Objectives The COVID-19 pandemic has had devastating worldwide impact but most prominent was its effect on marginalised, underserved and equity-deserving populations. Social media arose as an ...important platform from which health organisations could rapidly disseminate information to equity-deserving populations about COVID-19 risks and events, provide instructions on how to mitigate those risks, motivate compliance with health directives, address false information, provide the opportunity for engagement and immediate feedback. The objective of this scoping review was to synthesise the academic and grey literature on equity-informed social media risk communication strategies developed during the pandemic. Design The review followed the Arksey and O’Malley framework and focused on the research question: What are the promising principles, processes, and practices for producing equity-informed social media risk communications? Data sources CINAHL Complete, MEDLINE (OVID), Business Source Complete, EMBASE database OVID, Scopus and PubMed’s curated COVID-19 literature hub: LitCovid, PsycINFO OVID were searched using terms related to access to health services, social media, risk communication, misinformation, community engagement, infectious disease, pandemics and marginalisation, supplemented by grey literature from relevant health organisations. Eligibility criteria for selecting studies Studies were eligible if the population of interest was an equity-deserving population, the concept discussed was COVID-19 risk communication and the article was published in English between January 2019 and December 2022. Data extraction and synthesis COVIDENCE facilitated screening and extraction. Charted data were thematically analysed following Braun and Clarke’s phased process. Preliminary findings were collaboratively discussed with representatives from health agencies and community organisations focused on serving equity-deserving groups. Results 12 studies were included. In terms of principles and process, studies emphasised the need to collaboratively create plans for message construction and targeted dissemination using a risk communication framework, capitalise on access to community resources and pre-established communication mediums and be considerate of population-specific needs and concerns. Practice entails careful consideration of communication mediums, language usage, communication frequency and evaluation. Conclusion This scoping review provides valuable insights for health agencies and community organisations in developing principles, processes and practices to equitably communicate risk information through social media. Engagement with stakeholders further refined and confirmed the findings, offering insights for future crisis communication strategies.
Abstract
Objective
In response to the opioid epidemic, the Centers for Disease Control and Prevention issued guidelines (CDCG) in 2016 for the prescription of opioids for chronic pain. To facilitate ...research into whether CDCG implementation will lead to reductions in opioid prescribing and improved patient safety, we sought to validate a tool that quantifies CDCG adherence based on clinical documentation.
Design
The Safe Opioid Prescribing Evaluation Tool (SOPET) was developed in four phases as part of a study to improve the implementation of the CDCG in the clinical setting. Four raters with varying levels of clinical experience and expertise were trained to use the SOPET and then used it to evaluate 21 baseline patient encounters. Intraclass correlation coefficient (ICC) estimates and their 95% confident intervals (CIs) were calculated for the total SOPET score based on a mean-rating (k = 4), absolute-agreement, two-way random-effects model. For intrarater reliability, two-way mixed-effect models were used.
Results
Inter-rater reliability was good, with an average-measures ICC of 0.82 (95% CI = 0.63–0.92). Intrarater reliability was excellent for the three raters, who were MDs, with average-measures ICCs as follows: 0.92 (95% CI = 0.81–0.97), 0.97 (95% CI = 0.92–0.99), 0.99 (95% CI = 0.99–0.99). However, the intrarater reliability for the non-MD rater was lower 0.69 (95% CI = 0.22–0.88).
Conclusions
Overall, the SOPET is useful for evaluating implementation of the CDCG in clinical documentation. It is an important first step in the design of future studies assessing whether adherence to the CDCG improves patient safety outcomes.
It is widely acknowledged that the growing opioid epidemic and associated increase in overdose deaths necessitates a reexamination of processes and procedures related to an opioid prescription for ...the treatment of chronic pain. However, the perspectives of patients, including those at the highest risk for opioid-related harms, are largely missing from this reexamination. To partially address the gap, we conducted a pair of one-day public deliberations on opioid prescribing in the context of HIV care. Results included recommendations and perspectives from people living with HIV that detail how providers can best assess patient needs, communicate regarding opioids, and reduce the risk of misuse. Participants emphasized the importance of building trust with patients and taking an extensive patient history prior to making decisions about whether to initiate or end an opioid prescription. This trust - together with an understanding of the origin of a patient's pain, history of drug use and other therapies tried - was perceived as essential to effective monitoring and pain management, as well as promotion of positive health outcomes. Ensuring that such patient perspectives are incorporated into the operationalization of guidelines for safe opioid prescribing may help to improve outcomes and quality of care for people living with HIV.
