Meaningful inclusion of people living with HIV as a model for workplace policies: Key findings from the project PEER study.

BACKGROUND: As a large number of people live with HIV, it is worthwhile to examine the integration of this group in the workplace. OBJECTIVE: To investigate how the operationalization of GIPA/MEPA supports workplace policies and practices for PLHIV. The study aims to explore what is being offered to support PLHIV in community-based agencies and what can be done to enhance the offerings. METHODS: For this community-based research, 2 bilingual online surveys were sent to 150 Canadian organizations that work closely with PLHIV or offer support to them. One of the surveys was for Executive Directors of these organizations while the other was sent to peers; i.e. PLHIV whose job is to offer services to PLHIV. Questions in the surveys varied between open-ended, binary, and Likert. RESULTS: GIPA/MEPA are implemented in most organizations and Executive Directors affirmed that PLHIV and their impacts on the workplace are valued. There is a consensus among Executive Directors that formal support is provided but most respondents argued that this support is not specific for PLHIV. More than half of respondents were either unaware or uncertain about the existence of informal support. Peer-employees claimed that one of the challenges of disclosing HIV to receive peer support is that they may face stigma. CONCLUSION: The application of GIPA/MEPA results in positive outcomes in the workplace. The study emphasizes the need to facilitate access to informal support.

The cost of anticipating stigma: a longitudinal examination of HIV stigma and health.

Levels of HIV stigma remain high, however there is a limited understanding around how different types of stigma interact to impact health. This study uses data from two time points to examine how enacted and internalized stigma lead to worse health through anticipated stigma as a mediator. We recruited 341 participants in Ontario, Canada to complete the HIV Stigma Index survey at baseline (t1) from September 2018 to August 2019 and follow up (t2) approximately two years later. Mediation models were created with enacted and internalized stigma at t1 as the antecedents, anticipated stigma at t2 as the mediator, and physical health, mental health, and overall health at t2 as the outcomes. Only the model with internalized stigma (t1) as the antecedent had anticipated stigma (t2) as a significant mediator contributing to both decreased mental and overall health. This highlights the need to address internalized stigma and the potential for anticipated stigma interventions to be effective at improving the health and wellbeing of people living with HIV.

Building capacity in quantitative research and data storytelling to enhance knowledge translation: a training curriculum for peer researchers.

BACKGROUND: Many community-based HIV research studies incorporate principles of greater involvement and meaningful engagement of people living with HIV (GIPA/MEPA) by training people with HIV as peer researchers. Unfortunately, there are still some aspects of research (e.g., quantitative data analysis and interpretation) where many projects fall short in realizing GIPA/MEPA principles. To address these gaps, we developed an eight-week training course that aimed to build the capacity of peer researchers around the understanding and interpretation of quantitative data and incorporating lived experience to increase the impact of the knowledge transfer and exchange phase of a study. METHODS: Peer researchers (n = 8) participated from British Columbia, Alberta, and Ontario and lessons learned from the training were implemented throughout the dissemination of research findings from the People Living with HIV Stigma Index study. This paper presents the curriculum and main training components, course evaluation results, and challenges and lessons learned. The manuscript was created in collaboration with and includes the perspectives of both the peer researchers involved in the training, as well the course facilitators. RESULTS: Throughout the course, peer researchers' self-assessed knowledge and understanding of quantitative research and data storytelling improved and, through interactive activities and practice, they gained the confidence to deliver a full research presentation. This improved their understanding of research findings, which was beneficial for discussing results with community partners and study participants. The peer researchers also agreed that learning about integrating lived experience with quantitative data has helped them to make research findings more relatable and convey key messages in a more meaningful way. CONCLUSIONS: Our training curriculum provides a template for research teams to build capacity in areas of research where peer researchers and community members are less often engaged. In doing so, we continue to uphold the principles of GIPA/MEPA and enhance the translation of research knowledge in communities most greatly affected.

