scholarly journals Factors associated with transmission in COVID-19 outbreaks in long-term care facilities

Author(s):  
Rohit Vijh ◽  
Carmen H Ng ◽  
Mehdi Shirmaleki ◽  
Aamir Bharmal

Background: Severe acute respiratory syndrome coronavirus 2 (SARSCoV2) has had a disproportionate impact on residents in long-term care facilities (LTCFs). Through our experience and data from managing COVID-19 exposures and outbreaks in LTCFs in the Fraser Health region in British Columbia, Canada, we identified risk factors associated with outbreak severity to inform current outbreak management strategies and future pandemic preparedness planning efforts. Methods: We used a retrospective cohort study design to evaluate the association between non-modifiable factors (facility building, organization level, and resident population characteristics), modifiable factors (assessments for infection prevention and control (IPC) and public health measures), and severity of COVID-19 outbreaks (attack rate) in LTCFs. We modelled the COVID-19 attack rates in LTCF outbreaks using negative binomial regression models. Results: From March 1, 2020 to January 10, 2021, a total of 145 exposures to at least one confirmed case of COVID-19 in 82 LTCFs occurred. For every item not met in the assessment tool, a 22% increase in the attack rate was observed (rate ratio 1.2 [95% CI 1.1 to 1.4]) after adjusting for other risk factors such as age of the facility, index case type (resident vs. staff) and proportion of single bed rooms. Conclusion: Our findings highlight the importance of assessing IPC and public health measures for outbreak management. They also demonstrate the important modifiable and non-modifiable risk factors associated with COVID-19 outbreaks in our jurisdiction. We hope these findings will inform ongoing outbreak management and future pandemic planning efforts.

Antibiotics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 680
Author(s):  
Ángel Rodríguez-Villodres ◽  
Cecilia Martín-Gandul ◽  
Germán Peñalva ◽  
Ana Belén Guisado-Gil ◽  
Juan Carlos Crespo-Rivas ◽  
...  

Elderly people confined to chronic care facilities face an increased risk of acquiring infections by multidrug-resistant organisms (MDROs). This review presents the current knowledge of the prevalence and risk factors for colonization by MDROs in long-term care facilities (LTCF), thereby providing a useful reference to establish objectives for implementing successful antimicrobial stewardship programs (ASPs). We searched in PubMed and Scopus for studies examining the prevalence of MDROs and/or risk factors for the acquisition of MDROs in LTCF. One hundred and thirty-four studies published from 1987 to 2020 were included. The prevalence of MDROs in LTCF varies between the different continents, where Asia reported the highest prevalence of extended-spectrum ß-lactamase (ESBL) Enterobacterales (71.6%), carbapenem resistant (CR) Enterobacterales (6.9%) and methicillin-resistant Staphylococcus aureus (MRSA) (25.6%) and North America the highest prevalence to MDR Pseudomonas aeruginosa (5.4%), MDR Acinetobacter baumannii (15.0%), vancomycin-resistant Enterococcus spp. (VRE) (4.0%), and Clostridioides difficile (26.1%). Furthermore, MDRO prevalence has experienced changes over time, with increases in MDR P. aeruginosa and extended spectrum ß-lactamase producing Enterobacterales observed starting in 2015 and decreases of CR Enterobacterales, MDR A. baumannii, VRE, MRSA and C. difficile. Several risk factors have been found, such as male sex, chronic wounds, the use of medical devices, and previous antibiotic use. The last of these aspects represents one of the most important modifiable factors for reducing colonization with MDROs through implementing ASPs in LTCF.


2017 ◽  
Vol 1 (1) ◽  
pp. 22-32 ◽  
Author(s):  
L. O’Connor ◽  
H. Murphy ◽  
E. Montague ◽  
M. Boland

