Epidemiological data and genome sequencing reveals that nosocomial transmission of SARS-CoV-2 is underestimated and mostly mediated by a small number of highly infectious individuals

Morbidity and Mortality of Hospital-Onset SARS-CoV-2 Infections Due to Omicron Versus Prior Variants : A Propensity-Matched Analysis

BACKGROUND

Many hospitals have scaled back measures to prevent nosocomial SARS-CoV-2 infection given large decreases in the morbidity and mortality of SARS-CoV-2 infections for most people. Little is known, however, about the morbidity and mortality of nosocomial SARS-CoV-2 infections for hospitalized patients in the Omicron era.

OBJECTIVE

To estimate the effect of nosocomial SARS-CoV-2 infection on hospitalized patients' outcomes during the pre-Omicron and Omicron periods.

DESIGN

Retrospective matched cohort study.

SETTING

5 acute care hospitals in Massachusetts, December 2020 to April 2023.

PATIENTS

Adults testing positive for SARS-CoV-2 on or after hospital day 5, after negative SARS-CoV-2 test results on admission and on hospital day 3, were matched to control participants by hospital, service, time period, days since admission, and propensity scores that incorporated demographics, comorbid conditions, vaccination status, primary diagnosis category, vital signs, and laboratory test values.

MEASUREMENTS

Primary outcomes were hospital mortality and time to discharge. Secondary outcomes were intensive care unit (ICU) admission, need for advanced oxygen support, discharge destination, hospital-free days, and 30-day readmissions.

RESULTS

There were 274 cases of hospital-onset SARS-CoV-2 infection during the pre-Omicron period and 1037 cases during the Omicron period (0.17 vs. 0.49 cases per 100 admissions). Patients with hospital-onset SARS-CoV-2 infection were older and had more comorbid conditions than those without. During the pre-Omicron period, hospital-onset SARS-CoV-2 infection was associated with increased risk for ICU admission, increased need for high-flow oxygen, longer time to discharge (median difference, 4.7 days [95% CI, 2.9 to 6.6 days]), and higher mortality (risk ratio, 2.0 [CI, 1.1 to 3.8]) versus matched control participants. During the Omicron period, hospital-onset SARS-CoV-2 infection remained associated with increased risk for ICU admission and increased time to discharge (median difference, 4.2 days [CI, 3.6 to 5.0 days]). The association with increased hospital mortality was attenuated but still significant (risk ratio, 1.6 [CI, 1.2 to 2.3]).

LIMITATION

Residual confounding may be present.

CONCLUSION

Hospital-onset SARS-CoV-2 infection during the Omicron period remains associated with increased morbidity and mortality.

PRIMARY FUNDING SOURCE

Harvard Medical School Department of Population Medicine.

SARS-CoV-2 delta variant in African lions (Panthera leo) and humans at Utah's Hogle Zoo, USA, 2021-22

AIMS

We conducted a One Health investigation to assess the source and transmission dynamics of SARS-CoV-2 infection in African lions (Panthera leo) at Utah's Hogle Zoo in Salt Lake City from October 2021 to February 2022.

METHODS AND RESULTS

Following observation of respiratory illness in the lions, zoo staff collected pooled faecal samples and individual nasal swabs from four lions. All specimens tested positive for SARS-CoV-2 by reverse transcription-polymerase chain reaction (RT-PCR). The resulting investigation included: lion observation; RT-PCR testing of lion faeces every 1-7 days; RT-PCR testing of lion respiratory specimens every 2-3 weeks; staff interviews and RT-PCR testing; whole-genome sequencing of viruses from lions and staff; and comparison with existing SARS-CoV-2 human community surveillance sequences. In addition to all five lions, three staff displayed respiratory symptoms. All lions recovered and no hospitalizations or deaths were reported among staff. Three staff reported close contact with the lions in the 10 days before lion illness onset, one of whom developed symptoms and tested positive for SARS-CoV-2 on days 3 and 4, respectively, after lion illness onset. The other two did not report symptoms or test positive. Two staff who did not have close contact with the lions were symptomatic and tested positive on days 5 and 8, respectively, after lion illness onset. We detected SARS-CoV-2 RNA in lion faeces for 33 days and in lion respiratory specimens for 14 weeks after illness onset. The viruses from lions were genetically highly related to those from staff and two contemporaneous surveillance specimens from Salt Lake County; all were delta variants (AY.44).

CONCLUSIONS

We did not determine the sources of these infections, although human-to-lion transmission likely occurred. The observed period of respiratory shedding was longer than in previously documented SARS-CoV-2 infections in large felids, indicating the need to further assess duration and potential implications of shedding.

Nanopore sequencing of influenza A and B in Oxfordshire and the United Kingdom, 2022-23

OBJECTIVES

We evaluated Nanopore sequencing for influenza surveillance.

METHODS

Influenza A and B PCR-positive samples from hospital patients in Oxfordshire, UK, and a UK-wide population survey from winter 2022-23 underwent Nanopore sequencing following targeted rt-PCR amplification.

RESULTS

From 941 infections, successful sequencing was achieved in 292/388 (75 %) available Oxfordshire samples: 231 (79 %) A/H3N2, 53 (18 %) A/H1N1, and 8 (3 %) B/Victoria and in 53/113 (47 %) UK-wide samples. Sequencing was more successful at lower Ct values. Most same-sample replicate sequences had identical haemagglutinin segments (124/141, 88 %); 36/39 (92 %) Illumina vs. Nanopore comparisons were identical, and 3 (8 %) differed by 1 variant. Comparison of Oxfordshire and UK-wide sequences showed frequent inter-regional transmission. Infections were closely-related to 2022-23 vaccine strains. Only one sample had a neuraminidase inhibitor resistance mutation. 849/941 (90 %) Oxfordshire infections were community-acquired. 63/88 (72 %) potentially healthcare-associated cases shared a hospital ward with ≥ 1 known infectious case. 33 epidemiologically-plausible transmission links had sequencing data for both source and recipient: 8 were within ≤ 5 SNPs, of these, 5 (63 %) involved potential sources that were also hospital-acquired.

CONCLUSIONS

Nanopore influenza sequencing was reproducible and antiviral resistance rare. Inter-regional transmission was common; most infections were genomically similar. Hospital-acquired infections are likely an important source of nosocomial transmission and should be prioritised for infection prevention and control.

Outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 in a Rural Community Hospital during Omicron Predominance

Healthcare-associated infections due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has increased since the discovery of the Omicron variant. We describe a SARS-CoV-2 outbreak in the medicine-surgery unit of a rural community hospital at the time of high community transmission of Omicron variant in our county. The outbreak occurred in the medicine-surgery unit of an 89-bed rural community hospital in northern Maine. The characteristics of the patients and healthcare workers (HCWs) affected by the outbreak are described. Patient and HCW data collected as part of the outbreak investigation were used in this report. The outbreak control measures implemented are also described. A total of 24 people tested positive for SARS-CoV-2 including 11 patients and 13 HCWs. A total of 12 of the 24 (50%) persons were symptomatic, and rhinorrhea was the most common symptom noted (8/12, 67%). None of the symptomatic persons had gastrointestinal symptoms or symptoms of a loss of sense of smell or taste. All HCWs were vaccinated and 8 of the 11 patients were vaccinated. Outbreak control measures in the affected unit included implementation of full PPE (N95 respirators, eye protection, gowns and gloves) during all patient care, serial testing of employees and patients in the affected unit, cohorting positive patients, closing visitation and thorough environmental cleaning including use of ultraviolet (UV) light disinfection. This outbreak exemplifies the high transmissibility of the Omicron variant of SARS-CoV-2. The outbreak occurred despite a well-established infection control program. We noted that serial testing, use of N95 respirators during all patient care and UV disinfection were some of the measures that could be successful in outbreak control.

