Influence of Digital Intervention Messaging on Influenza Vaccination Rates Among Adults With Cardiovascular Disease in the United States: Decentralized Randomized Controlled Trial

BACKGROUND

Seasonal influenza affects 5% to 15% of Americans annually, resulting in preventable deaths and substantial economic impact. Influenza infection is particularly dangerous for people with cardiovascular disease, who therefore represent a priority group for vaccination campaigns.

OBJECTIVE

We aimed to assess the effects of digital intervention messaging on self-reported rates of seasonal influenza vaccination.

METHODS

This was a randomized, controlled, single-blind, and decentralized trial conducted at individual locations throughout the United States over the 2020-2021 influenza season. Adults with self-reported cardiovascular disease who were members of the Achievement mobile platform were randomized to receive or not receive a series of 6 patient-centered digital intervention messages promoting influenza vaccination. The primary end point was the between-group difference in self-reported vaccination rates at 6 months after randomization. Secondary outcomes included the levels of engagement with the messages and the relationship between vaccination rates and engagement with the messages. Subgroup analyses examined variation in intervention effects by race. Controlling for randomization group, we examined the impact of other predictors of vaccination status, including cardiovascular condition type, vaccine drivers or barriers, and vaccine knowledge.

RESULTS

Of the 49,138 randomized participants, responses on the primary end point were available for 11,237 (22.87%; 5575 in the intervention group and 5662 in the control group) participants. The vaccination rate was significantly higher in the intervention group (3418/5575, 61.31%) than the control group (3355/5662, 59.25%; relative risk 1.03, 95% CI 1.004-1.066; P=.03). Participants who were older, more educated, and White or Asian were more likely to report being vaccinated. The intervention was effective among White participants (P=.004) but not among people of color (P=.42). The vaccination rate was 13 percentage points higher among participants who completed all 6 intervention messages versus none, and at least 2 completed messages appeared to be needed for effectiveness. Participants who reported a diagnosis of COVID-19 were more likely to be vaccinated for influenza regardless of treatment assignment.

CONCLUSIONS

This personalized, evidence-based digital intervention was effective in increasing vaccination rates in this population of high-risk people with cardiovascular disease.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04584645; https://clinicaltrials.gov/ct2/show/NCT04584645.

A novel household-based patient outreach pilot program to boost late-season influenza vaccination rates during the COVID-19 pandemic

Background

The objective of this study was to test a novel household‐based approach to improve late‐season influenza vaccine uptake during the 2020–2021 season, using Epic's MyChart patient portal messages and/or interactive voice response telephone calls.

Methods

This study was a non‐blinded, quality improvement program using a block randomized design conducted among patients from Reliant Medical Group clinics residing in a traditional household (≥2 individuals clinically active in the Reliant system living at the same address). Households were randomized 1:1:1 into intervention arms: non‐tailored communication (messaging based on CDC's seasonal influenza vaccination campaign), tailored communication (comprehensive communication including reinforcement of the importance of influenza vaccination for high‐risk individuals), and standard‐of‐care control. Influenza vaccination during the program was captured via medical records, and the odds of vaccination among communication arms versus the control arm were assessed. A survey assessing influenza vaccination drivers was administered using MyChart.

Results

Influenza vaccination increased by 3.3% during the program period, and no significant differences in vaccination were observed in intervention arms relative to the control arm. Study operationalization faced substantial challenges related to the concurrent COVID‐19 pandemic. Compared with vaccinated survey respondents, unvaccinated respondents less frequently reported receiving a recommendation for influenza vaccination from their healthcare provider (15.8% vs. 42.3%, p < 0.001) or awareness that vaccination could protect themselves and higher risk contacts (82.3% vs. 92.6%, p < 0.001).

Conclusions

No significant effects of the interventions were observed. Survey results highlighted the importance of healthcare provider recommendations and the need for increased education around the benefits of vaccination.

