Porcine-derived pancreatic enzyme replacement therapy may be linked to chronic hepatitis E virus infection in cystic fibrosis lung transplant recipients.

OBJECTIVES: In high-income countries hepatitis E virus (HEV) is an uncommonly diagnosed porcine-derived zoonoses. After identifying disproportionate chronic HEV infections in persons with cystic fibrosis (pwCF) postlung transplant, we sought to understand its epidemiology and potential drivers. DESIGN: All pwCF post-transplant attending our regional CF centre were screened for HEV. HEV prevalence was compared against non-transplanted pwCF and with all persons screened for suspected HEV infection from 2016 to 2022 in Alberta, Canada. Those with chronic HEV infection underwent genomic sequencing and phylogenetic analysis. Owing to their swine derivation, independently sourced pancreatic enzyme replacement therapy (PERT) capsules were screened for HEV. RESULTS: HEV seropositivity was similar between transplanted and non-transplanted pwCF (6/29 (21%) vs 16/83 (19%); p=0.89). Relative to all other Albertans investigated for HEV as a cause of hepatitis (n=115/1079, 10.7%), pwCF had a twofold higher seropositivity relative risk and this was four times higher than the Canadian average. Only three chronic HEV infection cases were identified in all of Alberta, all in CF lung transplant recipients (n=3/29, 10.3%). Phylogenetics confirmed cases were unrelated porcine-derived HEV genotype 3a. Ninety-one per cent of pwCF were taking PERT (median 8760 capsules/person/year). HEV RNA was detected by RT-qPCR in 44% (47/107) of PERT capsules, and sequences clustered with chronic HEV cases. CONCLUSION: PwCF had disproportionate rates of HEV seropositivity, regardless of transplant status. Chronic HEV infection was evident only in CF transplant recipients. HEV may represent a significant risk for pwCF, particularly post-transplant. Studies to assess HEV incidence and prevalence in pwCF, and potential role of PERT are required.

A Bayesian framework for modeling COVID-19 case numbers through longitudinal monitoring of SARS-CoV-2 RNA in wastewater.

Wastewater-based surveillance has become an important tool for research groups and public health agencies investigating and monitoring the COVID-19 pandemic and other public health emergencies including other pathogens and drug abuse. While there is an emerging body of evidence exploring the possibility of predicting COVID-19 infections from wastewater signals, there remain significant challenges for statistical modeling. Longitudinal observations of viral copies in municipal wastewater can be influenced by noisy datasets and missing values with irregular and sparse samplings. We propose an integrative Bayesian framework to predict daily positive cases from weekly wastewater observations with missing values via functional data analysis techniques. In a unified procedure, the proposed analysis models severe acute respiratory syndrome coronavirus-2 RNA wastewater signals as a realization of a smooth process with error and combines the smooth process with COVID-19 cases to evaluate the prediction of positive cases. We demonstrate that the proposed framework can achieve these objectives with high predictive accuracies through simulated and observed real data.

Surveillance for SARS-CoV-2 and its variants in wastewater of tertiary care hospitals correlates with increasing case burden and outbreaks.

Wastewater-based SARS-CoV-2 surveillance enables unbiased and comprehensive monitoring of defined sewersheds. We performed real-time monitoring of hospital wastewater that differentiated Delta and Omicron variants within total SARS-CoV-2-RNA, enabling correlation to COVID-19 cases from three tertiary-care facilities with >2100 inpatient beds in Calgary, Canada. RNA was extracted from hospital wastewater between August/2021 and January/2022, and SARS-CoV-2 quantified using RT-qPCR. Assays targeting R203M and R203K/G204R established the proportional abundance of Delta and Omicron, respectively. Total and variant-specific SARS-CoV-2 in wastewater was compared to data for variant specific COVID-19 hospitalizations, hospital-acquired infections, and outbreaks. Ninety-six percent (188/196) of wastewater samples were SARS-CoV-2 positive. Total SARS-CoV-2 RNA levels in wastewater increased in tandem with total prevalent cases (Delta plus Omicron). Variant-specific assessments showed this increase to be mainly driven by Omicron. Hospital-acquired cases of COVID-19 were associated with large spikes in wastewater SARS-CoV-2 and levels were significantly increased during outbreaks relative to nonoutbreak periods for total SARS-CoV2, Delta and Omicron. SARS-CoV-2 in hospital wastewater was significantly higher during the Omicron-wave irrespective of outbreaks. Wastewater-based monitoring of SARS-CoV-2 and its variants represents a novel tool for passive COVID-19 infection surveillance, case identification, containment, and potentially to mitigate viral spread in hospitals.