In Support of Universal Admission Testing for SARS-CoV-2 During Significant Community Transmission

Many hospitals have stopped or are considering stopping universal admission testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We discuss reasons why admission testing should still be part of a layered system to prevent hospital-acquired SARS-CoV-2 infections during times of significant community transmission. These include the morbidity of SARS-CoV-2 in vulnerable patients, the predominant contribution of presymptomatic and asymptomatic people to transmission, the high rate of transmission between patients in shared rooms, and data suggesting surveillance testing is associated with fewer nosocomial infections. Preferences of diverse patient populations, particularly the hardest-hit communities, should be surveyed and used to inform prevention measures. Hospitals' ethical responsibility to protect patients from serious infections should predominate over concerns about costs, labor, and inconvenience. We call for more rigorous data on the incidence and morbidity of nosocomial SARS-CoV-2 infections and more research to help determine when to start, stop, and restart universal admission testing and other prevention measures.

The utility of whole-genome sequencing to inform epidemiologic investigations of SARS-CoV-2 clusters in acute-care hospitals

OBJECTIVE

To evaluate the utility of selective reactive whole-genome sequencing (WGS) in aiding healthcare-associated cluster investigations.

DESIGN

Mixed-methods quality-improvement study.

SETTING

Thes study was conducted across 8 acute-care facilities in an integrated health system.

METHODS

We analyzed healthcare-associated coronavirus disease 2019 (COVID-19) clusters between May 2020 and July 2022 for which facility infection prevention and control (IPC) teams selectively requested reactive WGS to aid the epidemiologic investigation. WGS was performed with real-time results provided to IPC teams, including genetic relatedness of sequenced isolates. We conducted structured interviews with IPC teams on the informativeness of WGS for transmission investigation and prevention.

RESULTS

In total, 8 IPC teams requested WGS to aid the investigation of 17 COVID-19 clusters comprising 226 cases and 116 (51%) sequenced isolates. Of these, 16 (94%) clusters had at least 1 WGS-defined transmission event. IPC teams hypothesized transmission pathways in 14 (82%) of 17 clusters and used data visualizations to characterize these pathways in 11 clusters (65%). The teams reported that in 15 clusters (88%), WGS identified a transmission pathway; the WGS-defined pathway was not one that was predicted by epidemiologic investigation in 7 clusters (41%). WGS changed the understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in 8 clusters (47%) and altered infection prevention interventions in 8 clusters (47%).

CONCLUSIONS

Selectively utilizing reactive WGS helped identify cryptic SARS-CoV-2 transmission pathways and frequently changed the understanding and response to SARS-CoV-2 outbreaks. Until WGS is widely adopted, a selective reactive WGS approach may be highly impactful in response to healthcare-associated cluster investigations.

Assessing airborne transmission risks in COVID-19 hospitals by systematically monitoring SARS-CoV-2 in the air

IMPORTANCE

Risk management and control of airborne transmission in hospitals is crucial in response to a respiratory virus pandemic. However, the formulation of these infection control measures is often based on epidemiological investigations, which are an indirect way of analyzing the transmission route of viruses. This can lead to careless omissions in infection prevention and control or excessively restrictive measures that increase the burden on healthcare workers. The study provides a starting point for standardizing transmission risk management in designated hospitals by systemically monitoring viruses in the air of typical spaces in COVID-19 hospitals. The negative results of 359 air samples in the clean and emergency zones demonstrated the existing measures to interrupt airborne transmission in a designated COVID-19 hospital. Some positive cases in the corridor of the contaminant zone during rounds and meal delivery highlighted the importance of monitoring airborne viruses for interrupting nosocomial infection.

The burden and dynamics of hospital-acquired SARS-CoV-2 in England

Hospital-based transmission had a dominant role in Middle East respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus (SARS-CoV) epidemics1,2, but large-scale studies of its role in the SARS-CoV-2 pandemic are lacking. Such transmission risks spreading the virus to the most vulnerable individuals and can have wider-scale impacts through hospital-community interactions. Using data from acute hospitals in England, we quantify within-hospital transmission, evaluate likely pathways of spread and factors associated with heightened transmission risk, and explore the wider dynamical consequences. We estimate that between June 2020 and March 2021 between 95,000 and 167,000 inpatients acquired SARS-CoV-2 in hospitals (1% to 2% of all hospital admissions in this period). Analysis of time series data provided evidence that patients who themselves acquired SARS-CoV-2 infection in hospital were the main sources of transmission to other patients. Increased transmission to inpatients was associated with hospitals having fewer single rooms and lower heated volume per bed. Moreover, we show that reducing hospital transmission could substantially enhance the efficiency of punctuated lockdown measures in suppressing community transmission. These findings reveal the previously unrecognized scale of hospital transmission, have direct implications for targeting of hospital control measures and highlight the need to design hospitals better equipped to limit the transmission of future high-consequence pathogens.

Whole-genome sequencing to investigate transmission of SARS-CoV-2 in the acute healthcare setting: a systematic review

BACKGROUND

Whole-genome sequencing (WGS) has been used widely to elucidate transmission of SARS-CoV-2 in acute healthcare settings, and to guide infection, prevention, and control (IPC) responses.

AIM

To systematically appraise available literature, published between January 1st, 2020 and June 30th, 2022, describing the implementation of WGS in acute healthcare settings to characterize nosocomial SARS-CoV-2 transmission.

METHODS

Searches of the PubMed, Embase, Ovid MEDLINE, EBSCO MEDLINE, and Cochrane Library databases identified studies in English reporting the use of WGS to investigate SARS-CoV-2 transmission in acute healthcare environments. Publications involved data collected up to December 31st, 2021, and findings were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.

FINDINGS

In all, 3088 non-duplicate records were retrieved; 97 met inclusion criteria, involving 62 outbreak analyses and 35 genomic surveillance studies. No publications from low-income countries were identified. In 87/97 (90%), WGS supported hypotheses for nosocomial transmission, while in 46 out of 97 (47%) suspected transmission events were excluded. An IPC intervention was attributed to the use of WGS in 18 out of 97 (18%); however, only three (3%) studies reported turnaround times ≤7 days facilitating near real-time IPC action, and none reported an impact on the incidence of nosocomial COVID-19 attributable to WGS.

CONCLUSION

WGS can elucidate transmission of SARS-CoV-2 in acute healthcare settings to enhance epidemiological investigations. However, evidence was not identified to support sequencing as an intervention to reduce the incidence of SARS-CoV-2 in hospital or to alter the trajectory of active outbreaks.

Assessment of Hospital-Onset SARS-CoV-2 Infection Rates and Testing Practices in the US, 2020-2022

Importance

Characterizing the scale and factors associated with hospital-onset SARS-CoV-2 infections could help inform hospital and public health policies regarding prevention and surveillance needs for these infections.

Objective

To evaluate associations of hospital-onset SARS-CoV-2 infection rates with different periods of the COVID-19 pandemic, hospital characteristics, and testing practices.

Design, Setting, and Participants

This cohort study of US hospitals reporting SARS-CoV-2 testing data in the PINC AI Healthcare Database COVID-19 special release files was conducted from July 2020 through June 2022. Data were collected from hospitals that reported at least 1 SARS-CoV-2 reverse transcription-polymerase chain reaction or antigen test during hospitalizations discharged that month. For each hospital-month where the hospital reported sufficient data, all hospitalizations discharged in that month were included in the cohort. SARS-CoV-2 viral tests and results reported in the microbiology files for all hospitalizations in the study period by discharge month were identified. Data analysis was conducted from September 2022 to March 2023.

Exposure

Hospitalizations discharged in an included hospital-month.

Main Outcomes and Measures

Multivariable generalized estimating equation negative-binomial regression models were used to assess associations of monthly rates of hospital-onset SARS-CoV-2 infections per 1000 patient-days (defined as a first positive SARS-CoV-2 test during after hospitalization day 7) with the phase of the pandemic (defined as the predominant SARS-CoV-2 variant in circulation), admission testing rates, and hospital characteristics (hospital bed size, teaching status, urban vs rural designation, Census region, and patient distribution variables).