We describe seasonal influenza-like illness (ILI) outbreaks in long-term care facilities in the Health Service Executive (HSE) East area of Ireland in the 2013/2014 influenza season, risk factors associated with outbreak duration and attack rates, and management challenges. Separate questionnaires were distributed to 28 facilities who reported an outbreak and to public health specialists leading outbreak management, with a 79% response rate. Mean outbreak duration (21 vs 17 days; p=0.046) was longer in facilities with staff vaccination rates of <40%. Facilities with a high attack rate (≥50%) were less likely to have an outbreak plan (p=0.03). Smaller facilities (under 50 residents) had a higher attack rate (50% vs 23%, p=0.003) even when controlled for staff vaccination rate (p=0.01). Prior to the outbreak, resident vaccination rates were high (82%, above the World Health Organization target of 75%) but staff vaccination rates were low (39%). Reported challenges to ILI outbreak management in long term care facilities included visitor restrictions, staff education issues, outbreak notification delays and lack of outbreak lead in facilities. Targeted public health-assisted planning, training and response, comprising of staff vaccination, education, written policies, with early notification and prompt response would facilitate a more co-ordinated approach to the management of outbreaks, and reduction in infection rates and consequent morbidity.


2020 ◽  
Vol 3 (7) ◽  
pp. e2015957 ◽  
Author(s):  
David N. Fisman ◽  
Isaac Bogoch ◽  
Lauren Lapointe-Shaw ◽  
Janine McCready ◽  
Ashleigh R. Tuite

2020 ◽  
Author(s):  
Kyoung Ja Moon ◽  
Chang-Sik Son ◽  
Jong-Ha Lee ◽  
Mina Park

BACKGROUND Long-term care facilities demonstrate low levels of knowledge and care for patients with delirium and are often not properly equipped with an electronic medical record system, thereby hindering systematic approaches to delirium monitoring. OBJECTIVE This study aims to develop a web-based delirium preventive application (app), with an integrated predictive model, for long-term care (LTC) facilities using artificial intelligence (AI). METHODS This methodological study was conducted to develop an app and link it with the Amazon cloud system. The app was developed based on an evidence-based literature review and the validity of the AI prediction model algorithm. Participants comprised 206 persons admitted to LTC facilities. The app was developed in 5 phases. First, through a review of evidence-based literature, risk factors for predicting delirium and non-pharmaceutical contents for preventive intervention were identified. Second, the app, consisting of several screens, was designed; this involved providing basic information, predicting the onset of delirium according to risk factors, assessing delirium, and intervening for prevention. Third, based on the existing data, predictive analysis was performed, and the algorithm developed through this was calculated at the site linked to the web through the Amazon cloud system and sent back to the app. Fourth, a pilot test using the developed app was conducted with 33 patients. Fifth, the app was finalized. RESULTS We developed the Web_DeliPREVENT_4LCF for patients of LTC facilities. This app provides information on delirium, inputs risk factors, predicts and informs the degree of delirium risk, and enables delirium measurement or delirium prevention interventions to be immediately implemented with a verified tool. CONCLUSIONS This web-based application is evidence-based and offers easy mobilization and care to patients with delirium in LTC facilities. Therefore, the use of this app improves the unrecognized of delirium and predicts the degree of delirium risk, thereby helping initiatives for delirium prevention and providing interventions. This would ultimately improve patient safety and quality of care. CLINICALTRIAL none


2020 ◽  
Vol 41 (S1) ◽  
pp. s527-s527
Author(s):  
Gabriela Andujar-Vazquez ◽  
Kirthana Beaulac ◽  
Shira Doron ◽  
David R Snydman

