An interactive data visualisation application to investigate nosocomial transmission of infections.
ABSTRACT: Background: Healthcare-associated infections represent a major threat to patient, staff and visitor safety. Identification of episodes that are likely to have resulted from nosocomial transmission has important implications for infection control. Routinely collected data on ward admissions and sample dates, combined with pathogen genomic information could provide useful insights. We describe a novel, open-source, application for visualising these data, and demonstrate its utility for investigating nosocomial transmission using a case study of a large outbreak of norovirus infection. Methods: We developed the application using Shiny, a web application framework for R. For the norovirus case study, cases were defined as patients who had a faecal sample collected at the hospital in a winter season that tested positive for norovirus. Patient demographics and ward admission dates were extracted from hospital systems. Detected norovirus strains were genotyped and further characterised through sequencing of the hypervariable P2 domain. The most commonly detected sub-strain was visualised using the interactive application. Results: There were 156 norovirus-positive specimens collected from 107 patients. The most commonly detected sub-strain affected 30 patients in five wards. We used the interactive application to produce three visualisations: a bar chart, a timeline, and a schematic ward plan highlighting plausible transmission links. Visualisations showed credible links between cases on the elderly care ward. Conclusions: Use of the interactive application provided insights into transmission in this large nosocomial outbreak of norovirus, highlighting where infection control practices worked well or could be improved. This is a flexible tool that could be used for investigation of any infection in any hospital by interactively changing parameters. Challenges include integration with hospital systems for extracting data. Prospective use of this application could inform better infection control in real time.
Project description:Noroviruses are a highly transmissible and major cause of nosocomial gastroenteritis resulting in bed and hospital-ward closures. Where hospital outbreaks are suspected, it is important to determine the routes of spread so that appropriate infection-control procedures can be implemented. To investigate a cluster of norovirus cases occurring in children undergoing bone marrow transplant, we undertook norovirus genome sequencing by next-generation methods. Detailed comparison of sequence data from 2 linked cases enabled us to identify the likely direction of spread.Norovirus complementary DNA was amplified by overlapping polymerase chain reaction (PCR) from 13 stool samples from 5 diagnostic real-time PCR-positive patients. The amplicons were sequenced by Roche 454, the genomes assembled by de novo assembly, and the data analyzed phylogenetically.Phylogenetic analysis indicated that patients were infected by viruses similar to 4 distinct GII.4 subtypes and 2 patients were linked by the same virus. Of the 14 sites at which there were differences between the consensus sequences of the 2 linked viral genomes, 9 had minor variants present within one or the other patient. Further analysis confirmed that minor variants at all 9 sites in patient B w ere present as the consensus sequence in patient A.Phylogenetic analysis excluded a common source of infection in this apparent outbreak. Two of 3 patients on the same ward had closely related viruses, raising the possibility of cross-infection despite protective isolation. Analysis of deep sequencing data enabled us to establish the likely direction of nosocomial transmission.
Project description:Background:Norovirus is a leading cause of worldwide and nosocomial gastroenteritis. The study aim was to assess the utility of molecular epidemiology using full genome sequences compared to routine infection prevention and control (IPC) investigations. Methods:Norovirus genomes were generated from new episodes of norovirus at a pediatric tertiary referral hospital over a 19-month period (n = 182). Phylogeny identified clusters of related sequences that were verified using epidemiological and clinical data. Results:Twenty-four clusters of related norovirus sequences ("sequence clusters") were observed, including 8 previously identified by IPC investigations ("IPC outbreaks"). Seventeen sequence clusters (involving 77/182 patients) were corroborated by epidemiological data ("epidemiologically supported clusters"), suggesting transmission between patients. Linked infections were identified among 44 patients who were missed by IPC investigations. Thirty-three percent of norovirus sequences were linked, suggesting nosocomial transmission; 24% of patients had nosocomial infections from an unknown source; and 43% were norovirus positive on admission. Conclusions:We show there are frequent introductions of multiple norovirus strains with extensive onward nosocomial transmission of norovirus in a pediatric hospital with a high proportion of immunosuppressed patients nursed in isolation. Phylogenetic analysis using full genome sequences is more sensitive than classic IPC investigations for identifying linked cases and should be considered when investigating norovirus nosocomial transmission. Sampling of staff, visitors, and the environment may be required for complete understanding of infection sources and transmission routes in patients with nosocomial infections not linked to other patients and among patients with phylogenetically linked cases but no evidence of direct contact.