Engaging patient groups or community members is commonplace in HIV research where people living with HIV are trained as peer researchers. There are still however some gaps where community members are less engaged, especially in quantitative data analysis. This presents a barrier preventing them from being meaningfully engaged in research about them. To build capacity in these areas, we designed an eight-week online course that taught peer researchers about quantitative data analysis and interpretation with a focus on concepts that would be important for talking about key messages from research findings. This was used to enhance the knowledge translation and dissemination initiatives for the People Living with HIV Stigma Index study­a survey tool containing quantitative measures examining stigma and related health factors. Peer researchers agreed that their knowledge and understanding of the key quantitative data concepts improved significantly throughout the course. This increased understanding helped them discuss quantitative data with community members and study participants, which was important to ensure that research findings reach the affected communities. Peer researchers also agreed that incorporating their new data analysis knowledge with existing lived experience helped them to make findings more relatable and understandable which is critical for translating knowledge to other researchers and policy makers. Overall, our training curriculum gave peer researchers the confidence to talk about quantitative data and improve their capacity to disseminate research. This work also provides guidelines for training peer researchers and ensuring that they are meaningfully engaged in research studies they are a part of.

Body size and food-web interactions mediate species range shifts under warming.

Species ranges are shifting in response to climate change, but most predictions disregard food-web interactions and, in particular, if and how such interactions change through time. Predator-prey interactions could speed up species range shifts through enemy release or create lags through biotic resistance. Here, we developed a spatially explicit model of interacting species, each with a thermal niche and embedded in a size-structured food-web across a temperature gradient that was then exposed to warming. We also created counterfactual single species models to contrast and highlight the effect of trophic interactions on range shifts. We found that dynamic trophic interactions hampered species range shifts across 450 simulated food-webs with up to 200 species each over 200 years of warming. All species experiencing dynamic trophic interactions shifted more slowly than single-species models would predict. In addition, the trailing edges of larger bodied species ranges shifted especially slowly because of ecological subsidies from small shifting prey. Trophic interactions also reduced the numbers of locally novel species, novel interactions and productive species, thus maintaining historical community compositions for longer. Current forecasts ignoring dynamic food-web interactions and allometry may overestimate species' tendency to track climate change.

Impact of experienced HIV stigma on health is mediated by internalized stigma and depression: results from the people living with HIV stigma index in Ontario.

BACKGROUND: Experiences of HIV stigma remain prevalent across Canada, causing significant stress and negatively affecting the health and wellbeing of people living with HIV. While studies have consistently demonstrated that stigma negatively impacts health, there has been limited research on the mechanisms behind these effects. This study aims to identify which dimensions of stigma have significant relationships with self-rated health and examine the mechanisms by which those types of stigma impact self-rated health. METHODS: We recruited 724 participants to complete the People Living with HIV Stigma Index in Ontario, designed by people living with HIV to measure nuanced changes in stigma and discrimination. The present study utilizes data from externally validated measures of stigma and health risks that were included in the survey. First, we conducted multiple regression analyses to examine which variables had a significant impact on self-rated health. Results from the multiple regression guided the mediation analysis. A parallel mediation model was created with enacted stigma as the antecedent, internalized stigma and depression as the mediators, and self-rated health as the outcome. RESULTS: In the multiple regression analysis, internalized stigma (coefficient = -0.20, p < 0.01) and depression (coefficient = -0.07, p < 0.01) were both significant and independent predictors of health. Mediation analyses demonstrated that the relationship between enacted stigma and self-rated health is mediated in parallel by both internalized stigma [coefficient = -0.08, se = 0.03, 95% CI (-0.14, -0.02)] and depression [coefficient = -0.16, se = 0.03, 95% CI (-0.22, -0.11)]. CONCLUSIONS: We developed a mediation model to explain how HIV-related stigma negatively impacts health. We found that that enacted stigma, or experiences of prejudice or discrimination, can lead to internalized stigma, or internalization of negative thoughts regarding one's HIV status and/or increased depressive symptoms which then may lead to worse overall health. Highlighting the importance of internalized stigma and depression has the potential to shape the development of targeted intervention strategies aimed at reducing the burden of stigma and improving the health and wellbeing of people living with HIV.

