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As part of a public health behavior change and communication strategy related to the identification of a novel ebolavirus in bats in Sierra Leone in 2016, a consortium of experts launched an effort to create a widely accessible resource for community awareness and education on reducing disease risk. The resulting picture book, Living Safely With Bats, includes technical content developed by a consortium of experts in public health, animal health, conservation, bats, and disease ecology from 30 countries. The book has now been adapted, translated, and used in more than 20 countries in Africa and Asia. We review the processes used to integrate feedback from local stakeholders and multidisciplinary experts. We also provide recommendations for One Health and other practitioners who choose to pursue the development and evaluation of this or similar zoonotic disease risk mitigation tools.

BackgroundAs the global population soars, human behaviours are increasing the risk of epidemics. Objective performance evaluation of outbreak responses requires that metrics of timeliness, or speed in response time, be recorded and reported. We sought to evaluate how timeliness data are being conveyed for multisectoral outbreaks and make recommendations on how One Health metrics can be used to improve response success.MethodsWe conducted a scoping review of outbreaks reported January 1, 2010- March 15, 2020, in organizational reports and peer-reviewed literature on PubMed and Embase databases. We tracked 11 outbreak milestones and calculated timeliness metrics, the median time in days, between the following: 1) Predict; 2) Prevent; 3) Start; 4) Detect; 5) Notify; 6) Verify; 7) Diagnostic; 8) Respond; 9) Communication; 10) End; and 11) After-Action Review.FindingsWe identified 26783 outbreak reports, 1014 of which involved more than just the human health sector. Only six of the eleven milestones were mentioned in >50% of reports. The time between most milestones was on average shorter for outbreaks reporting both Predict (alert of a potential outbreak) and Prevent (response to predictive alert) events.InterpretationTracking progress in timeliness during outbreaks can focus efforts to prevent outbreaks from evolving into epidemics or pandemics. Response to predictive alerts demonstrated improved expediency in time to most milestones. We recommend the adoption of universally defined One Health outbreak milestones, including After Action Review, such that timeliness metrics can be used to assess outbreak response improvements over time.FundingThis study was made possible by the United States Agency for International Development's One Health Workforce-Next Generation Project (Cooperative Agreement 7200AA19CA00018).

Host-virus associations have co-evolved under ecological and evolutionary selection pressures that shape cross-species transmission and spillover to humans. Observed virus-host associations provide relevant context for newly discovered wildlife viruses to assess knowledge gaps in host-range and estimate pathways for potential human infection. Using models to predict virus-host networks, we predicted the likelihood of humans as hosts for 513 newly discovered viruses detected by large-scale wildlife surveillance at high-risk animal-human interfaces in Africa, Asia, and Latin America. Predictions indicated that novel coronaviruses are likely to infect a greater number of host species than viruses from other families. Our models further characterize novel viruses through prioritization scores and directly inform surveillance targets to identify host ranges for newly discovered viruses.

Dry eye disease (DED) is a common, multifactorial ocular disease impacting 5% to 20% of people in Western countries and 45% to 70% in Asian countries. Despite the prevalence of DED and the number of treatment approaches available, signs and symptoms of the disease continue to limit the quality of life for many patients. Standard over-the-counter treatment approaches and behavior/environmental modifications may help some cases but more persistent forms often require pharmacological interventions. Approved and investigational pharmaceutical approaches attempt to treat the signs and symptoms of DED in different ways and tend to have varying tolerability among patients. While several pharmacological approaches are the standard for persistent and severe disease, mechanical options provide alternate treatment modalities that attempt to balance efficacy and comfort. Newer approaches target the causes of DED, utilizing novel delivery methods to minimize irritation and adverse events. Here, we review approved and investigational approaches to treating DED and compare patient tolerability. [ABSTRACT FROM AUTHOR]

