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Mpox, caused by monkeypox virus (MPXV), is a viral illness characterized by rash, influenza-like symptoms, and fever. A global outbreak of mpox attracted increased public attention in 2022 and became [...]

This pilot study explored effects of hearing loss on deaf children's reading comprehension in an online context. Eighteen deaf secondary students, ages 12-14 years (11 with British Sign Language as their dominant language, seven with English as their dominant language) engaged in an online research comprehension task. Six age-matched hearing spoken language bilingual students served as a comparison group. All participants were identified as confident readers by their teachers. Participants were asked to "think aloud" during an online search task to provide insights into their strategies. Additionally, participants completed a battery of assessments related to reading comprehension, vocabulary, non-verbal IQ, and working memory. Overall results showed similar use of strategies across all students. Strategies applied by the most skilled readers involved drawing on prior knowledge sources, e.g. informational websites or search engines, prior knowledge of the topic, and taking the time to read and evaluate website headings before deciding which one to use as source. Participants also made use of working memory skills. Findings highlight the importance of teaching online search and evaluation skills as part of the reading curriculum in schools.

When vaccinating a large population in response to an invading pathogen, it is often necessary to prioritize some individuals to be vaccinated first. One way to do this is to choose individuals to vaccinate based on their location. Methods for this prioritization include strategies that target those regions most at risk of importing the pathogen, and strategies that target regions with high centrality on the travel network. We use a simple infectious disease epidemic model to compare a risk-targeting strategy to two different centrality-targeting strategies based on betweenness centrality and random walk percolation centrality, respectively. We find that the relative effectiveness of these strategies in reducing the total number of infections varies with the basic reproduction number of the pathogen, travel rates, structure of the travel network and vaccine availability. We conclude that when a pathogen has high spreading capacity, or when vaccine availability is limited, centrality-targeting strategies should be considered as an alternative to the more commonly used risk-targeting strategies.

In the early stages of an outbreak, the term pandemic can be used to communicate about infectious disease risk, particularly by those who wish to encourage a large-scale public health response. However, the term lacks a widely accepted quantitative definition. We show that, under alternate quantitative definitions of pandemic, an epidemiological metapopulation model produces different estimates of the probability of a pandemic. Critically, we show that using different definitions alters the projected effects of key parameters-such as inter-regional travel rates, degree of pre-existing immunity, and heterogeneity in transmission rates between regions-on the risk of a pandemic. Our analysis provides a foundation for understanding the scientific importance of precise language when discussing pandemic risk, illustrating how alternative definitions affect the conclusions of modelling studies. This serves to highlight that those working on pandemic preparedness must remain alert to the variability in the use of the term pandemic, and provide specific quantitative definitions when undertaking one of the types of analysis that we show to be sensitive to the pandemic definition.

Single State Agencies (SSAs) are responsible for managing the publicly funded alcohol and other drug prevention, treatment, and recovery service system. Recovery housing (RH) is an important recovery support service (RSS) for individuals experiencing substance use disorder (SUD). Despite its effectiveness, information on state utilization and support is limited. To assess state-level support for RH and its incorporation within the SSA-managed SUD service systems, we administered a survey with SSAs in the 50 United States and the District of Columbia. In total, 48 out of the 51 SSAs responded, yielding a 94% response rate. Findings indicate strong state-level support for RH in terms of it being an integral RSS (98%), part of state-level strategic plans (73%) and prioritized for funding (87.5%). States are making progress to formalize RH with 68% reporting RH had been defined formally or within their agency. However, activities around understanding the capacity and need for RH are limited, with 44% indicating a needs assessment had not been conducted. At the same time, states perceive RH as a priority RSS, with growing recognition of its positive impact on long-term SUD recovery. This research identifies the opportunities for stakeholders to further evolve and expand RH at the federal, state, and local levels. [ABSTRACT FROM AUTHOR]

Mobile gaming has become immensely popular with the growing ease of access and the variety of inexpensive options now being offered. Pokémon Go, a cellular phone game that combines augmented reality (AR) and global positioning system (GPS) location to catch digital characters in the real world, is a free download that has broken participation records with its popularity. This article briefly reviews the evolution of mobile gaming and AR and then highlights the recent popularity and potential physical activity and recreational benefits of Pokémon Go. Moreover, this article also details how a Pokémon Go event was successfully hosted at Winthrop University by the Office of Recreational Services. In order to encourage more movement and social interaction, activity stations were integrated into the event that participants were able to complete for incentive prizes. A survey was completed after the event by the participants who returned to the starting point after visiting all four available stations. Survey results captured participants' perceived positives and negatives to playing Pokémon Go, their motivation for attending and overall opinion of the event, and their distance traveled during the event. Pokémon Go is an AR game that can be used to encourage recreation and movement. AR can provide many benefits and incentives when utilized in various technologies and curriculums. This article may assist recreation and physical activity leaders in creating events which integrate physical activity through mobile technology in a fun, unique way.

