Taking hospital pathogen surveillance to the next level.

High-throughput bacterial genomic sequencing and subsequent analyses can produce large volumes of high-quality data rapidly. Advances in sequencing technology, with commensurate developments in bioinformatics, have increased the speed and efficiency with which it is possible to apply genomics to outbreak analysis and broader public health surveillance. This approach has been focused on targeted pathogenic taxa, such as Mycobacteria, and diseases corresponding to different modes of transmission, including food-and-water-borne diseases (FWDs) and sexually transmitted infections (STIs). In addition, major healthcare-associated pathogens such as methicillin-resistant Staphylococcus aureus, vancomycin-resistant enterococci and carbapenemase-producing Klebsiella pneumoniae are the focus of research projects and initiatives to understand transmission dynamics and temporal trends on both local and global scales. Here, we discuss current and future public health priorities relating to genome-based surveillance of major healthcare-associated pathogens. We highlight the specific challenges for the surveillance of healthcare-associated infections (HAIs), and how recent technical advances might be deployed most effectively to mitigate the increasing public health burden they cause.

Collateral impacts of pandemic COVID-19 drive the nosocomial spread of antibiotic resistance: A modelling study.

BACKGROUND: Circulation of multidrug-resistant bacteria (MRB) in healthcare facilities is a major public health problem. These settings have been greatly impacted by the Coronavirus Disease 2019 (COVID-19) pandemic, notably due to surges in COVID-19 caseloads and the implementation of infection control measures. We sought to evaluate how such collateral impacts of COVID-19 impacted the nosocomial spread of MRB in an early pandemic context. METHODS AND FINDINGS: We developed a mathematical model in which Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and MRB cocirculate among patients and staff in a theoretical hospital population. Responses to COVID-19 were captured mechanistically via a range of parameters that reflect impacts of SARS-CoV-2 outbreaks on factors relevant for pathogen transmission. COVID-19 responses include both "policy responses" willingly enacted to limit SARS-CoV-2 transmission (e.g., universal masking, patient lockdown, and reinforced hand hygiene) and "caseload responses" unwillingly resulting from surges in COVID-19 caseloads (e.g., abandonment of antibiotic stewardship, disorganization of infection control programmes, and extended length of stay for COVID-19 patients). We conducted 2 main sets of model simulations, in which we quantified impacts of SARS-CoV-2 outbreaks on MRB colonization incidence and antibiotic resistance rates (the share of colonization due to antibiotic-resistant versus antibiotic-sensitive strains). The first set of simulations represents diverse MRB and nosocomial environments, accounting for high levels of heterogeneity across bacterial parameters (e.g., rates of transmission, antibiotic sensitivity, and colonization prevalence among newly admitted patients) and hospital parameters (e.g., rates of interindividual contact, antibiotic exposure, and patient admission/discharge). On average, COVID-19 control policies coincided with MRB prevention, including 28.2% [95% uncertainty interval: 2.5%, 60.2%] fewer incident cases of patient MRB colonization. Conversely, surges in COVID-19 caseloads favoured MRB transmission, resulting in a 13.8% [-3.5%, 77.0%] increase in colonization incidence and a 10.4% [0.2%, 46.9%] increase in antibiotic resistance rates in the absence of concomitant COVID-19 control policies. When COVID-19 policy responses and caseload responses were combined, MRB colonization incidence decreased by 24.2% [-7.8%, 59.3%], while resistance rates increased by 2.9% [-5.4%, 23.2%]. Impacts of COVID-19 responses varied across patients and staff and their respective routes of pathogen acquisition. The second set of simulations was tailored to specific hospital wards and nosocomial bacteria (methicillin-resistant Staphylococcus aureus, extended-spectrum beta-lactamase producing Escherichia coli). Consequences of nosocomial SARS-CoV-2 outbreaks were found to be highly context specific, with impacts depending on the specific ward and bacteria evaluated. In particular, SARS-CoV-2 outbreaks significantly impacted patient MRB colonization only in settings with high underlying risk of bacterial transmission. Yet across settings and species, antibiotic resistance burden was reduced in facilities with timelier implementation of effective COVID-19 control policies. CONCLUSIONS: Our model suggests that surges in nosocomial SARS-CoV-2 transmission generate selection for the spread of antibiotic-resistant bacteria. Timely implementation of efficient COVID-19 control measures thus has 2-fold benefits, preventing the transmission of both SARS-CoV-2 and MRB, and highlighting antibiotic resistance control as a collateral benefit of pandemic preparedness.