Background: The Tufts Medical Center Antimicrobial Stewardship (ASP) Team has partnered with the Massachusetts Department of Public Health (MDPH) to provide broad-based educational programs (BBEP) to long-term care facilities (LTCFs) in an effort to improve ASP and infection control practices. LTCFs have consistently expressed interest in individualized and hands-on involvement by ASP experts, yet they lack resources. The goal of this study was to determine whether “enhanced” individualized guidance provided by an ASP expert would lead to antibiotic start decreases in LTCFs participating in our pilot study. Methods: A pilot study was conducted to test the feasibility and efficacy of providing enhanced ASP and infection control practices to LTCFs. In total, 10 facilities already participating in MDPH BBEP and submitting monthly antibiotic start data were enrolled, were stratified by bed size and presence of dementia unit, and were randomized 1:1 to the “enhanced” group (defined as reviewing protocols and antibiotic start cases, providing lectures and feedback to staff and answering questions) versus the “nonenhanced” group. Antibiotic start data were validated and collected prospectively from January 2018 to July 2019, and the interventions began in April 2019. Due to staff turnover and lack of engagement, intervention was not possible in 2 of the 5 LTCFs randomized to the enhanced group, which were therefore analyzed as a nonenhanced group. An incidence rate ratios (IRRs) with 95% CIs were calculated comparing the antibiotic start rate per 1,000 resident days between periods in the pilot groups. Results: The average bed sizes for enhanced groups versus nonenhanced groups were 121 (±71.0) versus 108 (±32.8); the average resident days per facility per month were 3,415.7 (±2,131.2) versus 2,911.4 (±964.3). Comparatively, 3 facilities in the enhanced group had dementia unit versus 4 in the nonenhanced group. In the per protocol analysis, the antibiotic start rate in the enhanced group before versus after the intervention was 11.35 versus 9.41 starts per 1,000 resident days (IRR, 0.829; 95% CI, 0.794–0.865). The antibiotic start rate in the nonenhanced group before versus after the intervention was 7.90 versus 8.23 antibiotic starts per 1,000 resident days (IRR, 1.048; 95% CI, 1.007–1.089). Physician hours required for ASP for the enhanced group totaled 8.9 (±2.2) per facility per month. Conclusions: Although the number of hours required for intervention by an expert was not onerous, maintaining engagement proved difficult and in 2 facilities could not be achieved. A statistically significant 20% decrease in the antibiotic start rate was achieved in the enhanced group after interventions, potentially reflecting the benefit of enhanced ASP support by an expert.Funding: This study was funded by the Leadership in Epidemiology, Antimicrobial Stewardship, and Public Health (LEAP) fellowship training grant award from the CDC.Disclosures: None


2021 ◽  
Vol 2 (3) ◽  
pp. e129-e142 ◽  
Author(s):  
Laura Shallcross ◽  
Danielle Burke ◽  
Owen Abbott ◽  
Alasdair Donaldson ◽  
Gemma Hallatt ◽  
...  

BMJ Open ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. e052282
Author(s):  
Bonita E Lee ◽  
Christopher Sikora ◽  
Douglas Faulder ◽  
Eleanor Risling ◽  
Lorie A Little ◽  
...  

IntroductionThe COVID-19 pandemic has an excessive impact on residents in long-term care facilities (LTCF), causing high morbidity and mortality. Early detection of presymptomatic and asymptomatic COVID-19 cases supports the timely implementation of effective outbreak control measures but repetitive screening of residents and staff incurs costs and discomfort. Administration of vaccines is key to controlling the pandemic but the robustness and longevity of the antibody response, correlation of neutralising antibodies with commercial antibody assays, and the efficacy of current vaccines for emerging COVID-19 variants require further study. We propose to monitor SARS-CoV-2 in site-specific sewage as an early warning system for COVID-19 in LTCF and to study the immune response of the staff and residents in LTCF to COVID-19 vaccines.Methods and analysisThe study includes two parts: (1) detection and quantification of SARS-CoV-2 in LTCF site-specific sewage samples using a molecular assay followed by notification of Public Health within 24 hours as an early warning system for appropriate outbreak investigation and control measures and cost–benefit analyses of the system and (2) testing for SARS-CoV-2 antibodies among staff and residents in LTCF at various time points before and after COVID-19 vaccination using commercial assays and neutralising antibody testing performed at a reference laboratory.Ethics and disseminationEthics approval was obtained from the University of Alberta Health Research Ethics Board with considerations to minimise risk and discomforts for the participants. Early recognition of a COVID-19 case in an LTCF might prevent further transmission in residents and staff. There was no direct benefit identified to the participants of the immunity study. Anticipated dissemination of information includes a summary report to the immunity study participants, sharing of study data with the scientific community through the Canadian COVID-19 Immunity Task Force, and prompt dissemination of study results in meeting abstracts and manuscripts in peer-reviewed journals.


2021 ◽  
pp. e1-e3
Author(s):  
R. Tamara Konetzka

Approximately 40% of all COVID-19 deaths in the United States have been linked to long-term care facilities.1 Early in the pandemic, as the scope of the problem became apparent, the nursing home sector generated significant media attention and public alarm. A New York Times article in mid-April referred to nursing homes as “death pits”2 because of the seemingly uncontrollable spread of the virus through these facilities. This devastation continued during subsequent surges,3 but there is a role for policy to change this trajectory. (Am J Public Health. Published online ahead of print January 28, 2021: e1–e3. https://doi.org/10.2105/AJPH.2020.306107 )


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