SARS-CoV-2 rapid antigen screening of asymptomatic employees: a pilot project

SETTING

Rapid antigen screening can be effective in identifying infectious individuals in occupational settings to reduce transmission and outbreaks. We report results from a pilot project at the Greater Toronto Airports Authority (GTAA) and describe the operationalization. Toronto Pearson is a large international airport encompassing over 400 employers and, pre-pandemic, with approximately 50,000 employees.

INTERVENTION

An employee screening program was piloted between March 8 and May 28, 2021, to implement rapid antigen testing for asymptomatic employees. Recruitment targeted enrolment of 400 employees and yielded participation of 717 from 58 companies. Employees were recommended to book three times per week for nasal swabs on site, and were tested on the Abbot Panbio^TM rapid antigen test. No action was taken from a negative result, and if positive, the employee was told to isolate at home and obtain a confirmatory polymerase chain reaction test.

OUTCOMES

A total of 5117 tests were performed on 717 individuals over 12 weeks; 5091 tests were negative (99.5%), and 22 individuals tested positive (3.1% positivity rate). One hundred twenty-four (17%) completed the post-participation survey. All respondents reported that testing did not change their behaviour at work with respect to public health recommendations, and only 1 (1%) reported behaviour change outside of work (socializing with family) as a result of the program.

IMPLICATIONS

This pilot program identified 22 (3.1%) potentially infectious employees. Onsite testing was feasible and highly accepted by this group of employees who completed the survey. Education resulted in reasonable uptake and no substantial change in behaviour, although the survey response rate may limit generalizability. Home-based testing may facilitate larger recruitment.

Abstract P1059: Establishing The Mechanistic Basis Of Dilated Cardiomyopathy Associated With The Skeletal Muscle Actin Mutation R256H

Actin, which is expressed in all eukaryotic cells, is an essential component of the cardiac and skeletal muscle sarcomere thin filament. Mutations in actin have been associated with a wide range of diseases, including skeletal myopathies and cardiomyopathies. Humans express six actin isoforms with two that are thought to be highly enriched in sarcomeres and differ by only four amino acids: skeletal muscle actin (ACTA1) and cardiac actin (ACTC1). While ACTC1 is exclusively expressed in the adult heart, ACTA1 is predominantly expressed in skeletal muscle with lower levels detected in cardiac muscle. As such, ACTA1 mutations are well known to cause skeletal myopathy with minimal effects on cardiac function. However, I previously reported a family carrying a novel heterozygous mutation in ACTA1 (ACTA1 R256H) with dilated cardiomyopathy (DCM) and no clinical evidence of skeletal myopathy. The objective of this study is to elucidate the molecular mechanism(s) by which ACTA1 R256H may cause heart failure. I generated ACTA1 R256H/+ human pluripotent stem cells (hPSCs) using Cas9/CRISPR gene editing. Using traction force microscopy, I observed that ACTA1 R256H/+ hPSC-derived cardiomyocytes display reduced contractility. To define relevant mechanisms, I devised a novel approach to purify milligram quantities of recombinant human ACTA1, which has served as a remarkable challenge for the field. Importantly, this purification technique circumvents contamination from endogenous actins and produces functional protein capable of polymerization. Moreover, in vitro motility assays demonstrated that reconstituted human thin filaments containing recombinant ACTA1 are functional and activated in a calcium-regulated manner. Intriguingly, purified ACTA1 R256H appears to have a polymerization defect, suggesting a possible mechanism by which this mutation leads to a defect in contractility. Together, these studies suggest for the first time that a mutation in skeletal muscle actin, ACTA1 R256H, causes cardiomyocyte hypocontractility while also suggesting a potential molecular mechanism. Finally, this study also introduces a new purification method essential for biochemical and biophysical analysis of human ACTA1 mutations.

