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Implementation Science Communications Jun 2024Implementation research generally assumes established evidence-based practices and prior piloting of implementation strategies, which may not be feasible during a public...
BACKGROUND
Implementation research generally assumes established evidence-based practices and prior piloting of implementation strategies, which may not be feasible during a public health emergency. We describe the use of a simulation model of the effectiveness of COVID-19 mitigation strategies to inform a stakeholder-engaged process of rapidly designing a tailored intervention and implementation strategy for individuals with serious mental illness (SMI) and intellectual/developmental disabilities (ID/DD) in group homes in a hybrid effectiveness-implementation randomized trial.
METHODS
We used a validated dynamic microsimulation model of COVID-19 transmission and disease in late 2020/early 2021 to determine the most effective strategies to mitigate infections among Massachusetts group home staff and residents. Model inputs were informed by data from stakeholders, public records, and published literature. We assessed different prevention strategies, iterated over time with input from multidisciplinary stakeholders and pandemic evolution, including varying symptom screening, testing frequency, isolation, contact-time, use of personal protective equipment, and vaccination. Model outcomes included new infections in group home residents, new infections in group home staff, and resident hospital days. Sensitivity analyses were performed to account for parameter uncertainty. Results of the simulations informed a stakeholder-engaged process to select components of a tailored best practice intervention and implementation strategy.
RESULTS
The largest projected decrease in infections was with initial vaccination, with minimal benefit for additional routine testing. The initial level of actual vaccination in the group homes was estimated to reduce resident infections by 72.4% and staff infections by 55.9% over the 90-day time horizon. Increasing resident and staff vaccination uptake to a target goal of 90% further decreased resident infections by 45.2% and staff infections by 51.3%. Subsequent simulated removal of masking led to a 6.5% increase in infections among residents and 3.2% among staff. The simulation model results were presented to multidisciplinary stakeholders and policymakers to inform the "Tailored Best Practice" package for the hybrid effectiveness-implementation trial.
CONCLUSIONS
Vaccination and decreasing vaccine hesitancy among staff were predicted to have the greatest impact in mitigating COVID-19 risk in vulnerable populations of group home residents and staff. Simulation modeling was effective in rapidly informing the selection of the prevention and implementation strategy in a hybrid effectiveness-implementation trial. Future implementation may benefit from this approach when rapid deployment is necessary in the absence of data on tailored interventions.
TRIAL REGISTRATION
ClinicalTrials.gov NCT04726371.
PubMed: 38915130
DOI: 10.1186/s43058-024-00593-w -
PLoS Computational Biology Jun 2024Carbohydrates and glycoproteins modulate key biological functions. However, experimental structure determination of sugar polymers is notoriously difficult....
Carbohydrates and glycoproteins modulate key biological functions. However, experimental structure determination of sugar polymers is notoriously difficult. Computational approaches can aid in carbohydrate structure prediction, structure determination, and design. In this work, we developed a glycan-modeling algorithm, GlycanTreeModeler, that computationally builds glycans layer-by-layer, using adaptive kernel density estimates (KDE) of common glycan conformations derived from data in the Protein Data Bank (PDB) and from quantum mechanics (QM) calculations. GlycanTreeModeler was benchmarked on a test set of glycan structures of varying lengths, or "trees". Structures predicted by GlycanTreeModeler agreed with native structures at high accuracy for both de novo modeling and experimental density-guided building. We employed these tools to design de novo glycan trees into a protein nanoparticle vaccine to shield regions of the scaffold from antibody recognition, and experimentally verified shielding. This work will inform glycoprotein model prediction, glycan masking, and further aid computational methods in experimental structure determination and refinement.
PubMed: 38913746
DOI: 10.1371/journal.pcbi.1011895 -
Medical Research Archives May 2024Respiratory fluid dynamics is integral to comprehending the transmission of infectious diseases and the effectiveness of interventions such as face masks and social...
On the efficacy of facial masks to suppress the spreading of pathogen-carrying saliva particles during human respiratory events: Insights gained via high-fidelity numerical modeling.
Respiratory fluid dynamics is integral to comprehending the transmission of infectious diseases and the effectiveness of interventions such as face masks and social distancing. In this research, we present our recent studies that investigate respiratory particle transport via high-fidelity large eddy simulation coupled with the Lagrangian particle tracking method. Based on our numerical simulation results for human respiratory events with and without face masks, we demonstrate that facial masks could significantly suppress particle spreading. The studied respiratory events include coughing and normal breathing through mouth and nose. Using the Lagrangian particle tracking simulation results, we elucidated the transport pathways of saliva particles during inhalation and exhalation of breathing cycles, contributing to our understanding of respiratory physiology and potential disease transmission routes. Our findings underscore the importance of respiratory fluid dynamics research in informing public health strategies to reduce the spread of respiratory infections. Combining advanced mathematical modeling techniques with experimental data will help future research on airborne disease transmission dynamics and the effectiveness of preventive measures such as face masks.
