Epidemiological Clusters Research Articles

Characterisation of Staphylococci species from neonatal blood cultures in low- and middle-income countries

BackgroundIn low- and middle-income countries (LMIC) Staphylococcus aureus is regarded as one of the leading bacterial causes of neonatal sepsis, however there is limited knowledge on the species diversity and antimicrobial resistance caused by Gram-positive bacteria (GPB).MethodsWe characterised GPB isolates from neonatal blood cultures from LMICs in Africa (Ethiopia, Nigeria, Rwanda, and South Africa) and South-Asia (Bangladesh and Pakistan) between 2015–2017. We determined minimum inhibitory concentrations and performed whole genome sequencing (WGS) on Staphylococci isolates recovered and clinical data collected related to the onset of sepsis and the outcome of the neonate up to 60 days of age.ResultsFrom the isolates recovered from blood cultures, Staphylococci species were most frequently identified. Out of 100 S. aureus isolates sequenced, 18 different sequence types (ST) were found which unveiled two small epidemiological clusters caused by methicillin resistant S. aureus (MRSA) in Pakistan (ST8) and South Africa (ST5), both with high mortality (n = 6/17). One-third of S. aureus was MRSA, with methicillin resistance also detected in Staphylococcus epidermidis, Staphylococcus haemolyticus and Mammaliicoccus sciuri. Through additional WGS analysis we report a cluster of M. sciuri in Pakistan identified between July-November 2017.ConclusionsIn total we identified 14 different GPB bacterial species, however Staphylococci was dominant. These findings highlight the need of a prospective genomic epidemiology study to comprehensively assess the true burden of GPB neonatal sepsis focusing specifically on mechanisms of resistance and virulence across species and in relation to neonatal outcome.

Cervical cancer geographical burden analyzer: An interactive, open-access tool for understanding geographical disease burden in patients with recurrent or metastatic cervical cancer.

5523 Background: Examining geographic distributions of high and low proportions of recurrent or metastatic cervical cancer (r/mCC) can identify regions with high need of intervention and advance our understanding of r/mCC community-specific risk factors. Previous studies of epidemiologic or geographic clusters in late-stage cervical cancer were conducted prior to the availability of modern treatments for r/mCC. Due to the rapidly evolving treatment landscape for r/mCC use of commercial claims is an important way to follow dynamic practice changes. Our study objective was to understand recent geographical disparities among r/mCC patients in the US. Methods: We developed a web-based tool, Cervical Cancer Geographical Disease Burden Analyzer, that allows users to quantify r/mCC disease burden across metropolitan statistical areas (MSA) over multiple years. The inputs to the web-based tool were extracted through a retrospective analysis of the 2015-2020 MarketScan commercial claims database using a previously validated methodology. We then calculated the r/mCC rate as the ratio of r/mCC cases over cervical cancer (CC) cases for each of the >400 MSA considered. The calculated MSA-specific r/mCC rate was visualized in an interactive US map,. The online interactive tool allowed the users to filter the results by year, age group, and minimum number of diagnoses at the MSA level. Results: Our findings showed that there is large variation with respect to r/mCC disease burden across MSA in the US, with a range of 0-45%. The top five MSA with the highest r/mCC rates from 2018-2020 are presented in the table. In particular, r/mCC rates in Sacremento-Roseville-Arden-Arcade (SRAA), CA and Boston-Cambridge-Newton (BCN), MA were on an increasing trajectory (33% in 2018 to 50% in 2020 in SRAA, CA; and from 41% in 2018 to 50% in 2020 in BCN, MA). On the other hand, while disease burden remained high, we observed decreasing r/mCC rates in Grand Rapids, MI (55% in 2018 and 31% in 2020, resulting in an average r/mCC rate of 42%). Finally, in Cape Coral-Fort Myers, FL and Baltimore-Columbia-Towson, MD the r/mCC rates have fluctuated across time but were consistently >30%. Conclusions: Our web-based online interactive tool can help with identifying areas with high need of intervention, and inform how access, prevention and new or emerging therapies may potentially change the distribution of r/mCC disease burden. To better understand underlying drivers of geographic disparities observed, further efforts should be targeted towards identifying local-level factors. [Table: see text]

Monitoring AMR in Campylobacter jejuni from Italy in the last 10 years (2011-2021): Microbiological and WGS data risk assessment.