Collective behaviour can stabilize ecosystems.

Collective behaviour is common in bacteria, plants and animals, and therefore occurs across ecosystems, from biofilms to cities. With collective behaviour, social interactions among individuals propagate to affect the behaviour of groups, whereas group-level responses in turn affect individual behaviour. These cross-scale feedback loops between individuals, populations and their environments can provide fitness benefits, such as the efficient exploitation of uncertain resources, as well as costs, such as increased resource competition. Although the social mechanics of collective behaviour are increasingly well-studied, its role in ecosystems remains poorly understood. Here we introduce collective movement into a model of consumer-resource dynamics to demonstrate that collective behaviour can attenuate consumer-resource cycles and promote species coexistence. We focus on collective movement as a particularly well-understood example of collective behaviour. Adding collective movement to canonical unstable ecological scenarios causes emergent social-ecological feedback, which mitigates conditions that would otherwise result in extinction. Collective behaviour could play a key part in the maintenance of biodiversity.

Unsupervised manifold learning of collective behavior.

Collective behavior is an emergent property of numerous complex systems, from financial markets to cancer cells to predator-prey ecological systems. Characterizing modes of collective behavior is often done through human observation, training generative models, or other supervised learning techniques. Each of these cases requires knowledge of and a method for characterizing the macro-state(s) of the system. This presents a challenge for studying novel systems where there may be little prior knowledge. Here, we present a new unsupervised method of detecting emergent behavior in complex systems, and discerning between distinct collective behaviors. We require only metrics, d(1), d(2), defined on the set of agents, X, which measure agents' nearness in variables of interest. We apply the method of diffusion maps to the systems (X, d(i)) to recover efficient embeddings of their interaction networks. Comparing these geometries, we formulate a measure of similarity between two networks, called the map alignment statistic (MAS). A large MAS is evidence that the two networks are codetermined in some fashion, indicating an emergent relationship between the metrics d(1) and d(2). Additionally, the form of the macro-scale organization is encoded in the covariances among the two sets of diffusion map components. Using these covariances we discern between different modes of collective behavior in a data-driven, unsupervised manner. This method is demonstrated on a synthetic flocking model as well as empirical fish schooling data. We show that our state classification subdivides the known behaviors of the school in a meaningful manner, leading to a finer description of the system's behavior.

Climate shock effects and mediation in fisheries.

Climate shocks can reorganize the social-ecological linkages in food-producing communities, leading to a sudden loss of key products in food systems. The extent and persistence of this reorganization are difficult to observe and summarize, but are critical aspects of predicting and rapidly assessing community vulnerability to extreme events. We apply network analysis to evaluate the impact of a climate shock-an unprecedented marine heatwave-on patterns of resource use in California fishing communities, which were severely affected through closures of the Dungeness crab fishery. The climate shock significantly modified flows of users between fishery resources during the closures. These modifications were predicted by pre-shock patterns of resource use and were associated with three strategies used by fishing community member vessels to respond to the closures: temporary exit from the food system, spillover of effort from the Dungeness crab fishery into other fisheries, and spatial shifts in where crab were landed. Regional differences in resource use patterns and vessel-level responses highlighted the Dungeness crab fishery as a seasonal "gilded trap" for northern California fishing communities. We also detected disparities in climate shock response based on vessel size, with larger vessels more likely to display spatial mobility. Our study demonstrates the importance of highly connected and decentralized networks of resource use in reducing the vulnerability of human communities to climate shocks.

Fatal COVID-19 infection in a patient with long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency: A case report.

