Results We compared 221 VRE patients to 33,624 controls. Independent predictors of VRE colonization were ICU admission (OR 4.9, with 95% confidence interval [3.7–6.5], P < 0.001)], number of records in the database (a proxy for severity-of-illness, OR 1.1 [1.1–1.1], P < 0.001), length of hospital stay (OR 2.7 [2.0–3.5], P < 0.001), age (OR 1.3 [1.2–1.4], P < 0.001), and weeks of antibiotics (OR 1.2 [1.1–1.3], P < 0.001). By using complex network analysis, we were able to establish three main pathways by which the 221 VRE cases are connected: healthcare personnel, medical devices, and patient rooms. This multi-dimensional network extends beyond our current contact tracing strategy, which captures inpatients based on geographical proximity (cf. figure). Conclusion In this outbreak investigation based on a large electronic healthcare data collection, we found three main risk factors for being a VRE carrier (ICU admission, length of hospital stay, antibiotic exposure), along with three important links between VRE cases (healthcare personnel, medical devices, patient rooms). Data science is likely to provide a better understanding of outbreaks, but interpretations should take data maturity, the scope of included sources, and potential confounding factors into account. Disclosures All authors: No reported disclosures.

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Pandemic 2009 Influenza A (H1N1) Virus among Japanese Healthcare Workers: Seroprevalence and Risk Factors

Infection Control and Hospital Epidemiology ◽

10.1086/663208 ◽

2012 ◽

Vol 33 (1) ◽

pp. 58-62 ◽

Cited By ~ 2

Author(s):

Yoko Nukui ◽

Shuji Hatakeyama ◽

Takatoshi Kitazawa ◽

Tamami Mahira ◽

Yoshizumi Shintani ◽

...

Keyword(s):

Risk Factors ◽

Healthcare Workers ◽

Influenza A ◽

H1n1 Virus ◽

Healthcare Personnel ◽

Care Hospital ◽

Occupational Risk Factors ◽

Increased Risk ◽

Influenza A H1n1 ◽

2009 H1n1

Objective.To evaluate the seroprevalence and risk factors for 2009 influenza A (H1N1) virus infection among healthcare personnel.Design.Observational cross-sectional study.Patients and Setting.Healthcare workers (HCWs) in an acute care hospital.Methods.Between September 14 and October 4, 2009, before 2009 H1N1 vaccination, we collected serological samples from 461 healthy HCWs. Hemagglutination-inhibition antibody assays were conducted. To evaluate the risk factors of seropositivity for 2009 H1N1 virus, gender, age, profession, work department, usage of personal protective equipment, and seasonal influenza vaccination status data were gathered via questionnaires.Results.Our survey showed that doctors and nurses were at highest risk of seropositivity for the 2009 H1N1 virus (odds ratio [OR], 5.25 [95% confidence interval {CI}, 1.21–22.7]). An increased risk of seropositivity was observed among pediatric, emergency room, and internal medicine staff (adjusted OR, 1.98 [95% CI, 1.07–3.65]). Risk was also higher among HCWs who had high titers of antibodies against the seasonal H1N1 virus (adjusted OR, 1.59 [95% CI, 1.02–2.48]).Conclusions.Seropositivity for the 2009 H1N1 virus was associated with occupational risk factors among HCWs.Infect Control Hosp Epidemiol 2012;33(1):58-62

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Prevalence and risk factors of female sexual dysfunction among healthcare personnel in malaysia

Comprehensive Psychiatry ◽

10.1016/j.comppsych.2013.01.009 ◽

2014 ◽

Vol 55 ◽

pp. S17-S22 ◽

Cited By ~ 11

Author(s):

Gurdeep Singh Grewal ◽

Jesjeet Singh Gill ◽

Hatta Sidi ◽

Kaur Gurpreet ◽

Stephen Thevanathan Jambunathan ◽

...

Keyword(s):

Risk Factors ◽

Sexual Dysfunction ◽

Female Sexual Dysfunction ◽

Healthcare Personnel

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Case-control study evaluating risk factors for SARS-CoV-2 outbreak amongst healthcare personnel at a tertiary care center

American Journal of Infection Control ◽

10.1016/j.ajic.2021.09.004 ◽

2021 ◽

Author(s):

Joelle I. Rosser ◽

Ralph Tayyar ◽

Richard Giardina ◽

Peter Kolonoski ◽

Diane Kenski ◽

...

Keyword(s):

Risk Factors ◽

Case Control Study ◽

Care Center ◽

Tertiary Care ◽

Case Control ◽

Healthcare Personnel ◽

Tertiary Care Center ◽

Control Study

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Risk Factors for Middle East Respiratory Syndrome Coronavirus Infection among Healthcare Personnel

Emerging Infectious Diseases ◽

10.3201/eid2211.160920 ◽

2016 ◽

Vol 22 (11) ◽

pp. 1915-1920 ◽

Cited By ~ 33

Author(s):

Basem M. Alraddadi ◽

Hanadi S. Al-Salmi ◽

Kara Jacobs-Slifka ◽

Rachel B. Slayton ◽

Concepcion F. Estivariz ◽

...

Keyword(s):

Risk Factors ◽

Middle East ◽

Middle East Respiratory Syndrome ◽

Healthcare Personnel ◽

Coronavirus Infection

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Epidemiology and risk factors of needlestick injuries among healthcare workers in Iran: a systematic reviews and meta-analysis

Environmental Health and Preventive Medicine ◽

10.1186/s12199-021-00965-x ◽

2021 ◽

Vol 26 (1) ◽

Author(s):

Soheil Hassanipour ◽

Mojtaba Sepandi ◽

Reza Tavakkol ◽

Mousa Jabbari ◽

Hadiseh Rabiei ◽

...