Campylobacter jejuni is considered as the main pathogen in human food‐borne outbreaks worldwide. Over the past years, several studies have reported antimicrobial resistance (AMR) in C. jejuni strains. In Europe, the official monitoring of AMR comprises the testing of Campylobacter spp. from food‐producing animals because this microorganism is responsible for human infections and usually predominant in poultry. Food‐producing animals are considered to be a major source of campylobacteriosis through contamination of food products. Concerns are growing due to the current classification of C. jejuni by the WHO as a ‘high priority pathogen’ due to the emergence of resistance to multiple drugs such as those belonging to the fluoroquinolones, macrolides and other classes, which limits the treatment alternatives. Knowledge about the contributions of different food sources to gastrointestinal disease is fundamental to prioritise food safety interventions and to establish proper control strategies. Assessing the genetic diversity among Campylobacter species is essential to the understanding of their epidemiology and population structure. Using a population genetic approach and grouping the isolates into sequence types within different clonal complexes, it is possible to investigate the source of the human cases. The work programme was aimed for the fellow to assess the AMR of C. jejuni isolated from humans, poultry and birds from wild and urban Italian habitats. Given the public health concern represented by resistant pathogens in food‐producing animals and the paucity of data about this topic in Italy, the aim was to identify correlations between phenotypic and genotypic AMR and comparing the origin of the isolates. The work programme allowed the fellow to acquire knowledge, skills and competencies on the web‐based tools used by IZSAM to process the NGS data and perform bioinformatics analyses for the identification of epidemiological clusters, the study of AMR patterns in C. jejuni isolates, and the assessment of the human exposure to such AMR pathogens. Furthermore, the fellow became able to transfer the acquired knowledge through innovative web‐based didactical tools applied to WGS and clustering of specific food‐borne pathogens, with particular reference to C. jejuni. To achieve this objective, 2,734 C. jejuni strains isolated from domestic and wild animals and humans, during the period 2011–2021 were analysed. The resistance phenotypes of the isolates were determined using the microdilution method with EUCAST breakpoints, for the following antibiotics: nalidixic acid, ciprofloxacin, chloramphenicol, erythromycin, gentamicin, streptomycin, tetracycline. The data were complemented by WGS data for each strain, uploaded in the Italian information system for the collection and analysis of complete genome sequence of pathogens isolated from animal, food and environment (GENPAT) developed and maintained at IZSAM; information like clonal complex and sequence type to understand the phylogenetical distance between strains according to their origins were also considered. This work underlines that a better knowledge of the resistance levels of C. jejuni is necessary, and mandatory monitoring of Campylobacter species in the different animal productions is strongly suggested.

Limited genomic reconstruction of SARS-CoV-2 transmission history within local epidemiological clusters.

A detailed understanding of how and when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission occurs is crucial for designing effective prevention measures. Other than contact tracing, genome sequencing provides information to help infer who infected whom. However, the effectiveness of the genomic approach in this context depends on both (high enough) mutation and (low enough) transmission rates. Today, the level of resolution that we can obtain when describing SARS-CoV-2 outbreaks using just genomic information alone remains unclear. In order to answer this question, we sequenced forty-nine SARS-CoV-2 patient samples from ten local clusters in NW Spain for which partial epidemiological information was available and inferred transmission history using genomic variants. Importantly, we obtained high-quality genomic data, sequencing each sample twice and using unique barcodes to exclude cross-sample contamination. Phylogenetic and cluster analyses showed that consensus genomes were generally sufficient to discriminate among independent transmission clusters. However, levels of intrahost variation were low, which prevented in most cases the unambiguous identification of direct transmission events. After filtering out recurrent variants across clusters, the genomic data were generally compatible with the epidemiological information but did not support specific transmission events over possible alternatives. We estimated the effective transmission bottleneck size to be one to two viral particles for sample pairs whose donor–recipient relationship was likely. Our analyses suggest that intrahost genomic variation in SARS-CoV-2 might be generally limited and that homoplasy and recurrent errors complicate identifying shared intrahost variants. Reliable reconstruction of direct SARS-CoV-2 transmission based solely on genomic data seems hindered by a slow mutation rate, potential convergent events, and technical artifacts. Detailed contact tracing seems essential in most cases to study SARS-CoV-2 transmission at high resolution.

Dissemination of carbapenem resistant bacteria from hospital wastewater into the environment

Infections with antibiotic resistant pathogens threaten lives and cause substantial costs. For effective interventions, knowledge of the transmission paths of resistant bacteria to humans is essential. In this study, carbapenem resistant bacteria were isolated from the wastewater of a maximum care hospital during a period of two years, starting in the patient rooms and following the sewer system to the effluent of the wastewater treatment plant (WWTP). The bacteria belonged to six different species and 44 different sequence types (STs). The most frequent STs, ST147 K. pneumoniae (blaNDM/blaOXA-48) and ST235 P. aeruginosa (blaVIM) strains, were present at nearly all sampling sites from the hospital to the WWTP effluent. After core genome multi-locus sequence typing (cgMLST), all ST147 K. pneumoniae strains presented a single epidemiological cluster. In contrast, ST235 P. aeruginosa formed five cgMLST clusters and the largest cluster contained the strain from the WWTP effluent, indicating without doubt, a direct dissemination of both high-risk clones into the environment. Thus, there are - at least two - possible transmission pathways to humans, (i) within the hospital by contact with the drains of the sanitary installations and (ii) by recreational or irrigation use of surface waters that have received WWTP effluent. In conclusion, remediation measures must be installed at both ends of the wastewater system, targeting the drains of the hospital as well as at the effluent of the WWTP.