Long-chain fatty-acyl CoA dehydrogenase deficiency (LCHADD) is an inborn error of long chain fatty acid oxidation with various features including hypoketotic hypoglycemia, recurrent rhabdomyolysis, pigmentary retinopathy, peripheral neuropathy, cardiomyopathy, and arrhythmias. Various stresses trigger metabolic decompensation. Coronavirus disease 2019 (COVID-19) is a pandemic caused by the RNA virus SARS-CoV-2 with diverse presentations ranging from respiratory symptoms to myocarditis. We report a case of a patient with LCHADD who initially presented with typical metabolic decompensation symptoms including nausea, vomiting, and rhabdomyolysis in addition to mild cough, and was found to have COVID-19. She developed acute respiratory failure and refractory hypotension from severe cardiomyopathy which progressed to multiple organ failure and death. Our case illustrates the need for close monitoring of cardiac function in patients with a long-chain fatty acid oxidation disorder.

Pan-regional marine benthic cryptobiome biodiversity patterns revealed by metabarcoding Autonomous Reef Monitoring Structures.

Autonomous Reef Monitoring Structures (ARMS) have been applied worldwide to characterize the critical yet frequently overlooked biodiversity patterns of marine benthic organisms. In order to disentangle the relevance of environmental factors in benthic patterns, here, through standardized metabarcoding protocols, we analyse sessile and mobile (<2 mm) organisms collected using ARMS deployed across six regions with different environmental conditions (3 sites × 3 replicates per region): Baltic, Western Mediterranean, Adriatic, Black and Red Seas, and the Bay of Biscay. A total of 27,473 Amplicon Sequence Variants (ASVs) were observed ranging from 1,404 in the Black Sea to 9,958 in the Red Sea. No ASVs were shared among all regions. The highest number of shared ASVs was between the Western Mediterranean and the Adriatic Sea (116) and Bay of Biscay (115). Relatively high numbers of ASVs (103), mostly associated with the genus Amphibalanus, were also shared between the lower salinity seas (Baltic and Black Seas). We found that compositional differences in spatial patterns of rocky-shore benthos are determined slightly more by dispersal limitation than environmental filtering. Dispersal limitation was similar between sessile and mobile groups, while the sessile group had a larger environmental niche breadth than the mobile group. Further, our study can provide a foundation for future evaluations of biodiversity patterns in the cryptobiome, which can contribute up to 70% of the local biodiversity.

Remote sensing: generation of long-term kelp bed data sets for evaluation of impacts of climatic variation.

A critical tool in assessing ecosystem change is the analysis of long-term data sets, yet such information is generally sparse and often unavailable for many habitats. Kelp forests are an example of rapidly changing ecosystems that are in most cases data poor. Because kelp forests are highly dynamic and have high intrinsic interannual variability, understanding how regional-scale drivers are driving kelp populations-and particularly how kelp populations are responding to climate change-requires long-term data sets. However, much of the work on kelp responses to climate change has focused on just a few, relatively long-lived, perennial, canopy-forming species. To understand how kelp populations with different life history traits are responding to climate-related variability, we leverage 35 yr of Landsat satellite imagery to track the population size of an annual, ruderal kelp, Nereocystis luetkeana, across Oregon. We found high levels of interannual variability in Nereocystis canopy area and varying population trajectories over the last 35 yr. Surprisingly, Oregon Nereocystis population sizes were unresponsive to a 2014 marine heat wave accompanied by increases in urchin densities that decimated northern California Nereocystis populations. Some Oregon Nereocystis populations have even increased in area relative to pre-2014 levels. Analysis of environmental drivers found that Nereocystis population size was negatively correlated with estimated nitrate levels and positively correlated with winter wave height. This pattern is the inverse of the predicted relationship based on extensive prior work on the perennial kelp Macrocystis pyrifera and may be related to the annual life cycle of Nereocystis. This article demonstrates (1) the value of novel remote sensing tools to create long-term data sets that may challenge our understanding of nearshore marine species and (2) the need to incorporate life history traits into our theory of how climate change will shape the ocean of the future.

Identifying multiscale spatio-temporal patterns in human mobility using manifold learning.