Tracking Emergence and Spread of SARS-CoV-2 Omicron Variant in Large and Small Communities by Wastewater Monitoring in Alberta, Canada.

Wastewater monitoring of SARS-CoV-2 enables early detection and monitoring of the COVID-19 disease burden in communities and can track specific variants of concern. We determined proportions of the Omicron and Delta variants across 30 municipalities covering >75% of the province of Alberta (population 4.5 million), Canada, during November 2021-January 2022. Larger cities Calgary and Edmonton exhibited more rapid emergence of Omicron than did smaller and more remote municipalities. Notable exceptions were Banff, a small international resort town, and Fort McMurray, a medium-sized northern community that has many workers who fly in and out regularly. The integrated wastewater signal revealed that the Omicron variant represented close to 100% of SARS-CoV-2 burden by late December, before the peak in newly diagnosed clinical cases throughout Alberta in mid-January. These findings demonstrate that wastewater monitoring offers early and reliable population-level results for establishing the extent and spread of SARS-CoV-2 variants.

Stenotrophomonas maltophilia natural history and evolution in the airways of adults with cystic fibrosis.

Introduction: Stenotrophomonas maltophilia is an opportunistic pathogen infecting persons with cystic fibrosis (pwCF) and portends a worse prognosis. Studies of S. maltophilia infection dynamics have been limited by cohort size and follow-up. We investigated the natural history, transmission potential, and evolution of S. maltophilia in a large Canadian cohort of 321 pwCF over a 37-year period. Methods: One-hundred sixty-two isolates from 74 pwCF (23%) were typed by pulsed-field gel electrophoresis, and shared pulsotypes underwent whole-genome sequencing. Results: S. maltophilia was recovered at least once in 82 pwCF (25.5%). Sixty-four pwCF were infected by unique pulsotypes, but shared pulsotypes were observed between 10 pwCF. In chronic carriage, longer time periods between positive sputum cultures increased the likelihood that subsequent isolates were unrelated. Isolates from individual pwCF were largely clonal, with differences in gene content being the primary source of genetic diversity objectified by gene content differences. Disproportionate progression of CF lung disease was not observed amongst those infected with multiple strains over time (versus a single) or amongst those with shared clones (versus strains only infecting one patient). We did not observe evidence of patient-to-patient transmission despite relatedness between isolates. Twenty-four genes with ≥ 2 mutations accumulated over time were identified across 42 sequenced isolates from all 11 pwCF with ≥ 2 sequenced isolates, suggesting a potential role for these genes in adaptation of S. maltophilia to the CF lung. Discussion: Genomic analyses suggested common, indirect sources as the origins of S. maltophilia infections in the clinic population. The information derived from a genomics-based understanding of the natural history of S. maltophilia infection within CF provides unique insight into its potential for in-host evolution.

Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism.

Wastewater-based surveillance (WBS) of infectious diseases is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19's impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.4 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5 % (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4524 unrelated absences COVID-19 cases were recorded. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (P < 0.0001). The Poisson regression with wastewater as a one-week leading signal has an Akaike information criterion (AIC) of 858, compared to a null model (excluding wastewater predictor) with an AIC of 1895. The likelihood-ratio test comparing the model with wastewater signal with the null model shows statistical significance (P < 0.0001). We also assessed the variation of predictions when the regression model was applied to new data, with the predicted values and corresponding confidence intervals closely tracking actual absenteeism data. Wastewater-based surveillance has the potential to be used by employers to anticipate workforce requirements and optimize human resource allocation in response to trackable respiratory illnesses like COVID-19.

Campus node-based wastewater surveillance enables COVID-19 case localization and confirms lower SARS-CoV-2 burden relative to the surrounding community.

Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this approach has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021 and April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater using qPCR assays from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary's campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Real-time contact tracing data was used to evaluate an association between wastewater SARS-CoV-2 burden and clinically confirmed cases and to assess the potential of WBS as a tool for disease monitoring across worksites. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites - regardless of several normalization strategies - with certain catchments consistently demonstrating values 1-2 orders higher than the others. Relative to clinical cases identified in specific sewersheds, WBS provided one-week leading indicator. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p≤0.001). Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.

Effect of Disposable Elevator Cap Duodenoscopes on Persistent Microbial Contamination and Technical Performance of Endoscopic Retrograde Cholangiopancreatography: The ICECAP Randomized Clinical Trial.