Results

A total of 5687 hospital-months from 288 distinct hospitals were included, which contributed 4 421 268 hospitalization records. Among 171 564 hospitalizations with a positive SARS-CoV-2 test, 7591 (4.4%) were found to be hospital onset and 6455 (3.8%) were indeterminate onset. The mean monthly hospital-onset infection rate per 1000 patient-days was 0.27 (95 CI, 0.26-0.29). Hospital-onset infections occurred in 2217 of 5687 hospital-months (39.0%). The monthly percentage of discharged patients tested for SARS-CoV-2 at admission varied; 1673 hospital-months (29.4%) had less than 25% of hospitalizations tested at admission; 2199 hospital-months (38.7%) had 25% to 50% of all hospitalizations tested, and 1815 hospital months (31.9%) had more than 50% of all hospitalizations tested at admission. Postadmission testing rates and community-onset infection rates increased with admission testing rates. In multivariable models restricted to hospital-months testing at least 25% of hospitalizations at admission, a 10% increase in community-onset SARS-CoV-2 infection rate was associated with a 178% increase in the hospital-onset infection rate (rate ratio, 2.78; 95% CI, 2.52-3.07). Additionally, the phase of the COVID-19 pandemic, the admission testing rate, Census region, and bed size were all significantly associated with hospital-onset SARS-CoV-2 infection rates.

Conclusions and Relevance

In this cohort study of hospitals reporting SARS-CoV-2 infections, there was an increase of hospital-onset SARS-CoV-2 infections when community-onset infections were higher, indicating a need for ongoing and enhanced surveillance and prevention efforts to reduce in-hospital transmission of SARS-CoV-2 infections, particularly when community-incidence of SARS-CoV-2 infections is high.

Discontinuation of Universal Admission Testing for SARS-CoV-2 and Hospital-Onset COVID-19 Infections in England and Scotland

This quality improvement study examines the association between the discontinuation of universal admission testing for SARS-CoV-2 infections and hospital-onset SARS-CoV-2 infections in England and Scotland.

Nosocomial outbreak of SARS-CoV-2 delta variant among vaccinated healthcare workers and immunocompromised patients on a solid-organ transplant unit: Complexities of an epidemiologic and genomic investigation

In September 2021, a cluster of 6 patients with nosocomial coronavirus disease 2019 (COVID-19) were identified in a transplant unit. A visitor and 11 healthcare workers also tested positive for severe acute respiratory coronavirus virus 2 (SARS-CoV-2). Genomic sequencing identified 3 separate introductions of SARS-CoV-2 with related transmission among the identified patients and healthcare workers.

SARS-CoV-2 Outbreak Investigation Using Contact Tracing and Whole-Genome Sequencing in an Ontario Tertiary Care Hospital

Genomic epidemiology can facilitate an understanding of evolutionary history and transmission dynamics of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak. We used next-generation sequencing techniques to study SARS-CoV-2 genomes isolated from patients and health care workers (HCWs) across five wards of a Canadian hospital with an ongoing SARS-CoV-2 outbreak. Using traditional contact tracing methods, we show transmission events between patients and HCWs, which were also supported by the SARS-CoV-2 lineage assignments. The outbreak predominantly involved SARS-CoV-2 B.1.564.1 across all five wards, but we also show evidence of community introductions of lineages B.1, B.1.1.32, and B.1.231, falsely assumed to be outbreak related. Altogether, our study exemplifies the value of using contact tracing in combination with genomic epidemiology to understand the transmission dynamics and genetic underpinnings of a SARS-CoV-2 outbreak. IMPORTANCE Our manuscript describes a SARS-CoV-2 outbreak investigation in an Ontario tertiary care hospital. We use traditional contract tracing paired with whole-genome sequencing to facilitate an understanding of the evolutionary history and transmission dynamics of this SARS-CoV-2 outbreak in a clinical setting. These advancements have enabled the incorporation of phylogenetics and genomic epidemiology into the understanding of clinical outbreaks. We show that genomic epidemiology can help to explore the genetic evolution of a pathogen in real time, enabling the identification of the index case and helping understand its transmission dynamics to develop better strategies to prevent future spread of SARS-CoV-2 in congregate, clinical settings such as hospitals.

Combining epidemiological data and whole genome sequencing to understand SARS-CoV-2 transmission dynamics in a large tertiary care hospital during the first COVID-19 wave in The Netherlands focusing on healthcare workers

BACKGROUND

Healthcare facilities have been challenged by the risk of SARS-CoV-2 transmission between healthcare workers (HCW) and patients. During the first wave of the COVID-19 pandemic, infections among HCW were observed, questioning infection prevention and control (IPC) measures implemented at that time.

AIM

This study aimed to identify nosocomial transmission routes of SARS-CoV-2 between HCW and patients in a tertiary care hospital.

METHODS

All SARS-CoV-2 PCR positive HCW and patients identified between 1 March and 19 May 2020, were included in the analysis. Epidemiological data were collected from patient files and HCW contact tracing interviews. Whole genome sequences of SARS-CoV-2 were generated using Nanopore sequencing (WGS). Epidemiological clusters were identified, whereafter WGS and epidemiological data were combined for re-evaluation of epidemiological clusters and identification of potential transmission clusters. HCW infections were further classified into categories based on the likelihood that the infection was acquired via nosocomial transmission. Secondary cases were defined as COVID-19 cases in our hospital, part of a transmission cluster, of which the index case was either a patient or HCW from our hospital.

FINDINGS

The study population consisted of 293 HCW and 245 patients. Epidemiological data revealed 36 potential epidemiological clusters, with an estimated 222 (75.7%) HCW as secondary cases. WGS results were available for 195 HCW (88.2%) and 20 patients (12.8%) who belonged to an epidemiological cluster. Re-evaluation of the epidemiological clusters, with the available WGS data identified 31 transmission clusters with 65 (29.4%) HCW as secondary cases. Transmission clusters were all part of 18 (50.0%) previously determined epidemiological clusters, demonstrating that several larger outbreaks actually consisted, of several smaller transmission clusters. A total of 21 (7.2%) HCW infections were classified as from confirmed nosocomial, of which 18 were acquired from another HCW and 3 from a patient.

CONCLUSION

The majority of SARS-CoV-2 infections among HCW could be attributed to community-acquired infection. Infections among HCW that could be classified as due to nosocomial transmission, were mainly caused by HCW-to-HCW transmission rather than patient-to-HCW transmission. It is important to recognize the uncertainties of cluster analyses based solely on epidemiological data.

Risk factors for nosocomial COVID-19 in a French university hospital

OBJECTIVES

Prevention strategies implemented by hospitals to reduce nosocomial transmission of SARS-CoV-2 sometimes failed. Our aim was to determine the risk factors for nosocomial COVID-19.

PATIENTS AND METHODS

A case-control study was conducted (September 1, 2020-January 31, 2021) with adult patients hospitalized in medical or surgical units. Infants or patients hospitalized in ICU were excluded. Cases were patients with nosocomial COVID-19 (clinical symptoms and RT-PCR+ for SARS-CoV-2 or RT-PCR+ for SARS-CoV-2 with Ct ≤28 more than 5days after admission); controls were patients without infection (RT-PCR- for SARS-CoV-2 >5 days after admission). They were matched according to length of stay before diagnosis and period of admission. Analyses were performed with a conditional logistic regression.