Project description:<h4>Objective</h4>To assess the role of spatial proximity, defined as patients sharing bays, in the spread of norovirus during outbreaks in hospitals.<h4>Design</h4>Enhanced surveillance of norovirus outbreaks between November 2009 and November 2011.<h4>Methods</h4>Data were gathered during 149 outbreaks of norovirus in hospital wards from five hospitals in two major cities in England serving a population of two million. We used the time between the first two cases of each outbreak to estimate the serial interval for norovirus in this setting. This distribution and dates of illness onset were used to calculate epidemic trees for each outbreak. We then used a permutation test to assess whether proximity, for all outbreaks, was more extreme than would be expected by chance under the null hypothesis that proximity was not associated with transmission risk.<h4>Results</h4>65 outbreaks contained complete data on both onset dates and ward position. We estimated the serial interval to be 1.86 days (95% CI 1.6 to 2.2 days), and with this value found strong evidence to reject the null hypothesis that proximity was not significant (p<0.001). Sensitivity analysis using different values of the serial interval showed that there was evidence to reject the null hypothesis provided the assumed serial interval was less than 2.5 days.<h4>Conclusions</h4>Our results provide evidence that patients occupying the same bay as patients with symptomatic norovirus infection are at an increased risk of becoming infected by these patients compared with patients elsewhere in the same ward.
Project description:<h4>Background</h4>Norovirus outbreaks cause severe medico-socio-economic problems affecting healthcare workers and patients. The aim of the study was to investigate prevalence of norovirus infection and risk factors for infection in healthcare workers during nosocomial outbreaks.<h4>Methods</h4>A cross-sectional study of norovirus infections in healthcare workers was performed in seven outbreak wards in a large university hospital. Packs (swab for rectal sampling, and questionnaire) were posted to healthcare workers on notification of a ward outbreak. Rectal samples were examined with norovirus-specific real-time PCR. Replies from questionnaires were analysed using logistic regression models with norovirus genogroup (G)II positive findings as dependent variable. The results are expressed as odds ratios (OR) with 95% confidence intervals (CI). Sequencing and phylogenetic analyses (1040 nucleotides) were used to characterize norovirus strains from healthcare workers. Cluster analyses included norovirus GII.4 strains detected in ward patients during the ongoing outbreaks.<h4>Results</h4>Of 308 packs issued to healthcare workers, 129 (42%) were returned. norovirus GII was detected in 26 healthcare workers (20.2%). Work in cohort care (OR 4.8, 95% CI 1.4-16.3), work in wards for patients with dementia (OR 13.2, 95% CI 1.01-170.7), and having diarrhoea, loose stools or other gastrointestinal symptoms the last week (OR 7.7, 95% CI 2.5-27.2) were associated with increased norovirus prevalence in healthcare workers. Sequencing revealed norovirus GII.4 in healthcare workers samples, and strains detected in healthcare workers and ward patients during a given ward outbreak showed ≥ 99% similarity.<h4>Conclusion</h4>Norovirus positive findings in healthcare workers were strongly associated with symptomatic infection, close contact with sick patients, and dementia nursing.
Project description:Nosocomial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have severely affected bed capacity and patient flow. We utilized whole-genome sequencing (WGS) to identify outbreaks and focus infection control resources and intervention during the United Kingdom's second pandemic wave in late 2020. Phylogenetic analysis of WGS and epidemiological data pinpointed an initial transmission event to an admission ward, with immediate prior community infection linkage documented. High incidence of asymptomatic staff infection with genetically identical viral sequences was also observed, which may have contributed to the propagation of the outbreak. WGS allowed timely nosocomial transmission intervention measures, including admissions ward point-of-care testing and introduction of portable HEPA14 filters. Conversely, WGS excluded nosocomial transmission in 2 instances with temporospatial linkage, conserving time and resources. In summary, WGS significantly enhanced understanding of SARS-CoV-2 clusters in a hospital setting, both identifying high-risk areas and conversely validating existing control measures in other units, maintaining clinical service overall.