Importance: Infection transmission following endoscopic retrograde cholangiopancreatography (ERCP) can occur due to persistent contamination of duodenoscopes despite high-level disinfection to completely eliminate microorganisms on the instrument. Objective: To determine (1) contamination rates after high-level disinfection and (2) technical performance of duodenoscopes with disposable elevator caps compared with those with standard designs. Design, Setting, and Participants: In this parallel-arm multicenter randomized clinical trial at 2 tertiary ERCP centers in Canada, all patients 18 years and older and undergoing ERCP for any indication were eligible. Intervention: The intervention was use of duodenoscopes with disposable elevator caps compared with duodenoscopes with a standard design. Main Outcomes and Measures: Coprimary outcomes were persistent microbial contamination of the duodenoscope elevator or channel, defined as growth of at least 10 colony-forming units of any organism or any growth of gram-negative bacteria following high-level disinfection (superiority outcome), and technical success of ERCP according to a priori criteria (noninferiority outcome with an a priori noninferiority margin of 7%), assessed by blinded reviewers. Results: From December 2019 to February 2022, 518 patients were enrolled (259 disposable elevator cap duodenoscopes, 259 standard duodenoscopes). Patients had a mean (SD) age of 60.7 (17.0) years and 258 (49.8%) were female. No significant differences were observed between study groups, including in ERCP difficulty. Persistent microbial contamination was detected in 11.2% (24 of 214) of standard duodenoscopes and 3.8% (8 of 208) of disposable elevator cap duodenoscopes (P = .004), corresponding to a relative risk of 0.34 (95% CI, 0.16-0.75) and number needed to treat of 13.6 (95% CI, 8.1-42.7) to avoid persistent contamination. Technical success using the disposable cap scope was noninferior to that of the standard scope (94.6% vs 90.7%, P = .13). There were no differences between study groups in adverse events and other secondary outcomes. Conclusions and Relevance: In this randomized clinical trial, disposable elevator cap duodenoscopes exhibited reduced contamination following high-level disinfection compared with standard scope designs, without affecting the technical performance and safety of ERCP. Trial Registration: ClinicalTrials.gov Identifier: NCT04040504.

The natural history and genetic diversity of Haemophilus influenzae infecting the airways of adults with cystic fibrosis.

Haemophilus influenzae is a Gram-negative pathobiont, frequently recovered from the airways of persons with cystic fibrosis (pwCF). Previous studies of H. influenzae infection dynamics and transmission in CF predominantly used molecular methods, lacking resolution. In this retrospective cohort study, representative yearly H. influenzae isolates from all pwCF attending the Calgary Adult CF Clinic with H. influenzae positive sputum cultures between 2002 and 2016 were typed by pulsed-field gel electrophoresis. Isolates with shared pulsotypes common to ≥ 2 pwCF were sequenced by Illumina MiSeq. Phylogenetic and pangenomic analyses were used to assess genetic relatedness within shared pulsotypes, and epidemiological investigations were performed to assess potential for healthcare associated transmission. H. influenzae infection was observed to be common (33% of patients followed) and dynamic in pwCF. Most infected pwCF exhibited serial infections with new pulsotypes (75% of pwCF with ≥ 2 positive cultures), with up to four distinct pulsotypes identified from individual patients. Prolonged infection by a single pulsotype was only rarely observed. Intra-patient genetic diversity was observed at the single-nucleotide polymorphism and gene content levels. Seven shared pulsotypes encompassing 39% of pwCF with H. influenzae infection were identified, but there was no evidence, within our sampling scheme, of direct patient-to-patient infection transmission.

Longitudinal SARS-CoV-2 RNA wastewater monitoring across a range of scales correlates with total and regional COVID-19 burden in a well-defined urban population.

Wastewater-based epidemiology (WBE) is an emerging surveillance tool that has been used to monitor the ongoing COVID-19 pandemic by tracking SARS-CoV-2 RNA shed into wastewater. WBE was performed to monitor the occurrence and spread of SARS-CoV-2 from three wastewater treatment plants (WWTP) and six neighborhoods in the city of Calgary, Canada (population 1.44 million). A total of 222 WWTP and 192 neighborhood samples were collected from June 2020 to May 2021, encompassing the end of the first-wave (June 2020), the second-wave (November end to December 2020) and the third-wave of the COVID-19 pandemic (mid-April to May 2021). Flow-weighted 24-hour composite samples were processed to extract RNA that was then analyzed for two SARS-CoV-2-specific regions of the nucleocapsid gene, N1 and N2, using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Using this approach SARS-CoV-2 RNA was detected in 98.06% (406/414) of wastewater samples. SARS-CoV-2 RNA abundance was compared to clinically diagnosed COVID-19 cases organized by the three-digit postal code of affected individuals' primary residences, enabling correlation analysis at neighborhood, WWTP and city-wide scales. Strong correlations were observed between N1 & N2 gene signals in wastewater and new daily cases for WWTPs and neighborhoods. Similarly, when flow rates at Calgary's three WWTPs were used to normalize observed concentrations of SARS-CoV-2 RNA and combine them into a city-wide signal, this was strongly correlated with regionally diagnosed COVID-19 cases and clinical test percent positivity rate. Linked census data demonstrated disproportionate SARS-CoV-2 in wastewater from areas of the city with lower socioeconomic status and more racialized communities. WBE across a range of urban scales was demonstrated to be an effective mechanism of COVID-19 surveillance.

