Contact tracing for COVID-19 in England operated from May 2020 to February 2022. The clinical, demographic and exposure information collected on cases and their contacts offered a unique opportunity to study secondary transmission. We aimed to quantify the relative impact of host factors and exposure settings on secondary COVID-19 transmission risk using 550,000 sampled transmission links between cases and their contacts. Links, or ‘contact episodes’, were established where a contact subsequently became a case, using an algorithm accounting for incubation period, setting, and contact date. A mixed-effects logistic regression model was used to estimate adjusted odds of transmission. Of sampled episodes, 8.7% resulted in secondary cases. Living with a case (71% episodes) was the most significant risk factor (aOR = 2.6, CI = 1.9–3.6). Other risk factors included unvaccinated status (aOR = 1.2, CI = 1.2–1.3), symptoms, and older age (66–79 years; aOR = 1.4, CI = 1.4–1.5). Whilst global COVID-19 strategies emphasized protection outside the home, including education, travel, and gathering restrictions, this study evidences the relative importance of household transmission. There is a need to reconsider the contribution of household transmission to future control strategies and the requirement for effective infection control within households.

Background: Prompt identification of patients colonized or infected with carbapenem-resistant Enterobacterales (CRE) upon admission can help ensure rapid initiation of infection prevention measures and may reduce intrafacility transmission of CRE. The Chicago CDC Prevention Epicenters Program previously created a CRE prediction model using state-wide public health data (doi: 10.1093/ofid/ofz483). We evaluated how well a similar model performed using data from a single academic healthcare system in Atlanta, Georgia, and we sought to determine whether including additional variables improved performance. Methods: We performed a case–control study using electronic medical record data. We defined cases as adult encounters to acute-care hospitals in a 4-hospital academic healthcare system from January 1, 2014, to December 31, 2021, with CRE identified from a clinical culture within the first 3 hospital days. Only the first qualifying encounter per patient was included. We frequency matched cases to control admissions (no CRE identified) from the same hospital and year. Using multivariable logistic regression, we compared 2 models. The “public health model” included 4 variables from the Chicago Epicenters model (age, number of hospitalizations in the prior 365 days, mean length of stay in hospitalizations in the prior 365 days, and hospital admission with an infection diagnosis in the prior 365 days). The “healthcare system model” added 4 additional variables (admission to the ICU in the prior 365 days, malignancy diagnosis, Elixhauser score and inpatient antibiotic days of therapy in the prior 365 days) to the public health model. We used billing codes to determine Elixhauser score, malignancy status, and recent infection diagnoses. We compared model performance using the area under the receiver operating curve (AUC). Results: We identified 105 cases and 441,460 controls (Table 1). CRE was most frequently identified in urine cultures (46%). All 4 variables included in the public health model and the 4 additional variables in the healthcare system model were all significantly associated with being a case in unadjusted analyses (Table 1). The AUC for the public health model was 0.76, and the AUC for the healthcare system model was 0.79 (Table 2; Fig. 1). In both models, a prior admission with an infection diagnosis was the most significant risk factor. Conclusions: A modified CRE prediction model developed using public health data and focused on prior healthcare exposures performed reasonably well when applied to a different academic healthcare system. The addition of variables accessible in large healthcare networks did not meaningfully improve model discrimination.

Disclosures: None

We outline the potential for integrating economic and evolutionary approaches to marriage and the family. Our broad argument is that the approaches share a concern for competition. Evolutionary scholars are concerned with the fitness consequences of competition and economists are centrally concerned with the nature of competition: how the allocation of scarce resources is mediated by potentially complex forms of social interaction and conflicts of interest. We illustrate our argument by focusing on conceptual and empirical approaches to a topic of interest to economists and evolutionary scholars: polygynous marriage. In comparing conceptual approaches, we distinguish between those that emphasise the physical environment and those that emphasise the social environment. We discuss some advantages of analysing marriage through the lens of competitive markets, and outline some of the ways that economists analyse the emergence of rules governing the family. In discussing empirical approaches to polygynous marriage, we describe how a concern for informing contemporary policy leads economists to focus on the consequences of polygyny, and in particular we describe some of the ways in which economists attempt to distinguish causal effects from selection effects.