Predictive modeling of Pseudomonas syringae virulence on bean using gradient boosted decision trees

Pseudomonas syringae is a genetically diverse bacterial species complex responsible for numerous agronomically important crop diseases. Individual P. syringae isolates are assigned pathovar designations based on their host of isolation and the associated disease symptoms, and these pathovar designations are often assumed to reflect host specificity although this assumption has rarely been rigorously tested. Here we developed a rapid seed infection assay to measure the virulence of 121 diverse P. syringae isolates on common bean (Phaseolus vulgaris). This collection includes P. syringae phylogroup 2 (PG2) bean isolates (pathovar syringae) that cause bacterial spot disease and P. syringae phylogroup 3 (PG3) bean isolates (pathovar phaseolicola) that cause the more serious halo blight disease. We found that bean isolates in general were significantly more virulent on bean than non-bean isolates and observed no significant virulence difference between the PG2 and PG3 bean isolates. However, when we compared virulence within PGs we found that PG3 bean isolates were significantly more virulent than PG3 non-bean isolates, while there was no significant difference in virulence between PG2 bean and non-bean isolates. These results indicate that PG3 strains have a higher level of host specificity than PG2 strains. We then used gradient boosting machine learning to predict each strain’s virulence on bean based on whole genome k-mers, type III secreted effector k-mers, and the presence/absence of type III effectors and phytotoxins. Our model performed best using whole genome data and was able to predict virulence with high accuracy (mean absolute error = 0.05). Finally, we functionally validated the model by predicting virulence for 16 strains and found that 15 (94%) had virulence levels within the bounds of estimated predictions. This study strengthens the hypothesis that P. syringae PG2 strains have evolved a different lifestyle than other P. syringae strains as reflected in their lower level of host specificity. It also acts as a proof-of-principle to demonstrate the power of machine learning for predicting host specific adaptation.

Pseudomonas syringae is a genetically diverse Gammaproteobacterial species complex responsible for numerous agronomically important crop diseases. Strains in the P. syringae species complex are frequently categorized into pathovars depending on pathogenic characteristics such as host of isolation and disease symptoms. Common bean pathogens from P. syringae are known to cause two major diseases: (1) pathovar phaseolicola strains from phylogroup 3 cause halo blight disease, characterized by large necrotic lesions surrounded by a chlorotic zone or halo of yellow tissue; and (2) pathovar syringae strains from phylogroup 2 causes bacterial spot disease, characterized by brown leaf spots. While halo blight can cause serious crop losses, bacterial spot disease is generally of minor agronomic concern. Recently, statistical genetic and machine learning approaches have been applied to genomic data to identify genes underlying traits of interest or predict the outcome of host-microbe interactions. Here, we apply machine learning to P. syringae genomic data to predict virulence on bean. We first characterized the virulence of P. syringae isolates on common bean using a seed infection assay and then applied machine learning to the genomic data from the same strains to generate a predictive model for virulence on bean. We found that machine learning models built with k-mers from either full genome data or virulence factors could predict bean virulence with high accuracy. We also confirmed prior work showing that phylogroup 3 halo blight pathogens display a stronger degree of phylogenetic clustering and host specificity compared to phylogroup 2 brown spot pathogens. This works serves as a proof-of-principle for the power of machine learning for predicting host specificity and may find utility in agricultural diagnostic microbiology.

Neuropathology of Pediatric SARS-CoV-2 Infection in the Forensic Setting: Novel Application of Ex Vivo Imaging in Analysis of Brain Microvasculature