Epidemiological survey of allergic rhinitis in steppe area of Xilingol League, Inner Mongolian of China

Objective:To investigate the epidemiologic feature of allergic rhinitis （AR） in the grassland area of Xilin Gol League, in Inner Mongolia, including prevalence rate, clinical characteristics and main allergens, so as to provide scientific evidence for the prevention and treatment of AR. Methods:From May to August of 2015, in strict accordance with the requirements of epidemiological investigation, A multi-stage, stratified， random and cluster sampling method was adopted to investigate the population in three areas of Xilingol Grassland in Inner Mongolia （Xilinhot, Erlianhot and Duolun）, with a face to face questionnaire used to investigate the general situation, the main clinical symptoms and related symptoms of AR and the combined. Simultaneously, the skin prick test （SPT） of 10 common grassland allergens was carried out, and the gravity sedimentation method was used to monitor the daily pollen types and quantity in the area.SAS 9.4 software was used for data analysis． Results:A total of 2878 subjects in the cluster sample completed the questionnaire survey and allergen detection. The positive rate of SPT was 41.10% （1179/2787）, the self-reported prevalence rate of AR was 39.96%（1150/2878） and confirmed prevalence rate of AR was 22.72%（654/2878）. The most obvious clinical symptoms of AR were sneezing （91.13%, 1048/1150） and itchy nose （85.65%, 985/1150）. The most obvious clinical symptoms of ocular were itchy （55.13%, 634/1150） and tearing（42.96%，494/1150）. Fatigue and somnolence were prominent among other symptoms associated with AR. Among comorbidities, AR combined with conjunctivitis accounted for 60.52% （696/1150）, AR combined with asthma accounted for 13.57% （156/1150）. The major allergens of AR from high to low were Artemisia pollen, Chenopodium pollen, and Humulus pollen. The peak of AR symptoms mostly occuredin August.， and the peak period of allergic rhinitis symptoms coincided with the peak period of pollen quantity. Conclusion:The prevalence rate of AR in is extremely high due to the high seasonal pollen exposure in steppe area of Xilingol League in Inner Mongolian. Artemisia pollen is the main sensitized allergen.

SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels

BackgroundFaced with the ongoing global pandemic of coronavirus disease, the ‘National Reference Centre for Whole Genome Sequencing of microbial pathogens: database and bioinformatic analysis’ (GENPAT) formally established at the ‘Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise’ (IZSAM) in Teramo (Italy) is in charge of the SARS-CoV-2 surveillance at the genomic scale. In a context of SARS-CoV-2 surveillance requiring correct and fast assessment of epidemiological clusters from substantial amount of samples, the present study proposes an analytical workflow for identifying accurately the PANGO lineages of SARS-CoV-2 samples and building of discriminant minimum spanning trees (MST) bypassing the usual time consuming phylogenomic inferences based on multiple sequence alignment (MSA) and substitution model.ResultsGENPAT constituted two collections of SARS-CoV-2 samples. The first collection consisted of SARS-CoV-2 positive swabs collected by IZSAM from the Abruzzo region (Italy), then sequenced by next generation sequencing (NGS) and analyzed in GENPAT (n = 1592), while the second collection included samples from several Italian provinces and retrieved from the reference Global Initiative on Sharing All Influenza Data (GISAID) (n = 17,201). The main results of the present work showed that (i) GENPAT and GISAID detected the same PANGO lineages, (ii) the PANGO lineages B.1.177 (i.e. historical in Italy) and B.1.1.7 (i.e. ‘UK variant’) are major concerns today in several Italian provinces, and the new MST-based method (iii) clusters most of the PANGO lineages together, (iv) with a higher dicriminatory power than PANGO lineages, (v) and faster that the usual phylogenomic methods based on MSA and substitution model.ConclusionsThe genome sequencing efforts of Italian provinces, combined with a structured national system of NGS data management, provided support for surveillance SARS-CoV-2 in Italy. We propose to build phylogenomic trees of SARS-CoV-2 variants through an accurate, discriminant and fast MST-based method avoiding the typical time consuming steps related to MSA and substitution model-based phylogenomic inference.

