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1.
Lancet Digital Health ; 4(8):E573-E583, 2022.
Article in English | Web of Science | ID: covidwho-2092794

ABSTRACT

Background Real-time prediction is key to prevention and control of infections associated with health-care settings. Contacts enable spread of many infections, yet most risk prediction frameworks fail to account for their dynamics. We developed, tested, and internationally validated a real-time machine-learning framework, incorporating dynamic patient-contact networks to predict hospital-onset COVID-19 infections (HOCIs) at the individual level. Methods We report an international retrospective cohort study of our framework, which extracted patient-contact networks from routine hospital data and combined network-derived variables with clinical and contextual information to predict individual infection risk. We trained and tested the framework on HOCIs using the data from 51 157 hospital inpatients admitted to a UK National Health Service hospital group (Imperial College Healthcare NHS Trust) between April 1, 2020, and April 1, 2021, intersecting the first two COVID-19 surges. We validated the framework using data from a Swiss hospital group (Department of Rehabilitation, Geneva University Hospitals) during a COVID-19 surge (from March 1 to May 31, 2020;40 057 inpatients) and from the same UK group after COVID-19 surges (from April 2 to Aug 13, 2021;43 375 inpatients). All inpatients with a bed allocation during the study periods were included in the computation of network-derived and contextual variables. In predicting patient-level HOCI risk, only inpatients spending 3 or more days in hospital during the study period were examined for HOCI acquisition risk. Findings The framework was highly predictive across test data with all variable types (area under the curve [AUC]-receiver operating characteristic curve [ROC] 0.89 [95% CI 0.88-0.90]) and similarly predictive using only contact-network variables (0.88 [0.86-0.90]). Prediction was reduced when using only hospital contextual (AUC-ROC 0.82 [95% CI 0.80-0.84]) or patient clinical (0.64 [0.62-0.66]) variables. A model with only three variables (ie, network closeness, direct contacts with infectious patients [network derived], and hospital COVID-19 prevalence [hospital contextual]) achieved AUC-ROC 0.85 (95% CI 0.82-0.88). Incorporating contact-network variables improved performance across both validation datasets (AUC-ROC in the Geneva dataset increased from 0.84 [95% CI 0.82-0.86] to 0.88 [0.86-0.90];AUC-ROC in the UK post-surge dataset increased from 0.49 [0.46-0.52] to 0.68 [0.64-0.70]). Interpretation Dynamic contact networks are robust predictors of individual patient risk of HOCIs. Their integration in clinical care could enhance individualised infection prevention and early diagnosis of COVID-19 and other nosocomial infections. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

2.
J Hosp Infect ; 113: 104-114, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1531580

ABSTRACT

Healthcare-associated infections (HAIs) are the most common adverse outcomes due to delivery of medical care. HAIs increase morbidity and mortality, prolong hospital stay, and are associated with additional healthcare costs. Contaminated surfaces, particularly those that are touched frequently, act as reservoirs for pathogens and contribute towards pathogen transmission. Therefore, healthcare hygiene requires a comprehensive approach whereby different strategies may be implemented together, next to targeted, risk-based approaches, in order to reduce the risk of HAIs for patients. This approach includes hand hygiene in conjunction with environmental cleaning and disinfection of surfaces and clinical equipment. This review focuses on routine environmental cleaning and disinfection including areas with a moderate risk of contamination, such as general wards. As scientific evidence has not yet resulted in universally accepted guidelines nor led to universally accepted practical recommendations pertaining to surface cleaning and disinfection, this review provides expert guidance for healthcare workers in their daily practice. It also covers outbreak situations and suggests practical guidance for clinically relevant pathogens. Key elements of environmental cleaning and disinfection, including a fundamental clinical risk assessment, choice of appropriate disinfectants and cleaning equipment, definitions for standardized cleaning processes and the relevance of structured training, are reviewed in detail with a focus on practical topics and implementation.


Subject(s)
Cross Infection , Disinfectants , Cross Infection/prevention & control , Delivery of Health Care , Disinfection , Equipment Contamination/prevention & control , Humans , Hygiene
3.
Antimicrobial Resistance and Infection Control ; 10(SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1448409

ABSTRACT

Introduction: The assessment of COVID-19 associated mortality is crucial to evaluate the impact of the pandemic and to assess the effectiveness of measures. Objectives: We aimed to investigate trends in COVID-19 related mortality over time in Switzerland, using data from the COVID-19 Hospitalbased Surveillance (CH-SUR) database. Methods: Considering four different time periods of COVID-19 epidemic, we calculated crude and adjusted mortality rates and performed competing risks survival analyses for all patients and for patients admitted to intensive care (ICU). Results: Overall, 16,967 COVID-19 related hospitalizations and 2,307 deaths of adult patients were recorded. Crude hospital mortality rates were 15.6% in the 1st and 14.4% in the 2nd wave;for ICU patients it was 24% and 31.3%, respectively. The overall adjusted risk of death was lower for hospitalised patients during the 2nd compared to the 1st wave (HR 0.75, 95% CI 0.73 - 0.77). In contrast, patients admitted to ICU as well as patients with invasive ventilation presented a higher risk of death during the 2nd wave (HR 1.62, 95% CI 1.54-1.70 and HR 2.10, 95% CI 1.99-2.20, respectively). Conclusion: Our findings may be explained by various changes in the COVID-19 patient management in Swiss hospitals, e.g. with the use of effective drugs against complications or with different guidelines for ICU admission and invasive ventilation use.

