ABSTRACT
The COVID-19 pandemic has prompted an unprecedented global effort to understand and mitigate the spread of the SARS-CoV-2 virus. In this study, we present a comprehensive analysis of COVID-19 in Western New York, integrating individual patient-level genomic sequencing data with a spatially informed agent-based disease Susceptible-Exposed-Infectious-Removed (SEIR) computational model. The integration of genomic and spatial data enables a multi-faceted exploration of the factors influencing the transmission patterns of COVID-19, including population density, movement dynamics, and genetic variations in the viral genomes replicating in New York State (NYS). Our findings shed light on local dynamics of the pandemic, revealing potential hotspots of transmission. Additionally, the genomic analysis provides insights into the genetic heterogeneity of SARS-CoV-2 within a single lineage at a region-specific level. This interdisciplinary approach, bridging genomics and spatial modeling, contributes to a more holistic understanding of COVID-19 dynamics. The results of this study have implications for future public health strategies, guiding targeted interventions and resource allocation to effectively control the spread of similar viruses in the Western New York region.
Subject(s)
COVID-19ABSTRACT
The sequencing of human virus genomes from wastewater samples is an efficient method for tracking viral transmission and evolution at the community level. However, this requires the recovery of viral nucleic acids of high quality. We developed a reusable tangential-flow filtration system to concentrate and purify viruses from wastewater for genome sequencing. A pilot study was conducted with 94 wastewater samples from four local sewersheds, from which viral nucleic acids were extracted, and the whole genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was sequenced using the ARTIC V4.0 primers. Our method yielded a high probability (0.9) of recovering complete or near-complete SARS-CoV-2 genomes (>90% coverage at 10× depth) from wastewater when the COVID-19 incidence rate exceeded 33 cases per 100 000 people. The relative abundances of sequenced SARS-CoV-2 variants followed the trends observed from patient-derived samples. We also identified SARS-CoV-2 lineages in wastewater that were underrepresented or not present in the clinical whole-genome sequencing data. The developed tangential-flow filtration system can be easily adopted for the sequencing of other viruses in wastewater, particularly those at low concentrations. The tangential-flow filtration method extracts high-quality viral nucleic acids from wastewater for robust and reliable genome sequencing.
ABSTRACT
The sequencing of human virus genomes from wastewater samples is an efficient method for tracking viral transmission and evolution at the community level. However, this requires the recovery of viral nucleic acids of high quality. We developed a reusable tangential-flow filtration system to concentrate and purify viruses from wastewater for genome sequencing. A pilot study was conducted with 94 wastewater samples from four local sewersheds, from which viral nucleic acids were extracted, and the whole genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was sequenced using the ARTIC V4.0 primers. Our method yielded a high probability (0.9) of recovering complete or near-complete SARS-CoV-2 genomes (>90% coverage at 10× depth) from wastewater when the COVID-19 incidence rate exceeded 33 cases per 100 000 people. The relative abundances of sequenced SARS-CoV-2 variants followed the trends observed from patient-derived samples. We also identified SARS-CoV-2 lineages in wastewater that were underrepresented or not present in the clinical whole-genome sequencing data. The developed tangential-flow filtration system can be easily adopted for the sequencing of other viruses in wastewater, particularly those at low concentrations.