Outbreaks of mumps genotype G viruses in the Netherlands between October 2019 and March 2020: clusters associated with multiple introductions

BackgroundFrom October 2019–March 2020, several clusters of mumps cases were identified in the Netherlands. Our objective was to describe cluster-associated mumps virus transmission using epidemiological and molecular information in order to help future mumps outbreak investigation and control efforts.MethodsAn epidemiological cluster includes ≥ 2 mumps cases with at least an epidemiological-link to a laboratory-confirmed mumps case. A molecular group includes ≥ 2 mumps cases with identical mumps virus sequences. Cases with symptom onset date between 1 October 2019 and 31 March 2020 reported through the National Notifiable Diseases Surveillance System were included. We described epidemiological and clinical characteristics of mumps cases. Sequence data was obtained from selected regions of mumps virus genomes (2270 nucleotides). Associations between epidemiological and molecular information were investigated.ResultsIn total, 102 mumps cases were notified (90% laboratory-confirmed, 10% epidemiologically-linked). 71 out of 102 cases were identified as part of an epidemiological cluster and/or molecular group. Twenty-one (30%) of 71 cases were identified solely from epidemiological information, 25 (35%) solely from molecular surveillance, and 25 (35%) using both. Fourteen epidemiological clusters were identified containing a total of 46 (range: 2–12, median: 3) cases. Complete sequence data was obtained from 50 mumps genotype G viruses. Twelve molecular groups were identified containing 43 (range: 2–13) cases, dispersed geographically and timewise. Combined information grouped seven epidemiological clusters into two distinct molecular groups. The first lasting for 14 weeks, the other for 6. Additionally, one molecular group was detected, linked by geography and time but without an epidemiological-link.ConclusionsCombined epidemiological and molecular information indicated ongoing mumps virus transmission from multiple introductions for extended time periods. Sequence analysis provided valuable insights into epidemiological clustering. If combined information is available in a timely manner, this would improve outbreak detection, generate further insight into mumps transmission, and guide necessary control measures.

COVID-19: Integrating genomic and epidemiological data to inform public health interventions and policy in Tasmania, Australia

ObjectiveWe undertook an integrated analysis of genomic and epidemiological data to investigate a large health-care-associated outbreak of coronavirus disease 2019 (COVID-19) and to better understand the epidemiology of COVID-19 cases in Tasmania, Australia.MethodsEpidemiological data collected on COVID-19 cases notified in Tasmania between 2 March and 15 May 2020, and positive samples of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or RNA extracted from the samples were included. Sequencing was conducted by tiled amplicon polymerase chain reaction with ARTIC v1 or v3 primers and Illumina sequencing. Consensus sequences were generated, sequences were aligned to a reference sequence and phylogenetic analysis was performed. Genomic clusters were determined and integrated with epidemiological data to provide additional information.ResultsAll 231 COVID-19 cases notified in Tasmania during the study period and 266 SARS-CoV-2-positive samples, representing 217/231 (94%) notified cases, were included; 184/217 (84%) were clustered, 21/217 (10%) were unique and 12/217 (6%) could not be sequenced. Genomics confirmed the presence of seven clusters already identified through epidemiological links, clarified transmission networks in which the epidemiology had been unclear and identified one cluster that had not previously been recognized.DiscussionGenomic analysis provided useful additional information on COVID-19 in Tasmania, including evidence of a large health-care-associated outbreak linked to an overseas cruise, the probable source of infection in cases with no previously identified epidemiological link and confirmation that there was no identified community transmission from other imported cases. Genomic insights are an important component of the response to COVID-19, and continuing genomic surveillance is warranted.

Genomic Epidemiology and Strain Taxonomy of Corynebacterium diphtheriae.

Corynebacterium diphtheriae is highly transmissible and can cause large diphtheria outbreaks where vaccination coverage is insufficient. Sporadic cases or small clusters are observed in high-vaccination settings. The phylogeography and short timescale evolution of C. diphtheriae are not well understood, in part due to a lack of harmonized analytical approaches of genomic surveillance and strain tracking. We combined 1,305 genes with highly reproducible allele calls into a core genome multilocus sequence typing (cgMLST) scheme. We analyzed cgMLST gene diversity among 602 isolates from sporadic clinical cases, small clusters, or large outbreaks. We defined sublineages based on the phylogenetic structure within C. diphtheriae and strains based on the highest number of cgMLST mismatches within documented outbreaks. We performed time-scaled phylogenetic analyses of major sublineages. The cgMLST scheme showed high allele call rate in C. diphtheriae and the closely related species C. belfantii and C. rouxii. We demonstrate its utility to delineate epidemiological case clusters and outbreaks using a 25 mismatches threshold and reveal a number of cryptic transmission chains, most of which are geographically restricted to one or a few adjacent countries. Subcultures of the vaccine strain PW8 differed by up to 20 cgMLST mismatches. Phylogenetic analyses revealed a short-timescale evolutionary gain or loss of the diphtheria toxin and biovar-associated genes. We devised a genomic taxonomy of strains and deeper sublineages (defined using a 500-cgMLST-mismatch threshold), currently comprising 151 sublineages, only a few of which are geographically widespread based on current sampling. The cgMLST genotyping tool and nomenclature was made publicly accessible (https://bigsdb.pasteur.fr/diphtheria). Standardized genome-scale strain genotyping will help tracing transmission and geographic spread of C. diphtheriae. The unified genomic taxonomy of C. diphtheriae strains provides a common language for studies of ecology, evolution, and virulence heterogeneity among C. diphtheriae sublineages.