Two years into the COVID-19 pandemic, there are few published accounts of postmortem SARS-CoV-2 pathology in children. We report 8 such cases (4 infants aged 7–36 weeks, 4 children aged 5–15 years). Four underwent ex vivo magnetic resonance neuroimaging, to assist in identification of subtle lesions related to vascular compromise. All infants were found unresponsive (3 in unsafe sleeping conditions); all but 1 had recent rhinitis and/or influenza-like illness (ILI) in the family; 1 had history of sickle cell disease. Ex vivo neuroimaging in 1 case revealed white matter (WM) signal hyperintensity and diffuse exaggeration of perivascular spaces, corresponding microscopically to WM mineralization. Neurohistology in the remaining 3 infants variably encompassed WM gliosis and mineralization; brainstem gliosis; perivascular vacuolization; perivascular lymphocytes and brainstem microglia. One had ectopic hippocampal neurons (with pathogenic variant in DEPDC5). Among the children, 3 had underlying conditions (e.g., obesity, metabolic disease, autism) and all presented with ILI. Three had laboratory testing suggesting multisystem inflammatory syndrome (MIS-C). Two were hospitalized for critical care including mechanical ventilation and extracorporeal membrane oxygenation (ECMO); one (co-infected with adenovirus) developed right carotid stroke ipsilateral to the ECMO cannula and the other required surgery for an ingested foreign body. Autopsy findings included: acute lung injury in 3 (1 with microthrombi); and one each with diabetic ketoacidosis and cardiac hypertrophy; coronary and cerebral arteritis and aortitis, resembling Kawasaki disease; and neuronal storage and enlarged fatty liver. All 4 children had subtle meningoencephalitis, focally involving the brainstem. On ex vivo neuroimaging, 1 had focal pontine susceptibility with corresponding perivascular inflammation/expanded perivascular spaces on histopathology. Results suggest SARS-CoV-2 in infants may present as sudden unexpected infant death, while in older children, signs and symptoms point to severe disease. Underlying conditions may predispose to fatal outcomes. As in adults, the neuropathologic changes may be subtle, with vascular changes such as perivascular vacuolization and gliosis alongside sparse perivascular lymphocytes. Detection of subtle vascular pathology is enhanced by ex vivo neuroimaging. Additional analysis of the peripheral/autonomic nervous system and investigation of co-infection in children with COVID-19 is necessary to understand risk for cardiovascular collapse/sudden death.

Combining ecological, eco-cultural, and environmental justice parameters to create Eco-EJ indicators to monitor cultural and environmental justices for diverse communities around contaminated sites

Assessing environmental quality often requires selection of indicators that can be employed over large spatial scales and over long-time periods to assess the health and well-being of species, natural communities, and ecosystems, and to detect changes warranting intervention. Typically, the ecologic environment and the human environment are evaluated separately and selection of indicators and monitoring approaches are not integrated even though ecological indicators may also provide information on risk to human consumers from contaminants (e.g., eco-cultural indicators) or because of disease levels. This paper is a call for ecologists and managers to consider diverse cultural and environmental injustice disparities and health issues when selecting indicators for environmental assessment and monitoring. There is an opportunity for managers and community members to work together to preserve ecological and cultural resources and heritages. We propose a paradigm that selects indicators and monitoring approaches that lend themselves to the integration of human-diversity and uniqueness in the same manner that the selection of ecological indicators and monitoring approaches consider biological species diversity and uniqueness. The proposed paradigm builds on ecological risk assessment techniques, developing analogous endpoints for neighboring communities. For example, identification and protection of human communities, particularly culturally diverse and environmental justice communities, identification of contaminant corridors (e.g., through water or green corridors) into communities, and eco-monitoring of vulnerable communities are not routine at contaminated sites. Green corridors refers to a width of wild habitat (forest, grasslands) that connects other similar habitat paths (usually a corridor runs through an urban or suburban habitat). We coin the term Eco-EJ indicators for these endpoints, including examination of (1) unique cultural relationships to resources; (2) connectedness of on-site and off-site resources and habitats; (3) health of threatened, rare, and unique cultures and communities; and (4) linkages between ecological, eco-cultural, and public health for monitoring and assessment. We also propose that assessment and monitoring include these Eco-EJ indicators, especially for communities near facilities that have extensive chemical or radiological contamination.Developing these indicators to assess risk to culturally diverse and environmental justice communities would be an equivalent goal to reducing risk for significant ecological resources (e.g., endangered species, species of special concern). These Eco-EJ indicators are complementary to the usual human health-risk assessments, would include surveys of neighboring vulnerable communities, and require time and re-organization of current data and additional data collection at site boundaries and in adjacent communities, as well as rethinking the human component of indicators. This approach lends itself to addressing some diverse cultural and environmental justice issues with current indicator selection and biomonitoring, and helps identify specific hotspots of unique ecosystem risk and environmental justice community risk. We briefly discuss ecological and eco-cultural monitoring already on-going at three Department of Energy sites to illustrate how the addition of these indicators might work and add value to environmental management and to their relationships with surrounding communities. We recommend that managers of contaminated sites convene people from culturally diverse communities, environmental justice communities, local and federal government, Tribes, resource trustees, managers, and other stakeholders to develop appropriate site-specific indicators to address environmental inequities around contaminated facilities.

