Creating a sustainable residency research program is necessary to develop a sustainable research pipeline, as highlighted by the recent Society for Academic Emergency Medicine 2024 Consensus Conference. We sought to describe the implementation of a novel, immersive research program for first-year emergency medicine residents. We describe the curriculum development, rationale, implementation process, and lessons learned from the implementation of a year-long research curriculum for first-year residents. We further evaluated resident perception of confidence in research methodology, interest in research, and the importance of their research experience through a 32-item survey. In two cohorts, 25 first-year residents completed the program. All residents met their scholarly project requirements by the end of their first year. Two conference abstracts and one peer-reviewed publication were accepted for publication, and one is currently under review. Survey responses indicated that there was an increase in residents’ perceived confidence in research methodology, but this was limited by the small sample size. In summary, this novel resident research curriculum demonstrated a standardized, reproducible, and sustainable approach to provide residents with an immersive research program.

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.

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.

Introduction. While many individuals quit smoking during pregnancy, most relapse within one year postpartum. Research into methods to decrease smoking relapse postpartum has been hampered by difficulties with recruitment. Method. We conducted individual interviews with pregnant women (N = 22) who were interested in quitting smoking while pregnant about their attitudes regarding smoking and quitting during pregnancy, clinical trial participation, and smoking cessation medication use. Results. Participants were aware of the risks of smoking while pregnant. Many wanted to quit smoking before delivery. Few used empirically supported treatments to quit. While research was viewed positively, interest in taking on new commitments postpartum and taking a medication to prevent relapse was low. Medication concerns were evident among most participants, especially among those planning to breastfeed. Further, several women noted medication was unnecessary, as they did not believe they would relapse postpartum. Financial incentives, childcare, and fewer and/or remote visits were identified as facilitators to participating in research. However, these factors did not outweigh women’s concerns about medication use and time commitments. Conclusions. Women are aware that quitting smoking during pregnancy and remaining smoke-free postpartum are important. However, beliefs that personal relapse risk is low and that medications are dangerous reduced enthusiasm for taking medication for postpartum relapse prevention. Future medication trials should educate women about the high likelihood of relapse, prepare to answer detailed questions about risks of cessation medications, and connect with participants’ clinicians. For new mothers, studies conducted remotely with few scheduled appointments would reduce barriers to participation.

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.

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.

Domestic dogs display complex roaming behaviours, which need to be captured to more realistically model the spread of rabies. We have previously shown that roaming behaviours of domestic dogs can be categorised as stay-at-home, roamer and explorer in the Northern Peninsular Area (NPA), Queensland, Australia. These roaming behaviours are likely to cause heterogeneous contact rates that influence the speed or pattern of rabies spread in a dog population. The aim of this study was to define contact spatial kernels using the overlap of individual dog utilisation distributions to describe the daily probability of contact between pairs of dogs exhibiting these three a priori roaming behaviours. We further aimed to determine if the kernels lead to different predicted rabies outbreaks (outbreak duration and number of rabid dogs) by incorporating the spatial kernels into a previously developed rabies spread model for the NPA. Spatial kernels created with both dogs in a pair being explorers or one dog explorer and one dog roamer (who roamed away from their residence) produced short but large outbreaks compared with spatial kernels with at least one stay-at-home dog. Outputs from this model incorporating heterogeneous contacts demonstrate how roaming behaviours influence disease spread in domestic dog populations.

Improving geolocation accuracy in text data has long been a goal of automated text processing. We depart from the conventional method and introduce a two-stage supervised machine-learning algorithm that evaluates each location mention to be either correct or incorrect. We extract contextual information from texts, i.e., N-gram patterns for location words, mention frequency, and the context of sentences containing location words. We then estimate model parameters using a training data set and use this model to predict whether a location word in the test data set accurately represents the location of an event. We demonstrate these steps by constructing customized geolocation event data at the subnational level using news articles collected from around the world. The results show that the proposed algorithm outperforms existing geocoders even in a case added post hoc to test the generality of the developed algorithm.

This research aims to explore the submerged landscapes of the Pilbara of western Australia, using predictive archaeological modelling, airborne LiDAR, marine acoustics, coring and diver survey. It includes excavation and geophysical investigation of a submerged shell midden in Denmark to establish guidelines for the underwater discovery of such sites elsewhere.

Good education requires student experiences that deliver lessons about practice as well as theory and that encourage students to work for the public good—especially in the operation of democratic institutions (Dewey 1923; Dewy 1938). We report on an evaluation of the pedagogical value of a research project involving 23 colleges and universities across the country. Faculty trained and supervised students who observed polling places in the 2016 General Election. Our findings indicate that this was a valuable learning experience in both the short and long terms. Students found their experiences to be valuable and reported learning generally and specifically related to course material. Postelection, they also felt more knowledgeable about election science topics, voting behavior, and research methods. Students reported interest in participating in similar research in the future, would recommend other students to do so, and expressed interest in more learning and research about the topics central to their experience. Our results suggest that participants appreciated the importance of elections and their study. Collectively, the participating students are engaged and efficacious—essential qualities of citizens in a democracy.