We evaluated povidone-iodine (PVI) decolonization among 51 fracture-fixation surgery patients. PVI was applied twice on the day of surgery. Patients were tested for S. aureus nasal colonization and surveyed. Mean S. aureus concentrations decreased from 3.13 to 1.15 CFU/mL (P = .03). Also, 86% of patients stated that they felt neutral or positive about their PVI experience.

Background: Nasal decolonization significantly decreases the incidence of Staphylococcus aureus surgical-site infections (SSIs). Patient adherence with self-administration of a decolonization ointment (ie, mupirocin) is low, especially among patients having urgent surgery. Povidone-iodine decolonization may overcome patient adherence challenges because povidone-iodine needs to be applied only on the day of surgery. We assessed the effectiveness and acceptability of povidone-iodine decolonization given on the day of surgery among patients having orthopedic trauma surgery. Methods: Adult patients who underwent operative fixation of traumatic lower extremity fractures were consented to receive 10% intranasal povidone-iodine solution. Povidone-iodine was applied ~1 hour before surgical incision and was reapplied the evening after surgery. Patients were tested for S. aureus nasal colonization before surgery, the evening after surgery (before povidone-iodine reapplication), and the day after surgery. Swabs were inoculated into Dey-Engley neutralizer and processed in a vortexer. A series of dilutions were performed and plated on mannitol salt agar plates. S. aureus cultures were quantitatively assessed to determine the reduction in S. aureus after povidone-iodine use. Reductions in S. aureus nasal growth were evaluated using the Skillings-Mack test. SSIs manifesting within 30 and 90 days of surgery were identified using NHSN definitions. A survey was administered the morning after surgery to determine the acceptability of intranasal povidone-iodine. Results: In total, 51 patients participated in this pilot study between February 2020 and June 2021. Nasal samples from 12 participants (23.5%) grew S. aureus. The S. aureus concentration decreased significantly across the time points (P = .03) (Fig. 1). No SSIs were identified within 30 days of surgery. One SSI occurred within 90 days of surgery; this patient did not carry S. aureus, and cultures from the infected site were negative. Also, 31% of patients reported at least 1 mild side effect while using povidone-iodine: dripping (n = 7), itching (n = 6), dryness (n = 4), stinging (n = 4), staining (n = 3), unpleasant taste (n = 3), runny nose (n = 2), burning (n = 1), sneezing (n = 1), sore throat (n = 1), tickling (n = 1), and/or cough (n = 1). Also, 86% of patients stated that povidone-iodine felt neutral, pleasant, or very pleasant, and only 14% stated that it felt unpleasant or very unpleasant. Discussion: In this pilot study, 2 applications of nasal povidone-iodine on the day of surgery were acceptable for patients, and this protocol significantly reduced S. aureus concentration in nares of patients. Future large clinical trials should evaluate whether this 2-application regimen of povidone-iodine significantly decreases rates of SSI among orthopedic trauma surgery patients.

Funding: PDI Healthcare

Disclosures: None

Early in the COVID-19 pandemic, the World Health Organization stressed the importance of daily clinical assessments of infected patients, yet current approaches frequently consider cross-sectional timepoints, cumulative summary measures, or time-to-event analyses. Statistical methods are available that make use of the rich information content of longitudinal assessments. We demonstrate the use of a multistate transition model to assess the dynamic nature of COVID-19-associated critical illness using daily evaluations of COVID-19 patients from 9 academic hospitals. We describe the accessibility and utility of methods that consider the clinical trajectory of critically ill COVID-19 patients.

International relations scholarship concerns dyads, yet standard modeling approaches fail to adequately capture the data generating process behind dyadic events and processes. As a result, they suffer from biased coefficients and poorly calibrated standard errors. We show how a regression-based approach, the Additive and Multiplicative Effects (AME) model, can be used to account for the inherent dependencies in dyadic data and glean substantive insights in the interrelations between actors. First, we conduct a simulation to highlight how the model captures dependencies and show that accounting for these processes improves our ability to conduct inference on dyadic data. Second, we compare the AME model to approaches used in three prominent studies from recent international relations scholarship. For each study, we find that compared to AME, the modeling approach used performs notably worse at capturing the data generating process. Further, conventional methods misstate the effect of key variables and the uncertainty in these effects. Finally, AME outperforms standard approaches in terms of out-of-sample fit. In sum, our work shows the consequences of failing to take the dependencies inherent to dyadic data seriously. Most importantly, by better modeling the data generating process underlying political phenomena, the AME framework improves scholars’ ability to conduct inferential analyses on dyadic data.