ABSTRACT
Introduction: Since the emergence of the novel coronavirus SARS-CoV-2 in December 2019 in Wuhan, cases of the associated disease COVID-19 are seen worldwide. To collect clinical data of the pandemic the international, multicenter Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) registry was established. Here, we present a first description of cancer patients with COVID-19 from LEOSS. Patients and Methods: We retrospectively analyzed a cohort of 283 patients (pts) with cancer and COVID-19 from a total of 1808 pts enrolled between March 6th, 2020, and June 26th, 2020. Baseline characteristics include socio-demographics, comorbidity according to Charlson Comor-bidity Index (CCI), ECOG and outcome of COVID-19. Clinical manifestation of COVID-19 was described in four phases: uncomplicated (asymptomatic/mild symptoms), complicated (need for oxygen supplementation), critical (need for life supporting therapy) and recovery (clinical improvement/discharge). Result(s): Median observational period was 11 (range 0-48) days, median inpatients stay 12.5 (range 0-72) days. Most patients were aged 66 years or older (75.5%), 112 (39.5%) pts were female. Median CCI was 4 (0-15), 46/119 (16.5%) pts had an ECOG >2. Solid tumors were seen in 61%, lymphoma and leukemia in 14.5% and 10.5% respectively. One hundred and seven pts (38%) had an active malignant disease and 76 (27%) had received anti-cancer treatment within the last 3 months. In 181 (64%) pts COVID-19 remained in the uncomplicated phase whereas 93 (33%) pts developed a complicated or critical phase. Sixty-three (22.5%) pts required intensive care, 35 out of 63 needed mechanical ventilation. A total of 79 (28%) pts died, 67 (23.5%) from COVID-19. Median survival was 33 days and worse compared to non-cancer pts (non-cancer pts: med. survival not reached, p-value < 0.001). Conclusion(s): As expected, cancer patients hospitalized for COVID-19 frequently have severe disease and an adverse outcome. To confrm these results, age-and comorbidity adjusted analysis are needed. An update of the analysis will be presented at the DGHO Annual Meeting.
ABSTRACT
Wastewater-based surveillance (WBS) data normalization is an analyte measurement correction that addresses variations resulting from dilution of fecal discharge by non-sanitary sewage, stormwater or groundwater infiltration. No consensus exists on what WBS normalization parameters result in the strongest correlations and lead time between SARS-CoV-2 WBS data and COVID-19 cases. This study compared flow, population size and biomarker normalization impacts on the correlations and lead times for ten communities in twelve sewersheds in Alberta (Canada) between September 2020 and October 2021 (n = 1024) to determine if normalization by Pepper Mild Mottle Virus (PMMoV) provides any advantages compared to other normalization parameters (e.g., flow, reported and dynamic population sizes, BOD, TSS, NH3, TP). PMMoV concentrations (GC/mL) corresponded with plant influent flows and were highest in the urban centres. SARS-CoV-2 target genes E, N1 and N2 were all negatively associated with wastewater influent pH, while PMMoV was positively associated with temperature. Pooled data analysis showed that normalization increased ρ-values by almost 0.1 and was highest for ammonia, TKN and TP followed by PMMoV. Normalization by other parameters weakened associations. None of the differences were statistically significant. Site-specific correlations showed that normalization of SARS-CoV-2 data by PMMoV only improved correlations significantly in two of the twelve systems; neither were large sewersheds or combined sewer systems. In five systems, normalization by traditional wastewater strength parameters and dynamic population estimates improved correlations. Lead time ranged between 1 and 4 days in both pooled and site-specific comparisons. We recommend that WBS researchers and health departments: a) Investigate WWTP influent properties (e.g., pH) in the WBS planning phase and use at least two parallel approaches for normalization only if shown to provide value; b) Explore normalization by wastewater strength parameters and dynamic population size estimates further; and c) Evaluate purchasing an influent flow meter in small communities to support long-term WBS efforts and WWTP management.
Subject(s)
COVID-19 , Wastewater , Humans , SARS-CoV-2 , Alberta , Lead , Wastewater-Based Epidemiological MonitoringABSTRACT
The sequencing of human virus genomes from wastewater samples is an efficient method for tracking viral transmission and evolution at the community level. However, this requires the recovery of viral nucleic acids of high quality. We developed a reusable tangential-flow filtration system to concentrate and purify viruses from wastewater for whole-genome sequencing. A pilot study was conducted with 94 wastewater samples from four local sewersheds, from which viral nucleic acids were extracted, and the whole genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was sequenced using the ARTIC V4.0 primers. Our method yielded a high probability (0.9) of recovering complete or near-complete SARS-CoV-2 genomes (>90% coverage at 10x depth) from wastewater when the COVID-19 incidence rate exceeded 33 cases per 100 000 people. The relative abundances of sequenced SARS-CoV-2 variants followed the trends observed from patient-derived samples. We also identified SARS-CoV-2 lineages in wastewater that were underrepresented or not present in the clinical whole-genome sequencing data. The developed tangential-flow filtration system can be easily adopted for the sequencing of other viruses in wastewater, particularly those at low concentrations.