PubMed: 38911991
DOI: 10.18103/mra.v12i5.5441 -
Diabetes, Metabolic Syndrome and... 2024The prevalence of obesity continues to rise. People with obesity are at increased risk of several diseases. We tested an algorithm-based screening program for people...
PURPOSE
The prevalence of obesity continues to rise. People with obesity are at increased risk of several diseases. We tested an algorithm-based screening program for people with a BMI above 30 kg/m and present data on the prevalence of previously undiagnosed obesity-related diseases.
PATIENTS AND METHODS
Seven hundred and sixty-nine persons with BMI > 30 kg/m and age 18-60 years were screened for diabetes (assessed by glycosylated hemoglobin and oral glucose tolerance test at HbA1c 43-48 mmol/mol), sleep apnea (screened by questionnaires and assessed by cardiorespiratory monitoring at indication of sleep disorder), liver steatosis or liver fibrosis (assessed by biochemistry and fibroscan) and arterial hypertension (assessed by both office and 24-hour blood pressure measurement). A reference group of people with a BMI of 18.5-29.9 kg/m was established.
RESULTS
Of those referred, 73.0% were women. We identified new diabetes in 4.2%, prediabetes in 9.1%, moderate-to-severe sleep apnea in 25.1%, increased liver fat and increased liver stiffness in 68.1% and 17.4%, respectively, and hypertension or masked hypertension in 19.0%. The prevalence of diseases was much higher among men and increased with BMI. Except for hypertension, we found few participants with undiagnosed disease in the reference group.
CONCLUSION
An algorithm-based screening program is feasible and reveals undiagnosed obesity-related disease in a large proportion of the participants. The disproportional referral pattern calls for a tailored approach aiming to include more men with obesity.
TRIAL REGISTRATION
Inclusion of the non-obese group was approved by the Scientific Ethics Committee of The Region of Southern Denmark (project identification number: S-20210091), and the study was reported at clinicaltrials.gov (NCT05176132).
PubMed: 38910914
DOI: 10.2147/DMSO.S456028 -
The International Journal on Drug Policy Jun 2024Within Manitoba and Saskatchewan, pre-existing health inequities amongst Indigenous groups were intensified during the COVID-19 pandemic. Service disruptions in the...
BACKGROUND
Within Manitoba and Saskatchewan, pre-existing health inequities amongst Indigenous groups were intensified during the COVID-19 pandemic. Service disruptions in the health and social service sector-combined with the effects of intersectional stigma-disproportionately impacted Indigenous peoples living with HIV (IPLH). IPLH experience structural violence and necropolitical exclusion through systemic forms of stigma situated within Canada's expansive colonial history. Utilizing the theoretical foundations of structural violence and necropolitics, this qualitative study examines how the COVID-19 pandemic amplified preceding states of inequity for IPLH.
METHODS
Semi-structured interviews were conducted with 60 participants. The sample comprised of those with lived experience (n = 45) as well as those who provided services for IPLH (n = 15). Indigenous Storywork guided the data collection and analysis process. Topics explored within each interview included access to health and social services, harm reduction, substance use, and experiences in providing services during COVID-19 pandemic. Thematic analysis was used to identify common themes throughout each story.
RESULTS
Our results indicate that the COVID-19 pandemic exposed and amplified pre-existing forms of structural violence and necropolitical logics for IPLH within Manitoba and Saskatchewan. Specifically, we describe how structural violence and necropolitics are manifested via three main avenues- (i) restrictions and removal of care, (ii) bureaucracy and institutional care politics, and (iii) discrimination and systemic racism within the Canadian healthcare system.
CONCLUSION
The COVID-19 pandemic within Manitoba and Saskatchewan sparked massive changes in service provision within settler-colonial and neoliberal institutions of care. For those services that remained open to IPLH, masking requirements, questionnaire requirements, scheduling requirements, and a lack of in-person services acted as only some of the barriers described by community members as detrimental to care access. Increased experiences of discrimination in health care on the basis of substance use or HIV status further limited access to needed services.
