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Background:Clostridioides difficile infection (CDI) is a major cause of morbidity and healthcare costs in the United States. The epidemiology of CDI has recently shifted, with healthcare-associated (HCA) CDI trending downward and community-associated (CA)-CDI becoming more prominent. The cause of this shift is not well understood but may be related to changing genomic epidemiology. We assessed C. difficile strains across a CDC Emerging Infections Program (EIP) site in Western New York, including strains from both HCA-CDI and CA-CDI cases to characterize predominating strains and putative transmission across epidemiological classifications and between index and recurrent cases. Methods: In total, 535 isolates of C. difficile were collected over a 6-month period in 2018 from the Monroe Country, New York, EIP site and were analyzed using whole-genome sequencing (WGS). Standard epidemiological definitions were used to classify cases as hospital onset (HO-CDI); community associated (CA-CDI); community onset, healthcare associated (CO-HCFA-CDI); or long-term care onset (LTCO-CDI). Recurrent cases were defined as those diagnosed within 8 weeks of an initial positive test. Multilocus sequence types (MLSTs) were assigned according to PUBMLST and single-nucleotide polymorphisms (SNPs) were determined using a modified CFSAN analytical pipeline. Cases resulting from putative transmission were defined as those separated by 0–1 core SNPs. Results: Of 535 isolates, 454 were from index and 81 were from recurrent cases. The index cases were comprised of CA-CDI (47.4%), CO-HCFA-CDI (24%), LTCO-CDI (8.1%), and HO-CDI (19.3%). Cases with recurrent disease mirrored the epidemiological distribution of the larger set. Common MLSTs included ST2 (12.3%), ST8 (10.5%), ST42 (7.9%), ST58 (4.9%), ST43 (4.5%), and ST11 (4.3%). The previously widespread epidemic strain, NAP1/ST1/RT027 accounted for Conclusions: The genomic epidemiology of C. difficile across this large community cohort demonstrated a diverse group of strain types that was similarly distributed across epidemiological classifications and between index and recurrent cases. SNP analysis indicated that direct transmission between cases was uncommon.
Background: The epidemic NAP1/027 Clostridioides difficile strain (MLST1, ST1) that emerged in the mid-2000 is on the decline. The current distribution of C. difficile strain types and their transmission dynamics are poorly defined. We performed whole-genome sequencing (WGS) of C. difficile isolates in 2 regions to identify the predominant multilocus sequence types (MLSTs) in community- and healthcare-associated cases and potential transmission between cases using whole-genome single-nucleotide polymorphism (SNP) analysis. Methods: Isolates were collected through the CDC Emerging Infections Program population-based surveillance for C. difficile infections (CDI) for 3 months between 2016 and 2017 in 5 Minnesota counties and 1 New York county. Isolates were limited to incident cases (CDI in a county resident with no positive C. difficile test in the preceding 8 weeks). Cases were classified as healthcare associated (HA-CDI) or community associated (CA-CDI) based on healthcare exposures as previously described. WGS was performed on an Illumina Miseq. The CFSAN (FDA) pipeline was used to compute whole-genome SNPs, SPAdes was used for assembly, and MLST was assigned according to www.pubmlst.org. Results: Of 431 isolates, 269 originated from New York and 162 from Minnesota; 203 cases were classified as CA-CDI and 221 as HA-CDI. The proportion of CA-CDI cases was higher in Minnesota than in New York: 62% vs 38%. The predominant MLSTs across both sites were ST42 (9%), ST8 (8%), and ST2 (8%). MLSTs more frequently encountered in HA-CDI than CA-CDI included ST1 (note that this ST includes PCR Ribotype 027; 76% HA-CDI), ST53 (84% HA-CDI), and ST43 (80% HA-CDI). In contrast, ST110 (63% CA-CDI) and ST3 (67% CA-CDI) were more commonly isolated from CA-CDI cases. ST1 accounted for 7.6% of circulating strains and was more common in New York than Minnesota (10% vs 3%) and was concentrated among New York HA-CDI cases. Also, 412 isolates (1 per patient) were included in the final whole-genome SNP analysis. Of these, only 12 pairs were separated by 0–3 SNPs, indicating potential transmission, and most involved HA-CDI cases. ST1, ST17, and ST46 accounted for 8 of 12 pairs, with ST17 and ST46 potentially forming small clusters. Conclusions: This analysis provides a snapshot of the current genomic epidemiology of C. difficile across 2 geographically and epidemiologically distinct regions of the United States and supports other studies suggesting that the role of direct transmission in the spread of CDI may be limited.