Epidemiology of Primary and Recurrent Healthcare-Associated and Community-Associated Pediatric Clostridioides difficile Infection in Canada, 2015-2020.

Clostridioides difficile infection (CDI) among children remains a concerning cause of morbidity in hospital settings. We present epidemiological and molecular trends in healthcare- and community-associated CDI among children in Canadian inpatient and outpatient settings, including those who experienced recurrent infections.

Can COVID-19 pandemic surveillance reduce nosocomial urinary infections in urologic surgery?

INTRODUCTION: Since COVID-19 pandemic spread, strict preventive measures were adopted to reduce the risk of transmission. Antiseptic dispensers for hand hygiene were diffusely available for patients and hospital staff. To investigate the prophylactic role played by the strict antiseptic rules adopted during pandemic, the rates of nosocomial urinary infections in 2019 and 2020 were compared. MATERIALS AND METHODS: Patients' clinical pre-operative characteristics, symptoms, fever, and laboratory data were recorded pre- and post-operatively. Urological surgery was classified in five categories: 1. major surgery 2. upper urinary tract endoscopy, 3. lower urinary tract endoscopy, 4. minor surgery, and 5. Nephrostomy and ureteral stenting. Clavien-Dindo complication score was used. Statistical analysis was performed with R 3.4.2 software. RESULTS: Out of 495 patients, 383 (57.1%) underwent surgical intervention in pre-pandemic March-May 2019 period and 212 (42.9%) in the same pandemic 2020 interval. Preoperatively, 40 (14.1%) and 11 (5.2%) and 77 (27.3%) and 37 (17.5%) patients had fever (p < 0.003) and leukocytosis (p < 0.02), in 2019 and 2020 respectively. Urine culture was positive in 29 (10.2%) and 13 (6.2%) patients respectively (p = 0.22). Post-operatively, 54 (19.1%) and 22 (10.4%) patients and 17 (6.1%) and 2 (0.6%) patients showed fever (p < 0.003) and positive urineculture (p < 0.03), in 2019 and 2020 respectively. DISCUSSION AND CONCLUSION: Preoperative and post-operative clinical and laboratory signs of nosocomial urinary infection showed a statistically significant lower incidence during the pandemic period in 2020. This observation could be ascribed to the strong preventive measures, to the medical staff high adherence to hygiene and the diffuse availability of hand sanitizers.

Society for Healthcare Epidemiology of America Compendium updates 2022.

PURPOSE OF REVIEW: Healthcare-associated infections (HAIs) are a leading cause of preventable harm in US hospitals. Hospitals are required to conduct surveillance and report selected HAIs, including central line-associated bloodstream infections, catheter-associated urinary tract infections, colon and abdominal hysterectomy surgical-site infections, methicillin-resistant Staphylococcus aureus bacteremia, and Clostridioides difficile infections, to the CDC's National Healthcare Safety Network. RECENT FINDINGS: Up until the COVID-19 pandemic, there was significant progress in reducing HAIs. However, the pandemic resulted in extraordinary challenges for infection prevention in hospitals. Increases in HAIs were observed throughout 2020 and 2021. The Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals has recently been updated and provides common sense evidenced-based strategies to reduce HAIs. SUMMARY: The purpose of this review is to highlight important changes since the 2014 Compendium.

Wastewater-based epidemiology for surveillance of infectious diseases in healthcare settings.