When, where and how people move is a fundamental part of how human societies organize around every-day needs as well as how people adapt to risks, such as economic scarcity or instability, and natural disasters. Our ability to characterize and predict the diversity of human mobility patterns has been greatly expanded by the availability of Call Detail Records (CDR) from mobile phone cellular networks. The size and richness of these datasets is at the same time a blessing and a curse: while there is great opportunity to extract useful information from these datasets, it remains a challenge to do so in a meaningful way. In particular, human mobility is multiscale, meaning a diversity of patterns of mobility occur simultaneously, which vary according to timing, magnitude and spatial extent. To identify and characterize the main spatio-temporal scales and patterns of human mobility we examined CDR data from the Orange mobile network in Senegal using a new form of spectral graph wavelets, an approach from manifold learning. This unsupervised analysis reduces the dimensionality of the data to reveal seasonal changes in human mobility, as well as mobility patterns associated with large-scale but short-term religious events. The novel insight into human mobility patterns afforded by manifold learning methods like spectral graph wavelets have clear applications for urban planning, infrastructure design as well as hazard risk management, especially as climate change alters the biophysical landscape on which people work and live, leading to new patterns of human migration around the world.

Extreme temperature events will drive coral decline in the Coral Triangle.

In light of rapid environmental change, quantifying the contribution of regional- and local-scale drivers of coral persistence is necessary to characterize fully the resilience of coral reef systems. To assess multiscale responses to thermal perturbation of corals in the Coral Triangle (CT), we developed a spatially explicit metacommunity model with coral-algal competition, including seasonal larval dispersal and external spatiotemporal forcing. We tested coral sensitivity in 2,083 reefs across the CT region and surrounding areas under potential future temperature regimes, with and without interannual climate variability, exploring a range of 0.5-2.0°C overall increase in temperature in the system by 2054. We found that among future projections, reef survival probability and mean percent coral cover over time were largely determined by the presence or absence of interannual sea surface temperature (SST) extremes as well as absolute temperature increase. Overall, reefs that experienced SST time series that were filtered to remove interannual variability had approximately double the chance of survival than reefs subjected to unfiltered SST. By the end of the forecast period, the inclusion of thermal anomalies was equivalent to an increase of at least 0.5°C in SST projections without anomalies. Change in percent coral cover varied widely across the region within temperature scenarios, with some reefs experiencing local extinction while others remaining relatively unchanged. Sink strength and current thermal stress threshold were found to be significant drivers of these patterns, highlighting the importance of processes that underlie larval connectivity and bleaching sensitivity in coral networks.

Transnational corporations and the challenge of biosphere stewardship.

Sustainability within planetary boundaries requires concerted action by individuals, governments, civil society and private actors. For the private sector, there is concern that the power exercised by transnational corporations generates, and is even central to, global environmental change. Here, we ask under which conditions transnational corporations could either hinder or promote a global shift towards sustainability. We show that a handful of transnational corporations have become a major force shaping the global intertwined system of people and planet. Transnational corporations in agriculture, forestry, seafood, cement, minerals and fossil energy cause environmental impacts and possess the ability to influence critical functions of the biosphere. We review evidence of current practices and identify six observed features of change towards 'corporate biosphere stewardship', with significant potential for upscaling. Actions by transnational corporations, if combined with effective public policies and improved governmental regulations, could substantially accelerate sustainability efforts.

Supporting peer researchers: recommendations from our lived experience/expertise in community-based research in Canada.

Community-based research in HIV in Canada is a complex undertaking. Including peer researchers living with HIV meaningfully is intricate and costly. However, this inclusion guarantees results that translate to community action, policy-making, and public awareness. Including HIV+ peer researchers expedites the path from research to intervention. However, we must constantly review our support in light of three implicit tasks performed by peer researchers: constant disclosure, emotional labor, and advocating for meaningful participation. Our team offers four pillars of support to reduce harm and strengthen the self-determination, confidence, advocacy, and impact for HIV+ peer researchers. The provision of emotional, instrumental, educational, and cultural/spiritual support might seldom be standardized within a study, but to successfully engage in community-based research, study teams must articulate what support can be offered in each area.