In clinical and translational research, data science is often and fortuitously integrated with data collection. This contrasts to the typical position of data scientists in other settings, where they are isolated from data collectors. Because of this, effective use of data science techniques to resolve translational questions requires innovation in the organization and management of these data.
We propose an operational framework that respects this important difference in how research teams are organized. To maximize the accuracy and speed of the clinical and translational data science enterprise under this framework, we define a set of eight best practices for data management.
In our own work at the University of Rochester, we have strived to utilize these practices in a customized version of the open source LabKey platform for integrated data management and collaboration. We have applied this platform to cohorts that longitudinally track multidomain data from over 3000 subjects.
We argue that this has made analytical datasets more readily available and lowered the bar to interdisciplinary collaboration, enabling a team-based data science that is unique to the clinical and translational setting.
Care and follow-up of patients discharged from medium secure units in England and Wales is uncoordinated and inconsistent, although the perceived risk of violence by people with mental disorders is a primary political issue. This article outlines models of community support for these individuals, and describes a forensic mental health liaison service in operation in England.
Advocacy groups are all the rage! Over the past two decades, a new cottage industry has erupted in academia examining the seemingly explosive growth in new social movements, advocacy groups and non-governmental organizations (NGOs) that has occurred in Western industrialized nations and several developing nations as well. Many of these movements and NGOs have crossed international boundaries, feeding the notion that globalization is eroding boundaries between people all around the world. This literature certainly has added to our knowledge of how advocacy groups originate and operate. But curiously missing from these recent studies has been any discussion of what amounts to the world’s most common, oldest, and largest advocacy bodies – religious organizations.
Consider the following question: what is the world’s oldest formal, hierarchical institution that is still in existence today? If you answered the Roman Catholic Church, go to the head of the class. Depending on how one defines the hierarchical origins of the Roman Catholic Church, that institution has been around between 1,700 and 2,000 years. Even with the lower estimate, the Catholic Church has existed far longer than any contemporary state or historical dynasty and has done so even in the most turbulent of times. Further consider that the Catholic Church possesses roughly 1 billion members around the globe, with a presence in nearly every country. What other formal organization can boast of such tremendous size and international scope? One would imagine that social scientists interested in organizational emergence, preservation and collective action would want to know what makes this organization tick. But we should not just stop there. Protestantism, Judaism, Islam, Hinduism, and a variety of other religious traditions have existed for hundreds or thousands of years, often without the benefit of a centralized organization like the Catholic Church.
This article describes the testing of a model that proposes that people's beliefs regarding the effectiveness of hazard preparedness interact with social context factors (community participation, collective efficacy, empowerment and trust) to influence levels of hazard preparedness. Using data obtained from people living in coastal communities in Alaska and Oregon that are susceptible to experiencing tsunami, structural equation modelling analyses confirmed the ability of the model to help account for differences in levels of tsunami preparedness. Analysis revealed that community members and civic agencies influence preparedness in ways that are independent of the information provided per se. The model suggests that, to encourage people to prepare, outreach strategies must (a) encourage community members to discuss tsunami hazard issues and to identify the resources and information they need to deal with the consequences a tsunami would pose for them and (b) ensure that the community-agency relationship is complementary and empowering.
Epidemiological studies of dementia subtypes have revealed widely varying distribution rates. There are almost no published community prevalence data for dementia with Lewy bodies (DLB) or the frontal lobe dementias (FLD).
To identify the distribution of dementia subtypes in a representative community population of older people.
People aged ⩾65 years in randomised enumeration districts in Islington, north London, were screened using a reliable and valid questionnaire. People screened as having dementia were assessed in detail and diagnoses were made according to standard diagnostic criteria.
Of 1085 people interviewed, 107 (9.86%) met screening criteria for dementia. Diagnoses were made for 72 people (67.3%). Distribution of subtypes varied according to the criteria used; the best-validated criteria yielding: Alzheimer's disease 31.3%; vascular dementia 21.9%; DLB 10.9%; and FLD 7.8%.
Alzheimer's disease is confirmed as the most common cause of dementia in older people, followed by vascular dementia. However, DLB and FLD occur sufficiently often to be seen frequently in clinical practice and should be incorporated into future editions of standard diagnostic criteria.
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