Total cost estimates for crime in the USA are both out-of-date and incomplete. We estimated incidence and costs of personal crimes (both violent and non-violent) and property crimes in 2017. Incidence came from national arrest data, multi-state estimates of police-reported crimes per arrest, national victimization and road crash surveys, and police underreporting studies. We updated and expanded upon published unit costs. Estimated crime costs totaled $2.6 trillion ($620 billion in monetary costs plus quality of life losses valued at $1.95 trillion; 95 % uncertainty interval $2.2–$3.0 trillion). Violent crime accounted for 85 % of costs. Principal contributors to the 10.9 million quality-adjusted life years lost were sexual violence, physical assault/robbery, and child maltreatment. Monetary expenditures caused by criminal victimization represent 3 % of Gross Domestic Product – equivalent to the amount spent on national defense. These estimates exclude the additional costs of preventing and avoiding crime such as enhanced lighting and burglar alarms. They also exclude crimes against businesses and most white-collar and corporate offenses.

A case–case–control investigation (216 patients) examined the risk factors and outcomes of carbapenem-resistant Enterobacter (CR-En) acquisition. Recent exposure to fluoroquinolones, intensive care unit (ICU) stay, and rapidly fatal McCabe condition were independent predictors for acquisition. Acquiring CR-En was independently associated with discharge to a long-term care facility after being admitted from home.

Background: Pseudomonas aeruginosa is an important nosocomial pathogen associated with intrinsic and acquired resistance mechanisms to major classes of antibiotics. To better understand clinical risk factors for drug-resistant P. aeruginosa infection, decision-tree models for the prediction of fluoroquinolone and carbapenem-resistant P. aeruginosa were constructed and compared to multivariable logistic regression models using performance characteristics. Methods: In total, 5,636 patients admitted to 4 hospitals within a New York City healthcare system from 2010 to 2016 with blood, respiratory, wound, or urine cultures growing PA were included in the analysis. Presence or absence of drug-resistance was defined using the first culture of any source positive for P. aeruginosa during each hospitalization. To train and validate the prediction models, cases were randomly split (60 of 40) into training and validation datasets. Clinical decision-tree models for both fluoroquinolone and carbapenem resistance were built from the training dataset using 21 clinical variables of interest, and multivariable logistic regression models were built using the 16 clinical variables associated with resistance in bivariate analyses. Decision-tree models were optimized using K-fold cross validation, and performance characteristics between the 4 models were compared. Results: From 2010 through 2016, prevalence of fluoroquinolone and carbapenem resistance was 32% and 18%, respectively. For fluoroquinolone resistance, the logistic regression algorithm attained a positive predictive value (PPV) of 0.57 and a negative predictive value (NPV) of 0.73 (sensitivity, 0.27; specificity, 0.90) and the decision-tree algorithm attained a PPV of 0.65 and an NPV of 0.72 (sensitivity 0.21, specificity 0.95). For carbapenem resistance, the logistic regression algorithm attained a PPV of 0.53 and a NPV of 0.85 (sensitivity 0.20, specificity 0.96) and the decision-tree algorithm attained a PPV of 0.59 and an NPV of 0.84 (sensitivity 0.22, specificity 0.96). The decision-tree partitioning algorithm identified prior fluoroquinolone resistance, SNF stay, sex, and length-of-stay as variables of greatest importance for fluoroquinolone resistance compared to prior carbapenem resistance, age, and length-of-stay for carbapenem resistance. The highest-performing decision tree for fluoroquinolone resistance is illustrated in Fig. 1. Conclusions: Supervised machine-learning techniques may facilitate prediction of P. aeruginosa resistance and risk factors driving resistance patterns in hospitalized patients. Such techniques may be applied to readily available clinical information from hospital electronic health records to aid with clinical decision making.

Funding: None

Disclosures: None

Previous genetic association studies have failed to identify loci robustly associated with sepsis, and there have been no published genetic association studies or polygenic risk score analyses of patients with septic shock, despite evidence suggesting genetic factors may be involved. We systematically collected genotype and clinical outcome data in the context of a randomized controlled trial from patients with septic shock to enrich the presence of disease-associated genetic variants. We performed genomewide association studies of susceptibility and mortality in septic shock using 493 patients with septic shock and 2442 population controls, and polygenic risk score analysis to assess genetic overlap between septic shock risk/mortality with clinically relevant traits. One variant, rs9489328, located in AL589740.1 noncoding RNA, was significantly associated with septic shock (p = 1.05 × 10–10); however, it is likely a false-positive. We were unable to replicate variants previously reported to be associated (p < 1.00 × 10–6 in previous scans) with susceptibility to and mortality from sepsis. Polygenic risk scores for hematocrit and granulocyte count were negatively associated with 28-day mortality (p = 3.04 × 10–3; p = 2.29 × 10–3), and scores for C-reactive protein levels were positively associated with susceptibility to septic shock (p = 1.44 × 10–3). Results suggest that common variants of large effect do not influence septic shock susceptibility, mortality and resolution; however, genetic predispositions to clinically relevant traits are significantly associated with increased susceptibility and mortality in septic individuals.

