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Abstract Researchers have long sought to understand and predict an animal’s response to stressful stimuli. Since the introduction of the concept of homeostasis, a variety of model frameworks have been proposed to describe what is necessary for an animal to remain within this stable physiological state and the ramifications of leaving it. Romero et al. (Horm Behav 55(3):375–389, 2009) introduced the reactive scope model to provide a novel conceptual framework for the stress response that assumes an animal’s ability to tolerate a stressful stimulus may degrade over time in response to the stimulus. We provide a mathematical formulation for the reactive scope model using a system of ordinary differential equations and show that this model is capable of recreating existing experimental data. We also provide an experimental method that may be used to verify the model as well as several potential additions to the model. If future experimentation provides the necessary data to estimate the model’s parameters, the model presented here may be used to make quantitative predictions about physiological mediator levels during a stress response and predict the onset of homeostatic overload. 

One of the biggest unanswered questions in the field of stress physiology is whether variation in chronic stress intensity will produce proportional (a gradient or graded) physiological response. We were specifically interested in the timing of the entrance into homeostatic overload, or the start of chronic stress symptoms. To attempt to fill this knowledge gap we split 40 captive house sparrows (Passer domesticus) into four groups (high stress, medium stress, low stress, and a captivity-only control) and subjected them to six bouts of chronic stress over a 6-month period. We varied the number of stressors/day and the length of each individual bout with the goal of producing groups that would experience different magnitudes of wear-and-tear. To evaluate the impact of chronic stress, at the start and end of each stress bout we measured body weight and three plasma metabolites (glucose, ketones, and uric acid) in both a fasted and fed state. All metrics showed significant differences across treatment groups, with the high stress group most frequently showing the greatest changes. However, the changes did not produce a consistent profile that matched the different chronic stress intensities. We also took samples after a prolonged recovery period of 6 weeks after the chronic stressors ended. The only group difference that persisted after 6 weeks was weight—all differences across groups in metabolites recovered. The results indicate that common blood metabolites are sensitive to stressors and may show signs of wear-and-tear, but are not reliable indicators of the intensity of long-term chronic stress. Furthermore, regulatory mechanisms are robust enough to recover within 6 weeks post-stress. 

Abstract Background Individual behavioural decisions are responses to a person’s perceived social norms that could be shaped by both their physical and social environment. In the context of the COVID-19 pandemic, these environments correspond to epidemiological risk from contacts and the social construction of risk by communication within networks of friends. Understanding the circumstances under which the influence of these different social networks can promote the acceptance of non-pharmaceutical interventions and consequently the adoption of protective behaviours is critical for guiding useful, practical public health messaging. Methods We explore how information from both physical contact and social communication layers of a multiplex network can contribute to flattening the epidemic curve in a community. Connections in the physical contact layer represent opportunities for transmission, while connections in the communication layer represent social interactions through which individuals may gain information, e.g. messaging friends. Results We show that maintaining focus on awareness of risk among each individual’s physical contacts promotes the greatest reduction in disease spread, but only when an individual is aware of the symptoms of a non-trivial proportion of their physical contacts (~ ≥ 20%). Information from the social communication layer without was less useful when these connections matched less well with physical contacts and contributed little in combination with accurate information from physical contacts. Conclusions We conclude that maintaining social focus on local outbreak status will allow individuals to structure their perceived social norms appropriately and respond more rapidly when risk increases. Finding ways to relay accurate local information from trusted community leaders could improve mitigation even where more intrusive/costly strategies, such as contact-tracing, are not possible. 

Abstract When a novel disease strikes a naïve host population, there is evidence that the most immediate response can involve host evolution while the pathogen remains relatively unchanged. When hosts also live in metapopulations, there may be critical differences in the dynamics that emerge from the synergy among evolutionary, ecological, and epidemiological factors. Here we used a Susceptible-Infected-Recovery model to explore how spatial and temporal ecological factors may drive the epidemiological and rapid-evolutionary dynamics of host metapopulations. For simplicity, we assumed two host genotypes: wild type, which has a positive intrinsic growth rate in the absence of disease, and robust type, which is less likely to catch the infection given exposure but has a lower intrinsic growth rate in the absence of infection. We found that the robust-type host would be strongly selected for in the presence of disease when transmission differences between the two types is large. The growth rate of the wild type had dual but opposite effects on host composition: a smaller increase in wild-type growth increased wild-type competition and lead to periodical disease outbreaks over the first generations after pathogen introduction, while larger growth increased disease by providing more susceptibles, which increased robust host density but decreased periodical outbreaks. Increased migration had a similar impact as the increased differential susceptibility, both of which led to an increase in robust hosts and a decrease in periodical outbreaks. Our study provided a comprehensive understanding of the combined effects among migration, disease epidemiology, and host demography on host evolution with an unchanging pathogen. The findings have important implications for wildlife conservation and zoonotic disease control. 

The global pandemic of COVID-19 revealed the dynamic heterogeneity in how individuals respond to infection risks, government orders, and community-specific social norms. Here we demonstrate how both individual observation and social learning are likely to shape behavioral, and therefore epidemiological, dynamics over time. Efforts to delay and reduce infections can compromise their own success, especially when disease risk and social learning interact within sub-populations, as when people observe others who are (a) infected and/or (b) socially distancing to protect themselves from infection. Simulating socially-learning agents who observe effects of a contagious virus, our modelling results are consistent with with 2020 data on mask-wearing in the U.S. and also concur with general observations of cohort induced differences in reactions to public health recommendations. We show how shifting reliance on types of learning affect the course of an outbreak, and could therefore factor into policy-based interventions incorporating age-based cohort differences in response behavior. 

Abstract To further elucidate the role that wear‐and‐tear plays in the transition from acute to chronic stress, we manipulated the intensity and duration of applied chronic stress to determine if behavior would respond proportionately. We brought wild house sparrows into captivity and subjected them to high‐stress, medium‐stress, low‐stress, or captivity‐only. We varied the number of stressors per day and the duration of stress periods to vary wear‐and‐tear, and thus the potential to exhibit chronic stress symptoms. The behaviors we assessed were neophobia (the fear of the new; assessed via food approach latency) and perch hopping (activity). We predicted that our birds would show proportionate decreases in neophobia and activity throughout a long‐term chronic stress paradigm. Our results indicate that neophobia is sensitive to the intensity of chronic stress, however, the birds became more neophobic, which was the opposite of what we expected. Conversely, perch hopping did not differ across treatment groups and is thus not sensitive to the intensity of chronic stress. Together, these data show that different behavioral measurements are impacted differently by chronic stress. 

COVID-19 is challenging many societal institutions, including our criminal justice systems. Some have proposed or enacted (e.g., the State of New Jersey) reductions in the jail and/or prison populations. We present a mathematical model to explore the epidemiologic impact of such interventions in jails and contrast them with the consequences of maintaining unaltered practices. We consider infection risk and likely in-custody deaths, and estimate how within-jail dynamics lead to spill-over risks, not only affecting incarcerated people but increasing exposure, infection, and death rates for both corrections officers and the broader community beyond the justice system. We show that, given a typical jail-community dynamic, operating in a business-as-usual way results in substantial, rapid, and ongoing loss of life. Our results are consistent with the hypothesis that large-scale reductions in arrest and speeding of releases are likely to save the lives of incarcerated people, jail staff, and the wider community.