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

Risk of SARS-CoV-2 infection before and after the Omicron wave in a cohort of healthcare workers in Ontario, Canada

BACKGROUND

Longitudinal healthcare worker (HCW) cohorts throughout the COVID-19 pandemic provide a unique opportunity to study the relative contributions of various exposures to infection risk over time. This study aimed to examine how demographic, health, occupational, household and community factors influenced the SARS-CoV-2 infection risk in a cohort of HCWs in Southeastern Ontario, Canada, during the early pandemic and the Omicron waves. We compared the contribution of these factors to infection risk and explored the implications for future epidemic preparedness and the protection of HCWs.

METHODS

We conducted a longitudinal analysis using data from a cohort of HCWs recruited from one acute care hospital and four long-term care homes. The analysis was divided into two periods: the initial phase of the pandemic (period #1) and the first three Omicron waves (period #2). We employed Poisson regression for period #1 and Cox regression for period #2 to examine associations of demographic factors (age, sex, ethnicity, migration status, income insufficiency), health factors (chronic conditions, smoking history, SARS-CoV-2 vaccination status), household factors (exposure to COVID-19), occupational factors (work role, exposure to COVID-19 patients, personal protective equipment access, aerosol-generating procedures) and community exposures (use of masks, distance, hand-washing) with SARS-CoV-2 infection.

RESULTS

At period #1, 17/208 (8.2%) HCWs reported having had SARS-CoV-2 infection. At period #2, 65/167 (38.3%) reported at least one SARS-CoV-2 infection. In period #1, factors associated with increased risk of infection included working in a long-term care home, exposure to more COVID-19-positive patients, working as a nurse or therapist, and inadequate use of personal protective equipment. In period #2, the hazard of infection was higher among HCWs who had COVID-19-infected children at home, whereas the use of protective measures in the community (maintaining social distance, mask-wearing) and receiving a vaccine booster were associated with reduced risk. Providing care to COVID-19 patients was not associated with the risk of acquiring SARS-CoV-2 infection at period #2.

CONCLUSIONS

During the Omicron wave, community and household exposures, but not occupational exposure to COVID-19 cases, were the primary factors contributing to infection risk in HCWs. This contrasts with the early waves of the pandemic where occupational exposures played a significant role. These findings may be explained by the effectiveness of institutional interventions in reducing the risk of SARS-CoV-2 transmission in healthcare settings, alongside the failure of community-level interventions to mitigate risk during the Omicron period.

The potential of genomic epidemiology: capitalizing on its practical use for impact in the healthcare setting

The rapid detection and containment of healthcare-associated infections (HCAIs) is critical in preventing and controlling infectious disease outbreaks within healthcare settings. Whole genome sequencing (WGS) has emerged as a powerful tool for tracking the transmission dynamics of pathogens and when used alongside traditional epidemiological methods it can better inform our understanding of the pathogen origin, pathway and extent of transmission. Additionally, WGS can aid in identifying previously unrecognized reservoirs of infection, allowing for more effective control strategies and targeted interventions. This article describes the incorporation of WGS into infectious disease management in Wales and explores it in the context of COVID-19 and Clostridioides difficile. We also describe the developments made to the workforce in Wales to enable the expansion of WGS and reflect on the resources, infrastructure and training frameworks still required.

COVID-19 outbreak among employees of a German hospital: risk factor analysis based on a follow-up questionnaire and seroprevalence

BACKGROUND

The Co-FriSero study describes a COVID-19 outbreak at the Friedrichroda hospital in Thuringia, Germany, with 185 beds and 404 employees, at the onset of the pandemic between March 30th, 2020, and April 13th, 2020. This study aimed to analyze potential sources of SARS-CoV-2 transmission amongst hospital employees.

METHODS

After the outbreak, a comprehensive follow-up was conducted through a questionnaire and a seroprevalence study using two different immunoassays for IgG detection and a third for discordant results.

RESULTS

PCR screenings confirmed SARS-CoV-2 infection in 25 of 229 employees, with an additional 7 detected through serology. Statistical analysis indicated that direct patient contact, exposure to high flow ventilation in non-isolated rooms, direct contact with colleagues, shared use of recreational rooms, and carpooling were associated with an increased infection risk. Conversely, contact with family and friends, public transportation, public events, and use of locker rooms were not associated with infection. Male gender showed a lower infection likelihood, independent of age and other risk factors.

