Protocol and statistical analysis plan for the PREOXI trial of preoxygenation with noninvasive ventilation vs oxygen mask.

Background: Hypoxemia is a common and life-threatening complication during emergency tracheal intubation of critically ill adults. The administration of supplemental oxygen prior to the procedure ("preoxygenation") decreases the risk of hypoxemia during intubation. Research Question: Whether preoxygenation with noninvasive ventilation prevents hypoxemia during tracheal intubation of critically ill adults, compared to preoxygenation with oxygen mask, remains uncertain. Study Design and Methods: The PRagmatic trial Examining OXygenation prior to Intubation (PREOXI) is a prospective, multicenter, non-blinded randomized comparative effectiveness trial being conducted in 7 emergency departments and 17 intensive care units across the United States. The trial compares preoxygenation with noninvasive ventilation versus oxygen mask among 1300 critically ill adults undergoing emergency tracheal intubation. Eligible patients are randomized in a 1:1 ratio to receive either noninvasive ventilation or an oxygen mask prior to induction. The primary outcome is the incidence of hypoxemia, defined as a peripheral oxygen saturation <85% between induction and 2 minutes after intubation. The secondary outcome is the lowest oxygen saturation between induction and 2 minutes after intubation. Enrollment began on 10 March 2022 and is expected to conclude in 2023. Interpretation: The PREOXI trial will provide important data on the effectiveness of noninvasive ventilation and oxygen mask preoxygenation for the prevention of hypoxemia during emergency tracheal intubation. Specifying the protocol and statistical analysis plan prior to the conclusion of enrollment increases the rigor, reproducibility, and interpretability of the trial. Clinical trial registration number: NCT05267652.

Characterization of swine movements in the United States and implications for disease control.

Understanding between-farm movement patterns is an essential component in developing effective surveillance and control programs in livestock populations. Quantitative knowledge on movement patterns is particularly important for the commercial swine industry, in which large numbers of pigs are frequently moved between farms. Here, we described the annual movement patterns between swine farms in three production systems of the United States and identified farms that may be targeted to increase the efficacy of infectious disease control strategies. Research results revealed a high amount of variability in movement patterns across production systems, indicating that quantities captured from one production system and applied to another may lead to invalid estimations of disease spread. Furthermore, we showed that targeting farms based on their mean infection potential, a metric that captured the temporal sequence of movements, substantially reduced the potential for transmission of an infectious pathogen in the contact network and performed consistently well across production systems. Specifically, we found that by targeting farms based on their mean infection potential, we could reduce the potential spread of an infectious pathogen by 80% when removing approximately 25% of farms in each of the production systems. Whereas other metrics, such as degree, required 26-35% of farms to be removed in two of the production systems to reach the same outcome; this outcome was not achievable in one of the production systems. Our results demonstrate the importance of fine-scale temporal movement data and the need for in-depth understanding of the contact structure in developing more efficient disease surveillance and response strategies in swine production systems.

Risk factors for infectious pancreatic necrosis in farmed Chilean Atlantic salmon (Salmo salar L.) from 2010 to 2013.

Infectious pancreatic necrosis (IPN) is a widespread and economically devastating fish disease caused by infection with a virus referred to as IPN virus (IPNv). In Chile, the disease is endemic and prevalent in both fresh- and salt-water farms affecting cultured salmonids, mainly Atlantic salmon. Here, we present the results of a retrospective cohort study of Atlantic salmon farms stocked between 2010 and 2013, aimed at quantifying the extent to which certain epidemiological factors influence the time interval between stocking and onset of IPN mortality (time to mortality, ttm) in marine farms. Six variables were retained in a final multivariable Cox proportional hazard model. Compared to the 2010 stocking year, ttm was shorter for salmon stocked in years 2012 (HR = 2.1; p = 0.005) and 2013 (HR = 4.3; p = 0.01). The number of salmon farms within a 10-km radius (HR = 1.07; p = 0.002), positive report of IPN in the previous production cycle (HR = 1.95; p = 0.006), three or more smolt batches (HR = 2.27; p < 0.001), and positive report of mortality attributable to BKD (HR = 2.02; p < 0.001) were also associated with low ttm; conversely, ttm was longer for farms that stocked heavier fish (HR = 0.94; p = 0.001). The results presented here were consistent with early studies of IPN epidemiology in Norway and Scotland. Some of the risk factors identified in this study also influenced the risk for other diseases, such as infectious salmon anemia, suggesting that implementation of selected management practices may help to mitigate the burden of important infectious diseases of salmon in Chile.

Managing complexity: Simplifying assumptions of foot-and-mouth disease models for swine.

Compartmental models have often been used to test the effectiveness and efficiency of alternative control strategies to mitigate the spread of infectious animal diseases. A fundamental principle of epidemiological modelling is that models should start as simple as possible and become as complex as needed. The simplest version of a compartmental model assumes that the population is closed, void of births and deaths and that this closed population mixes homogeneously, meaning that each infected individual has an equal probability of coming into contact with each susceptible individual in the population. However, this assumption may oversimplify field conditions, leading to conclusions about disease mitigation strategies that are suboptimal. Here, we assessed the impact of the homogeneous mixing/closed population assumption, which is commonly assumed for within-farm models of highly contagious diseases of swine, such as foot-and-mouth disease (FMD), on predictions about disease spread. Incorporation of farm structure (different barns or rooms for breeding and gestation, farrowing, nursery and finishing) and demography (piglet births and deaths, and animal movement within and off of the farm) resulted in transmission dynamics that differed in the latter portion of an outbreak. Specifically, farm structure and demography, which were included in the farrow to finish and farrow to wean farms, resulted in FMD virus persistence within the population under certain conditions. Results here demonstrate the impact of incorporating farm structure and demography into models of FMD spread in swine populations and will ultimately contribute to the design and evaluation of effective disease control strategies to mitigate the impact of potential incursions.

Mosquitoes in Moose Country: A Mosquito Survey of Northern Minnesota.

An adult mosquito survey was conducted at 12 sites using carbon dioxide traps in northern Minnesota throughout the summer of 2012. Specimens were counted, identified to species, sorted into pools, and tested for eastern equine encephalitis (EEEV) and West Nile virus (WNV). Our findings extend the known range of Culiseta melanura, Anopheles barberi, and An. quadrimaculatus and document the presence and abundance of 27 other mosquito taxa in the region. None of the pools tested positive for EEEV or WNV.