PURPOSE OF REVIEW: Wastewater-based surveillance (WBS) (epidemiology) using near-source sampling (NSS) in large buildings, hospitals and care homes is reviewed covering three main areas: state-of-the-art WBS, benefits/opportunities NSS has for hospital infection control systems and new insights from hospital wastewater surveillance and policy implications. RECENT FINDINGS: Wastewater provides aggregate, anonymous sources of data where the spatial resolution can be linked to populations being served. In hospitals, clear links established between wastewater RNA-fragments signal to nosocomial COVID-19 cases/outbreaks. Detecting other targets from hospital wastewater such as antimicrobial resistance markers is considered a substantial opportunity for this technology. Other clinically relevant infections, that is influenza and monkeypox, can be perceived, and sub-variant resolution to target public health response in near real time to benefit hospital infection control. WBS can reduce hospitals' clinical testing requirements, as diagnostic costs are aggregated into fewer samples while still detecting single cases. SUMMARY: WBS using NSS can inform infectious disease monitoring earlier, faster and cheaper than conventional monitoring. Routine sampling using wastewater provides a platform for risk-based sampling and enables smarter allocation of resources. Finally, hospital wastewater can be used for the benefit of the wastewater surveillance field as a promising source to monitor emerging threats and resolve longstanding questions on faecal shedding. Hospital monitoring in low-income settings is considered a priority for future research.

Implication of COVID-19 pandemic on the incidence of Clostridioides difficile infection in a Greek tertiary hospital.

Introduction. C. difficile infection (CDI) represents an important global threat. In the COVID-19 era, the multifactorial nature of CDI has emerged.Hypothesis - Aim. The aim was to assess the impact of COVID-19 pandemic on the incidence of CDI in a Greek hospital.Methodology. A retrospective study was performed throughout a 51 month period (January 2018 to March 2022), divided into two periods: pre-pandemic (January 2018 to February 2020) and COVID-19 pandemic (March 2020 to March 2022). The effects of the pandemic compared to the pre-pandemic period on the incidence of CDI [expressed as infections per 10 000 bed days (IBD)] were studied using interrupted time-series analysis.Results. Throughout the study, there was an increase in the monthly CDI incidence from 0.00 to 11.77 IBD (P<0.001). Interrupted time-series disclosed an increase in CDI incidence during the pre-pandemic period from 0.00 to 3.36 IBD (P<0.001). During the COVID-19 pandemic period the linear trend for monthly CDI rose from 2.65 to 13.93 IBD (P<0.001). The increase rate was higher during the COVID-19 pandemic period (r2 = +0.47) compared to the pre-pandemic period (r1 = +0.16).Conclusion. A significant increase of CDI incidence was observed, with the rate of the rise being more intense during the COVID-19 pandemic.

Evaluation of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for Molecular Typing of Acinetobacter baumannii in Comparison with Orthogonal Methods.

Colonization and subsequent health care-associated infection (HCAI) with Acinetobacter baumannii are a concern for vulnerable patient groups within the hospital setting. Outbreaks involving multidrug-resistant strains are associated with increased patient morbidity and mortality and poorer overall outcomes. Reliable molecular typing methods can help to trace transmission routes and manage outbreaks. In addition to methods deployed by reference laboratories, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) may assist by making initial in-house judgments on strain relatedness. However, limited studies on method reproducibility exist for this application. We applied MALDI-TOF MS typing to A. baumannii isolates associated with a nosocomial outbreak and evaluated different methods for data analysis. In addition, we compared MALDI-TOF MS with whole-genome sequencing (WGS) and Fourier transform infrared spectroscopy (FTIR) as orthogonal methods to further explore their resolution for bacterial strain typing. A related subgroup of isolates consistently clustered separately from the main outbreak group by all investigated methods. This finding, combined with epidemiological data from the outbreak, indicates that these methods identified a separate transmission event unrelated to the main outbreak. However, the MALDI-TOF MS upstream approach introduced measurement variability impacting method reproducibility and limiting its reliability as a standalone typing method. Availability of in-house typing methods with well-characterized sources of measurement uncertainty could assist with rapid and dependable confirmation (or denial) of suspected transmission events. This work highlights some of the steps to be improved before such tools can be fully integrated into routine diagnostic service workflows for strain typing. IMPORTANCE Managing the transmission of antimicrobial resistance necessitates reliable methods for tracking outbreaks. We compared the performance of MALDI-TOF MS with orthogonal approaches for strain typing, including WGS and FTIR, for Acinetobacter baumannii isolates correlated with a health care-associated infection (HCAI) event. Combined with epidemiological data, all methods investigated identified a group of isolates that were temporally and spatially linked to the outbreak, yet potentially attributed to a separate transmission event. This may have implications for guiding infection control strategies during an outbreak. However, the technical reproducibility of MALDI-TOF MS needs to be improved for it to be employed as a standalone typing method, as different stages of the experimental workflow introduced bias influencing interpretation of biomarker peak data. Availability of in-house methods for strain typing of bacteria could improve infection control practices following increased reports of outbreaks of antimicrobial-resistant organisms during the COVID-19 pandemic, related to sessional usage of personal protective equipment (PPE).