4.
Antimicrobial Resistance and Infection Control ; 10(SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1448365

ABSTRACT

Introduction: LTCFs are at risk of COVID-19 outbreaks but evidence regarding SARS-CoV-2 acquisition and transmission routes among their employees remains weak. Objectives: We investigated the relative contribution of occupational (vs. community) exposure for COVID-19 acquisition among employees of a university affiliated LTCF in Switzerland, from March to June 2020. Methods: This is a prospective cohort study with a nested analysis of a COVID-19 seroprevalence study among LTCF staff. We performed Poisson regression to determine risk factors for seropositivity and to measure the influence of community vs. nosocomial exposure to COVID-19 on SARS-CoV-2 seropositivity using adjusted prevalence ratios (aPR). In addition, we conducted a COVID-19 outbreak investigation in a LTCF ward using both epidemiological and genetic sequencing data. We constructed a maximum likelihood phylogenetic tree and evaluated strain relatedness to discriminate between community- vs. hospital-acquired infections among employees. Results: Among 285 LTCF employees, we included 176 participants in the seroprevalence study, of whom 30 (17%) became seropositive for SARS-CoV-2. The majority (141/176, 80%) were healthcare workers and had ≥ 1 symptom compatible with COVID-19 (127/167, 76%). Risk factors for seropositivity included exposure to a COVID- 19 patient in the LTCF (aPR 2.6;95%CI 0.9-8.1) and exposure to a SARS-CoV-2 positive person in the community (aPR 1.7;95%CI 0.8- 3.5). Among 18 employees included in the outbreak investigation, phylogenetic analysis suggests that 8 (44%) acquired their infection in the community. Conclusion: During the first pandemic wave, there was a high burden of COVID-19 among LTCF employees. Both occupational and community exposures contributed to seropositivity and infection risk. These data may allow to better assess occupational health hazards and related legal implications during the COVID-19 pandemic. (Figure Presented).

5.
Antimicrobial Resistance and Infection Control ; 10(SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1448316

ABSTRACT

Introduction: Numerous reports of healthcare-associated COVID- 19 (HA-COVID-19) outbreaks have highlighted that hospitals can be a platform for SARS-CoV-2 transmission. Uncertainty remains with regards to clinical outcomes of patients who contracted SARS-CoV-2 in healthcare facilities compared to those hospitalized after community acquisition (CA-COVID-19). Objectives: The objective of this study was to describe and compare characteristics and clinical outcomes of patients with HA-COVID-19 versus CA-COVID-19. Methods: We used data from 16 hospitals included in the prospective national surveillance on COVID-19 in Switzerland. We included all hospitalized COVID-19 adult cases with a laboratory confirmed infection. HA-COVID-19 cases were defined as those detected > 5 days after hospital admission. Only the first hospital stay after diagnosis for CACOVID- 19 cases, and during diagnosis for HA-COVID-19 cases, were considered. Cases with no information on place of acquisition were excluded. Results: Between February and December 2020, 1'389 HA-COVID-19 cases and 9'139 CA-COVID-19 were included. HA-COVID-19 patients were older than CA-COVID-19 (median [IQR] age: 79 [70-86] versus 70 [57-80], predominantly female (48.2% versus 39.6%), and were more likely to have a Charlson comorbidity index > 4 (78.2% versus 54.9%). At the time of diagnosis, HA-COVID cases were most frequently hospitalized in general medical (570, 41%) and Geriatric/Rehabilitation wards (409, 29.4%). Length of stay was shorter for CA-COVID-19 cases (median 15, IQR [10-23] days from admission) than for HA-COVID-19 (17 [9-30] days from COVID-19 diagnosis). Fewer HA-COVID-19 patients stayed in intermediate or intensive care units (ICU) (223 [16.1%] versus 2'031 [22%] of CA-COVID-19 cases) (p < 0.001), and fewer HA-COVID-19 cases experienced any COVID-19 complications (770 (65.7%) versus 6665 (83.5%), p < 0.001). Overally, 350 (26.6%) HA-COVID-19 and 1225 (13.9%) CA-COVID-19 died. Conclusion: Patients who acquired COVID-19 within the hospital were older and more comorbid. They were less frequently transferred to the intermediate or ICU and experienced fewer COVID-19 complications, but suffered from higher rates of hospital mortality.