Background: Hospitalized patients may unknowingly carry severe acute respiratory coronavirus virus 2 (SARS-CoV-2), even if they are admitted for other reasons. Because SARS-CoV-2 may remain positive by reverse-transcriptase polymerase chain reaction (RT-PCR) for months after infection, patients with a positive result may not necessarily be infectious. We aimed to determine the frequency of SARS-CoV-2 infections in patients admitted for reasons unrelated to coronavirus disease 2019 (COVID-19). Methods: The University of Iowa Hospitals and Clinics is an 811-bed tertiary-care center. We use a nasopharyngeal SARS-CoV-2 RT-PCR to screen admitted patients without signs or symptoms compatible with COVID-19. Patients with positive tests undergo a repeat test to assess cycle threshold (Ct) value kinetics. We reviewed records for patients with positive RT-PCR screening admitted during July–October 2020. We used a combination of history, serologies, and RT-PCR Ct values to assess and qualify likelihood of infectiousness: (1) likely infectious, if Ct values were <29, or (2) likely not infectious, if 1 or both samples had Cts <30 with or without a positive SARS-CoV-2 antinucleocapsid IgG/IgM test or history of a positive result in the past 90 days. Contact tracing was only conducted for patients likely to be infectious. We describe the isolation duration and contact tracing data. Results: In total, 6,447 patients were tested on hospital admission for any reason (persons under investigation or admitted for reasons other than COVID-19). Of these, 240 (4%) had positive results, but 65 (27%) of these were admitted for reasons other than COVID-19. In total, 55 patients had Ct values available and were included in this analysis. The median age was 56 years (range, 0–91), 28 (51%) were male, and 12 (5%) were children. The most frequent admission syndromes were neurological (36%), gastrointestinal (16%), and trauma (16%). Our assessment revealed 23 likely infections (42%; 14 definite, 9 possible) and 32 cases likely not infectious (58%). The mean Ct for patients who were likely infectious was 22; it was 34 for patients who were likely not infectious. Mean duration of in-hospital isolation was 6 days for those who were likely infectious and 2 days for those who were likely not infectious. We detected 8 individuals (1 healthcare worker and 7 patients) who were exposed to a likely infectious patient. Conclusions: SARS-CoV-2 infection in patients hospitalized for other reasons was infrequent. An assessment of the likelihood of infectiousness including history, RT-PCR Cts, and serology may help prioritize patients in need of isolation and contact investigations.

Funding: No

Disclosures: None

We analyse oscillatory instabilities for a coupled partial-ordinary differential equation (PDE-ODE) system modelling the communication between localised spatially segregated dynamically active signalling compartments that are coupled through a passive extracellular bulk diffusion field in a bounded 2D domain. Each signalling compartment is assumed to secrete a chemical into the extracellular medium (bulk region), and it can also sense the concentration of this chemical in the region around its boundary. This feedback from the bulk region, resulting from the entire collection of cells, in turn modifies the intracellular dynamics within each cell. In the limit where the signalling compartments are circular discs with a small common radius ɛ ≪ 1 and where the bulk diffusivity is asymptotically large, a matched asymptotic analysis is used to reduce the dimensionless PDE–ODE system into a nonlinear ODE system with global coupling. For Sel’kov reaction kinetics, this ODE system for the intracellular dynamics and the spatial average of the bulk diffusion field are then used to investigate oscillatory instabilities in the dynamics of the cells that are triggered due to the global coupling. In particular, numerical bifurcation software on the ODEs is used to study the overall effect of coupling defective cells (cells that behave differently from the remaining cells) to a group of identical cells. Moreover, when the number of cells is large, the Kuramoto order parameter is computed to predict the degree of phase synchronisation of the intracellular dynamics. Quorum sensing behaviour, characterised by the onset of collective behaviour in the intracellular dynamics as the number of cells increases above a threshold, is also studied. Our analysis shows that the cell population density plays a dual role of triggering and then quenching synchronous oscillations in the intracellular dynamics.