Rates of opioid use disorder and associated deaths remain alarmingly high. Measures to address the epidemic have included reductions in opioid prescribing, in part guided by the Centers for Disease ...Control Opioid Prescribing Guideline (CDCG). While reductions in over-prescribing have occurred, these measures have also resulted in decreased access and adverse outcomes for some stable opioid-treated chronic pain patients. The TOWard SafER Opioid Prescribing (TOWER) intervention was designed to support HIV primary care providers in use of the CDCG and in decision-making and patient-provider communication regarding safe opioid prescribing. Eleven HIV primary care providers and 40 of their patients were randomized into intervention and control groups. Transcripts from 21 patient visits were analyzed, focusing on opioid and pain-related communications. Findings from this research indicate greater alignment with the CDCG among visits carried out with providers in the TOWER intervention group. However, control group visits were notably consistent with guideline recommendations in several key areas. Differences observed between the intervention and control group visits demonstrate intervention strengths, as well as areas where additional work needs to be done to ensure prescribing and communication consistent with the CDCG.
DNA methylation comprises a cumulative record of lifetime exposures superimposed on genetically determined markers. Little is known about methylation dynamics in humans following an acute ...perturbation, such as infection. We characterized the temporal trajectory of blood epigenetic remodeling in 133 participants in a prospective study of young adults before, during, and after asymptomatic and mildly symptomatic SARS‐CoV‐2 infection. The differential methylation caused by asymptomatic or mildly symptomatic infections was indistinguishable. While differential gene expression largely returned to baseline levels after the virus became undetectable, some differentially methylated sites persisted for months of follow‐up, with a pattern resembling autoimmune or inflammatory disease. We leveraged these responses to construct methylation‐based machine learning models that distinguished samples from pre‐, during‐, and postinfection time periods, and quantitatively predicted the time since infection. The clinical trajectory in the young adults and in a diverse cohort with more severe outcomes was predicted by the similarity of methylation before or early after SARS‐CoV‐2 infection to the model‐defined postinfection state. Unlike the phenomenon of trained immunity, the postacute SARS‐CoV‐2 epigenetic landscape we identify is antiprotective.
Synopsis
Characterization of the temporal dynamics of blood methylation changes in young adults following asymptomatic and mild SARS‐CoV‐2 infection brings insights into the long‐term memory of environmental exposure and potential disease associations.
Both symptomatic and asymptomatic infections induce methylation changes that are not always associated with gene expression changes.
Methylation changes persist for longer than gene expression changes.
The complex dynamics of methylation alterations can be used to predict the timing of infection.
Contrary to the trained immunity phenomenon, the presence of a post‐infection‐like methylation state at baseline is anti‐protective for subsequent SARS‐CoV‐2 infection.
Characterization of the temporal dynamics of blood methylation changes in young adults following asymptomatic and mild SARS‐CoV‐2 infection brings insights into the long‐term memory of environmental exposure and potential disease associations.
Young adults infected with SARS-CoV-2 are frequently asymptomatic or develop only mild disease. Because capturing representative mild and asymptomatic cases require active surveillance, they are less ...characterized than moderate or severe cases of COVID-19. However, a better understanding of SARS-CoV-2 asymptomatic infections might shed light into the immune mechanisms associated with the control of symptoms and protection. To this aim, we have determined the temporal dynamics of the humoral immune response, as well as the serum inflammatory profile, of mild and asymptomatic SARS-CoV-2 infections in a cohort of 172 initially seronegative prospectively studied United States Marine recruits, 149 of whom were subsequently found to be SARS-CoV-2 infected. The participants had blood samples taken, symptoms surveyed and PCR tests for SARS-CoV-2 performed periodically for up to 105 days. We found similar dynamics in the profiles of viral load and in the generation of specific antibody responses in asymptomatic and mild symptomatic participants. A proteomic analysis using an inflammatory panel including 92 analytes revealed a pattern of three temporal waves of inflammatory and immunoregulatory mediators, and a return to baseline for most of the inflammatory markers by 35 days post-infection. We found that 23 analytes were significantly higher in those participants that reported symptoms at the time of the first positive SARS-CoV-2 PCR compared with asymptomatic participants, including mostly chemokines and cytokines associated with inflammatory response or immune activation (i.e., TNF-α, TNF-β, CXCL10, IL-8). Notably, we detected 7 analytes (IL-17C, MMP-10, FGF-19, FGF-21, FGF-23, CXCL5 and CCL23) that were higher in asymptomatic participants than in participants with symptoms; these are known to be involved in tissue repair and may be related to the control of symptoms. Overall, we found a serum proteomic signature that differentiates asymptomatic and mild symptomatic infections in young adults, including potential targets for developing new therapies and prognostic tests.