Plutonium Disposition: Using and Explaining Complex Risk-Related Methods

Applying risk assessment and management tools to plutonium disposition is a long-standing challenge for the U.S. government. The science is complicated, which has helped push risk assessment and management tools in new creative directions. Yet, communicating effectively about increasingly complicated risk-science issues like plutonium disposition requires careful planning and speakers who can address why specific tools are selected, the past record of applying these tools, why assumptions sometimes are applied instead of reliable data, and how uncertainty is characterized. Speakers addressing risk issues must also overcome obstacles in communication arising from expert-audience differences in knowledge and legal restrictions on disclosing information. This perspective seeks to highlight and illustrate five key risk questions, about probabilistic risk assessment (PRA) and performance assessment (PA) in the context of managing plutonium defense nuclear waste: objectives, experience, gaps, transparency, and difficulty of applying and communicating using each tool. While the general public needs to be involved, some issues require a level of expertise that is typically beyond local communities and therefore an expert panel should support community access.

Digital intervention increases influenza vaccination rates for people with diabetes in a decentralized randomized trial

People with diabetes (PWD) have an increased risk of developing influenza-related complications, including pneumonia, abnormal glycemic events, and hospitalization. Annual influenza vaccination is recommended for PWD, but vaccination rates are suboptimal. The study aimed to increase influenza vaccination rate in people with self-reported diabetes. This study was a prospective, 1:1 randomized controlled trial of a 6-month Digital Diabetes Intervention in U.S. adults with diabetes. The intervention group received monthly messages through an online health platform. The control group received no intervention. Difference in self-reported vaccination rates was tested using multivariable logistic regression controlling for demographics and comorbidities. The study was registered at clinicaltrials.gov: NCT03870997. A total of 10,429 participants reported influenza vaccination status (5158 intervention, mean age (±SD) = 46.8 (11.1), 78.5% female; 5271 control, Mean age (±SD) = 46.7 (11.2), 79.4% female). After a 6-month intervention, 64.2% of the intervention arm reported influenza vaccination, vers us 61.1% in the control arm (diff = 3.1, RR = 1.05, 95% CI [1.02, 1.08], p = 0.0013, number needed to treat = 33 to obtain 1 additional vaccination). Completion of one or more intervention messages was associated with up to an 8% increase in vaccination rate (OR 1.27, 95% CI [1.17, 1.38], p < 0.0001). The intervention improved influenza vaccination rates in PWD, suggesting that leveraging new technology to deliver knowledge and information can improve influenza vaccination rates in high-risk populations to reduce public health burden of influenza. Rapid cycle innovation could maximize the effects of these digital interventions in the future with other populations and vaccines.

Resident cardiac macrophages mediate adaptive myocardial remodeling

Cardiac macrophages represent a heterogeneous cell population with distinct origins, dynamics, and functions. Recent studies have revealed that C-C Chemokine Receptor 2 positive (CCR2+) macrophages derived from infiltrating monocytes regulate myocardial inflammation and heart failure pathogenesis. Comparatively little is known about the functions of tissue resident (CCR2-) macrophages. Herein, we identified an essential role for CCR2- macrophages in the chronically failing heart. Depletion of CCR2- macrophages in mice with dilated cardiomyopathy accelerated mortality and impaired ventricular remodeling and coronary angiogenesis, adaptive changes necessary to maintain cardiac output in the setting of reduced cardiac contractility. Mechanistically, CCR2- macrophages interacted with neighboring cardiomyocytes via focal adhesion complexes and were activated in response to mechanical stretch through a transient receptor potential vanilloid 4 (TRPV4)-dependent pathway that controlled growth factor expression. These findings establish a role for tissue-resident macrophages in adaptive cardiac remodeling and implicate mechanical sensing in cardiac macrophage activation.