Purpose Currently, people leaving prisons face concurrent risks from the COVID-19 pandemic and the overdose public health emergency. The closure or reduction of community services people rely on after release such as treatment centres and shelters has exacerbated the risks of poor health outcomes and harms. This paper aims to learn from peer health mentors (PHM) about changes to their work during overlapping health emergencies, as well as barriers and opportunities to support people leaving prison in this context. Design/methodology/approach The Unlocking the Gates (UTG) Peer Health Mentoring Program supports people leaving prison in British Columbia during the first three days after release. The authors conducted two focus groups with PHM over video conference in May 2020. Focus groups were recorded and transcribed, and themes were iteratively developed using narrative thematic analysis. Findings The findings highlighted the importance of peer health mentorship for people leaving prisons. PHM discussed increased opportunities for collaboration, ways the pandemic has changed how they are able to provide support, and how PHM are able to remain responsive and flexible to meet client needs. Additionally, PHM illuminated ways that COVID-19 has exacerbated existing barriers and identified specific actions needed to support client health, including increased housing and recovery beds, and tools for social and emotional well-being. Originality/value This study contributes to our understanding of peer health mentorship during the COVID-19 pandemic from the perspective of mentors. PHM expertise can support release planning, improved health and well-being of people leaving prison and facilitate policy-supported pandemic responses.

Background: The development and authorization of COVID-19 vaccines has provided the clearest path forward to eliminate community spread and thus end the ongoing SARS-CoV-2 pandemic. However, the limited pace at which the vaccine can be administered motivates the question, to what extent must we continue to adhere to social intervention measures such as mask wearing and social distancing? Methods: We develop a mathematical model of COVID-19 spread incorporating both vaccine dynamics and socio-epidemiological parameters. We use this model to study two important measures of disease control and eradication, the effective reproductive number Rt and the peak intensive care unit (ICU) caseload, over three key parameters: social measure adherence, vaccination rate, and vaccination coverage. Results: Our results suggest that, due to the slow pace of vaccine administration, social measures must be maintained by a large proportion of the population until a sufficient proportion of the population becomes vaccinated for the pandemic to be eradicated. By contrast, with reduced adherence to social measures, hospital ICU cases will greatly exceed capacity, resulting in increased avoidable loss of life. We then investigate the threat of localized outbreaks in low-vaccinated populations that have removed all social intervention mandates, and show that such populations could remain highly susceptible to major outbreaks particularly in the face of more easily transmissible variants.  Conclusions: These findings highlight the complex interplay involved between vaccination and social protective measures, and indicate the practical importance of continuing with extant social measures while vaccines are scaled up to allow the development of the herd immunity needed to end or control SARS-CoV-2 sustainably.

We develop a novel optimization framework to study strategies in ecological competition processes. The optimization method uses theory from dynamical systems describing the asymptotic behavior of a bistable system based on initial conditions, which we implement using a numerical boundary value problem. As an application of our method, we develop a model of the competition between Salmonella Typhimurium and the host's native microflora, which constantly and densely inhabit the intestinal lining of most mammals. S. Typhimurium invades the gut in two distinct phenotypic populations, one virulent and one avirulent, though the avirulent bacteria have the ability to activate a virulence factor and thereby "switch" into the virulent population. Counterintuitively, some studies have found that the combined population of S. Typhimurium gains an environmental advantage over the commensal microbiota after the virulent subpopulation provokes the body's inflammatory defenses. Our model represents the competition between the commensal microbiota, the avirulent salmonella, and the virulent salmonella populations and incorporates a simple representation of the immune response. We use our model to predict optimal strategies that would favor salmonella in its competition with the commensal bacteria.

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Environmental variation can play an important role in ecological competition by influencing the relative advantage between competing species. Here, we consider such effects by extending a classical, competitive Moran model to incorporate an environment that fluctuates periodically in time. We adapt methods from work on these classical models to investigate the effects of the magnitude and frequency of environmental fluctuations on two important population statistics: the probability of fixation and the mean time to fixation. In particular, we find that for small frequencies, the system behaves similar to a system with a constant fitness difference between the two species, and for large frequencies, the system behaves similar to a neutrally competitive model. Most interestingly, the system exhibits nontrivial behavior for intermediate frequencies.We conclude by showing that our results agree quite well with recent theoretical work on competitive models with a stochastically changing environment, and discuss how the methods we develop ease the mathematical analysis required to study such models.