PubMed: 38905942
DOI: 10.1016/j.drugpo.2024.104503 -
PLOS Global Public Health 2024Community Health Workers (CHWs) are a key human resource for health particularly in low- and middle-income countries. In many parts of the world, CHWs are known to have...
Community Health Workers (CHWs) are a key human resource for health particularly in low- and middle-income countries. In many parts of the world, CHWs are known to have played an instrumental role in controlling the COVID-19 pandemic. This study explored the involvement of CHWs in the COVID-19 response in Uganda. A qualitative study that involved 10 focus group discussions (FGDs) among CHWs was conducted. The study was carried out in 5 districts of Amuria, Karenga, Kamwenge, Bugiri and Pader. The FGD guide used explored the role of CHWs in the COVID-19 response in their communities including lived experiences, challenges, and coping mechanisms. The data were analyzed thematically with the support of NVivo version 12 pro (QSR International). CHWs were at the frontline of COVID-19 prevention interventions at households and in the community. CHWs raised awareness on prevention measures including wearing face masks, hand hygiene, and social distancing. They identified suspected cases such as new members entering the community, as well as individuals returning from abroad with signs and symptoms of COVID-19. CHWs mobilized the community and increased awareness on COVID-19 vaccination which played an important role in reducing misinformation. They also supported home-based management of mild COVID-19 cases through isolation of patients; provided health and nutritional guidance among patients in their homes; and referred suspected cases to health facilities for testing and management. Both monetary and non-monetary incentives were provided to support CHWs in the COVID-19 response. However, the adequacy and timing of the incentives were inadequate. Routine services of CHWs such as health promotion and treatment of childhood illnesses were disrupted during the pandemic. CHWs played an instrumental role in response to the pandemic especially on surveillance, risk communication, and observance of preventing measures. Strategies to ensure that routine services of CHWs are not disrupted during pandemics are needed.
PubMed: 38905244
DOI: 10.1371/journal.pgph.0003312 -
Frontiers in Psychiatry 2024COVID-19 necessitated a rapid move from face-to-face services to remote care for eating disorders/eating distress (EDs). This study explores the advantages and...
INTRODUCTION
COVID-19 necessitated a rapid move from face-to-face services to remote care for eating disorders/eating distress (EDs). This study explores the advantages and challenges of remote care, identifying future implications for service provision. Remote care has been considered in the broadest of terms, including therapeutic care (e.g., Cognitive Behavioural Therapy, peer support, forums, one-to-one and group care options).
METHODS
Using a mixed methods approach, data were collected from 211 people with lived experience of EDs (PWLE), with and without formal diagnosis. 27 participants took part in semi-structured interviews/workshops and a further 184 participants took part via an online survey. Participants reported on their ED status, the impact of the pandemic on symptoms, the benefits, and challenges of remote care (and type of support accessed), and any reasons for not accessing support. Participants were invited to make future care recommendations.
RESULTS
ED symptoms were reported as worsening during the pandemic with contributing factors including isolation, lack of routine, negative emotions, and feeling like the external situation was outside of one's control. Remote care was positively attributed to increased flexibility and facilitation of social connection. Identified barriers to access included lack of awareness about support availability, digital access/literacy, and competing commitments. Further challenges included approaches being perceived as too clinical (e.g., ED information and support presented using clinical language and/or limited to support within medical care settings, without acknowledging the broader context of disordered eating), uncertainty around remote care quality, and concerns that remote platforms may facilitate masking of symptoms. Participants reported distress caused by online platforms where self-view is the default during video calls. They expressed a need for more holistic approaches to remote care, including: "real stories" of recovery, and hybrid (online and offline) options for greater flexibility and widening of access and choice. Participants also expressed a need for appropriate digital literacy training.
DISCUSSION
Future recommendations emphasise user-centred holistic and hybrid approaches to ED remote support, with training to address digital literacy barriers and facilitate user control of platform functionalities (e.g., self-view). This study underscores the need for continued remote care with a focus on inclusivity and user empowerment.
PubMed: 38903648
DOI: 10.3389/fpsyt.2024.1383080 -
Frontiers in Sociology 2024In September 2021 I made a collection of interview transcripts available for public use under a CreativeCommons license through the Princeton DataSpace. The interviews...