Subject(s)
Coronavirus Infections , COVID-19ABSTRACT
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.
Subject(s)
COVID-19 , Humans , Pandemics , RNA, Viral , SARS-CoV-2 , Urban Population , WastewaterABSTRACT
Using a Family Stress Model framework, we used quantitative and qualitative methods to investigate the impact of the pandemic on Latinx pregnant and parenting adolescents and their families. Participants were 406 adolescents (ages 14?19) in the southwestern U.S. who participated in a school-based relationship education program for pregnant and parenting adolescents. In the quantitative analysis, we compared self-reported mental health (depressive symptoms, worry, parental stress), coparental relationships (conflict and communication), and parenting of adolescents who participated prior to the pandemic (N?=?357;83.6% female;84.7% Latinx) with those who participated during the pandemic (N?=?49;74.6% female;87.8% Latinx). Unexpectedly, the pandemic-period cohort reported fewer depressive symptoms, less parental stress, more frequent coparental communication, and more positive coparental communication and conflict management than the pre-pandemic cohort. For the qualitative analysis, we conducted focus groups and individual interviews with 21 adolescent parents (95.2% female;90.5% Latinx) from the pandemic-period cohort and analyzed the data using thematic analysis. Participants reported many negative effects of the pandemic including increased economic and health stress, yet also discussed reduced pressure with school and more time with family members. These findings have important implications for enhancing the well-being of adolescent parents and their children after the pandemic.
ABSTRACT
BACKGROUND: Although much research has focused on nurses' retirement intentions, little is known about nurses who formally retire yet continue to practice, particularly in rural and remote settings where mobilization of all nurses is needed to assure essential health services. To optimize practice and sustain the workforce stretched thin by the COVID-19 pandemic, it is necessary to understand what it means for retired registered nurses (RNs) and licensed practical nurses (LPNs) to work after retirement. This study explored what nursing practice means for RNs and LPNs who have formally retired but continue to practice in rural and remote communities. METHODS: A pan-Canadian cross-sectional survey conducted in 2014-2015 of nurses in rural and remote Canada provided data for analysis. Textual responses from 82 RNs and 19 LPNs who indicated they had retired but were occasionally employed in nursing were interpreted hermeneutically. RESULTS: Retired nurses who continued to practice took on new challenges as well as sought opportunities to continue to learn, grow, and give back. Worklife flexibility was important, including having control over working hours. Nurses' everyday practice was inextricably tied up with their lives in rural and remote communities, with RNs emphasizing serving their communities and LPNs appreciating community recognition and the family-like character of their work settings. CONCLUSIONS: Retired nurses who continue to work in nursing see retirement as the next phase in their profession and a vital way of engaging with their rural and remote communities. This study counters the conventional view of retaining retired nurses only to combat nursing shortages and alleviate a knowledge drain from the workplace. Rural and remote nurses who retire and continue working contribute to their workplaces and communities in important and innovative ways. They can be characterized as dedicated, independent, and resilient. Transitioning to retirement in rural and remote practice can be re-imagined in ways that involve both the community and the workplace. Supporting work flexibility for retired nurses while facilitating their practice, technological acumen, and professional development, can allow retired nurses to contribute their joy of being a nurse along with their extensive knowledge and in-depth experience of nursing and the community.
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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.
Subject(s)
COVID-19 , SARS-CoV-2 , Disease Outbreaks , Humans , Tertiary Care Centers , Viral Load , WastewaterABSTRACT
Background: 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. Methods: Between August and December 2020, twice-weekly wastewater samples from three tertiary-care hospitals (totalling >2100 dedicated inpatient beds) were collected. 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. Results: 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 amount of detectable virus and the proportion of samples that were positive, consistent with increasing hospitalizations (Pearsons r=0.679, P<0.0001, Pearsons r=0.728, P<0.0001, respectively). Despite increasing hospitalizations through the study period, wastewater analysis was able to identify incident nosocomial-acquired cases of COVID-19 (Pearsons r =0.389, P<0.001) and unit-specific outbreaks by increases in detectable SARS-CoV-2 N1-RNA (median 112 copies/ml) versus outbreak-free periods (0 copies/ml; P<0.0001). Conclusions: 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.