Project description:In this work, we study the environmental and operational factors that influence airborne transmission of nosocomial infections. We link a deterministic zonal ventilation model for the airborne distribution of infectious material in a hospital ward, with a Markovian multicompartment SIS model for the infection of individuals within this ward, in order to conduct a parametric study on ventilation rates and their effect on the epidemic dynamics. Our stochastic model includes arrival and discharge of patients, as well as the detection of the outbreak by screening events or due to symptoms being shown by infective patients. For each ventilation setting, we measure the infectious potential of a nosocomial outbreak in the hospital ward by means of a summary statistic: the number of infections occurred within the hospital ward until end or declaration of the outbreak. We analytically compute the distribution of this summary statistic, and carry out local and global sensitivity analysis in order to identify the particular characteristics of each ventilation regime with the largest impact on the epidemic spread. Our results show that ward ventilation can have a significant impact on the infection spread, especially under slow detection scenarios or in overoccupied wards, and that decreasing the infection risk for the whole hospital ward might increase the risk in specific areas of the health-care facility. Moreover, the location of the initial infective individual and the protocol in place for outbreak declaration both form an interplay with ventilation of the ward.
Project description:<h4>Background</h4>Nosocomial spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been widely reported, but the transmission pathways among patients and healthcare workers (HCWs) are unclear. Identifying the risk factors and drivers for these nosocomial transmissions is critical for infection prevention and control interventions. The main aim of our study was to quantify the relative importance of different transmission pathways of SARS-CoV-2 in the hospital setting.<h4>Methods and findings</h4>This is an observational cohort study using data from 4 teaching hospitals in Oxfordshire, United Kingdom, from January to October 2020. Associations between infectious SARS-CoV-2 individuals and infection risk were quantified using logistic, generalised additive and linear mixed models. Cases were classified as community- or hospital-acquired using likely incubation periods of 3 to 7 days. Of 66,184 patients who were hospitalised during the study period, 920 had a positive SARS-CoV-2 PCR test within the same period (1.4%). The mean age was 67.9 (±20.7) years, 49.2% were females, and 68.5% were from the white ethnic group. Out of these, 571 patients had their first positive PCR tests while hospitalised (62.1%), and 97 of these occurred at least 7 days after admission (10.5%). Among the 5,596 HCWs, 615 (11.0%) tested positive during the study period using PCR or serological tests. The mean age was 39.5 (±11.1) years, 78.9% were females, and 49.8% were nurses. For susceptible patients, 1 day in the same ward with another patient with hospital-acquired SARS-CoV-2 was associated with an additional 7.5 infections per 1,000 susceptible patients (95% credible interval (CrI) 5.5 to 9.5/1,000 susceptible patients/day) per day. Exposure to an infectious patient with community-acquired Coronavirus Disease 2019 (COVID-19) or to an infectious HCW was associated with substantially lower infection risks (2.0/1,000 susceptible patients/day, 95% CrI 1.6 to 2.2). As for HCW infections, exposure to an infectious patient with hospital-acquired SARS-CoV-2 or to an infectious HCW were both associated with an additional 0.8 infection per 1,000 susceptible HCWs per day (95% CrI 0.3 to 1.6 and 0.6 to 1.0, respectively). Exposure to an infectious patient with community-acquired SARS-CoV-2 was associated with less than half this risk (0.2/1,000 susceptible HCWs/day, 95% CrI 0.2 to 0.2). These assumptions were tested in sensitivity analysis, which showed broadly similar results. The main limitations were that the symptom onset dates and HCW absence days were not available.<h4>Conclusions</h4>In this study, we observed that exposure to patients with hospital-acquired SARS-CoV-2 is associated with a substantial infection risk to both HCWs and other hospitalised patients. Infection control measures to limit nosocomial transmission must be optimised to protect both staff and patients from SARS-CoV-2 infection.