Anti-clustering in the national SARS-CoV-2 daily infection counts.

The noise in daily infection counts of an epidemic should be super-Poissonian due to intrinsic epidemiological and administrative clustering. Here, we use this clustering to classify the official national SARS-CoV-2 daily infection counts and check for infection counts that are unusually anti-clustered. We adopt a one-parameter model of n}{}phi _i^{prime} infections per cluster, dividing any daily count ni into n}{}n_i/ _i^{prime} ‘clusters’, for ‘country’ i. We assume that n}{}{n_i}/phi _i^{prime} on a given day j is drawn from a Poisson distribution whose mean is robustly estimated from the four neighbouring days, and calculate the inferred Poisson probability n}{}P_{ij}^{prime} of the observation. The n}{}P_{ij}^{prime} values should be uniformly distributed. We find the value n}{}phi_i that minimises the Kolmogorov–Smirnov distance from a uniform distribution. We investigate the (ϕi, Ni) distribution, for total infection count Ni. We consider consecutive count sequences above a threshold of 50 daily infections. We find that most of the daily infection count sequences are inconsistent with a Poissonian model. Most are found to be consistent with the ϕi model. The 28-, 14- and 7-day least noisy sequences for several countries are best modelled as sub-Poissonian, suggesting a distinct epidemiological family. The 28-day least noisy sequence of Algeria has a preferred model that is strongly sub-Poissonian, with n}{}phi _i^{28} < 0.1. Tajikistan, Turkey, Russia, Belarus, Albania, United Arab Emirates and Nicaragua have preferred models that are also sub-Poissonian, with n}{}phi _i^{28} < 0.5. A statistically significant (Pτ < 0.05) correlation was found between the lack of media freedom in a country, as represented by a high Reporters sans frontieres Press Freedom Index (PFI2020), and the lack of statistical noise in the country’s daily counts. The ϕi model appears to be an effective detector of suspiciously low statistical noise in the national SARS-CoV-2 daily infection counts.

Anti-clustering in the national SARS-CoV-2 daily infection counts

The noise in daily infection counts of an epidemic should be super-Poissonian due to intrinsic epidemiological and administrative clustering. Here, we use this clustering to classify the official national SARS-CoV-2 daily infection counts and check for infection counts that are unusually anti-clustered. We adopt a one-parameter model of $\phi'_i$ infections per cluster, dividing any daily count $n_i$ into $n_i/\phi'_i$ 'clusters', for 'country' $i$. We assume that $n_i/\phi'_i$ on a given day $j$ is drawn from a Poisson distribution whose mean is robustly estimated from the four neighbouring days, and calculate the inferred Poisson probability $P'_{ij}$ of the observation. The $P'_{ij}$ values should be uniformly distributed. We find the value $\phi_i$ that minimises the Kolmogorov-Smirnov distance from a uniform distribution. We investigate the $(\phi_i, N_i)$ distribution, for total infection count $N_i$. We find that most of the daily infection count sequences are inconsistent with a Poissonian model. Most are found to be consistent with the $\phi_i$ model. The 28-, 14- and 7-day least noisy sequences for several countries are best modelled as sub-Poissonian, suggesting a distinct epidemiological family. The 28-day least noisy sequence of Algeria has a preferred model that is strongly sub-Poissonian, with $\phi_i^{28} < 0.1$. TJ, TR, RU, BY, AL, AE, and NI have preferred models that are also sub-Poissonian, with $\phi_i^{28} < 0.5$. A statistically significant ($P^{\tau} < 0.05$) correlation was found between the lack of media freedom in a country, as represented by a high Reporters sans frontieres Press Freedom Index (PFI$^{2020}$), and the lack of statistical noise in the country's daily counts. The $\phi_i$ model appears to be an effective detector of suspiciously low statistical noise in the national SARS-CoV-2 daily infection counts.