Resilience through risk management: cooperative insurance in small-holder aquaculture systems.

Aquaculture is a booming industry. It currently supplies almost half of all fish and shellfish eaten today, and it continues to grow faster than any other food production sector. But it is immature relative to terrestrial crop and livestock sectors, and as a consequence it lags behind in terms of the use of aquaculture specific financial risk management tools. In particular, the use of insurance instruments to manage weather related losses is little used. In the aquaculture industry there is a need for new insurance products that achieve both financial gains, in terms of reduced production and revenue risk, and environmental wins, in terms of incentivizing improved management practices. Here, we have developed a cooperative form of indemnity insurance for application to small-holder aquaculture communities in developing nations. We use and advance the theory of risk pools, applying it to an aquaculture community in Myanmar, using empirical data recently collected from a comprehensive farm survey. These data were used to parameterize numerical simulations of this aquaculture system with and without a risk pool. Results highlight the benefits and costs of a risk pool, for various combinations of key parameters. This information reveals a path forward for creating new risk management products for aquaculturalists around the world.

Revenue-sharing clubs provide economic insurance and incentives for sustainability in common-pool resource systems.

Harvesting behaviors of natural resource users, such as farmers, fishermen and aquaculturists, are shaped by season-to-season and day-to-day variability, or in other words risk. Here, we explore how risk-mitigation strategies can lead to sustainable use and improved management of common-pool natural resources. Over-exploitation of unmanaged natural resources, which lowers their long-term productivity, is a central challenge facing societies. While effective top-down management is a possible solution, it is not available if the resource is outside the jurisdictional bounds of any management entity, or if existing institutions cannot effectively impose sustainable-use rules. Under these conditions, alternative approaches to natural resource governance are required. Here, we study revenue-sharing clubs as a mechanism by which resource users can mitigate their income volatility and importantly, as a co-benefit, are also incentivized to reduce their effort, leading to reduced over-exploitation and improved resource governance. We use game theoretic analyses and agent-based modeling to determine the conditions in which revenue-sharing can be beneficial for resource management as well as resource users. We find that revenue-sharing agreements can emerge and lead to improvements in resource management when there is large variability in production/revenue and when this variability is uncorrelated across members of the revenue-sharing club. Further, we show that if members of the revenue-sharing collective can sell their product at a price premium, then the range of ecological and economic conditions under which revenue-sharing can be a tool for management greatly expands. These results have implications for the design of bottom-up management, where resource users themselves are incentivized to operate in ecologically sustainable and economically advantageous ways.

How ecology shapes exploitation: a framework to predict the behavioural response of human and animal foragers along exploration-exploitation trade-offs.

Understanding how humans and other animals behave in response to changes in their environments is vital for predicting population dynamics and the trajectory of coupled social-ecological systems. Here, we present a novel framework for identifying emergent social behaviours in foragers (including humans engaged in fishing or hunting) in predator-prey contexts based on the exploration difficulty and exploitation potential of a renewable natural resource. A qualitative framework is introduced that predicts when foragers should behave territorially, search collectively, act independently or switch among these states. To validate it, we derived quantitative predictions from two models of different structure: a generic mathematical model, and a lattice-based evolutionary model emphasising exploitation and exclusion costs. These models independently identified that the exploration difficulty and exploitation potential of the natural resource controls the social behaviour of resource exploiters. Our theoretical predictions were finally compared to a diverse set of empirical cases focusing on fisheries and aquatic organisms across a range of taxa, substantiating the framework's predictions. Understanding social behaviour for given social-ecological characteristics has important implications, particularly for the design of governance structures and regulations to move exploited systems, such as fisheries, towards sustainability. Our framework provides concrete steps in this direction.