The coronavirus disease 2019 (COVID-19) has greatly impacted health-care systems worldwide, leading to an unprecedented rise in demand for health-care resources. In anticipation of an acute strain on established medical facilities in Dallas, Texas, federal officials worked in conjunction with local medical personnel to convert a convention center into a Federal Medical Station capable of caring for patients affected by COVID-19. A 200,000 square foot event space was designated as a direct patient care area, with surrounding spaces repurposed to house ancillary services. Given the highly transmissible nature of the novel coronavirus, the donning and doffing of personal protective equipment (PPE) was of particular importance for personnel staffing the facility. Furthermore, nationwide shortages in the availability of PPE necessitated the reuse of certain protective materials. This article seeks to delineate the procedures implemented regarding PPE in the setting of a COVID-19 disaster response shelter, including workspace flow, donning and doffing procedures, PPE conservation, and exposure event protocols.

Hydrogen lithography has been used to template phosphine-based surface chemistry to fabricate atomic-scale devices, a process we abbreviate as atomic precision advanced manufacturing (APAM). Here, we use mid-infrared variable angle spectroscopic ellipsometry (IR-VASE) to characterize single-nanometer thickness phosphorus dopant layers (δ-layers) in silicon made using APAM compatible processes. A large Drude response is directly attributable to the δ-layer and can be used for nondestructive monitoring of the condition of the APAM layer when integrating additional processing steps. The carrier density and mobility extracted from our room temperature IR-VASE measurements are consistent with cryogenic magneto-transport measurements, showing that APAM δ-layers function at room temperature. Finally, the permittivity extracted from these measurements shows that the doping in the APAM δ-layers is so large that their low-frequency in-plane response is reminiscent of a silicide. However, there is no indication of a plasma resonance, likely due to reduced dimensionality and/or low scattering lifetime.

In a singularly perturbed limit, we analyse the existence and linear stability of steady-state hotspot solutions for an extension of the 1-D three-component reaction-diffusion (RD) system formulated and studied numerically in Jones et. al. [Math. Models. Meth. Appl. Sci., 20, Suppl., (2010)], which models urban crime with police intervention. In our extended RD model, the field variables are the attractiveness field for burglary, the criminal population density and the police population density. Our model includes a scalar parameter that determines the strength of the police drift towards maxima of the attractiveness field. For a special choice of this parameter, we recover the ‘cops-on-the-dots’ policing strategy of Jones et. al., where the police mimic the drift of the criminals towards maxima of the attractiveness field. For our extended model, the method of matched asymptotic expansions is used to construct 1-D steady-state hotspot patterns as well as to derive nonlocal eigenvalue problems (NLEPs) that characterise the linear stability of these hotspot steady states to ${\cal O}$(1) timescale instabilities. For a cops-on-the-dots policing strategy, we prove that a multi-hotspot steady state is linearly stable to synchronous perturbations of the hotspot amplitudes. Alternatively, for asynchronous perturbations of the hotspot amplitudes, a hybrid analytical–numerical method is used to construct linear stability phase diagrams in the police vs. criminal diffusivity parameter space. In one particular region of these phase diagrams, the hotspot steady states are shown to be unstable to asynchronous oscillatory instabilities in the hotspot amplitudes that arise from a Hopf bifurcation. Within the context of our model, this provides a parameter range where the effect of a cops-on-the-dots policing strategy is to only displace crime temporally between neighbouring spatial regions. Our hybrid approach to study the NLEPs combines rigorous spectral results with a numerical parameterisation of any Hopf bifurcation threshold. For the cops-on-the-dots policing strategy, our linear stability predictions for steady-state hotspot patterns are confirmed from full numerical PDE simulations of the three-component RD system.