Combined epidemiological and genomic analysis of nosocomial SARS-CoV-2 infection early in the pandemic and the role of unidentified cases in transmission

ObjectivesTo analyse nosocomial transmission in the early stages of the coronavirus 2019 (COVID-19) pandemic at a large multisite healthcare institution. Nosocomial incidence is linked with infection control interventions. MethodsViral genome sequence and epidemiological data were analysed for 574 consecutive patients, including 86 nosocomial cases, with a positive PCR test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the first 19 days of the pandemic. ResultsForty-four putative transmission clusters were found through epidemiological analysis; these included 234 cases and all 86 nosocomial cases. SARS-CoV-2 genome sequences were obtained from 168/234 (72%) of these cases in epidemiological clusters, including 77/86 nosocomial cases (90%). Only 75/168 (45%) of epidemiologically linked, sequenced cases were not refuted by applying genomic data, creating 14 final clusters accounting for 59/77 sequenced nosocomial cases (77%). Viral haplotypes from these clusters were enriched 1–14x (median 4x) compared to the community. Three factors implicated unidentified cases in transmission: (a) community-onset or indeterminate cases were absent in 7/14 clusters (50%), (b) four clusters (29%) had additional evidence of cryptic transmission, and (c) in three clusters (21%) diagnosis of the earliest case was delayed, which may have facilitated transmission. Nosocomial cases decreased to low levels (0–2 per day) despite continuing high numbers of admissions of community-onset SARS-CoV-2 cases (40–50 per day) and before the impact of introducing universal face masks and banning hospital visitors. ConclusionGenomics was necessary to accurately resolve transmission clusters. Our data support unidentified cases—such as healthcare workers or asymptomatic patients—as important vectors of transmission. Evidence is needed to ascertain whether routine screening increases case ascertainment and limits nosocomial transmission.

Genomic Epidemiology of Carbapenemase-Producing Enterobacterales at a Hospital System in Toronto, Ontario, Canada, 2007 to 2018.

At a hospital system (H1) in Ontario, Canada, we investigated whether whole-genome sequencing (WGS) altered initial epidemiological interpretation of carbapenemase-producing Enterobacterales (CPE) transmission. We included patients with CPE colonization/infection identified by population-based surveillance from October 2007 to August 2018 who received health care at H1 in the year before/after CPE detection. H1 reported epidemiological transmission clusters. We combined single nucleotide variant (SNV) analysis, plasmid characterization, and epidemiological data. Eighty-five patients were included. H1 identified 7 epidemiological transmission clusters, namely, A to G, involving 24/85 (28%) patients. SNV analysis confirmed transmission clusters C, D, and G and identified two additional cases belonging to cluster A. One was a travel-related case that was the likely index case (0 to 6 SNVs from other isolates); this case stayed on the same unit as the initially presumed index case 4 months prior to detection of the initially presumed index case on another unit. The second additional case occupied a room previously occupied by 5 cluster A cases. Plasmid sequence analysis excluded a case from cluster A and identified clusters E and F as possibly two parts of a single cluster. SNV analysis also identified a case without direct epidemiologic links that was 18 to 21 SNVs away from cluster B, suggesting possible undetected interhospital transmission. SNV and plasmid sequence analysis identified cases belonging to transmission clusters that conventional epidemiology missed and excluded other cases. Implementation of routine WGS to complement epidemiological transmission investigations has the potential to improve prevention and control of CPE in hospitals.

Integrative transnational analysis to dissect tuberculosis transmission events along the migratory route from Africa to Europe.

Growing international migration has increased the complexity of tuberculosis transmission patterns. Italy's decision to close its borders in 2018 made of Spain the new European porte entrée for migration from the Horn of Africa (HA). In one of the first rescues of migrants from this region at the end of 2018, tuberculosis was diagnosed in eight subjects, mainly unaccompanied minors. Mycobacterium tuberculosis isolates from these recently arrived migrants were analysed by Mycobacterial Interspersed Repetitive-Unit/Variable-Number of Tandem Repeat (MIRU-VNTR) and subsequent whole genome sequencing (WGS) analysis. Data were compared with those from collections from other European countries receiving migrants from the HA and a strain-specific PCR was applied for a fast searching of common strains. Infections in a cellular model were performed to assess strain virulence. MIRU-VNTR analysis allowed identifying an epidemiological cluster involving three of the eight cases from Somalia (0 single-nucleotide polymorphisms between isolates, HA cluster). Following detailed interviews revealed that two of these cases had shared the same migratory route in most of the trip and had spent a long time at a detention camp in Libya. To confirm potential en route transmission for the three cases, we searched the same strain in collections from other European countries receiving migrants from the HA. MIRU-VNTR, WGS and a strain-specific PCR for the HA strain were applied. The same strain was identified in 12 cases from Eritrea diagnosed soon after their arrival in 2018 to the Netherlands, Belgium and Italy. Intracellular replication rate of the strain did not reveal abnormal virulence. Our study suggests a potential en route transmission of a pan-susceptible strain, which caused at least 15 tuberculosis cases in Somalian and Eritrean migrants diagnosed in four different European countries.