RESULTS

A total of 281 cases and 441 controls were included. In the bivariate analysis, cases were older (OR per 10years: 1.22; 95%CI [1.10;1.36]), had more often shared a room (OR: 1.74; 95%CI [1.25;2.43]) or a risk factor for severe COVID-19 (OR: 1.94; 95%CI [1.09;3.45]), were more often hospitalized in medical units [OR: 1.59; 95%CI [1.12;2.25]), had higher exposure to contagious health care workers (HCW; OR per 1person-day: 1.12; 95%CI [1.08;1.17]) and patients (OR per 1 person-day: 1.11; 95%CI [1.08;1.14]) than controls. In an adjusted model, risk factors for nosocomial COVID-19 were exposure to contagious HCW (aOR per 1person-day: 1.08; 95%CI [1.03;1.14]) and to contagious patients (aOR per 1person-day: 1.10; 95%CI [1.07;1.13]).

CONCLUSIONS

Exposure to contagious professionals and patients are the main risk factors for nosocomial COVID-19.

Exposure to airborne SARS-CoV-2 in four hospital wards and ICUs of Cyprus. A detailed study accounting for day-to-day operations and aerosol generating procedures

In any infectious disease, understanding the modes of transmission is key to selecting effective public health measures. In the case of COVID-19 spread, the strictness of the imposed measures outlined the lack of understanding on how SARS-CoV-2 transmits, particularly via airborne pathways. With the aim to characterize the transmission dynamics of airborne SARS-CoV-2, 165 and 62 air and environmental samples, respectively, were collected in four COVID-19 wards and ICUs in Cyprus and analyzed by RT-PCR. An alternative method for SARS-CoV-2 detection in air that provides comparable results but is less cumbersome and time demanding, is also proposed. Considering that all clinics employed 14 regenerations per hour of full fresh air inside patient rooms, it was hypothesized that the viral levels and the frequency of positive samples would be minimum outside of the rooms. However, it is shown that leaving the door opened in patient rooms hinders the efficiency of the ventilation system applied, allowing the virus to escape. As a result, the highest observed viral levels (135 copies m^-3) were observed in the corridor of a ward and the frequency of positive samples in the same area was comparable to that inside a two-bed cohort. SARS-CoV-2 in that corridor was found primarily to lie in the coarse mode, at sizes between 1.8 and 10 μm. Similar to previous studies, the frequency of positive samples and viral levels were the lowest inside intensive care units. However, if a patient with sufficient viral load (Ct-value 31) underwent aerosol generating procedures, positive samples with viral levels below 45 copies m^-3 were acquired within a 2 m distance of the patient. Our results suggest that a robust ventilation system can prevent unnecessary exposure to SARS-CoV-2 but with limitations related to foot traffic or the operations taking place at the time.

Epidemiology of healthcare-associated SARS-CoV-2 outbreaks in Germany between March 2020 and May 2022

BACKGROUND

Outbreaks in healthcare facilities played a pivotal role in the course of the coronavirus (COVID-19) pandemic.

AIM

To investigate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks in hospitals, outpatient care, and rehabilitation facilities in Germany from March 2020 to May 2022.

METHODS

Data from the German mandatory notification system were used to describe outbreaks by number of cases and case fatality ratio (CFR), and outbreak cases by age and gender. Using Pearson correlation, the dynamics of cases in the general population were compared with cases in healthcare-associated infection (HAI) SARS-CoV-2 outbreaks before and after the start of the vaccination campaign. Additionally, a counterfactual scenario was used to estimate numbers of prevented HAI cases, using the phase before vaccination as baseline.

FINDINGS

By the end of May 2022, 8941 healthcare-associated outbreaks were observed with 73,626 cases: 51,504 in hospitals, 15,524 in outpatient care, and 6598 in rehabilitation facilities. Median number of cases per outbreak was 4 (range: 2-342) and cases were more frequently reported in women with 46,818 (63.6%). Overall CFR was 8.1%, higher in men (12.4%) than in women (5.7%). After the vaccination campaign was fully introduced, the association between increasing incidence in the general population and consecutive outbreak cases was decreased by a factor of 10. Furthermore, our counterfactual analysis suggests that more than 55,000 outbreak cases could have been prevented until the end of 2021.

CONCLUSION

The vaccination campaign in combination with non-pharmaceutical measures was key to reduce number, size and CFR of healthcare-associated outbreaks.

Investigation of SARS-CoV-2 Transmission in The Tabernacle Choir at Temple Square in the Context of Prevention Protocols, Utah, September-November 2021

Group singing and playing of wind instruments increase COVID-19 transmission risk. After a pause during the initial period of the COVID-19 pandemic, The Tabernacle Choir at Temple Square organization (hereinafter, Choir) resumed musical events in September 2021 with prevention protocols, including required vaccination and pre-event rapid antigen testing. We investigated potential SARS-CoV-2 transmission at Choir events during September 21-November 7, 2021. We interviewed COVID-19-positive members (hereinafter, case-members) and identified members exposed when a case-member attended a Choir event during his or her infectious period. We compared whole genome sequencing results to assess the genetic relatedness of available SARS-CoV-2 specimens obtained from case-members. We identified 30 case-members through pre-event testing (n = 10), self-reported positive test results (n = 18), and a review of Utah's disease surveillance system (n = 2). All 30 case-members reported symptoms; 21 (70%) were women and 23 (77%) received a positive test result by nucleic acid amplification test. No hospitalizations or deaths were reported. We identified 176 test-eligible exposed members from 14 instances of case-members attending events during their infectious periods. All were tested at least once 2 to 14 days after exposure: 74 (42%) by rapid antigen test only (all negative) and 102 (58%) by nucleic acid amplification test (4 positive, 97 negative, and 1 equivocal). Among viral sequences available from 15 case-members, the smallest single-nucleotide polymorphism distance between 2 sequences was 2, and the next-smallest distance was 10. The lack of disease detected in most exposed members suggests that minimal, if any, transmission occurred at Choir events. When community COVID-19 incidence is high, prevention protocols might help limit SARS-CoV-2 transmission during group musical activities.

Dynamics of nosocomial SARS-CoV-2 transmissions: Facing the challenge of variants of concern in a Brazilian reference hospital

The hospital environment can be considered a high risk for the occurrence of SARS-CoV-2 transmission outbreaks, either for health professionals who are directly involved in the care of suspected or confirmed cases of the disease, or for patients, for being in an environment more vulnerable to the acquisition of nosocomial infections. In this molecular epidemiology study, we aimed to analyze the occurrence and transmission dynamics of SARS-CoV-2 in outbreaks and local chains of transmission in a large tertiary teaching hospital in southern Brazil, in addition to verifying circulating strains and their epidemiological relation in the local context, from September 21, 2020 to October 5, 2021. Positive samples involved in COVID-19 clusters or outbreaks were analyzed using clinical, epidemiological and genomic data. Different lineages and sublineages among patients in the same room were observed. Most patients had their first clinical manifestation, evidence of suspicion, and diagnostic confirmation within 7-14 days or >14 days after hospital admission. The patients who have contact with confirmed cases of COVID-19 spent, on average, 6.28 days in the same environment until the positive test. There was a significant association between the outcome and the number of vaccine doses (p < 0.05), where those who received two doses presented a lower occurrence of death. There was a total replacement of variant of concern (VOC) Gamma by VOC Delta from August 2021 at the study site. Although the epidemiological analysis indicates nosocomial infections, through genomic sequencing, it was established that most of the hospital outbreaks had different origins. These findings highlight the utility of integrating epidemiological and genomic data to identify possible routes of viral entry and dissemination.

Analysis of SARS-CoV-2 genomic surveillance data during the Delta and Omicron waves at a Saudi tertiary referral hospital

BACKGROUND

Studying the genomic evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may help determine outbreak clusters and virus transmission advantages to aid public health efforts during the pandemic. Thus, we tracked the evolution of SARS-CoV-2 by variant epidemiology, breakthrough infection, and patient characteristics as the virus spread during the Delta and Omicron waves. We also conducted phylogenetic analyses to assess modes of transmission.

