Applying prospective genomic surveillance to support investigation of hospital-onset COVID-19.
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ABSTRACT:
SUBMITTER: Hamilton WL
PROVIDER: S-EPMC8110208 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Hospital-onset COVID-19 infections (HOCIs) are associated with excess morbidity and mortality in patients and healthcare workers. The aim of this review was to explore and describe the current literature in HOCI surveillance. Medline, EMBASE, the Cochrane Database of Systematic Reviews, the Cochrane Register of Controlled Trials, and MedRxiv were searched up to 30 November 2020 using broad search criteria. Articles of HOCI surveillance systems were included. Data describing HOCI definitions, HOCI incidence, types of HOCI identification surveillance systems, and level of system implementation were extracted. A total of 292 citations were identified. Nine studies on HOCI surveillance were included. Six studies reported on the proportion of HOCI among hospitalized COVID-19 patients, which ranged from 0 to 15.2%. Six studies provided HOCI case definitions. Standardized national definitions provided by the UK and US governments were identified. Four studies included healthcare workers in the surveillance. One study articulated a multimodal strategy of infection prevention and control practices including HOCI surveillance. All identified HOCI surveillance systems were implemented at institutional level, with eight studies focusing on all hospital inpatients and one study focusing on patients in the emergency department. Multiple types of surveillance were identified. Four studies reported automated surveillance, of which one included real-time analysis, and one included genomic data. Overall, the study quality was limited by the observational nature with short follow-up periods. In conclusion, HOCI case definitions and surveillance methods were developed pragmatically. Whilst standardized case definitions and surveillance systems are ideal for integration with existing routine surveillance activities and adoption in different settings, we acknowledged the difficulties in establishing such standards in the short-term.
| S-EPMC8278304 | biostudies-literature
Project description:BackgroundUnderstanding nosocomial acquisition, outbreaks, and transmission chains in real time will be fundamental to ensuring infection-prevention measures are effective in controlling coronavirus disease 2019 (COVID-19) in healthcare. We report the design and implementation of a hospital-onset COVID-19 infection (HOCI) surveillance system for an acute healthcare setting to target prevention interventions.MethodsThe study took place in a large teaching hospital group in London, United Kingdom. All patients tested for SARS-CoV-2 between 4 March and 14 April 2020 were included. Utilizing data routinely collected through electronic healthcare systems we developed a novel surveillance system for determining and reporting HOCI incidence and providing real-time network analysis. We provided daily reports on incidence and trends over time to support HOCI investigation and generated geotemporal reports using network analysis to interrogate admission pathways for common epidemiological links to infer transmission chains. By working with stakeholders the reports were co-designed for end users.ResultsReal-time surveillance reports revealed changing rates of HOCI throughout the course of the COVID-19 epidemic, key wards fueling probable transmission events, HOCIs overrepresented in particular specialties managing high-risk patients, the importance of integrating analysis of individual prior pathways, and the value of co-design in producing data visualization. Our surveillance system can effectively support national surveillance.ConclusionsThrough early analysis of the novel surveillance system we have provided a description of HOCI rates and trends over time using real-time shifting denominator data. We demonstrate the importance of including the analysis of patient pathways and networks in characterizing risk of transmission and targeting infection-control interventions.
| S-EPMC7454383 | biostudies-literature
Project description:The spread of SARS-CoV-2 in Beijing before May, 2020 resulted from transmission following both domestic and global importation of cases. Here we present genomic surveillance data on 102 imported cases, which account for 17.2% of the total cases in Beijing. Our data suggest that all of the cases in Beijing can be broadly classified into one of three groups: Wuhan exposure, local transmission and overseas imports. We classify all sequenced genomes into seven clusters based on representative high-frequency single nucleotide polymorphisms (SNPs). Genomic comparisons reveal higher genomic diversity in the imported group compared to both the Wuhan exposure and local transmission groups, indicating continuous genomic evolution during global transmission. The imported group show region-specific SNPs, while the intra-host single nucleotide variations present as random features, and show no significant differences among groups. Epidemiological data suggest that detection of cases at immigration with mandatory quarantine may be an effective way to prevent recurring outbreaks triggered by imported cases. Notably, we also identify a set of novel indels. Our data imply that SARS-CoV-2 genomes may have high mutational tolerance.