SARS-CoV-2 on Ocular Surfaces in a Cohort of Patients With COVID-19 From the Lombardy Region, Italy

Since February 2020, coronavirus disease 2019 (COVID-19) has spread rapidly all over the world, with an epidemiological cluster in Lombardy, Italy. The viral communicability may be mediated by various body fluids, but insufficient information is available on the presence of the virus in human tears. To investigate the rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in tears collected from patients with COVID-19 by means of real-time reverse transcriptase-polymerase chain reaction (rRT-PCR) assay and to assess the association of virus presence with concomitant clinical conditions. Cross-sectional study conducted between April 9 and May 5, 2020. The setting was intensive care units at Azienda Socio-Sanitaria Territoriale (ASST) Sette-Laghi Hospital, University of Insubria, in Varese, Lombardy, Italy. A conjunctival swab was performed in 91 patients hospitalized for COVID-19, which was clinically diagnosed by rRT-PCR assay on nasopharyngeal swabs and by radiological imaging. Conjunctival swabs from 17 additional healthy volunteer participants with no symptoms of COVID-19 were examined to evaluate the availability and applicability of the conjunctival swab test. SARS-CoV-2 detection by means of rRT-PCR assay performed on the collected samples obtained by conjunctival swabs. Conjunctival swab and nasopharyngeal swab results are reported, as well as demographic and clinical data. A total of 108 participants (mean [SD] age, 58.7 [14.2] years; 55 female and 53 male) were tested for SARS-CoV-2 using rRT-PCR assay, including 91 patients hospitalized with COVID-19 and 17 were healthy volunteers. SARS-CoV-2 was found on the ocular surface in 52 of 91 patients with COVID-19 (57.1%; 95% CI, 46.3%-67.5%), with a wide variability in the mean viral load from both eyes. Among a subset of 41 patients, concordance of 63.0% (95% CI, 41.0%-81.0%) was found between positive conjunctival and nasopharyngeal swab test results when performed within 2 days of each other. In 17 of these patients, nasopharyngeal swab results were negative for SARS-CoV-2. In 10 of these 17 patients, conjunctival swab results were positive for the virus. In this study, SARS-CoV-2 RNA was found on the ocular surface in a large part of this cohort of patients with COVID-19, although the infectivity of this material could not be determined. Because patients may have positive test results with a conjunctival swab and negative results with a nasopharyngeal swab, use of the slightly invasive conjunctival swab may be considered as a supplementary diagnostic test.

The characteristics of and responses to the two COVID-19 outbreak waves in Hebei Province of China, January 2020 to February 2021.

Hebei Province was affected by two coronavirus disease 2019 (COVID-19) outbreak waves during the period 22 January 2020 through 27 February 2020 (wave 1) and 2 January 2021 through 14 February 2021 (wave 2). To evaluate and compare the epidemiological characteristics, containment delay, cluster events and social activity, as well as non-pharmaceutical interventions of the two COVID-19 outbreak waves, we examined real-time update information on all COVID-19-confirmed cases from a publicly available database. Wave 1 was closely linked with the COVID-19 pandemic in Wuhan, whereas wave 2 was triggered, to a certain extent, by the increasing social activities such as weddings, multi-household gatherings and church events during the slack agricultural period. In wave 2, the epidemic spread undetected in the rural areas, and people living in the rural areas had a higher incidence rate than those living in the urban areas (5.3 vs. 22.0 per 1 000 000). Furthermore, Rt was greater than 1 in the early stage of the two outbreak waves, and decreased substantially after massive non-pharmaceutical interventions were implemented. In China's 'new-normal' situation, development of targeted and effective intervention remains key for COVID-19 control in consideration of the potential threat of new coronavirus strains.