METHODS

Nasopharyngeal samples were collected from a cohort of 900 patients with positive polymerase chain reaction (PCR) test results confirming COVID-19 disease. Samples underwent real-time PCR detection using TaqPath assays. Sequencing was performed with Ion GeneStudio using the Ion AmpliSeq™ SARS-CoV-2 panel. Variant calling was performed with Torrent Suite™ on the Torrent Server. For phylogenetic analyses, the MAFFT tool was used for alignment and the maximum likelihood method with the IQ-TREE tool to build the phylogenetic tree. Data were analyzed using SAS statistical software. Analysis of variance or t tests were used to assess continuous variables, and χ² tests were used to assess categorical variables. Univariate and multivariate logistic regression analyses were preformed to estimate odds ratios (ORs).

RESULTS

The predominant variants in our cohort of 900 patients were non-variants of concern (11.1 %), followed by Alpha (4.1 %), Beta (5.6 %), Delta (21.2 %), and Omicron (58 %). The Delta wave had more male than female cases (112 vs. 78), whereas the Omicron wave had more female than male cases (311 vs. 208). The oldest patients (mean age, 43.4 years) were infected with non-variants of concern; the youngest (mean age, 33.7 years), with Omicron. Younger patients were mostly unvaccinated, whereas elderly patients were mostly vaccinated, a statistically significant difference. The highest risk for breakthrough infection by age was for patients aged 30-39 years (OR = 12.4, CI 95 %: 6.6-23.2), followed by patients aged 40-49 years (OR = 11.2, CI 95 %: 6.1-23.1) and then 20-29 years (OR = 8.2, CI 95 %: 4.4-15.4). Phylogenetic analyses suggested the interaction of multiple cases related to outbreaks for breakthrough infections, healthcare workers, and intensive care unit admission.

CONCLUSION

The findings of this study highlighted several major public health ramifications, including the distribution of variants over a wide range of demographic and clinical variables and by vaccination status.

Multiple pathways of SARS-CoV-2 nosocomial transmission uncovered by integrated genomic and epidemiological analyses during the second wave of the COVID-19 pandemic in the UK

Introduction

Throughout the global COVID-19 pandemic, nosocomial transmission has represented a major concern for healthcare settings and has accounted for many infections diagnosed within hospitals. As restrictions ease and novel variants continue to spread, it is important to uncover the specific pathways by which nosocomial outbreaks occur to understand the most suitable transmission control strategies for the future.

Methods

In this investigation, SARS-CoV-2 genome sequences obtained from 694 healthcare workers and 1,181 patients were analyzed at a large acute NHS hospital in the UK between September 2020 and May 2021. These viral genomic data were combined with epidemiological data to uncover transmission routes within the hospital. We also investigated the effects of the introduction of the highly transmissible variant of concern (VOC), Alpha, over this period, as well as the effects of the national vaccination program on SARS-CoV-2 infection in the hospital.

Results

Our results show that infections of all variants within the hospital increased as community prevalence of Alpha increased, resulting in several outbreaks and super-spreader events. Nosocomial infections were enriched amongst older and more vulnerable patients more likely to be in hospital for longer periods but had no impact on disease severity. Infections appeared to be transmitted most regularly from patient to patient and from patients to HCWs. In contrast, infections from HCWs to patients appeared rare, highlighting the benefits of PPE in infection control. The introduction of the vaccine at this time also reduced infections amongst HCWs by over four-times.

Discussion

These analyses have highlighted the importance of control measures such as regular testing, rapid lateral flow testing alongside polymerase chain reaction (PCR) testing, isolation of positive patients in the emergency department (where possible), and physical distancing of patient beds on hospital wards to minimize nosocomial transmission of infectious diseases such as COVID-19.

Detection and Molecular Characterization of the SARS-CoV-2 Delta Variant and the Specific Immune Response in Companion Animals in Switzerland

In human beings, there are five reported variants of concern of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). However, in contrast to human beings, descriptions of infections of animals with specific variants are still rare. The aim of this study is to systematically investigate SARS-CoV-2 infections in companion animals in close contact with SARS-CoV-2-positive owners ("COVID-19 households") with a focus on the Delta variant. Samples, obtained from companion animals and their owners were analyzed using a real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) and next-generation sequencing (NGS). Animals were also tested for antibodies and neutralizing activity against SARS-CoV-2. Eleven cats and three dogs in nine COVID-19-positive households were RT-qPCR and/or serologically positive for the SARS-CoV-2 Delta variant. For seven animals, the genetic sequence could be determined. The animals were infected by one of the pangolin lineages B.1.617.2, AY.4, AY.43 and AY.129 and between zero and three single-nucleotide polymorphisms (SNPs) were detected between the viral genomes of animals and their owners, indicating within-household transmission between animal and owner and in multi-pet households also between the animals. NGS data identified SNPs that occur at a higher frequency in the viral sequences of companion animals than in viral sequences of humans, as well as SNPs, which were exclusively found in the animals investigated in the current study and not in their owners. In conclusion, our study is the first to describe the SARS-CoV-2 Delta variant transmission to animals in Switzerland and provides the first-ever description of Delta-variant pangolin lineages AY.129 and AY.4 in animals. Our results reinforce the need of a One Health approach in the monitoring of SARS-CoV-2 in animals.

Lessons learned: use of WGS in real-time investigation of suspected intrahospital SARS-CoV-2 outbreaks

BACKGROUND

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been a continuing source of hospital-acquired infection and outbreaks. At Akershus University Hospital in Norway, traditional contact tracing has been combined with whole-genome sequencing (WGS) surveillance in real-time to investigate potential hospital outbreaks.

AIM

To describe the advantages and challenges encountered when using WGS as a real-time tool in hospital outbreak investigation and surveillance during the SARS-CoV-2 pandemic.

METHODS

Routine contact tracing in the hospital was performed for all healthcare workers (HCWs) who tested positive for SARS-CoV-2. Viral RNA from all positive patient and HCW samples was sequenced in real-time using nanopore sequencing and the ARTIC Network protocol. Suspected outbreaks involving five or more individuals with viral sequences were described.

FINDINGS

Nine outbreaks were suspected based on contact tracing, and one outbreak was suspected based on WGS results. Five outbreaks were confirmed; of these, two outbreaks were supported but could not be confirmed by WGS with high confidence, one outbreak was found to consist of two different lineages, and two outbreaks were refuted.

CONCLUSIONS

WGS is a valuable tool in hospital outbreak investigations when combined with traditional contact tracing. Inclusion of WGS data improved outbreak demarcation, identified unknown transmission chains, and highlighted weaknesses in existing infection control measures.

Investigating healthcare worker mobility and patient contacts within a UK hospital during the COVID-19 pandemic

BACKGROUND

Insights into behaviours relevant to the transmission of infections are extremely valuable for epidemiological investigations. Healthcare worker (HCW) mobility and patient contacts within the hospital can contribute to nosocomial outbreaks, yet data on these behaviours are often limited.

METHODS

Using electronic medical records and door access logs from a London teaching hospital during the COVID-19 pandemic, we derive indicators for HCW mobility and patient contacts at an aggregate level. We assess the spatial-temporal variations in HCW behaviour and, to demonstrate the utility of these behavioural markers, investigate changes in the indirect connectivity of patients (resulting from shared contacts with HCWs) and spatial connectivity of floors (owing to the movements of HCWs).

RESULTS

Fluctuations in HCW mobility and patient contacts were identified during the pandemic, with the most prominent changes in behaviour on floors handling the majority of COVID-19 patients. The connectivity between floors was disrupted by the pandemic and, while this stabilised after the first wave, the interconnectivity of COVID-19 and non-COVID-19 wards always featured. Daily rates of indirect contact between patients provided evidence for reactive staff cohorting in response to the number of COVID-19 patients in the hospital.

CONCLUSIONS

Routinely collected electronic records in the healthcare environment provide a means to rapidly assess and investigate behaviour change in the HCW population, and can support evidence based infection prevention and control activities. Integrating frameworks like ours into routine practice will empower decision makers and improve pandemic preparedness by providing tools to help curtail nosocomial outbreaks of communicable diseases.