In September 2021 I made a collection of interview transcripts available for public use under a CreativeCommons license through the Princeton DataSpace. The interviews include 39 conversations I had with gig workers at AmazonFlex, Uber, and Lyft in 2019 as part of a study on automation efforts within these organizations. I made this decision because (1) I was required to contribute to a publicly available data set as a requirement of my funding and (2) I saw it as an opportunity to engage in the collaborative qualitative science experiments emerging in Science and Technology studies. This article documents my thought process and step-by-step design decisions for designing a study, gathering data, masking it, and publishing it in a public archive. Importantly, once I decided to publish these data, I determined that each choice about how the study would be designed and implemented had to be assessed for risk to the interviewee in a very deliberate way. It is not meant to be comprehensive and cover every possible condition a researcher may face while producing qualitative data. I aimed to be transparent both in my interview data and the process it took to gather and publish these data. I use this article to illustrate my thought process as I made each design decision for this study in hopes that it could be useful to a future researcher considering their own data publishing process.
PubMed: 38903395
DOI: 10.3389/fsoc.2024.1157514 -
Scientific Reports Jun 2024As interest in using machine learning models to support clinical decision-making increases, explainability is an unequivocal priority for clinicians, researchers and...
As interest in using machine learning models to support clinical decision-making increases, explainability is an unequivocal priority for clinicians, researchers and regulators to comprehend and trust their results. With many clinical datasets containing a range of modalities, from the free-text of clinician notes to structured tabular data entries, there is a need for frameworks capable of providing comprehensive explanation values across diverse modalities. Here, we present a multimodal masking framework to extend the reach of SHapley Additive exPlanations (SHAP) to text and tabular datasets to identify risk factors for companion animal mortality in first-opinion veterinary electronic health records (EHRs) from across the United Kingdom. The framework is designed to treat each modality consistently, ensuring uniform and consistent treatment of features and thereby fostering predictability in unimodal and multimodal contexts. We present five multimodality approaches, with the best-performing method utilising PetBERT, a language model pre-trained on a veterinary dataset. Utilising our framework, we shed light for the first time on the reasons each model makes its decision and identify the inclination of PetBERT towards a more pronounced engagement with free-text narratives compared to BERT-base's predominant emphasis on tabular data. The investigation also explores the important features on a more granular level, identifying distinct words and phrases that substantially influenced an animal's life status prediction. PetBERT showcased a heightened ability to grasp phrases associated with veterinary clinical nomenclature, signalling the productivity of additional pre-training of language models.
Topics: Animals; Pets; Electronic Health Records; Machine Learning; United Kingdom; Risk Factors; Cats; Dogs
PubMed: 38902282
DOI: 10.1038/s41598-024-64551-1 -
NPJ Biofilms and Microbiomes Jun 2024During the COVID-19 pandemic, facemasks played a pivotal role in preventing person-person droplet transmission of viral particles. However, prolonged facemask wearing...
During the COVID-19 pandemic, facemasks played a pivotal role in preventing person-person droplet transmission of viral particles. However, prolonged facemask wearing causes skin irritations colloquially referred to as 'maskne' (mask + acne), which manifests as acne and contact dermatitis and is mostly caused by pathogenic skin microbes. Previous studies revealed that the putative causal microbes were anaerobic bacteria, but the pathogenesis of facemask-associated skin conditions remains poorly defined. We therefore characterized the role of the facemask-associated skin microbiota in the development of maskne using culture-dependent and -independent methodologies. Metagenomic analysis revealed that the majority of the facemask microbiota were anaerobic bacteria that originated from the skin rather than saliva. Previous work demonstrated direct interaction between pathogenic bacteria and antagonistic strains in the microbiome. We expanded this analysis to include indirect interaction between pathogenic bacteria and other indigenous bacteria classified as either 'pathogen helper (PH)' or 'pathogen inhibitor (PIn)' strains. In vitro screening of bacteria isolated from facemasks identified both strains that antagonized and promoted pathogen growth. These data were validated using a mouse skin infection model, where we observed attenuation of symptoms following pathogen infection. Moreover, the inhibitor of pathogen helper (IPH) strain, which did not directly attenuate pathogen growth in vitro and in vivo, functioned to suppress symptom development and pathogen growth indirectly through PH inhibitory antibacterial products such as phenyl lactic acid. Taken together, our study is the first to define a mechanism by which indirect microbiota interactions under facemasks can control symptoms of maskne by suppressing a skin pathogen.
Topics: Animals; Mice; Masks; Microbiota; Humans; COVID-19; Skin; Acne Vulgaris; SARS-CoV-2; Female; Metagenomics; Disease Models, Animal; Bacteria; Microbial Interactions; Dermatitis, Contact
PubMed: 38902263
DOI: 10.1038/s41522-024-00512-w