The impact of the COVID-19 pandemic on nosocomial infections: a retrospective analysis in a tertiary maternal and child healthcare hospital.

Objective: The constant changes in the control strategies of the Corona Virus Disease 2019 (COVID-19) pandemic have greatly affected the prevention and control of nosocomial infections (NIs). This study assessed the impact of these control strategies on the surveillance of NIs in a regional maternity hospital during the COVID-19 pandemic. Methods: This retrospective study compared the observation indicators of nosocomial infections and their changing trends in the hospital before and during the COVID-19 pandemic. Results: In total, 2,56,092 patients were admitted to the hospital during the study. During the COVID-19 pandemic, the main drug-resistant bacteria in hospitals were Escherichia coli, Streptococcus agalactiae, Staphylococcus aureus, Klebsiella pneumoniae, and Enterococcus faecalis. The detection rate of S. agalactiae increased annually, while that of E. faecalis remained the same. The detection rate of multidrug-resistant bacteria decreased during the pandemic (16.86 vs. 11.42%), especially that of CRKP (carbapenem-resistant Klebsiella pneumoniae 13.14 vs. 4.39, P < 0.001). The incidence of nosocomial infections in the pediatric surgery department decreased significantly (OR: 2.031, 95% CI: 1.405-2.934, P < 0.001). Regarding the source of infection, a significant reduction was observed in respiratory infections, followed by gastrointestinal infections. In the routine monitoring of the ICU, the incidence of central line-associated bloodstream infection (CLABSI) decreased significantly (9.4/1,000 catheter days vs. 2.2/1,000 catheter days, P < 0.001). Conclusion: The incidence of nosocomial infections was lower than that before the COVID-19 pandemic. The prevention and control measures for the COVID-19 pandemic have reduced the number of nosocomial infections, especially respiratory, gastrointestinal, and catheter-related infections.

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.

The impact of COVID-19 pandemic on healthcare associated infections: A teaching hospital experience.

Coronavirus disease-19 (COVID-19) is a global pandemic, with a high capability of contagious distribution, where national secondary and co-infections characterization are lacking. The objective of this study was to assess the impact of the COVID-19 pandemic on infection rates among patients admitted to the intensive care units at King Abdullah University Hospital, profiling the drug resistance rates nationally. This is a cross-sectional study of COVID-19 associated infections that was conducted at a teaching hospital, in the north of Jordan. It included all COVID-19 patients who were admitted to intensive care units during the first and second pandemic waves. Data on age, gender, length of stay, co-morbidities, co-infections and sensitivity to antibiotics were retrospectively collected from the hospital information database. Statistical analyses were performed using SPSS software. A total of 589 COVID-19 patients were included, of whom 20% developed bacterial associated infections. The ratio of bacterial co-infection to secondary infections was 1:8. Gram-negative bacteria, Acinetobacter baumannii (40.1%), Eschericia coli (17.5%), Klebsiella pneumonia (6.8%), and Pseudomonas aeruginosa (5.1%) were the most abundant isolated species. The detection rates of E coli (ESBL), K pneumonia (ESBL), A baumannii (CRO), P aeruginosa (CRO), S aureus (MRSA) were 52%, 67%, 97%, 44%, and 67%, respectively.