Understanding Early Pandemic Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in a Medical Center by Incorporating Public Sequencing Databases to Mitigate Bias

BACKGROUND

Throughout the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, healthcare workers (HCWs) have faced risk of infection from within the workplace via patients and staff as well as from the outside community, complicating our ability to resolve transmission chains in order to inform hospital infection control policy. Here we show how the incorporation of sequences from public genomic databases aided genomic surveillance early in the pandemic when circulating viral diversity was limited.

METHODS

We sequenced a subset of discarded, diagnostic SARS-CoV-2 isolates between March and May 2020 from Boston Medical Center HCWs and combined this data set with publicly available sequences from the surrounding community deposited in GISAID with the goal of inferring specific transmission routes.

RESULTS

Contextualizing our data with publicly available sequences reveals that 73% (95% confidence interval, 63%-84%) of coronavirus disease 2019 cases in HCWs are likely novel introductions rather than nosocomial spread.

CONCLUSIONS

We argue that introductions of SARS-CoV-2 into the hospital environment are frequent and that expanding public genomic surveillance can better aid infection control when determining routes of transmission.

Genomic Investigation to Identify Sources of Severe Acute Respiratory Syndrome Coronavirus 2 Infection Among Healthcare Personnel in an Acute Care Hospital

Background

Identifying the source of healthcare personnel (HCP) coronavirus disease 2019 (COVID-19) is important to guide occupational safety efforts. We used a combined whole genome sequencing (WGS) and epidemiologic approach to investigate the source of HCP COVID-19 at a tertiary-care center early in the COVID-19 pandemic.

Methods

Remnant nasopharyngeal swab samples from HCP and patients with polymerase chain reaction-proven COVID-19 from a period with complete sample retention (14 March 2020 to 10 April 2020) at Rush University Medical Center in Chicago, Illinois, underwent viral RNA extraction and WGS. Genomes with >90% coverage underwent cluster detection using a 2 single-nucleotide variant genetic distance cutoff. Genomic clusters were evaluated for epidemiologic linkages, with strong linkages defined by evidence of time/location overlap.

Results

We analyzed 1031 sequences, identifying 49 clusters that included ≥1 HCP (265 patients, 115 HCP). Most HCP infections were not healthcare associated (88/115 [76.5%]). We did not identify any strong epidemiologic linkages for patient-to-HCP transmission. Thirteen HCP cases (11.3%) were attributed to a potential patient source (weak evidence involving nonclinical staff that lacked location data to prove or disprove contact with patients in same cluster). Fourteen HCP cases (12.2%) were attributed to HCP source (11 with strong evidence).

Conclusions

Using genomic and epidemiologic data, we found that most HCP severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections were not healthcare associated. We did not find strong evidence of patient-to-HCP transmission of SARS-CoV-2.

Factors contributing to a coronavirus disease 2019 (COVID-19) outbreak on a mixed medical-surgical unit in a Canadian acute-care hospital

OBJECTIVE

To identify preventable factors that contribute to the cross transmission of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) to patients in healthcare facilities.

DESIGN

A case-control study was conducted among inpatients on a coronavirus disease 2019 (COVID-19) outbreak unit.

SETTING

This study was conducted in a medical-surgical unit of a tertiary-care hospital in Nova Scotia in May 2021.

PATIENTS

Patients hospitalized on the unit for at least 12 hours and healthcare workers (HCW) working on the unit within 2 weeks of outbreak declaration were included.

METHODS

Risk factors for SARS-CoV-2 infection were analyzed using simple and multiple logistic regression. Whole-genome sequencing (WGS) was performed to identify SARS-CoV-2 strain relatedness. Network analysis was used to describe patient accommodation.

RESULTS

SARS-CoV-2 infections were identified in 21 patients (29.6%) and 11 HCWs (6.6%). WGS data revealed 4 distinct clades of related sequences. Several factors likely contributed to the outbreak, including failure to identify SARS-CoV-2, a largely incomplete or unvaccinated population, and patient wandering behaviors. The most significant risk factor for SARS-CoV-2 infection was room sharing with an infectious patient, which was the only factor that remained statistically significant following multivariate analysis (odds ratio [OR], 9.2l; 95% confidence interval [CI], 2.04-41.67; P = .004).

CONCLUSIONS

This outbreak likely resulted from admission of 2 patients with COVID-19, with subsequent transmissions to 17 patients and 11 staff. WGS and bioinformatics analyses were critical to identifying previously unrecognized nosocomial transmissions of SARS-CoV-2. This study supports strategies to reduce nosocomial transmissions of SARS-CoV-2, such as single-patient rooms, promotion of COVID-19 vaccination, and infection prevention and control measures including management of wandering behaviors.

State-wide genomic epidemiology investigations of COVID-19 in healthcare workers in 2020 Victoria, Australia: Qualitative thematic analysis to provide insights for future pandemic preparedness

Background

COVID-19 has affected many healthcare workers (HCWs) globally. We performed state-wide SARS-CoV-2 genomic epidemiological investigations to identify HCW transmission dynamics and provide recommendations to optimise healthcare system preparedness for future outbreaks.

Methods

Genome sequencing was attempted on all COVID-19 cases in Victoria, Australia. We combined genomic and epidemiologic data to investigate the source of HCW infections across multiple healthcare facilities (HCFs) in the state. Phylogenetic analysis and fine-scale hierarchical clustering were performed for the entire dataset including community and healthcare cases. Facilities provided standardised epidemiological data and putative transmission links.

Findings

Between March-October 2020, approximately 1,240 HCW COVID-19 infection cases were identified; 765 are included here, requested for hospital investigations. Genomic sequencing was successful for 612 (80%) cases. Thirty-six investigations were undertaken across 12 HCFs. Genomic analysis revealed that multiple introductions of COVID-19 into facilities (31/36) were more common than single introductions (5/36). Major contributors to HCW acquisitions included mobility of staff and patients between wards and facilities, and characteristics and behaviours of patients that generated numerous secondary infections. Key limitations at the HCF level were identified.

Interpretation

Genomic epidemiological analyses enhanced understanding of HCW infections, revealing unsuspected clusters and transmission networks. Combined analysis of all HCWs and patients in a HCF should be conducted, supported by high rates of sequencing coverage for all cases in the population. Established systems for integrated genomic epidemiological investigations in healthcare settings will improve HCW safety in future pandemics.

Funding

The Victorian Government, the National Health and Medical Research Council Australia, and the Medical Research Future Fund.

Prediction of hospital-onset COVID-19 infections using dynamic networks of patient contact: an international retrospective cohort study

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.

FUNDING

Medical Research Foundation, WHO, Engineering and Physical Sciences Research Council, National Institute for Health Research (NIHR), Swiss National Science Foundation, and German Research Foundation.

Repeated transmission of SARS-CoV-2 in an overcrowded Irish emergency department elucidated by whole-genome sequencing

AIM

To provide a detailed genomic-epidemiological description of a complex multi-ward SARS-CoV-2 outbreak, which originated in the crowded emergency department (ED) in our hospital during the third wave of the COVID-19 pandemic, and was elucidated promptly by local whole-genome sequencing (WGS).

METHODS

SARS-CoV-2 was detected by reverse transcriptase real-time polymerase chain reaction on viral RNA extracted from nasopharyngeal swabs. WGS was performed using an Oxford MinION Mk1C instrument following the ARTIC v3 sequencing protocol. High-quality consensus genomes were assembled with the artic-ncov2019 bioinformatics pipeline and viral phylogenetic trees were built, inferred by maximum-likelihood. Clusters were defined using a threshold of 0-1 single nucleotide polymorphisms (SNPs) between epidemiologically linked sequences.