Presently, unmanned aerial vehicles (UAVs) have a broad spectrum of applications, in which regular monitoring of critical infrastructure assets is an important risk mitigation usage. This paper ...presents a novel approach for modeling leakage from natural gas pipelines using machine learning algorithms operating on the gas leakage detection (Methane) data collected using an UAV having a gas sensor and a light detecting and ranging (LiDAR) payload. The detection system has a lightweight design along with a small form factor to ensure compatibility with most autonomous mobile platforms like UAVs or wheeled robots. Two experiments were conducted to collect the gas leakage detection data at various loitering heights in real atmospheric conditions before applying the estimation algorithms. The first experiment measured natural gas leakage data in varying loitering radiuses and altitudes for leakage pressures around one pound per square inch (PSI), while the second experiment did the same for leakage pressures around two PSI. Real atmospheric conditions were incorporated along with additional aspects of propeller down-wash and environmental air movements that can influence leakage detection. Two estimation algorithms, viz., reduced support vector machine (RSVM) and artificial neural network (ANN) were applied to the leakage data collected from the UAV experiments. It was found that the ANN approach resulted in more faster and accurate detection than RSVM that heavily depended on the kernel function for its performance. The efficacy of leakage detection of natural gas using a UAV payload was demonstrated, which is a faster and cost-effective alternative to the manual inspection process.
Curved bridges are commonly used for logistics and emergencies in urban areas such as highway interchange bridges. These types of bridges have complicated dynamic behaviors and also are vulnerable to ...earthquakes, so their functionality is a critical parameter for decision makers. For this purpose, this study aims to evaluate the bridge seismic resilience under the effects of changes in deck radius (50, 100, 150 m, and infinity), pier height irregularity (Regular and Irregular), and incident seismic wave angle (0°, 45°, and 90°) under short- and long-period records. In the first step, fragility curves are calculated based on the incremental dynamic analysis and probabilistic seismic demand models. Finally, seismic resilience curves/surfaces are constructed and their interpolated values of the log-normal distribution function presented for assessing system resilience. It is found that when long-period records are applied in one given direction, the angle of incidence has the most significant effect on seismic resilience, and bridges are most vulnerable when the angle of incidence tends to 0°. The effect of deck radius on seismic resilience became more remarkable as the angle of incidence increased. Additionally, results indicate that the bridge vulnerability in long-period records is more significant than that under short-period records.
Botulinum neurotoxins E (BoNT/E) and A (BoNT/A) act by cleaving Synaptosome-Associated Protein 25 (SNAP25) at two different C-terminal sites, but they display very distinct durations of action, ...BoNT/E being short acting and BoNT/A long acting. We investigated the duration of action, spread and neuronal transport of BoNT/E (6.5 ng/kg) and BoNT/A (125 pg/kg) after single intramuscular administrations of high equivalent efficacious doses, in rats, over a 30- or 75-day periods, respectively. To achieve this, we used (i) digit abduction score assay, (ii) immunohistochemistry for SNAP25 (N-ter part; SNAP25
and C-ter part; SNAP25
) and its cleavage sites (cleaved SNAP25; c-SNAP25
and c-SNAP25
) and (iii) muscular changes in histopathology evaluation. Combined in vivo observation and immunohistochemistry analysis revealed that, compared to BoNT/A, BoNT/E induces minimal muscular changes, possesses a lower duration of action, a reduced ability to spread and a decreased capacity to be transported to the lumbar spinal cord. Interestingly, SNAP25
completely disappeared for both toxins during the peak of efficacy, suggesting that the persistence of toxin effects is driven by the persistence of proteases in tissues. These data unveil some new molecular mechanisms of action of the short-acting BoNT/E and long-acting BoNT/A, and reinforce their overall safety profiles.
AbstractAccurate numerical values of aerodynamic parameters are important in aircraft design. The knowledge of stability and control aerodynamic parameters is essential to postulate high-fidelity ...control laws. The aerodynamic forces and moments are strong functions of the angle of attack (AOA), Reynolds number, and control surface deflections. Typically, conventional estimation techniques such as maximum likelihood (MLE) and least-squares (LS) principles facilitate the determination of these parameters. Unsteady aerodynamics may complicate the estimation of aerodynamic parameters at high AOA. Data-driven techniques employing neural networks provide an alternative for modeling the system behavior based on its observed state and control input variables. Nonlinearity increases because of flow separation at high AOA, which is close to stall. This paper explores the feasibility of employing a machine learning approach using neural networks to predict aircraft dynamics in a limited sense to identify aerodynamic characteristics. Integrating a neural network with the artificial bee colony (ABC) method facilitated the optimization of unknowns of the proposed aerodynamic model (AM). The proposed neural artificial bee colony (NABC) optimization approach estimated the longitudinal dynamics and stall properties for two experimental aircraft. Comparison of the estimates provided by the NABC approach with those of the standard MLE and neural Gauss–Newton (NGN) techniques established its efficacy. Furthermore, robust statistical analysis indicated that the proposed method provides a viable alternative for parameter estimation in nonlinear applications.
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