Trends in Severe Outcomes Among Adult and Pediatric Patients Hospitalized With COVID-19 in the Canadian Nosocomial Infection Surveillance Program, March 2020 to May 2022.

Importance: Trends in COVID-19 severe outcomes have significant implications for the health care system and are key to informing public health measures. However, data summarizing trends in severe outcomes among patients hospitalized with COVID-19 in Canada are not well described. Objective: To describe trends in severe outcomes among patients hospitalized with COVID-19 during the first 2 years of the COVID-19 pandemic. Design, Setting, and Participants: Active prospective surveillance in this cohort study was conducted from March 15, 2020, to May 28, 2022, at a sentinel network of 155 acute care hospitals across Canada. Participants included adult (aged ≥18 years) and pediatric (aged 0-17 years) patients hospitalized with laboratory-confirmed COVID-19 at a Canadian Nosocomial Infection Surveillance Program (CNISP)-participating hospital. Exposures: COVID-19 waves, COVID-19 vaccination status, and age group. Main Outcomes and Measures: The CNISP collected weekly aggregate data on the following severe outcomes: hospitalization, admission to an intensive care unit (ICU), receipt of mechanical ventilation, receipt of extracorporeal membrane oxygenation, and all-cause in-hospital death. Results: Among 1 513 065 admissions, the proportion of adult (n = 51 679) and pediatric (n = 4035) patients hospitalized with laboratory-confirmed COVID-19 was highest in waves 5 and 6 of the pandemic compared with waves 1 to 4 (77.3 vs 24.7 per 1000 patient admissions). Despite this, the proportion of patients with positive test results for COVID-19 who were admitted to an ICU, received mechanical ventilation, received extracorporeal membrane oxygenation, and died were each significantly lower in waves 5 and 6 when compared with waves 1 through 4. Admission to the ICU and in-hospital all-cause death rates were significantly higher among those who were unvaccinated against COVID-19 when compared with those who were fully vaccinated (incidence rate ratio, 4.3 and 3.9, respectively) or fully vaccinated with an additional dose (incidence rate ratio, 12.2 and 15.1, respectively). Conclusions and Relevance: The findings of this cohort study of patients hospitalized with laboratory-confirmed COVID-19 suggest that COVID-19 vaccination is important to reduce the burden on the Canadian health care system as well as severe outcomes associated with COVID-19.

A systematic outbreak investigation of SARS-CoV-2 transmission clusters in a tertiary academic care center.

BACKGROUND: We sought to decipher transmission pathways in healthcare-associated infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within our hospital by epidemiological work-up and complementary whole genome sequencing (WGS). We report the findings of the four largest epidemiologic clusters of SARS-CoV-2 transmission occurring during the second wave of the pandemic from 11/2020 to 12/2020. METHODS: At the University Hospital Basel, Switzerland, systematic outbreak investigation is initiated at detection of any nosocomial case of SARS-CoV-2 infection, as confirmed by polymerase chain reaction, occurring more than five days after admission. Clusters of nosocomial infections, defined as the detection of at least two positive patients and/or healthcare workers (HCWs) within one week with an epidemiological link, were further investigated by WGS on respective strains. RESULTS: The four epidemiologic clusters included 40 patients and 60 HCWs. Sequencing data was available for 70% of all involved cases (28 patients and 42 HCWs), confirmed epidemiologically suspected in house transmission in 33 cases (47.1% of sequenced cases) and excluded transmission in the remaining 37 cases (52.9%). Among cases with identical strains, epidemiologic work-up suggested transmission mainly through a ward-based exposure (24/33, 72.7%), more commonly affecting HCWs (16/24, 66.7%) than patients (8/24, 33.3%), followed by transmission between patients (6/33, 18.2%), and among HCWs and patients (3/33, 9.1%, respectively two HCWs and one patient). CONCLUSIONS: Phylogenetic analyses revealed important insights into transmission pathways supporting less than 50% of epidemiologically suspected SARS-CoV-2 transmissions. The remainder of cases most likely reflect community-acquired infection randomly detected by outbreak investigation. Notably, most transmissions occurred between HCWs, possibly indicating lower perception of the risk of infection during contacts among HCWs.