6.
J Hosp Infect ; 117: 124-134, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1373121

ABSTRACT

BACKGROUND: Nosocomial outbreaks of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are frequent despite implementation of conventional infection control measures. An outbreak investigation was undertaken using advanced genomic and statistical techniques to reconstruct likely transmission chains and assess the role of healthcare workers (HCWs) in SARS-CoV-2 transmission. METHODS: A nosocomial SARS-CoV-2 outbreak in a university-affiliated rehabilitation clinic was investigated, involving patients and HCWs, with high coverage of pathogen whole-genome sequences (WGS). The time-varying reproduction number from epidemiological data (Rt) was estimated, and maximum likelihood phylogeny was used to assess genetic diversity of the pathogen. Genomic and epidemiological data were combined into a Bayesian framework to model the directionality of transmission, and a case-control study was performed to investigate risk factors for nosocomial SARS-CoV-2 acquisition in patients. FINDINGS: The outbreak lasted from 14th March to 12th April 2020, and involved 37 patients (31 with WGS) and 39 employees (31 with WGS), 37 of whom were HCWs. Peak Rt was estimated to be between 2.2 and 3.6. The phylogenetic tree showed very limited genetic diversity, with 60 of 62 (96.7%) isolates forming one large cluster of identical genomes. Despite the resulting uncertainty in reconstructed transmission events, the analyses suggest that HCWs (one of whom was the index case) played an essential role in cross-transmission, with a significantly greater fraction of infections (P<2.2e-16) attributable to HCWs (70.7%) than expected given the number of HCW cases (46.7%). The excess of transmission from HCWs was higher when considering infection of patients [79.0%; 95% confidence interval (CI) 78.5-79.5%] and frail patients (Clinical Frailty Scale score >5; 82.3%; 95% CI 81.8-83.4%). Furthermore, frail patients were found to be at greater risk for nosocomial COVID-19 than other patients (adjusted odds ratio 6.94, 95% CI 2.13-22.57). INTERPRETATION: This outbreak report highlights the essential role of HCWs in SARS-CoV-2 transmission dynamics in healthcare settings. Limited genetic diversity in pathogen genomes hampered the reconstruction of individual transmission events, resulting in substantial uncertainty in who infected whom. However, this study shows that despite such uncertainty, significant transmission patterns can be observed.


Subject(s)
COVID-19 , Cross Infection , Explosive Agents , Bayes Theorem , Case-Control Studies , Cross Infection/epidemiology , Disease Outbreaks , Genomics , Health Personnel , Humans , Phylogeny , SARS-CoV-2
7.
JMIR Research Protocols ; 10(4):e26927, 2021.
Article in English | MEDLINE | ID: covidwho-1209304

ABSTRACT

BACKGROUND: The COVID-19 pandemic has brought attention to the importance of correctly using personal protective equipment (PPE). Doffing is a critical phase that increases the risk of contamination of health care workers. Although a gamified electronic learning (e-learning) module has been shown to increase the adequate choice of PPE among prehospital personnel, it failed to enhance knowledge regarding donning and doffing sequences. Adding other training modalities such as face-to-face training to these e-learning tools is therefore necessary to increase prehospital staff proficiency and thus help reduce the risk of contamination. OBJECTIVE: The aim of this study is to assess the impact of the Peyton 4-step approach in addition to a gamified e-learning module for teaching the PPE doffing sequence to first-year paramedic students. METHODS: Participants will first follow a gamified e-learning module before being randomized into one of two groups. In the control group, participants will be asked to perform a PPE doffing sequence, which will be video-recorded to allow for subsequent assessment. In the experimental group, participants will first undergo face-to-face training performed by third-year students using the Peyton 4-step approach before performing the doffing sequence themselves, which will also be video-recorded. All participants will then be asked to reconstruct the doffing sequence on an online platform. The recorded sequences will be assessed independently by two investigators: a prehospital emergency medicine expert and an infection prevention and control specialist. The assessors will be blinded to group allocation. Four to eight weeks after this first intervention, all participants will be asked to record the doffing sequence once again for a subsequent skill retention assessment and to reconstruct the sequence on the same online platform to assess knowledge retention. Finally, participants belonging to the control group will follow face-to-face training. RESULTS: The study protocol has been presented to the regional ethics committee (Req-2020-01340), which issued a declaration of no objection as such projects do not fall within the scope of the Swiss federal law on human research. Study sessions were performed in January and February 2021 in Geneva, and will be performed in April and June 2021 in Bern. CONCLUSIONS: This study should help to determine whether face-to-face training using the Peyton 4-step approach improves the application and knowledge retention of a complex procedure when combined with an e-learning module. International registered report identifier (irrid): Prr1-10.2196/26927.

9.
Rev Med Suisse ; 16(714):2153-2155, 2020.
Article in French | PubMed | ID: covidwho-918745

ABSTRACT

The older patients have been the most affected by the SARS-CoV-2 pandemic. In addition, this infection has been responsible for high mortality rate in this population. In this article we wanted to describe the clinical findings we encountered in older people with COVID-19 and share some of the issues and challenges we faced during the COVID-19 pandemic.

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