Keyword(s):

Risk Factors ◽

Systematic Reviews ◽

Work Experience ◽

Healthcare Workers ◽

Meta Analysis ◽

Significant Risk ◽

Female Gender ◽

Healthcare Personnel ◽

Needlestick Injuries ◽

Factors Affecting

Abstract Background Occupational contact with blood and body fluids poses a significant risk to healthcare workers. The aim of this systematic review is to investigate the epidemiology and risk factors affecting needlestick injuries (NSI) in healthcare personnel in Iran. Methods In March 2020, researchers studied six international databases such as Medline/PubMed, ProQuest, ISI/WOS, Scopus, Embase, and Google Scholar for English papers and two Iranian databases (MagIran and SID) for Persian papers. Joanna Briggs Institute (JBI) Critical Appraisal Checklist was used to assess quality of studies. The method of reporting was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. Results A total of 43 articles were included in the analysis. Results showed that females (OR = 1.30, 95 % CI 1.06–1.58, P value = 0.009), younger age (OR = 2.75, 95 % CI 2.27–3.33, P value < 0.001, rotated shift workers (OR = 2.16, 95 % CI 1.47–3.15, P value < 0.001), not attending training courses (OR = 1.30, 95 % CI 1.07–1.56, P value = 0.006), working in the surgery ward (OR = 1.83, 95 % CI 1.33–2.50, P value < 0.001), less work experience (OR = 1.43, 95 % CI 1.04–1.95, P value = 0.025) apposed a greater risk factors for NSI among healthcare workers. Conclusion Based on the results of this review, factors such as young age, less work experience, work shift, and female gender are considered as strong risk factors for NSI injury in Iran. Preventive measures including education programs can reduce the burden of NSI among healthcare personnel.

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Risk factors for transmission of carbapenem-resistant Enterobacterales to healthcare personnel gloves and gowns in the USA

Journal of Hospital Infection ◽

10.1016/j.jhin.2020.12.012 ◽

2021 ◽

Vol 109 ◽

pp. 58-64

Author(s):

L.M. O'Hara ◽

M.H. Nguyen ◽

D.P. Calfee ◽

L.G. Miller ◽

L. Pineles ◽

...

Keyword(s):

Risk Factors ◽

Healthcare Personnel ◽

Carbapenem Resistant ◽

The Usa

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Occupational Risk Factors for SARS-CoV-2 Infection among Healthcare Personnel: A Cross-Sectional Analysis of Subjects Enrolled in the COPE Study

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2021.54 ◽

2021 ◽

pp. 1-20

Author(s):

Jessica Howard-Anderson ◽

Carly Adams ◽

Amy C. Sherman ◽

William C. Dube ◽

Teresa C. Smith ◽

...

Keyword(s):

Risk Factors ◽

Occupational Risk ◽

Healthcare Personnel ◽

Cross Sectional ◽

Occupational Risk Factors ◽

Longitudinal Cohort ◽

Black Race ◽

Cross Sectional Analysis ◽

Sectional Analysis

Abstract Among 353 healthcare personnel in a longitudinal cohort in four hospitals in Atlanta, GA (May-June 2020), 23 (6.5%) had SARS-CoV-2 antibodies. Spending >50% of a typical shift at bedside (OR 3.4, 95% CI: 1.2–10.5) and Black race (OR 8.4, 95% CI: 2.7–27.4) were associated with SARS-CoV-2 seropositivity.

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SARS-CoV-2 Infection in Healthcare Personnel and Their Household Contacts at a Tertiary Academic Medical Center: Protocol for a Longitudinal Cohort Study (Preprint)

10.2196/preprints.25410 ◽

2020 ◽

Author(s):

Emily J Ciccone ◽

Paul N Zivich ◽

Evans K Lodge ◽

Deanna Zhu ◽

Elle Law ◽

...

Keyword(s):

Risk Factors ◽

Personal Protective Equipment ◽

Medical Center ◽

Academic Medical Center ◽

Tertiary Care ◽

Well Being ◽

Healthcare Personnel ◽

Protective Equipment ◽

Household Contacts ◽

Tertiary Care Medical Center

BACKGROUND Healthcare personnel are at high risk for exposure to the SARS-CoV-2 virus. While personal protective equipment may mitigate this risk, prospective data collection on its use and other risk factors for seroconversion in this population is needed. OBJECTIVE The primary objectives of this study are to (1) determine the incidence of and risk factors for SARS-CoV-2 infection among healthcare personnel at a tertiary medical center and (2) actively monitor personal protective equipment use, interactions between study participants via electronic sensors, secondary cases in households, and participant mental health and well-being. METHODS To achieve these objectives, we designed a prospective, observational study of SARS-CoV-2 infection among healthcare personnel and their household contacts at an academic tertiary care medical center. Enrolled healthcare personnel completed frequent surveys on symptoms and work activities and provided serum and nasal samples for SARS-CoV-2 testing every two weeks. Additionally, interactions between participants and their movement within the clinical environment were captured with a smartphone app and Bluetooth sensors. Finally, a subset of participants' households was randomly selected every two weeks for further investigation, and enrolled households provided serum and nasal samples via at-home collection kits. RESULTS As of September 30, 2020, 164 healthcare personnel and 33 household participants have been enrolled. Recruitment and follow-up are ongoing and expected to continue until March 2021. CONCLUSIONS Much remains to be learned regarding risk of SARS-CoV-2 infection among healthcare personnel and their household contacts. Through use of a multi-faceted study design enrolling a well-characterized cohort, we will collect critical information regarding SARS-CoV-2 transmission in the healthcare setting and its linkage to the community.

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