Health Care-Associated Infections Among Hospitalized Patients With COVID-19, March 2020-March 2022.

Importance: The reported incidence of many health care-associated infections (HAIs) increased during the COVID-19 pandemic; however, it is unclear whether this is due to increased patient risk or to increased pressure on the health care system. Objective: To assess HAI occurrence among patients admitted to hospitals with and without COVID-19. Design, Setting, and Participants: A cross-sectional retrospective analysis of inpatients discharged both with and without laboratory-confirmed COVID-19 infection was conducted. Data were obtained between January 1, 2019, and March 31, 2022, from community hospitals affiliated with a large health care system in the US. Exposure: COVID-19 infection. Main Outcomes and Measures: Occurrence of central line-associated bloodstream infection (CLABSI), catheter-associated urinary tract infection (CAUTI), methicillin-resistant Staphylococcus aureus (MRSA) bacteremia, and Clostridioides difficile infection as reported to the National Healthcare Safety Network. Results: Among nearly 5 million hospitalizations in 182 hospitals between 2020 and 2022, the occurrence of health care-associated infections (HAIs) was high among the 313 200 COVID-19 inpatients (median [SD] age, 57 [27.3] years; 56.0% women). Incidence per 100 000 patient-days showed higher HAIs among those with COVID-19 compared with those without. For CLABSI, the incidence for the full 9 quarters of the study was nearly 4-fold higher among the COVID-19 population than the non-COVID-19 population (25.4 vs 6.9). For CAUTI, the incidence in the COVID-19 population was 2.7-fold higher in the COVID-19 population (16.5 vs 6.1), and for MRSA, 3.0-fold higher (11.2 vs 3.7). Quarterly trends were compared with the same quarter in 2019. The greatest increase in the incidence of HAI in comparison with the same quarter in 2019 for the entire population occurred in quarter 3 of 2020 for CLABSI (11.0 vs 7.3), quarter 4 of 2021 for CAUTI (7.8 vs 6.8), and quarter 3 of 2021 for MRSA (5.2 vs 3.9). When limited to the non-COVID-19 population, the increase in CLABSI incidence vs the 2019 incidence was eliminated, and the quarterly rates of MRSA and CAUTI were lower vs the prepandemic 2019 comparator quarter. Conclusions and Relevance: In this cross-sectional study of hospitals during the pandemic, HAI occurrence among inpatients without COVID-19 was similar to that during 2019 despite additional pressures for infection control and health care professionals. The findings suggest that patients with COVID-19 may be more susceptible to HAIs and may require additional prevention measures.

Surveillance of device associated infections in intensive care units at a Saudi Arabian Hospital, 2017-2020.