The Rapid ASKAP Continuum Survey (RACS) is the first large-area survey to be conducted with the full 36-antenna Australian Square Kilometre Array Pathfinder (ASKAP) telescope. RACS will provide a shallow model of the ASKAP sky that will aid the calibration of future deep ASKAP surveys. RACS will cover the whole sky visible from the ASKAP site in Western Australia and will cover the full ASKAP band of 700–1800 MHz. The RACS images are generally deeper than the existing NRAO VLA Sky Survey and Sydney University Molonglo Sky Survey radio surveys and have better spatial resolution. All RACS survey products will be public, including radio images (with $\sim$ 15 arcsec resolution) and catalogues of about three million source components with spectral index and polarisation information. In this paper, we present a description of the RACS survey and the first data release of 903 images covering the sky south of declination $+41^\circ$ made over a 288-MHz band centred at 887.5 MHz.

Background: Carbapenem-resistant Enterobacteriaceae (CRE), particularly carbapenemase-producing (CP) CRE, pose a major public health threat. In 2016, the phenotypic definition of CRE expanded to include ertapenem resistance to improve sensitivity for detecting CP-CRE. We compared characteristics of CRE resistant to ertapenem only (CRE-EO) to CRE resistant to ≥1 other carbapenem (CRE-O). Methods: The Georgia Emerging Infections Program performs active, population-based CRE surveillance in metropolitan Atlanta. CRE cases were defined as any Escherichia coli, Klebsiella pneumoniae, K. oxytoca, K. variicola, Enterobacter cloacae complex, or Enterobacter aerogenes resistant to ≥1 carbapenem by the clinical laboratory and isolated from urine or a sterile site between 2016 and 2018. Data were extracted from retrospective chart review and 90-day mortality from Georgia vital statistics for 2016–2017. Polymerase chain reaction (PCR) for carbapenemase genes was performed on a convenience sample of isolates by the CDC or Georgia Public Health Laboratory. We compared characteristics of CRE-EO cases to CRE-O cases using χ2 tests or t tests. Results: Among 927 CRE isolates, 553 (60%) were CRE-EO. CRE-EO were less frequently isolated from blood (5% vs 12%; P < .01) and less commonly K. pneumoniae (21% vs 58%; P < .01) than CRE-O. CRE-EO cases were more often women (65% vs 50%; P < .01), had a lower Charlson comorbidity index (mean ± SD, 2.4±2.3 vs 3.0±2.6; P < .01), and were less commonly at a long-term care facility (24% vs 31%) or hospital (15% vs 21%; P < .01) in the 4 days prior to the CRE culture. CRE-EO were more susceptible to all antibiotics tested at the clinical laboratory (P < .01) except for tigecycline (P = 1.0) (Table 1). Of the 300 (32%) isolates tested for carbapenemase genes, 98 (33%) were positive (7% CRE-EO vs 62% CRE-O; P < .01). Of the CP isolates, we identified blaKPC in 93 cases (95%), blaNDM in 3 cases (3%), blaOXA-48-like in 2 cases (2%). CRE-EO cases had lower 90-day mortality (13% vs 21%; P < .01). Conclusions: CRE-EO are epidemiologically distinct from CRE-O and are less likely to harbor carbapenemase genes. CRE-EO may require less intensive infection prevention interventions and have more therapeutic options.