| S-EPMC7603498 | biostudies-literature
Project description:BackgroundDuring the second COVID-19 wave, a large COVID-19 outbreak happened at a 90-bed geriatric palliative care hospital in December 2020, whereby 32 % of the healthcare personnel (HCP) and 29 patients became infected within 23 days and 13 patients died. The bed occupancy rate dropped to 20 %. Drastically enhanced hygiene measures directly after outbreak detection could stop further nosocomial infections among patients but were less effective among HCP.ObjectiveOutbreak investigation and detection of risk factors for infection in HCP.Material and methodsAnonymous online survey among HCP from January and February 2021 investigating potential risk factors for PCR positive infections (poorly fitting FFP2 masks, close contacts with positive patients, team meetings with positive HCP).ResultsOf 184 HCP, 96 completed the survey (52.2 %), including 38 who became infected. Of the HCP 8 remained asymptomatic/oligosymptomatic, 30 HCP became ill for a median of 10 days and in 2 continuously. Factors associated with an infection were close contacts with positive patients in a time-dependent manner despite wearing an FFP2 mask (OR 6.0; 95 % CI 1.6-22). Out of 88 HCP 55 described poorly fitting FFP2 masks. An infection was mostly attributed to a longer contact with positive, sometimes restless patients. The overall exhausting working situation was repeatedly mentioned.ConclusionA COVID outbreak within the care-intense geriatric context is challenging to control especially among HCP. Longer patient contacts and limited compliance by patients counteracts strict hygiene measures. Vulnerability of HCP and patients requires additional preventive interventions by rapidly effective vaccinations and has to be a priority for health policy.
| S-EPMC8258484 | biostudies-literature
Project description:COVID-19 Health Surveillance FVG
| PRJEB46661 | ENA
Project description:ObjectiveTo directly measure the fatal impact of coronavirus disease 2019 (covid-19) in an urban African population.DesignProspective systematic postmortem surveillance study.SettingZambia's largest tertiary care referral hospital.ParticipantsDeceased people of all ages at the University Teaching Hospital morgue in Lusaka, Zambia, enrolled within 48 hours of death.Main outcome measurePostmortem nasopharyngeal swabs were tested via reverse transcriptase quantitative polymerase chain reaction (PCR) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Deaths were stratified by covis-19 status, location, age, sex, and underlying risk factors.Results372 participants were enrolled between June and September 2020; PCR results were available for 364 (97.8%). SARS-CoV-2 was detected in 58/364 (15.9%) according to the recommended cycle threshold value of <40 and in 70/364 (19.2%) when expanded to any level of PCR detection. The median age at death among people with a positive test for SARS-CoV-2 was 48 (interquartile range 36-72) years, and 69% (n=48) were male. Most deaths in people with covid-19 (51/70; 73%) occurred in the community; none had been tested for SARS-CoV-2 before death. Among the 19/70 people who died in hospital, six were tested before death. Among the 52/70 people with data on symptoms, 44/52 had typical symptoms of covid-19 (cough, fever, shortness of breath), of whom only five were tested before death. Covid-19 was identified in seven children, only one of whom had been tested before death. The proportion of deaths with covid-19 increased with age, but 76% (n=53) of people who died were aged under 60 years. The five most common comorbidities among people who died with covid-19 were tuberculosis (22; 31%), hypertension (19; 27%), HIV/AIDS (16; 23%), alcohol misuse (12; 17%), and diabetes (9; 13%).ConclusionsContrary to expectations, deaths with covid-19 were common in Lusaka. Most occurred in the community, where testing capacity is lacking. However, few people who died at facilities were tested, despite presenting with typical symptoms of covid-19. Therefore, cases of covid-19 were under-reported because testing was rarely done not because covid-19 was rare. If these data are generalizable, the impact of covid-19 in Africa has been vastly underestimated.