CONCLUSION

This study highlights the role of direct patient care and internal staff interactions in the spread of SARS-CoV-2 in the hospital setting. It suggests that non-traditional transmission routes like carpooling require consideration in pandemic preparedness.

Nosocomial Outbreak of SARS-CoV-2 in a Hospital Ward during the Omicron Variant-Dominant Wave with a Review of the Relevant Literature

Clusters of nosocomial coronavirus disease 2019 (COVID-19) have been reported globally during the recent pandemic. Unfortunately, these clusters negatively affect inpatient morbidity, mortality, and hospital functioning. Using epidemiological data and whole-genome sequencing (WGS) of SARS-CoV-2, this study investigated the outbreak of COVID-19 at a university hospital. Eight inpatients and 13 healthcare workers tested positive for SARS-CoV-2 during a 1-month period. WGS of the virus in 11 patients revealed that the two variants of concern belonging to the Omicron sublineages, BA.2.3 and BA1.1.2, caused an outbreak when the proportion of the Omicron lineage in the community changed. When variants of concern undergo mutation, a response to the outbreak should be made with multiple variants in mind, even in the absence of epidemiological data showing close contact or other potential vectors of infection. Awareness of infection prevention and control should be raised to safeguard patient safety.

AMRomics: a scalable workflow to analyze large microbial genome collections

Whole genome analysis for microbial genomics is critical to studying and monitoring antimicrobial resistance strains. The exponential growth of microbial sequencing data necessitates a fast and scalable computational pipeline to generate the desired outputs in a timely and cost-effective manner. Recent methods have been implemented to integrate individual genomes into large collections of specific bacterial populations and are widely employed for systematic genomic surveillance. However, they do not scale well when the population expands and turnaround time remains the main issue for this type of analysis. Here, we introduce AMRomics, an optimized microbial genomics pipeline that can work efficiently with big datasets. We use different bacterial data collections to compare AMRomics against competitive tools and show that our pipeline can generate similar results of interest but with better performance. The software is open source and is publicly available at https://github.com/amromics/amromics under an MIT license.

The Use of Contact Tracing Technologies for Infection Prevention and Control Purposes in Nosocomial Settings: A Systematic Literature Review

BACKGROUND

Pandemic management and preparedness are more needed than ever before and there is widespread governmental interest in learning from the COVID-19 pandemic in order to ensure the availability of evidence-based Infection Prevention and Control measures. Contact tracing is integral to Infection Prevention and Control, facilitating breaks in the chain of transmission in a targeted way, identifying individuals who have come into contact with an infected person, and providing them with instruction/advice relating to testing, medical advice and/or self-isolation.

AIM

This study aims to improve our understanding of the use of contact tracing technologies in healthcare settings. This research seeks to contribute to the field of Infection Prevention and Control by investigating how these technologies can mitigate the spread of nosocomial infections. Ultimately, this study aims to improve the quality and safety of healthcare delivery.

METHODS

A systematic literature review was conducted, and journal articles investigating the use of contact tracing technologies in healthcare settings were retrieved from databases held on the OvidSP platform between March and September 2022, with no date for a lower limit.

RESULTS

In total, 277 studies were retrieved and screened, and 14 studies were finally included in the systematic literature review. Most studies investigated proximity sensing technologies, reporting promising results. However, studies were limited by small sample sizes and confounding factors, revealing contact tracing technologies remain at a nascent stage. Investment in research and development of new testing technologies is necessary to strengthen national and international contact tracing capabilities.

CONCLUSION

This review aims to contribute to those who intend to create robust surveillance systems and implement infectious disease reporting protocols.