BACKGROUND: Device-associated infections (DAIs) are important components of healthcare associated infection and are associated with increased morbidity and mortality. This study describes DAIs across different intensive care units (ICUs) in a hospital in Saudi Arabia. METHODS: The study was conducted between 2017 and 2020 and followed the definitions of National Healthcare Safety Network (NHSN) for DAIs. The calculated the rates of ventilator-associated events (VAE), catheter-associated urinary tract infections (CAUTI) and central line-associated blood stream infections (CLABSI) followed NHSN definitions. RESULTS: During the study period, there were 82 DAIs in adult ICUs and of these 16 (19.5%) were CLABSI, 26 (31.7%) were CAUTI and 40 (48.7%) were VAE. The overall rates for adult ICUs were 1.6, 1.9, 3.8 per 1000 device-days for CAUTI, CLABSI and VAE, respectively. The device-utilization ratio was 0.5, 0.6, and 0.48 for urinary catheters, central lines, and ventilators, respectively. VAE rates for medical and surgical ICU were about 2.8 times the rate in the coronary care unit and the rates were high in 2020 corresponding with the COVID-19 pandemic. Of the adult ICUS, medical ICU had a CLABSI rate of 2.13/1000 device-days and was about double the rate in surgical and cardiac ICU. For CAUTI, the rates per 1000 device-days were 2.19, 1.73, and 1.65 for medical, surgical, and coronary ICUs, respectively. The rate of CLABSI per 1000 device-days for pediatric and neonatal ICUs were 3.38 and 2.28, respectively. CONCLUSIONS: CAUTI was the most common infections among adult ICUs and medical ICU had higher rates than other adult ICUs. VAE rate was higher in the first year of the COVID-19 pandemic, indicating increased device-use, change in patients characteristics as well as possible change in practices across the ICUs.

Modeling transmission of pathogens in healthcare settings.

PURPOSE OF REVIEW: Mathematical, statistical, and computational models provide insight into the transmission mechanisms and optimal control of healthcare-associated infections. To contextualize recent findings, we offer a summative review of recent literature focused on modeling transmission of pathogens in healthcare settings. RECENT FINDINGS: The COVID-19 pandemic has led to a dramatic shift in the modeling landscape as the healthcare community has raced to characterize the transmission dynamics of SARS-CoV-2 and develop effective interventions. Inequities in COVID-19 outcomes have inspired new efforts to quantify how structural bias impacts both health outcomes and model parameterization. Meanwhile, developments in the modeling of methicillin-resistant Staphylococcus aureus, Clostridioides difficile, and other nosocomial infections continue to advance. Machine learning continues to be applied in novel ways, and genomic data is being increasingly incorporated into modeling efforts. SUMMARY: As the type and amount of data continues to grow, mathematical, statistical, and computational modeling will play an increasing role in healthcare epidemiology. Gaps remain in producing models that are generalizable to a variety of time periods, geographic locations, and populations. However, with effective communication of findings and interdisciplinary collaboration, opportunities for implementing models for clinical decision-making and public health decision-making are bound to increase.

Factors Associated With Nosocomial COVID-19 Infection Among Health Care Workers in an Urban-Setting Malaysia Hospital.

This single-center study aimed to explore the factors associated with coronavirus disease (COVID-19) transmission in a hospital. All laboratory-confirmed COVID-19 cases among health care workers (HCWs) in a tertiary hospital in Malaysia were analyzed cross-sectionally from January 25, 2020, to September 10, 2021. A total of 897 HCWs in the hospital had laboratory-confirmed COVID-19 infection during the study period. Around 37.4% of HCWs were suspected to acquire COVID-19 infection from the hospital workplace. Factors associated with lower odds of workplace COVID-19 transmission were being females, ≥30 years old, fully vaccinated, and working as clinical support staff. Involvement in COVID-19 patient care was significantly associated with higher odds (adjusted odds ratio = 3.53) of workplace COVID-19 transmission as compared with non-workplace transmission. Most HCWs in the tertiary hospital acquired COVID-19 infection from non-workplace settings. During a pandemic, it is important to communicate with HCWs about the risk of both workplace and non-workplace COVID-19 transmission and to implement measures to reduce both workplace and non-workplace COVID-19 transmission.

Nosocomial SARS-CoV-2 transmission in multi-bedded hospital cubicles over successive pandemic waves: Lower mortality but wider spread with Omicron despite enhanced infection-prevention measures.