The rapid development of vaccines against SARS-CoV-2 altered the course of the COVID-19 pandemic. In most countries, vaccinations were initially targeted at high-risk populations, including older individuals and healthcare workers. Now, despite substantial infection- and vaccine-induced immunity in host populations worldwide, waning immunity and the emergence of novel variants continue to cause significant waves of infection and disease. Policy makers must determine how to deploy booster vaccinations, particularly when constraints in vaccine supply, delivery and cost mean that booster vaccines cannot be administered to everyone. A key question is therefore whether older individuals should again be prioritised for vaccination, or whether alternative strategies (e.g. offering booster vaccines to the individuals who have most contacts with others and therefore drive infection) can instead offer indirect protection to older individuals. Here, we use mathematical modelling to address this question, considering SARS-CoV-2 transmission in a range of countries with different socio-economic backgrounds. We show that the population structures of different countries can have a pronounced effect on the impact of booster vaccination, even when identical booster vaccination targeting strategies are adopted. However, under the assumed transmission model, prioritising older individuals for booster vaccination consistently leads to the most favourable public health outcomes in every setting considered. This remains true for a range of assumptions about booster vaccine supply and timing, and for different assumed policy objectives of booster vaccination. Author summary: Computational modelling is used increasingly to assess interventions against infectious diseases. For COVID-19, booster vaccines are being deployed worldwide to mitigate the effect of waning immunity following past infections and vaccinations, and to protect against new SARS-CoV-2 variants. However, booster vaccine availability is limited, making it necessary to consider who should receive booster vaccinations. It is essential that booster vaccine prioritisation is considered not only in the context of high income countries, but also low and middle income countries where the population age structure is very different. We have therefore developed a computational model to guide booster vaccination prioritisation in different socio-economic settings. We show that vaccinated populations can have different compositions between countries, even when identical booster vaccination strategies are adopted. Despite these differences, our modelling results suggest that booster vaccination strategies prioritising the oldest individuals lead to the best possible public health outcomes, due to the substantial skew in the risk of severe outcomes of infection towards older (and other vulnerable) hosts. This remains true even when quantifying the extent of premature, rather than absolute, mortality. This research therefore supports policy advice recommending prioritisation of older individuals for booster vaccines in countries worldwide when vaccine supply is limited. [ABSTRACT FROM AUTHOR]

During an infectious disease outbreak, public health policy makers are tasked with strategically implementing interventions whilst balancing competing objectives. To provide a quantitative framework that can be used to guide these decisions, it is helpful to devise a clear and specific objective function that can be evaluated to determine the optimal outbreak response. In this study, we have developed a mathematical modelling framework representing outbreaks of a novel emerging pathogen for which non-pharmaceutical interventions (NPIs) are imposed or removed based on thresholds for hospital occupancy. These thresholds are set at different levels to define four unique strategies for disease control. We illustrate that the optimal intervention strategy is contingent on the choice of objective function. Specifically, the optimal strategy depends on the extent to which policy makers prioritise reducing health costs due to infection over the costs associated with maintaining interventions. Motivated by the scenario early in the COVID-19 pandemic, we incorporate the development of a vaccine into our modelling framework and demonstrate that a policy maker's belief about when a vaccine will become available in future, and its eventual coverage (and/or effectiveness), affects the optimal strategy to adopt early in the outbreak. Furthermore, we show how uncertainty in these quantities can be accounted for when deciding which interventions to introduce. This research highlights the benefits of policy makers being explicit about the precise objectives of introducing interventions. Author summary: While often necessary to contain an infectious disease outbreak, extensive interventions result in education, economic and societal harms. For the optimal response to be determined, the trade-off between the costs and benefits of disease control requires policy makers to define and communicate their objectives for managing the outbreak. We use a mathematical model to simulate outbreaks where social distancing is implemented when disease prevalence within hospital settings is high. We consider four distinct strategies for managing the outbreak based on different hospital prevalence thresholds for switching between levels of social distancing. The optimal strategy to implement depends on how a policy maker balances the importance of reducing the number of hospitalisations and the costs of maintaining interventions. The optimal strategy to implement at the beginning of the outbreak is further impacted by beliefs regarding the future availability of a vaccine. We develop a quantitative decision making framework which explicitly considers the objectives of policy makers and allows robust strategies for future disease outbreaks to be designed. [ABSTRACT FROM AUTHOR]

People tend to look at uninformative, blank locations inspace when retrieving information. This gaze behaviour,known as looking at nothing, is assumed to be driven by theuse of spatial indices associated with external information.We investigated whether people form spatial indices andlook at nothing when retrieving words from memory.Participants were simultaneously presented four words.During retrieval participants looked at the relevant, blanklocation, where the probe word had appeared previously,longer than the other blank locations. Additionally, wordpresentation was sometimes followed by a visual cue eitherco-located or not with the probe word. Valid cues functionedas visual reinforcement while invalid cues causedinterference. Finally, participants with better visuospatialmemory looked less at the relevant, blank location,suggesting a dynamic relationship between so-called“external” and “internal” memory. Overall findings suggestan automatic, instantaneous spatial indexing mechanism forwords and a dynamic looking at nothing behaviour.