Viral genome sequencing to decipher in-hospital SARS-CoV-2 transmission events

The SARS-CoV-2 pandemic has highlighted the need to better define in-hospital transmissions, a need that extends to all other common infectious diseases encountered in clinical settings. To evaluate how whole viral genome sequencing can contribute to deciphering nosocomial SARS-CoV-2 transmission 926 SARS-CoV-2 viral genomes from 622 staff members and patients were collected between February 2020 and January 2021 at a university hospital in Munich, Germany, and analysed along with the place of work, duration of hospital stay, and ward transfers. Bioinformatically defined transmission clusters inferred from viral genome sequencing were compared to those inferred from interview-based contact tracing. An additional dataset collected at the same time at another university hospital in the same city was used to account for multiple independent introductions. Clustering analysis of 619 viral genomes generated 19 clusters ranging from 3 to 31 individuals. Sequencing-based transmission clusters showed little overlap with those based on contact tracing data. The viral genomes were significantly more closely related to each other than comparable genomes collected simultaneously at other hospitals in the same city (n = 829), suggesting nosocomial transmission. Longitudinal sampling from individual patients suggested possible cross-infection events during the hospital stay in 19.2% of individuals (14 of 73 individuals). Clustering analysis of SARS-CoV-2 whole genome sequences can reveal cryptic transmission events missed by classical, interview-based contact tracing, helping to decipher in-hospital transmissions. These results, in line with other studies, advocate for viral genome sequencing as a pathogen transmission surveillance tool in hospitals.

Identification of key potential infection processes and risk factors in the computed tomography examination process by FMEA method under COVID-19

PURPOSE

To identify the key infection processes and risk factors in Computed Tomography (CT) examination process within the standard prevention and control measures for the COVID-19 epidemic, aiming to mitigate cross-infection occurrences in the hospital.

METHOD

The case hospital has assembled a team of 30 experts specialized in CT examination. Based on the CT examination process, the potential failure modes were assessed from the perspective of severity (S), occurrence probability (O), and detectability (D); they were then combined with corresponding risk prevention measures. Finally, key infection processes and risk factors were identified according to the risk priority number (RPN) and expert analysis.

RESULTS

Through the application of RPN and further analysis, four key potential infection processes were identified, including "CT request form (A1)," "during the scan of CT patient (B2)," "CT room and objects disposal (C2)," and "medical waste (garbage) disposal (C3)". In addition, eight key risk factors were also identified, including "cleaning personnel does not wear masks normatively (C32)," "nurse does not select the vein well, resulting in extravasation of the peripheral vein for enhanced CT (B25)," "patient cannot find the CT room (A13)," "patient has obtained a CT request form but does not know the procedure (A12)," "patient is too unwell to continue with the CT scan (B24)," "auxiliary staff (or technician) does not have a good grasp of the sterilization and disinfection standards (C21)," "auxiliary staff (or technician) does not sterilize the CT machine thoroughly (C22)," and "cleaning personnel lacks of knowledge of COVID-19 prevention and control (C33)".

CONCLUSION

Hospitals can publicize the precautions regarding CT examination through various channels, reducing the incidence of CT examination failure. Hospitals' cleaning services are usually outsourced, and the educational background of the staff employed in these services is generally not high. Therefore, during training and communication, it is more necessary to provide a series of scope and training programs that are aligned with their understanding level. The model developed in this study effectively identifies the key infection prevention process and critical risk factors, enhancing the safety of medical staff and patients. This has significant research implications for the potential epidemic of major infectious diseases.

Perspectives on Assessing the Flexibility of Hospitals for Crisis Mode Operations: Lessons From the COVID-19 Pandemic in the Netherlands

BACKGROUND

The COVID-19 pandemic placed healthcare design at the heart of the crisis. Hospitals faced challenges such as rapidly increasing their intensive care unit capacity, enabling physical distancing measures, quickly converting to telehealth and telework practices, and above all, keeping patients and staff safe. Improving flexibility in hospital facility design and adaptability of hospital operations to function in "crisis mode" can be seen as ways of future-proofing for pandemics. In a design brief, flexibility is typically mentioned as an important target. Meanwhile, robustness of technical infrastructure is called for, and standardization at unit level with single-occupancy inpatient accommodation may be considered a way to enhance flexibility and adaptability in dealing with a surge in infectious patients.

AIM

To future-proof facility design with pandemic preparedness and resilience in mind, this study evaluated what kinds of interventions were taken in Dutch hospital facilities and what perspectives need to be considered when hospitals operate in crisis mode.

METHODS

We have collected data from facility and estate professionals from 30 Dutch hospitals. Using a practice-based approach, in-depth interviewing helped uncover and compare successful operational strategies and design elements that provided the flexibility needed in the early stages of the recent crisis.

RESULTS

As we looked at existing facilities and alterations made to allow hospitals to operate during the COVID-19 pandemic, we discovered that staff availability and adaptability were deemed crucial.

CONCLUSION

We add the perspective of staff as an essential factor to be considered when future-proofing hospital facility desigr crisis mode operation.