Project description:This study was addressed to the relationship between norovirus and acute diarrhea in hospitalized children, including hospital-acquired infection (HAI) and community-acquired infection (CAI) in a children's hospital in Beijing. RT-PCR was used to detect norovirus in stool specimen, followed by sequence analysis for PCR products. From 2010 to 2013, a total of 1248 specimens, including 661 from the HAI group and 587 from the CAI group were tested for norovirus. Norovirus were detected in 380 of 1248 (30.4%) diarrheal specimens. The positive rate for norovirus detection was higher in children within HAI group than CAI group (35.3%, 232/661 vs. 25.6%, 148/587), and the difference was significant (X2 = 14.35, P<0.05). For age distribution, the highest positivity rates of norovirus were in age of 0-5 months for HAI group and 12-23 months for CAI group. In the study, 262 amplicons of the VP1 region from norovirus-positive specimens were sequenced, which showed GII.3 and GII.4 norovirus were the most common genotypes detected in 50.0% (n = 131) and 48.9% (n = 128) of the positive specimens, respectively. Regarding the wards distribution, GII.3 norovirus was mainly detected in ward for neonatal diseases (36/85 in HAI group; 19/46 in CAI group), GII.4 norovirus was mainly detected in ward for respiratory and digestive diseases (21/85 in HAI group; 15/33 in CAI group).The data elaborated the importance of norovirus in hospital associated infectious diarrhea. The prevalence of norovirus is higher from HAI group than CAI group, and the norovirus from the patients in CAI group could be the source of infection in HAI group.
Project description:<h4>Background</h4>Oseltamivir resistance among 2009 pandemic influenza A (H1N1) viruses (pH1N1) is rare. We investigated a cluster of oseltamivir-resistant pH1N1 infections in a hospital ward.<h4>Methods</h4>We reviewed patient records and infection control measures and interviewed health care personnel (HCP) and visitors. Oseltamivir-resistant pH1N1 infections were found with real-time reverse-transcription polymerase chain reaction and pyrosequencing for the H275Y neuraminidase (NA) mutation. We compared hemagglutinin (HA) sequences from clinical samples from the outbreak with those of other surveillance viruses.<h4>Results</h4>During the period 6-11 October 2009, 4 immunocompromised patients within a hematology-oncology ward exhibited symptoms of pH1N1 infection. The likely index patient became febrile 8 days after completing a course of oseltamivir; isolation was instituted 9 days after symptom onset. Three other case patients developed symptoms 1, 3, and 5 days after the index patient. Three case patients were located in adjacent rooms. HA and NA sequences from case patients were identical. Twelve HCP and 6 visitors reported influenza symptoms during the study period. No other pH1N1 isolates from the hospital or from throughout the state carried the H275Y mutation.<h4>Conclusions</h4>Geographic proximity, temporal clustering, presence of H275Y mutation, and viral sequence homology confirmed nosocomial transmission of oseltamivir-resistant pH1N1. Diagnostic vigilance and prompt isolation may prevent nosocomial transmission of influenza.
Project description:Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of nosocomial infection. Whole-genome sequencing of MRSA has been used to define phylogeny and transmission in well-resourced healthcare settings, yet the greatest burden of nosocomial infection occurs in resource-restricted settings where barriers to transmission are lower. Here, we study the flux and genetic diversity of MRSA on ward and individual patient levels in a hospital where transmission was common. We repeatedly screened all patients on two intensive care units for MRSA carriage over a 3-mo period. All MRSA belonged to multilocus sequence type 239 (ST 239). We defined the population structure and charted the spread of MRSA by sequencing 79 isolates from 46 patients and five members of staff, including the first MRSA-positive screen isolates and up to two repeat isolates where available. Phylogenetic analysis identified a flux of distinct ST 239 clades over time in each intensive care unit. In total, five main clades were identified, which varied in the carriage of plasmids encoding antiseptic and antimicrobial resistance determinants. Sequence data confirmed intra- and interwards transmission events and identified individual patients who were colonized by more than one clade. One patient on each unit was the source of numerous transmission events, and deep sampling of one of these cases demonstrated colonization with a "cloud" of related MRSA variants. The application of whole-genome sequencing and analysis provides novel insights into the transmission of MRSA in under-resourced healthcare settings and has relevance to wider global health.