Background and Aims: Behavioral economic theory predicts that high alcohol demand and high proportionate alcohol‐related reinforcement are important determinants of risky alcohol use in emerging adults, but the majority of research to date has been cross‐sectional in nature. The present study investigated prospective and dynamic relationships between alcohol demand and proportionate alcohol‐related reinforcement in relation to heavy drinking days and alcohol problems. Design: Longitudinal cohort with assessments every 4 months for 20 months. Setting: Ontario, Canada. Participants: Emerging adults reporting regular heavy episodic drinking (n = 636, Mage = 21.44; 55.8% female). Measurements Heavy drinking days (HDD; Daily Drinking Questionnaire), alcohol problems (Brief Young Adult Alcohol Consequences Questionnaire), alcohol demand (Alcohol Purchase Task) and proportionate alcohol‐related reinforcement (Activity Level Questionnaire). Findings Linear mixed effects models revealed that behavioral economic indicators and alcohol‐related outcomes significantly decreased over the study, consistent with 'aging out' of risky alcohol use. Random intercept cross‐lagged panel models revealed significant between‐person relationships, such that higher alcohol demand and alcohol‐related reinforcement were positively associated with HDD and alcohol problems (random intercepts = 0.187–0.534, Ps < 0.01). Moreover, alcohol demand indicators (particularly the rate of change in elasticity of the demand curve, as measured by α, and the maximum expenditure, Omax) and proportionate alcohol‐related reinforcement significantly forecasted changes in HDD at all time points (|βs| = 0.063–0.103, Ps < 0.05) in cross‐lagged relationships, with bidirectional associations noted for the rate of change in elasticity (βs = −0.085 to −0.104, Ps < 0.01). Proportionate alcohol‐related reinforcement also significantly forecasted changes in alcohol problems at all time points (βs = 0.072–0.112, Ps < 0.01). Conclusions: Multiple behavioral economic indicators (demand elasticity, maximum expenditure and reinforcement ratio) forecast changes in heavy episodic drinking and alcohol problems over the course of emerging adulthood. These results further implicate alcohol demand and proportionate alcohol‐related reinforcement as etiologically and developmentally important mechanisms in alcohol use trajectories. [ABSTRACT FROM AUTHOR]

Delay discounting—the extent to which individuals show a preference for smaller immediate rewards over larger delayed rewards—has been proposed as a transdiagnostic neurocognitive process across mental health conditions, but its examination in relation to posttraumatic stress disorder (PTSD) is comparatively recent. To assess the aggregated evidence for elevated delay discounting in relation to posttraumatic stress, we conducted a meta-analysis on existing empirical literature. Bibliographic searches identified 209 candidate articles, of which 13 articles with 14 independent effect sizes were eligible for meta-analysis, reflecting a combined sample size of N = 6897. Individual study designs included case-control (e.g. examination of differences in delay discounting between individuals with and without PTSD) and continuous association studies (e.g. relationship between posttraumatic stress symptom severity and delay discounting). In a combined analysis of all studies, the overall relationship was a small but statistically significant positive association between posttraumatic stress and delay discounting (r =.135, p <.0001). The same relationship was statistically significant for continuous association studies (r =.092, p =.027) and case-control designs (r =.179, p <.001). Evidence of publication bias was minimal. The included studies were limited in that many did not concurrently incorporate other psychiatric conditions in the analyses, leaving the specificity of the relationship to posttraumatic stress less clear. Nonetheless, these findings are broadly consistent with previous meta-analyses of delayed reward discounting in relation to other mental health conditions and provide further evidence for the transdiagnostic utility of this construct. [ABSTRACT FROM AUTHOR]

Background Primary cardiac lymphoma (PCL) is rare and its presentation can be variable. Thorough workup of suspected PCL or other cardiac tumours typically incorporates a range of imaging techniques and laboratory investigations but ultimately diagnosis is confirmed by histological analysis of myocardial tissue. Case Summary An 80-year-old Caucasian female presented with complete heart block and symptomatic cardiac tamponade. A pericardiocentesis was performed and a dual-chamber permanent pacemaker was implanted for the management of her complete heart block. Subsequently, a right atrial mass was discovered on imaging and the patient underwent endomyocardial biopsy of the mass. Histological analysis of the sample confirmed a primary cardiac lymphoma. The patient opted to forgo treatment with chemotherapy and died from her disease 1 month later. Discussion Cardiac arrhythmias can occur in PCL due to infiltration of conduction pathways. Characterization of cardiac masses on various imaging modalities and laboratory tests guides diagnosis. Tissue diagnosis is required to confirm PCL. The location of a cardiac mass may present technical challenges when undertaking a biopsy, so the best approach to tissue sampling should be considered on an individual basis. Without treatment survival is less than one month but with modern chemoimmunotherapy five-year survival may exceed 50%. [ABSTRACT FROM AUTHOR]

Zoonotic diseases threaten human health worldwide and are often associated with anthropogenic disturbance. Predicting how disturbance influences spillover risk is critical for effective disease intervention but difficult to achieve at fine spatial scales. Here, we develop a method that learns the spatial distribution of a reservoir species from aerial imagery. Our approach uses neural networks to extract features of known or hypothesized importance from images. The spatial distribution of these features is then summarized and linked to spatially explicit reservoir presence/absence data using boosted regression trees. We demonstrate the utility of our method by applying it to the reservoir of Lassa virus, Mastomys natalensis, within the West African nations of Sierra Leone and Guinea. We show that, when trained using reservoir trapping data and publicly available aerial imagery, our framework learns relationships between environmental features and reservoir occurrence and accurately ranks areas according to the likelihood of reservoir presence. [ABSTRACT FROM AUTHOR]