A national need is to prepare for and respond to accidental or intentional disasters categorized as chemical, biological, radiological, nuclear, or explosive (CBRNE). These incidents require specific subject-matter expertise, yet have commonalities. We identify 7 core elements comprising CBRNE science that require integration for effective preparedness planning and public health and medical response and recovery. These core elements are (1) basic and clinical sciences, (2) modeling and systems management, (3) planning, (4) response and incident management, (5) recovery and resilience, (6) lessons learned, and (7) continuous improvement. A key feature is the ability of relevant subject matter experts to integrate information into response operations. We propose the CBRNE medical operations science support expert as a professional who (1) understands that CBRNE incidents require an integrated systems approach, (2) understands the key functions and contributions of CBRNE science practitioners, (3) helps direct strategic and tactical CBRNE planning and responses through first-hand experience, and (4) provides advice to senior decision-makers managing response activities. Recognition of both CBRNE science as a distinct competency and the establishment of the CBRNE medical operations science support expert informs the public of the enormous progress made, broadcasts opportunities for new talent, and enhances the sophistication and analytic expertise of senior managers planning for and responding to CBRNE incidents.

OBJECTIVES/SPECIFIC AIMS: Objective: Approximately 86 million people in the US have prediabetes, but only a fraction of them receive proven effective therapies to prevent diabetes. Further, the effectiveness of these therapies varies with individual risk of progression to diabetes. We estimated the value of targeting those individuals at highest diabetes risk for treatment, compared to treating all individuals meeting inclusion criteria for the Diabetes Prevention Program (DPP). METHODS/STUDY POPULATION: METHODS: Using a micro-simulation model, we estimated total lifetime costs and quality-adjusted life expectancy (QALE) for individuals receiving: (1) lifestyle intervention involving an intensive program focused on healthy diet and exercise, (2) metformin administration, or (3) no intervention. The model combines several components. First a Cox proportional hazards model predicted onset of diabetes from baseline characteristics for each pre-diabetic individual and yielded a probability distribution for each alternative. We derived this risk model from the Diabetes Prevention Program (DPP) clinical trial data and the follow-up study DPP-OS. The Michigan Diabetes Research Center Model for Diabetes then estimated costs and outcomes for individuals after diabetes diagnosis using standard of care diabetes treatment. Based on individual costs and QALE, we evaluated NMB of the two interventions at population and individual levels, stratified by risk quintiles for diabetes onset at 3 years. RESULTS/ANTICIPATED RESULTS: Results: Compared to usual care, lifestyle modification conferred positive benefits for all eligible individuals. Metformin’s NMB was negative for the lowest population risk quintile. By avoiding use among individuals who would not benefit, targeted administration of metformin conferred a benefit of $500-$800 per person, depending on duration of treatment effect. When treating only 20% of the population (e.g., due to capacity constraints), targeting conferred a NMB of $14,000-$18,000 per person for lifestyle modification and $16,000-$20,000 for metformin. DISCUSSION/SIGNIFICANCE OF IMPACT: Conclusions: Metformin confers value only among higher risk individuals, so targeting its use is worthwhile. While lifestyle modification confers value for all eligible individuals, prioritizing the intervention to high risk patients when capacity is constrained substantially increases societal benefits.

Hepatitis E virus (HEV) is an emerging cause of viral hepatitis worldwide. Recently, HEV-7 has been shown to infect camels and humans. We studied HEV seroprevalence in dromedary camels and among Bedouins, Arabs (Muslims, none-Bedouins) and Jews and assessed factors associated with anti-HEV seropositivity. Serum samples from dromedary camels (n = 86) were used to determine camel anti-HEV IgG and HEV RNA positivity. Human samples collected between 2009 and 2016 from >20 years old Bedouins (n = 305), non-Bedouin Arabs (n = 320) and Jews (n = 195), were randomly selected using an age-stratified sampling design. Human HEV IgG levels were determined using Wantai IgG ELISA assay. Of the samples obtained from camels, 68.6% were anti-HEV positive. Among the human populations, Bedouins and non-Bedouin Arabs had a significantly higher prevalence of HEV antibodies (21.6% and 15.0%, respectively) compared with the Jewish population (3.1%). Seropositivity increased significantly with age in all human populations, reaching 47.6% and 34.8% among ⩾40 years old, in Bedouins and non-Bedouin Arabs, respectively. The high seropositivity in camels and in ⩾40 years old Bedouins and non-Bedouin Arabs suggests that HEV is endemic in Israel. The low HEV seroprevalence in Jews could be attributed to higher socio-economic status.

A space X is said to be Lipschitz 1-connected if every Lipschitz loop 𝛾 : S1 → X bounds a O (Lip(𝛾))-Lipschitz disk f : D2 → X. A Lipschitz 1-connected space admits a quadratic isoperimetric inequality, but it is unknown whether the converse is true. Cornulier and Tessera showed that certain solvable Lie groups have quadratic isoperimetric inequalities, and we extend their result to show that these groups are Lipschitz 1-connected.

Financial and economic sanctions are often adopted to serve multiple ends, including deterrence and prevention, but they are best understood as a tool to incentivize change in a target's behavior. In pursuit of this coercive objective, it is generally—but not always—the case that sanctions are more effective when they are imposed multilaterally, and the broader the coalition the better. This is because multilateral sanctions leverage the diverse sources of pressure that coalition partners can bring to bear on a target and carry with them the legitimacy of broad international support. Taken to its extreme, this argument may suggest that sanctions should always be multilateral, whether adopted through the United Nations, another forum, or an ad hoc coalition. But as we explain below, there are at least two significant reasons that militate in favor of unilateral sanctions. First, within the broad limits of international law, every country must retain the authority to impose sanctions to protect its sovereign security interests, even when it cannot muster a coalition of like-minded allies or a sufficient number of votes—and avoid a veto—on the UN Security Council. Second, imposing “smart” sanctions is actually a difficult business, requiring a complex administrative apparatus to design, build, implement, enforce, and defend them. International institutions, including the United Nations, are inherently less able to build the necessary structures to effectively enforce sanctions. For all of these reasons, two systems of sanctions—one national, one supranational—will likely coexist into the future.