Exploring the dynamics of the 2022 mpox outbreak in Canada.

The 2022 mpox outbreak predominantly impacted gay, bisexual, and other men who have sex with men (gbMSM). Two models were developed to support situational awareness and management decisions in Canada. A compartmental model characterized epidemic drivers at national/provincial levels, while an agent-based model (ABM) assessed municipal-level impacts of vaccination. The models were parameterized and calibrated using empirical case and vaccination data between 2022 and 2023. The compartmental model explored: (1) the epidemic trajectory through community transmission, (2) the potential for transmission among non-gbMSM, and (3) impacts of vaccination and the proportion of gbMSM contributing to disease transmission. The ABM incorporated sexual-contact data and modeled: (1) effects of vaccine uptake on disease dynamics, and (2) impacts of case importation on outbreak resurgence. The calibrated, compartmental model followed the trajectory of the epidemic, which peaked in July 2022, and died out in December 2022. Most cases occurred among gbMSM, and epidemic trajectories were not consistent with sustained transmission among non-gbMSM. The ABM suggested that unprioritized vaccination strategies could increase the outbreak size by 47%, and that consistent importation (≥5 cases per 10 000) is necessary for outbreak resurgence. These models can inform time-sensitive situational awareness and policy decisions for similar future outbreaks.

So Many Variables: Joint Modeling in Community Ecology.

Technological advances have enabled a new class of multivariate models for ecology, with the potential now to specify a statistical model for abundances jointly across many taxa, to simultaneously explore interactions across taxa and the response of abundance to environmental variables. Joint models can be used for several purposes of interest to ecologists, including estimating patterns of residual correlation across taxa, ordination, multivariate inference about environmental effects and environment-by-trait interactions, accounting for missing predictors, and improving predictions in situations where one can leverage knowledge of some species to predict others. We demonstrate this by example and discuss recent computation tools and future directions.

Bumblebees learn to forage like Bayesians.

Bayesian foraging in patchy environments requires that foragers have information about the distribution of resources among patches (prior information), either set by natural selection or learned from past experience. We test the hypothesis that bumblebee foragers can rapidly learn prior information from past experience in two very different experimental environments. In the high-variance environment (patches of low and high quality), stochastic optimality models predicted that finding rewards should sometimes sharply increase an optimal forager's tendency to stay in a patch (an incremental response), whereas in the uniform environment, finding rewards should always decrease the tendency to stay (a decremental response). We use Cox regression models to show that, in a matter of hours, bees learned to match both predicted responses, resulting in a reward intake rate that averaged 80% of the predicted maximum. Following training in either environment, bees' adaptive behavior carried over to a common test environment, thus confirming the influence of memorized prior information. Although Bayesian foraging by learning is often presumed, this study is the first to clearly isolate the adaptive use of a learned prior expectation. More generally, it highlights the remarkable adaptive plasticity of an important generalist pollinator and agent of selection.

Functional-diversity indices can be driven by methodological choices and species richness.

Functional diversity is an important concept in community ecology because it captures information on functional traits absent in measures of species diversity. One popular method of measuring functional diversity is the dendrogram-based method, FD. To calculate FD, a variety of methodological choices are required, and it has been debated about whether biological conclusions are sensitive to such choices. We studied the probability that conclusions regarding FD were sensitive, and that patterns in sensitivity were related to alpha and beta components of species richness. We developed a randomization procedure that iteratively calculated FD by assigning species into two assemblages and calculating the probability that the community with higher FD varied across methods. We found evidence of sensitivity in all five communities we examined, ranging from a probability of sensitivity of 0 (no sensitivity) to 0.976 (almost completely sensitive). Variations in these probabilities were driven by differences in alpha diversity between assemblages and not by beta diversity. Importantly, FD was most sensitive when it was most useful (i.e., when differences in alpha diversity were low). We demonstrate that trends in functional-diversity analyses can be largely driven by methodological choices or species richness, rather than functional trait information alone.

When and why do non-neutral metacommunities appear neutral?

Hubbell's neutral theory assumes that all species in a community have the same per capita fitness. Despite the overwhelming evidence against this assumption in most communities the neutral theory has often been, though not always, successful at predicting patterns of diversity in nature. I analyze a non-neutral model in order to suggest conditions under which observed species-abundance distributions (SADs) could be expected to resemble neutral distributions. The non-neutral model consists of two guilds of species such that (1) individuals between guilds do not interact, (2) dynamics within guilds follow Hubbell's model and (3) neutral parameters between guilds differ. This two-guild model generates SADs that appear neutral in some cases and clearly non-neutral in other cases. This result suggests that SADs may be more informative about niche structure than previously thought. The two-guild model could be tested in communities composed of fairly well-defined guilds or functional groups.

One hundred ninety-five cases of high-voltage electric injury.

High-voltage electric injury (HVEI) is associated with a high incidence of extremity compartment syndrome and of major amputation. The purpose of this study was to review our experience with HVEI and to attempt to develop predictors of the need for fasciotomy and amputation in patients with HVEI. The records of the 195 patients with HVEI who were admitted to a single burn center during a 19-year period were reviewed. Evidence for muscle necrosis, to include myoglobinuria and elevated creatine phosphokinase (CPK) levels, was noted. A total 187 patients (95.9%) survived to hospital discharge. A total of 56 underwent fasciotomy within 24 h of injury; 80 patients underwent an amputation during the hospitalization. Fasciotomy was predicted by presence of myoglobinuria with an overall accuracy of 72.8%. Amputation was predicted by a logistic model incorporating myoglobinuria, undergoing a previous fasciotomy, and age, with an overall accuracy of 73.3%. HVEI was associated with high amputation risk and a low rate of mortality in patients admitted to our burn center. Patients with gross myoglobinuria are at higher risk of requiring fasciotomy and/or amputation.

Predicting increased fluid requirements during the resuscitation of thermally injured patients.

BACKGROUND: We determined whether factors present soon after burn predict which patients will receive more than 4 mL/kg/% burn during the first 24 hours, and whether total fluid intake during the first 24 hours (VOL) contributes to in-hospital mortality (MORT). METHODS: We reviewed the records of patients admitted during 1987-97. The modified Brooke resuscitation formula was used. One hundred four patients met inclusion criteria: total body surface area burned (TBSA) > or = 20%; admission directly from the field; weight > 30 kg; no electric injury, mechanical trauma, or blood transfusions; and survival > or = 24 hours postburn. Eighty-nine records were complete. RESULTS: Mean TBSA was 43%, mean full-thickness burn size was 21%, mean age was 41 years, mean VOL was 4.9 mL/kg/% burn, and mean lactated Ringer's volume was 4.4 mL/kg/% burn; 53% had inhalation injury. MORT was 25.8%. Mean urine output was 0.77 mL/kg/h. By linear regression, VOL was associated with weight (negatively) and full-thickness burn size (r2 = 0.151). By logistic regression, receipt of over 4 mL/kg/% burn was predicted at admission by weight (negatively) and TBSA; by 24 hours postburn, mechanical ventilation replaced TBSA. With respect to MORT, logistic regression of admission factors yielded a model incorporating TBSA and an age function; by 24 hours postburn, the worst base deficit was added. CONCLUSION: Burn size and weight (negatively) were associated with greater VOL. However, a close linear relationship between burn size and VOL was not observed. Mechanical ventilation supplanted TBSA by 24 hours as a predictor of high VOL. Worst base deficit, TBSA, and an age function, but not VOL, were predictors of MORT.