RESULTS

In April 2021, outbreaks of COVID-19 were declared on two wards at University Hospital Limerick after 4 healthcare-associated SARS-CoV-2 infections were detected by post-admission surveillance testing. Contact tracing identified 12 further connected cases; all with direct or indirect links to the ED 'COVID Zone'. All sequences were assigned to the Pangolin B.1.1.7 lineage by WGS, and SNP-level analysis revealed two distinct but simultaneous clusters of infections. Repeated transmission in the ED was demonstrated, involving patients accommodated on trolleys in crowded areas, resulting in multiple generations of infections across three inpatient hospital wards and subsequently to the local community. These findings informed mitigation efforts to prevent cross-transmission in the ED.

CONCLUSION

Cross-transmission of SARS-CoV-2 occurred repeatedly in an overcrowded emergency department. Viral WGS elucidated complex viral transmission networks in our hospital and informed infection, prevention and control practice.

Association of Omicron vs Wild-type SARS-CoV-2 Variants With Hospital-Onset SARS-CoV-2 Infections in a US Regional Hospital System

This retrospective hospital-based study examines all SARS-CoV-2 nosocomial infections in 1 US health care system during the Omicron surge vs an earlier wave when wild-type variants predominated.

Unraveling the hurdles of a large COVID-19 epidemiological investigation by viral genomics

COVID-19 local outbreak response relies on subjective information to reconstruct transmission chains. We assessed the concordance between epidemiologically linked cases and viral genetic profiles, in the Baixo Vouga Region (Portugal), from March to June 2020. A total of 1925 COVID-19 cases were identified, with 1143 being assigned to 154 epiclusters. Viral genomic data was available for 128 cases. Public health authorities identified two large epiclusters (280 and 101 cases each) with a central role on the spread of the disease. Still, the genomic data revealed that each epicluster included two distinct SARS-CoV-2 genetic profiles and thus more than one transmission network. We were able to show that the initial transmission dynamics reconstruction was most likely accurate, but the increasing dimension of the epiclusters and its extension to densely populated settings (healthcare and nursing home settings) triggered the misidentification of links. Genomics was also key to resolve some sporadic cases and misidentified direction of transmission. The epidemiological investigation showed a sensitivity of 70%-86% to detect transmission chains. This study contributes to the understanding of the hurdles and caveats associated with the epidemiological investigation of hundreds of community cases in the context of a massive outbreak caused by a highly transmissible and new respiratory virus.

Integration of Sequencing and Epidemiologic Data for Surveillance of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infections in a Tertiary-Care Hospital

BACKGROUND

The ongoing coronavirus disease 2019 pandemic significantly burdens hospitals and other healthcare facilities. Therefore, understanding the entry and transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical for effective prevention and preparedness measures. We performed surveillance and analysis of testing and transmission of SARS-CoV-2 infections in a tertiary-care hospital in Germany during the second and third pandemic waves in fall/winter 2020.

METHODS

Between calendar week 41 in 2020 and calendar week 1 in 2021, 40%, of all positive patient and staff samples (284 total) were subjected to full-length viral genome sequencing. Clusters were defined based on similar genotypes indicating common sources of infection. We integrated phylogenetic, spatial, and temporal metadata to detect nosocomial infections and outbreaks, uncover transmission chains, and evaluate containment measures' effectiveness.

RESULTS

Epidemiologic data and contact tracing readily recognize most healthcare-associated (HA) patient infections. However, sequencing data reveal that temporally preceding index cases and transmission routes can be missed using epidemiologic methods, resulting in delayed interventions and serially linked outbreaks being counted as independent events. While hospital-associated transmissions were significantly elevated at a moderate rate of community transmission during the second wave, systematic testing and high vaccination rates among staff have led to a substantial decrease in HA infections at the end of the second/beginning of the third wave despite high community transmissions.

CONCLUSIONS

While epidemiologic analysis is critical for immediate containment of HA SARS-CoV-2 outbreaks, integration of genomic surveillance revealed weaknesses in identifying staff contacts. Our study underscores the importance of high testing frequency and genomic surveillance to detect, contain and prevent SARS-CoV-2-associated infections in healthcare settings.

Strategies to prevent ventilator-associated pneumonia, ventilator-associated events, and nonventilator hospital-acquired pneumonia in acute-care hospitals: 2022 Update

The purpose of this document is to highlight practical recommendations to assist acute care hospitals to prioritize and implement strategies to prevent ventilator-associated pneumonia (VAP), ventilator-associated events (VAE), and non-ventilator hospital-acquired pneumonia (NV-HAP) in adults, children, and neonates. This document updates the Strategies to Prevent Ventilator-Associated Pneumonia in Acute Care Hospitals published in 2014. This expert guidance document is sponsored by the Society for Healthcare Epidemiology (SHEA), and is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America, the American Hospital Association, the Association for Professionals in Infection Control and Epidemiology, and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise.

Catwalk: identifying closely related sequences in large microbial sequence databases

There is a need to identify microbial sequences that may form part of transmission chains, or that may represent importations across national boundaries, amidst large numbers of SARS-CoV-2 and other bacterial or viral sequences. Reference-based compression is a sequence analysis technique that allows both a compact storage of sequence data and comparisons between sequences. Published implementations of the approach are being challenged by the large sample collections now being generated. Our aim was to develop a fast software detecting highly similar sequences in large collections of microbial genomes, including millions of SARS-CoV-2 genomes. To do so, we developed Catwalk, a tool that bypasses bottlenecks in the generation, comparison and in-memory storage of microbial genomes generated by reference mapping. It is a compiled solution, coded in Nim to increase performance. It can be accessed via command line, rest api or web server interfaces. We tested Catwalk using both SARS-CoV-2 and Mycobacterium tuberculosis genomes generated by prospective public-health sequencing programmes. Pairwise sequence comparisons, using clinically relevant similarity cut-offs, took about 0.39 and 0.66 μs, respectively; in 1 s, between 1 and 2 million sequences can be searched. Catwalk operates about 1700 times faster than, and uses about 8 % of the RAM of, a Python reference-based compression and comparison tool in current use for outbreak detection. Catwalk can rapidly identify close relatives of a SARS-CoV-2 or M. tuberculosis genome amidst millions of samples.

Linking sporadic hospital clusters during a community surge of the severe acute respiratory coronavirus virus 2 (SARS-CoV-2) B.1.617.2 delta variant: The utility of whole-genome sequencing

Sporadic clusters of healthcare-associated coronavirus disease 2019 (COVID-19) occurred despite intense rostered routine surveillance and a highly vaccinated healthcare worker (HCW) population, during a community surge of the severe acute respiratory coronavirus virus 2 (SARS-CoV-2) B.1.617.2 δ (delta) variant. Genomic analysis facilitated timely cluster detection and uncovered additional linkages via HCWs moving between clinical areas and among HCWs sharing a common lunch area, enabling early intervention.

Sporadic outbreaks of healthcare-associated COVID-19 infection in a highly-vaccinated inpatient population during a community outbreak of the B.1.617.2 variant: The role of enhanced infection-prevention measures

Sporadic clusters of health care-associated COVID-19 infection occurred in a highly vaccinated health care-workers and patient population, over a 3-month period during ongoing community transmission of the B.1.617.2 variant. Enhanced infection-prevention measures and robust surveillance systems, including routine-rostered-testing of all inpatients and staff and usage of N95-respirators in all clinical areas, were insufficient in achieving zero health care-associated transmission. The unvaccinated and immunocompromised remain at-risk and should be prioritized for enhanced surveillance.

Clinico-Genomic Analysis Reiterates Mild Symptoms Post-vaccination Breakthrough: Should We Focus on Low-Frequency Mutations?