BACKGROUND: Increased transmissibility of severe-acute-respiratory-syndrome-coronavirus-2(SARS-CoV-2) variants, such as the Omicron-variant, presents an infection-control challenge. We contrasted nosocomial transmission amongst hospitalized inpatients across successive pandemic waves attributed to the Delta- and Omicron variants, over a 9-month period in which enhanced-infection-prevention-measures were constantly maintained. METHODS: Enhanced-infection-prevention-measures in-place at a large tertiary hospital included universal N95-usage, routine-rostered-testing (RRT) for all inpatient/healthcare-workers (HCWs), rapid-antigen-testing (RAT) for visitors, and outbreak-investigation coupled with enhanced-surveillance (daily-testing) of exposed patients. The study-period lasted from 21st June 2021-21st March 2022. Chi-square test and multivariate-logistic-regression was utilized to identify factors associated with onward transmission and 28d-mortality amongst inpatient cases of hospital-onset COVID-19. RESULTS: During the Delta-wave, hospital-onset cases formed 2.7% (47/1727) of all COVID-19 cases requiring hospitalisation; in contrast, hospital onset-cases formed a greater proportion (17.7%, 265/1483; odds-ratio, OR = 7.78, 95%CI = 5.65-10.70) during the Omicron-wave, despite universal N95-usage and other enhanced infection-prevention measures that remained unchanged. The odds of 28d-mortality were higher during the Delta-wave compared to the Omicron-wave (27.7%, 13/47, vs. 10.6%, 28/265, adjusted-odds-ratio, aOR = 2.78, 95%CI = 1.02-7.69). Onward-transmission occurred in 21.2% (66/312) of hospital-onset cases; being on enhanced-surveillance (daily-testing) was independently associated with lower odds of onward-transmission (aOR = 0.18, 95%CI = 0.09-0.38). Costs amounted to $USD7141 per-hospital-onset COVID-19 case. CONCLUSION: A surge of hospital-onset COVID-19 cases was encountered during the Omicron-wave, despite continuation of enhanced infection-prevention measures; mortality amongst hospital-onset cases was reduced. The Omicron variant poses an infection-control challenge in contrast to Delta; surveillance is important especially in settings where infrastructural limitations make room-sharing unavoidable, despite the high risk of transmission.

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.

Patient and ward related risk factors in a multi-ward nosocomial outbreak of COVID-19: Outbreak investigation and matched case-control study.

BACKGROUND: Risk factors for nosocomial COVID-19 outbreaks continue to evolve. The aim of this study was to investigate a multi-ward nosocomial outbreak of COVID-19 between 1st September and 15th November 2020, occurring in a setting without vaccination for any healthcare workers or patients. METHODS: Outbreak report and retrospective, matched case-control study using incidence density sampling in three cardiac wards in an 1100-bed tertiary teaching hospital in Calgary, Alberta, Canada. Patients were confirmed/probable COVID-19 cases and contemporaneous control patients without COVID-19. COVID-19 outbreak definitions were based on Public Health guidelines. Clinical and environmental specimens were tested by RT-PCR and as applicable quantitative viral cultures and whole genome sequencing were conducted. Controls were inpatients on the cardiac wards during the study period confirmed to be without COVID-19, matched to outbreak cases by time of symptom onset dates, age within ± 15 years and were admitted in hospital for at least 2 days. Demographics, Braden Score, baseline medications, laboratory measures, co-morbidities, and hospitalization characteristics were collected on cases and controls. Univariate and multivariate conditional logistical regression was used to identify independent risk factors for nosocomial COVID-19. RESULTS: The outbreak involved 42 healthcare workers and 39 patients. The strongest independent risk factor for nosocomial COVID-19 (IRR 3.21, 95% CI 1.47-7.02) was exposure in a multi-bedded room. Of 45 strains successfully sequenced, 44 (97.8%) were B.1.128 and differed from the most common circulating community lineages. SARS-CoV-2 positive cultures were detected in 56.7% (34/60) of clinical and environmental specimens. The multidisciplinary outbreak team observed eleven contributing events to transmission during the outbreak. CONCLUSIONS: Transmission routes of SARS-CoV-2 in hospital outbreaks are complex; however multi-bedded rooms play a significant role in the transmission of SARS-CoV-2.