| S-EPMC7887952 | biostudies-literature
Project description:SARS-CoV-2 is notable both for its rapid spread, and for the heterogeneity of its patterns of transmission, with multiple published incidences of superspreading behaviour. Here, we applied a novel network reconstruction algorithm to infer patterns of viral transmission occurring between patients and health care workers (HCWs) in the largest clusters of COVID-19 infection identified during the first wave of the epidemic at Cambridge University Hospitals NHS Foundation Trust, UK. Based upon dates of individuals reporting symptoms, recorded individual locations, and viral genome sequence data, we show an uneven pattern of transmission between individuals, with patients being much more likely to be infected by other patients than by HCWs. Further, the data were consistent with a pattern of superspreading, whereby 21% of individuals caused 80% of transmission events. Our study provides a detailed retrospective analysis of nosocomial SARS-CoV-2 transmission, and sheds light on the need for intensive and pervasive infection control procedures.
| S-EPMC8384420 | biostudies-literature
Project description:The long-term sequelae of coronavirus disease 2019 (COVID-19) are only now beginning to be defined, but it is already known that the disease can have direct and indirect impacts mainly on the cardiorespiratory and neuromuscular systems and may affect mental health. A role for rehabilitation professionals from all disciplines in addressing COVID-19 sequelae is recognised, but it is essential that patient assessment be systematic if health complications are to be identified and treated and, if possible, prevented. The aim is to present a COVID-19 prospective surveillance model based on sensitive and easily used assessment tools, which is urgently required. Following the Oxford Centre for Evidence-Based Medicine Level of Evidence Tool, an expert team in cardiorespiratory, neuromuscular and mental health worked via telemeetings to establish a model that provides guidelines to rehabilitation professionals working with patients who require rehabilitation after suffering from COVID-19. A COVID-19 prospective surveillance model is proposed for use by rehabilitation professionals and includes both face-to-face and telematic monitoring components. This model should facilitate the early identification and management of long-term COVID-19 sequelae, thus responding to an arising need.
| S-EPMC8071011 | biostudies-literature
Project description:COVID-19 Health Surveillance FVG-0
| PRJEB46741 | ENA
Project description:BackgroundThe burden and influence of health-care associated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is unknown. We aimed to examine the use of rapid SARS-CoV-2 sequencing combined with detailed epidemiological analysis to investigate health-care associated SARS-CoV-2 infections and inform infection control measures.MethodsIn this prospective surveillance study, we set up rapid SARS-CoV-2 nanopore sequencing from PCR-positive diagnostic samples collected from our hospital (Cambridge, UK) and a random selection from hospitals in the East of England, enabling sample-to-sequence in less than 24 h. We established a weekly review and reporting system with integration of genomic and epidemiological data to investigate suspected health-care associated COVID-19 cases.FindingsBetween March 13 and April 24, 2020, we collected clinical data and samples from 5613 patients with COVID-19 from across the East of England. We sequenced 1000 samples producing 747 high-quality genomes. We combined epidemiological and genomic analysis of the 299 patients from our hospital and identified 35 clusters of identical viruses involving 159 patients. 92 (58%) of 159 patients had strong epidemiological links and 32 (20%) patients had plausible epidemiological links. These results were fed back to clinical, infection control, and hospital management teams, leading to infection-control interventions and informing patient safety reporting.InterpretationWe established real-time genomic surveillance of SARS-CoV-2 in a UK hospital and showed the benefit of combined genomic and epidemiological analysis for the investigation of health-care associated COVID-19. This approach enabled us to detect cryptic transmission events and identify opportunities to target infection-control interventions to further reduce health-care associated infections. Our findings have important implications for national public health policy as they enable rapid tracking and investigation of infections in hospital and community settings.FundingCOVID-19 Genomics UK funded by the Department of Health and Social Care, UK Research and Innovation, and the Wellcome Sanger Institute.
| S-EPMC7806511 | biostudies-literature