Vaccine development against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been of primary importance to contain the ongoing global pandemic. However, studies have demonstrated that vaccine effectiveness is reduced and the immune response is evaded by variants of concern (VOCs), which include Alpha, Beta, Delta, and, the most recent, Omicron. Subsequently, several vaccine breakthrough (VBT) infections have been reported among healthcare workers (HCWs) due to their prolonged exposure to viruses at healthcare facilities. We conducted a clinico-genomic study of ChAdOx1 (Covishield) VBT cases in HCWs after complete vaccination. Based on the clinical data analysis, most of the cases were categorized as mild, with minimal healthcare support requirements. These patients were divided into two sub-phenotypes based on symptoms: mild and mild plus. Statistical analysis showed a significant correlation of specific clinical parameters with VBT sub-phenotypes. Viral genomic sequence analysis of VBT cases revealed a spectrum of high- and low-frequency mutations. More in-depth analysis revealed the presence of low-frequency mutations within the functionally important regions of SARS-CoV-2 genomes. Emphasizing the potential benefits of surveillance, low-frequency mutations, D144H in the N gene and D138Y in the S gene, were observed to potentially alter the protein secondary structure with possible influence on viral characteristics. Substantiated by the literature, our study highlights the importance of integrative analysis of pathogen genomic and clinical data to offer insights into low-frequency mutations that could be a modulator of VBT infections.

Characterising within-hospitalSARS-CoV-2 transmission events using epidemiological and viral genomic data across two pandemic waves

Hospital outbreaks of COVID19 result in considerable mortality and disruption to healthcare services and yet little is known about transmission within this setting. We characterise within hospital transmission by combining viral genomic and epidemiological data using Bayesian modelling amongst 2181 patients and healthcare workers from a large UK NHS Trust. Transmission events were compared between Wave 1 (1st March to 25th J'uly 2020) and Wave 2 (30th November 2020 to 24th January 2021). We show that staff-to-staff transmissions reduced from 31.6% to 12.9% of all infections. Patient-to-patient transmissions increased from 27.1% to 52.1%. 40%-50% of hospital-onset patient cases resulted in onward transmission compared to 4% of community-acquired cases. Control measures introduced during the pandemic likely reduced transmissions between healthcare workers but were insufficient to prevent increasing numbers of patient-to-patient transmissions. As hospital-acquired cases drive most onward transmission, earlier identification of nosocomial cases will be required to break hospital transmission chains.

Infection prevention and control insights from a decade of pathogen whole-genome sequencing

Pathogen whole-genome sequencing has become an important tool for understanding the transmission and epidemiology of infectious diseases. It has improved our understanding of sources of infection and transmission routes for important healthcare-associated pathogens, including Clostridioides difficile and Staphylococcus aureus. Transmission from known infected or colonized patients in hospitals may explain fewer cases than previously thought and multiple introductions of these pathogens from the community may play a greater a role. The findings have had important implications for infection prevention and control. Sequencing has identified heterogeneity within pathogen species, with some subtypes transmitting and persisting in hospitals better than others. It has identified sources of infection in healthcare-associated outbreaks of food-borne pathogens, Candida auris and Mycobacterium chimera, as well as individuals or groups involved in transmission and historical sources of infection. SARS-CoV-2 sequencing has been central to tracking variants during the COVID-19 pandemic and has helped understand transmission to and from patients and healthcare workers despite prevention efforts. Metagenomic sequencing is an emerging technology for culture-independent diagnosis of infection and antimicrobial resistance. In future, sequencing is likely to become more accessible and widely available. Real-time use in hospitals may allow infection prevention and control teams to identify transmission and to target interventions. It may also provide surveillance and infection control benchmarking. Attention to ethical and wellbeing issues arising from sequencing identifying individuals involved in transmission is important. Pathogen whole-genome sequencing has provided an incredible new lens to understand the epidemiology of healthcare-associated infection and to better control and prevent these infections.

The unseen pandemic: treatment delays and loss to follow-up due to fear of COVID

BACKGROUND

Fear of contracting SARS-CoV-2 has transformed public interaction with healthcare professionals and hospitals alike. In turn, this has resulted in a collateral impact on patients' health across medical and surgical paradigms. Understanding the causative factors of this fear, and tackling it head on, is vital to return to pre-pandemic levels of healthcare.

MAIN BODY

In this editorial, we explore the evidence base behind the fear of healthcare professionals and facilities that has developed during the course of the SARS-CoV-2pandemic. We also reflect on the ways in which these fears have affected the general public. In so doing, we review a recent article from Montalto et al. that has explored fear of SARS-CoV-2 among patients undergoing surgery in Italy.

CONCLUSION

While fear of SARS-CoV-2 is uncommon among surgical patients, there are still those who delay or avoiding seeking medical care due to fear of transmission. Physicians must lead the fight against this fear in a hope to regain the trust of the public.

New Insights into the Prevention of Hospital-Acquired Pneumonia/Ventilator-Associated Pneumonia Caused by Viruses

A fifth or more of hospital-acquired pneumonias may be attributable to respiratory viruses. The SARS-CoV-2 pandemic has clearly demonstrated the potential morbidity and mortality of respiratory viruses and the constant threat of nosocomial transmission and hospital-based clusters. Data from before the pandemic suggest the same can be true of influenza, respiratory syncytial virus, and other respiratory viruses. The pandemic has also helped clarify the primary mechanisms and risk factors for viral transmission. Respiratory viruses are primarily transmitted by respiratory aerosols that are routinely emitted when people exhale, talk, and cough. Labored breathing and coughing increase aerosol generation to a much greater extent than intubation, extubation, positive pressure ventilation, and other so-called aerosol-generating procedures. Transmission risk is proportional to the amount of viral exposure. Most transmissions take place over short distances because respiratory emissions are densest immediately adjacent to the source but then rapidly dilute and diffuse with distance leading to less viral exposure. The primary risk factors for transmission then are high viral loads, proximity, sustained exposure, and poor ventilation as these all increase net viral exposure. Poor ventilation increases the risk of long-distance transmission by allowing aerosol-borne viruses to accumulate over time leading to higher levels of exposure throughout an enclosed space. Surgical and procedural masks reduce viral exposure but do not eradicate it and thus lower but do not eliminate transmission risk. Most hospital-based clusters have been attributed to delayed diagnoses, transmission between roommates, and staff-to-patient infections. Strategies to prevent nosocomial respiratory viral infections include testing all patients upon admission, preventing healthcare providers from working while sick, assuring adequate ventilation, universal masking, and vaccinating both patients and healthcare workers.

Hidden hazards of SARS-CoV-2 transmission in hospitals: A systematic review

Despite their considerable prevalence, dynamics of hospital-associated COVID-19 are still not well understood. We assessed the nature and extent of air- and surface-borne SARS-CoV-2 contamination in hospitals to identify hazards of viral dispersal and enable more precise targeting of infection prevention and control. PubMed, ScienceDirect, Web of Science, Medrxiv, and Biorxiv were searched for relevant articles until June 1, 2021. In total, 51 observational cross-sectional studies comprising 6258 samples were included. SARS-CoV-2 RNA was detected in one in six air and surface samples throughout the hospital and up to 7.62 m away from the nearest patients. The highest detection rates and viral concentrations were reported from patient areas. The most frequently and heavily contaminated types of surfaces comprised air outlets and hospital floors. Viable virus was recovered from the air and fomites. Among size-fractionated air samples, only fine aerosols contained viable virus. Aerosol-generating procedures significantly increased (OR_air  = 2.56 (1.46-4.51); OR_surface  = 1.95 (1.27-2.99)), whereas patient masking significantly decreased air- and surface-borne SARS-CoV-2 contamination (OR_air  = 0.41 (0.25-0.70); OR_surface  = 0.45 (0.34-0.61)). The nature and extent of hospital contamination indicate that SARS-CoV-2 is likely dispersed conjointly through several transmission routes, including short- and long-range aerosol, droplet, and fomite transmission.

Explosive nosocomial outbreak of SARS-CoV-2 in a rehabilitation clinic: the limits of genomics for outbreak reconstruction

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 (R_t) 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 14^th March to 12^th April 2020, and involved 37 patients (31 with WGS) and 39 employees (31 with WGS), 37 of whom were HCWs. Peak R_t 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.