A multicenter study investigating SARS-CoV-2 in tertiary-care hospital wastewater. viral burden correlates with increasing hospitalized cases as well as hospital-associated transmissions and outbreaks.

SARS-CoV-2 has been detected in wastewater and its abundance correlated with community COVID-19 cases, hospitalizations and deaths. We sought to use wastewater-based detection of SARS-CoV-2 to assess the epidemiology of SARS-CoV-2 in hospitals. Between August and December 2020, twice-weekly wastewater samples from three tertiary-care hospitals (totaling > 2100 dedicated inpatient beds) were collected. Hospital-1 and Hospital-2 could be captured with a single sampling point whereas Hospital-3 required three separate monitoring sites. Wastewater samples were concentrated and cleaned using the 4S-silica column method and assessed for SARS-CoV-2 gene-targets (N1, N2 and E) and controls using RT-qPCR. Wastewater SARS-CoV-2 as measured by quantification cycle (Cq), genome copies and genomes normalized to the fecal biomarker PMMoV were compared to the total daily number of patients hospitalized with active COVID-19, confirmed cases of hospital-acquired infection, and the occurrence of unit-specific outbreaks. Of 165 wastewater samples collected, 159 (96%) were assayable. The N1-gene from SARS-CoV-2 was detected in 64.1% of samples, N2 in 49.7% and E in 10%. N1 and N2 in wastewater increased over time both in terms of the amount of detectable virus and the proportion of samples that were positive, consistent with increasing hospitalizations at those sites with single monitoring points (Pearson's r = 0.679, P < 0.0001, Pearson's r = 0.799, P < 0.0001, respectively). Despite increasing hospitalizations through the study period, nosocomial-acquired cases of COVID-19 (Pearson's r = 0.389, P < 0.001) and unit-specific outbreaks were discernable with significant increases in detectable SARS-CoV-2 N1-RNA (median 112 copies/ml) versus outbreak-free periods (0 copies/ml; P < 0.0001). Wastewater-based monitoring of SARS-CoV-2 represents a promising tool for SARS-CoV-2 passive surveillance and case identification, containment, and mitigation in acute- care medical facilities.

The effects of cycled inhaled aztreonam on the cystic fibrosis (CF) lung microbiome.

BACKGROUND: To improve clinical outcomes, cystic fibrosis (CF) patients with chronic Pseudomonas aeruginosa infections are prescribed inhaled anti-pseudomonal antibiotics. Although, a diverse microbial community exists within CF airways, little is known about how the CF microbiota influences patient outcomes. We hypothesized that organisms within the CF microbiota are affected by inhaled-antibiotics and baseline microbiome may be used to predict therapeutic response. METHODS: Adults with chronic P. aeruginosa infection from four clinics were observed during a single 28-day on/off inhaled-aztreonam cycle. Patients performed serial sputum collection, CF-respiratory infection symptom scores (CRISS), and spirometry. Patients achieving a decrease of ≥2 CRISS by day 28 were categorized as subjective responders (SR). The airway microbiome was defined by Illumina MiSeq analysis of the 16S rRNA gene. RESULTS: Thirty-seven patients (median 37.4 years and FEV1 44% predicted) were enrolled. No significant cohort-wide changes in the microbiome were observed between on/off AZLI cycles in either alpha- or beta-diversity metrics. However, at an individual level shifts were apparent. Twenty-one patients (57%) were SR and fourteen patients did not subjectively respond. While alpha-diversity metrics did not associate with response, patients who did not subjectively respond had a higher abundance of Staphylococcus and Streptococcus, and lower abundance of Haemophilus. CONCLUSIONS: The CF microbiome is relatively resilient to AZLI perturbations. However, associated changes were observed at the individual patient level. The relative abundance of key "off-target" organisms associated with subjective improvements suggesting that the microbiome may be used as a tool to predict patient response - potentially improving outcomes.