Funding: None

Disclosures: None

Background: Carbapenem-resistant Enterobacteriaceae (CRE) represent a significant antibiotic resistance threat, in part because carbapenemase genes can spread on mobile genetic elements. Here, we describe the molecular epidemiology and outcomes of patients with CRE bacteriuria from the same city in a nonoutbreak setting. Methods: The Georgia Emerging Infections Program performs active, population-based CRE surveillance in Atlanta. We studied a cohort of patients with CRE (resistant to all tested third-generation cephalosporins and ≥1 carbapenem, excluding ertapenem) first identified in urine, and not in a prior or simultaneous sterile site, between 2012 and 2015. Whole-genome sequencing (WGS) was performed on a convenience sample. We obtained epidemiologic and outcome data through chart review and Georgia Vital Statistics records (90-day mortality). Using WGS, we created a core-genome alignment-based phylogenetic tree of the Klebsiella pneumoniae isolates and calculated the SNP difference between each sample. Using SAS version 9.4 software, we performed the Fisher exact test and univariable odds ratios (OR) with 95% CI to compare patient isolates with and without a carbapenemase gene. Results: Among 81 patients included, the median age was 68 (IQR, 57–74) years, and most were female (58%), black (60%), and resided in a long-term care facility 4 days prior to culture isolation (53%). Organisms isolated were K. pneumoniae (84%), Escherichia coli (7%), Enterobacter cloacae (7%), and Klebsiella oxytoca (1%). WGS identified at least 1 β-lactamase gene in 91% of the isolates; 85% contained a carbapenemase gene, the most frequent of which was blaKPC-3 (94%). Patients with CRE containing a carbapenemase gene were more likely to be black (OR, 3.7; 95% CI, 1.0–13.8) and to have K. pneumoniae (OR, 8.9; 95% CI, 2.2–35.0). Using a core-genome alignment of 3,708 genes (~63% of the complete genome), we identified a median of 67 (IQR, 23–3,881) SNP differences between each K. pneumoniae isolate. A phylogenetic tree identified clustering around carbapenemase gene and multilocus sequence type (84% were ST 258) but not based on referring laboratory or county of residence (Fig. 1). Although 7% of patients developed an invasive CRE infection within 1 year and 21% died within 90 days, having a carbapenemase gene was not associated with these outcomes. Conclusions: Molecular sequencing of a convenience sample of CRE bacteriuria support K. pneumoniae ST258 harboring blaKPC-3 being distributed throughout the Atlanta area, across the healthcare continuum. Overall mortality was high in this population, but the presence of carbapenemase genes was not associated with worse outcomes.

Funding: None

Disclosures: None

Disclosures: None

Funding: None

While gas-phase reactions and surface reactions on bare carbonaceous or siliceous dust grains contribute to cosmic chemistry, the energetic processing of cosmic ices via photochemistry and radiation chemistry is thought to be the dominant mechanism for the cosmic synthesis of prebiotic molecules. Because most previous laboratory astrochemical studies have used light sources that produce >10 eV photons and are, therefore, capable of ionizing cosmic ice analogs, discerning the role of photochemistry vs. radiation chemistry in astrochemistry is challenging. By using a source whose photon energy does not exceed 8 eV, we have studied ammonia and methanol cosmic ice reactions attributable solely to photochemistry. We compare these results to those obtained in the same ultrahigh vacuum chamber with 1 keV electrons which instead initiate radiation chemistry in cosmic ice analogs.

The successful development of quantum computers is dependent on identifying quantum systems to function as qubits. Paramagnetic states of point defects in semiconductors or insulators have been shown to provide an effective implementation, with the nitrogen-vacancy center in diamond being a prominent example. The spin-1 ground state of this center can be initialized, manipulated, and read out at room temperature. Identifying defects with similar properties in other materials would add flexibility in device design and possibly lead to superior performance or greater functionality. A systematic search for defect-based qubits has been initiated, starting from a list of physical criteria that such centers and their hosts should satisfy. First-principles calculations of atomic and electronic structure are essential in supporting this quest: They provide a deeper understanding of defects that are already being exploited and allow efficient exploration of new materials systems and “defects by design.”

Objectives: The aim of this study was to describe the evolution of a cost-utility model used to inform the UK National Institute for Health and Clinical Excellence's (NICE) most recent decisions on the cost-utility of drug treatments for Alzheimer's disease (AD), and to explore the impact of structural assumptions on the cost-utility results.

Methods: Changes informed by noted limitations of the decision model used in NICE's previous decisions (in 2006) were made cumulatively to the original decision model for donepezil compared with best supportive care (for patients with mild to moderate AD). Deterministic and probabilistic analyses were undertaken for each cumulative change of the model. The expected value of perfect information (EVPI) of parameter estimates and structural assumptions was also calculated.

Results: Cumulative changes to the decision model highlighted how the results of the original model (incremental cost-effectiveness ratio of £81,000 per quality-adjusted life-year gained) related to those of the new model (where donepezil was estimated to be cost-saving), mainly due to uncertainty in the incremental cost of donepezil treatment over best supportive care (ranging from -£600 to £3,000 per patient). The partial EVPI analysis reflected this finding where further information on treatment discontinuations and cost parameter estimates were shown to be valuable in terms of reducing decision uncertainty.

Conclusions: Assessing the evolution of the cost-utility model helped to identify and explore structural differences between cohort-based models and is likely to be useful for decision models in other disease areas. This approach makes the structural uncertainty explicit, forcing decision makers to address structural uncertainty in addition to parameter uncertainty.