Multiple detection and spread of novel strains of the SARS-CoV-2 B.1.177 (B.1.177.75) lineage that test negative by a commercially available nucleocapsid gene real-time RT-PCR

ABSTRACT Several lineages of SARS-CoV-2 are currently circulating worldwide. During SARS-CoV-2 diagnostic activities performed in Abruzzo region (central Italy) several strains belonging to the B.1.177.75 lineage tested negative for the N gene but positive for the ORF1ab and S genes (+/+/- pattern) by the TaqPath COVID-19 CE-IVD RT-PCR Kit manufactured by Thermofisher. By sequencing, a unique mutation, synonymous 28948C > T, was found in the N-negative B.1.177.75 strains. Although we do not have any knowledge upon the nucleotide sequences of the primers and probe adopted by this kit, it is likely that N gene dropout only occurs when 28948C > T is coupled with 28932C > T, this latter present, in turn, in all B.1.177.75 sequences available on public databases. Furthermore, epidemiological analysis was also performed. The majority of the N-negative B.1.177.75 cases belonged to two clusters apparently unrelated to each other and both clusters involved young people. However, the phylogeny for sequences containing the +/+/- pattern strongly supports a genetic connection and one common source for both clusters. Though, genetic comparison suggests a connection rather than indicating the independent emergence of the same mutation in two apparently unrelated clusters. This study highlights once more the importance of sharing genomic data to link apparently unrelated epidemiological clusters and to, remarkably, update molecular tests.

Exploring the value of MALDI-TOF MS for the detection of clonal outbreaks of Burkholderia contaminans

BackgroundMolecular genetics has risen in both output and affordability to become the gold standard in diagnosis, however it is not yet available for most routine clinical microbiology due to cost and the level of skill it requires. Matrix assisted laser desorption/ionisation – time of flight mass spectrometry (MALDI-TOF MS) approaches may be useful in bridging the gap between low-resolution phenotypic methods and bulky genotypic methods in the goal of epidemiological source-typing of microbes. Burkholderia has been shown to be identifiable at the subspecies level using MALDI-TOF MS. There have not yet been studies assessing the ability of MALDI-TOF MS to source-type Burkholderia contaminans isolates into epidemiologically relevant outbreak clusters. Methods55 well-characterised B. contaminans isolates were used to create a panel for analysis of MALDI-TOF MS biomarker peaks and their relation to outbreak strains, location, source, patient, diagnosis and isolate genetics. Unsupervised clustering was performed and classification models were generated using biostatistical analysis software. ResultsB. contaminans spectra derived from MALDI-TOF MS were of sufficiently high resolution to identify 100% of isolates. Unsupervised clustering methods showed poor evidence of spectra clustering by all characteristics measured. Classification algorithms were discriminatory, with Genetic Algorithm models showing 100% recognition capability for all outbreaks, the pulsed-field gel electrophoresis (PFGE) typeability model, and 96.63% recognition for the location model. A consistent peak at m/z of approximately 6943 was identified in all non-typeable strains but in none of the typeable strains. ConclusionsMALDI-TOF MS successfully discriminates B. contaminans isolates into clonal, epidemiological clusters, and can recognise isolates non-typeable by PFGE. Further work should investigate this capability, and include peptide studies and genomic sequencing to identify individual proteins or genes responsible for this non-typeablity, particularly at the peak weight identified.

Development and Validation of a New Risk Score for Infection with Coronavirus (Ri.S.I.Co) Obtained from Treating Coronavirus Disease (COVID-19) Patients on the Field

Background: The Coronavirus Disease 2019 (COVID-19) pandemic has necessitated the alteration of the organization of entire hospitals to try to prevent them from becoming epidemiological clusters. The adopted diagnostic tools lack sensitivity or specificity. Objectives: The aim of the study was to create an easy-to-get risk score (Ri.S.I.Co., risk score for infection with the new coronavirus) developed on the field to stratify patients admitted to hospitals according to their risk of COVID-19 infection. Methods: In this prospective study, we included all patients who were consecutively admitted to the suspected COVID-19 department of the Bufalini Hospital, Cesena (Italy). All clinical, radiological, and laboratory predictors were included in the multivariate logistic regression model to create a risk model. A simplified model was internally and externally validated, and two score thresholds for stratifying the probability of COVID-19 infection were introduced. Results: From 11th March to 5th April 2020, 200 patients were consecutively admitted. A Ri.S.I.Co lower than 2 showed a higher sensitivity than SARS-Cov-2 nucleic acid detection (96.2% vs. 65.4%; P &lt; 0.001). The presence of ground-glass pattern on the lung-CT scan had a lower sensitivity than a Ri.S.I.Co lower than 2 (88.5% vs. 96.2%; P &lt; 0.001) and a lower specificity than a Ri.S.I.Co higher than 6 (75.0% vs. 96.9%; P &lt; 0.001). Conclusions: We believe that the Ri.S.I.Co could allow to stratify admitted patients according to their risk, preventing hospitals from becoming the main COVID-19 carriers themselves. Furthermore, it could guide clinicians in starting therapies early in severe-onset cases with a high probability of COVID-19, before molecular SARS-CoV-2 infection is confirmed.