Evaluating public health uses of health information exchange

AbstractHealth information exchange (HIE) initiatives are in various stages of development across the United States. They aim to bring previously unavailable clinical data from patients’ disparate health records, which may be spread over multiple provider and payer networks, to the point of care where clinicians and their patients need it most. The implications of these initiatives on public health are numerous. This article provides general evaluation methods for measuring the impact of HIE on public health in six use cases: (1) mandated reporting of laboratory diagnoses, (2) mandated reporting of physician-based diagnoses, (3) public health investigation, (4) disease-based non-reportable laboratory data, (5) antibiotic-resistant organism surveillance, and (6) population-level quality monitoring

UPΦ phages, a new group of filamentous phages found in several members of Enterobacteriales

Filamentous phages establish chronic infections in their bacterial hosts, and new phages are secreted by infected bacteria for multiple generations, typically without causing host death. Often, these viruses integrate in their host’s genome by co-opting the host’s XerCD recombinase system. In several cases, these viruses also encode genes that increase bacterial virulence in plants and animals. Here, we describe a new filamentous phage, UPϕ901, which we originally found integrated in a clinical isolate of Escherichia coli from urine. UPϕ901 and closely related phages can be found in published genomes of over 200 other bacteria, including strains of Citrobacter koseri, Salmonella enterica, Yersinia enterocolitica, and Klebsiella pneumoniae. Its closest relatives are consistently found in urine or in the blood and feces of patients with urinary tract infections. More distant relatives can be found in isolates from other environments, including sewage, water, soil, and contaminated food. Each of these phages, which we collectively call ‘UPϕ viruses’, also harbors two or more novel genes of unknown function

Gene Co-occurrence Networks Reflect Bacteriophage Ecology and Evolution

Bacteriophages are the most abundant and diverse biological entities on the planet, and new phage genomes are being discovered at a rapid pace. As more phage genomes are published, new methods are needed for placing these genomes in an ecological and evolutionary context. Phages are difficult to study by phylogenetic methods, because they exchange genes regularly, and no single gene is conserved across all phages. Here, we demonstrate how gene-level networks can provide a high-resolution view of phage genetic diversity and offer a novel perspective on virus ecology. We focus our analyses on virus host range and show how network topology corresponds to host relatedness, how to find groups of genes with the strongest host-specific signatures, and how this perspective can complement phage host prediction tools. We discuss extensions of gene network analysis to predicting the emergence of phages on new hosts, as well as applications to features of phage biology beyond host range

Rephine.r: A pipeline for correcting gene calls and clusters to improve phage pangenomes and phylogenies

Background. A pangenome is the collection of all genes found in a set of related genomes. For microbes, these genomes are often different strains of the same species, and the pangenome offers a means to compare gene content variation with differences in phenotypes, ecology, and phylogenetic relatedness. Though most frequently applied to bacteria, there is growing interest in adapting pangenome analysis to bacteriophages. However, working with phage genomes presents new challenges. First, most phage families are under-sampled, and homologous genes in related viruses can be difficult to identify. Second, homing endonucleases and intron-like sequences may be present, resulting in fragmented gene calls. Each of these issues can reduce the accuracy of standard pangenome analysis tools. Methods. We developed an R pipeline called Rephine.r that takes as input the gene clusters produced by an initial pangenomics workflow. Rephine.r then proceeds in two primary steps. First, it identifies three common causes of fragmented gene calls: (1) indels creating early stop codons and new start codons; (2) interruption by a selfish genetic element; and (3) splitting at the ends of the reported genome. Fragmented genes are then fused to create new sequence alignments. In tandem, Rephine.r searches for distant homologs separated into different gene families using Hidden Markov Models. Significant hits are used to merge families into larger clusters. A final round of fragment identification is then run, and results may be used to infer single-copy core genomes and phylogenetic trees. Results. We applied Rephine.r to three well-studied phage groups: the Tevenvirinae (e.g., T4), the Studiervirinae (e.g., T7), and the Pbunaviruses (e.g., PB1). In each case, Rephine.r recovered additional members of the single-copy core genome and increased the overall bootstrap support of the phylogeny. The Rephine.r pipeline is provided through GitHub (https://www.github.com/coevoeco/Rephine.r) as a single script for automated analysis and with utility functions to assist in building single-copy core genomes and predicting the sources of fragmented genes

An analysis of factors affecting affiliation in the Marine Corps Reserves

MBA Professional ReportThe purpose of this study is to examine key factors in Marine Corps Reserve turnover in order to better understand reservists’ decisions to affiliate in the United States Marine Corps. Across the Marine Force Reserve there are communities, occupational fields, and grades with persistent manning shortfalls in non–obligor populations. Non– obligor reservists are those who serve at their own discretion, with each individual reservist having well–developed rationale and reasons for affiliating with a reserve unit. Monetary incentives are the primary stimulus employed to prompt reservists to affiliate and fill billets in units where there are persistent shortfalls. Money has had a positive impact, but the utilization of monetary incentives is not based upon a deep understanding of the reservists’ underlying motivations. This study explores individual non–obligor reservist motivations and rationales for affiliating to provide initial insights and a framework for future research. This study conducted a conceptual review of academic and military literature and six semi–structured telephone interviews in order to develop a predictive conceptual model of USMCR affiliation, allowing for more efficient targeting of retention methods and the development of non–monetary incentives.http://archive.org/details/annalysisoffacto1094544683Outstanding ThesisLieutenant Commander, United States NavyLieutenant, United States NavyCaptain, United States Marine CorpsApproved for public release; distribution is unlimited