The Impact of Community Engagement in the Design and Implementation of the Flint Registry.

BACKGROUND: The Flint water crisis (FWC) was a public health tragedy caused by crumbling infrastructure, subverted democracy, and indifference toward a predominantly poor and Black community that resulted in lead-in-water exposure, Legionnaires' disease, and emotional and health-related trauma. Through the cooperation of community partners, the Flint Registry (FR) was conceived to track long-term health and improve public health via service connections. OBJECTIVES: This study sought to share the FR's community-partnered, multi-tiered engagement strategy and determine the efficacy of this strategy to engage the community and reach Flint residents. METHODS: Community engagement and impact were measured by collecting and describing feedback from the community engagement strategies and by comparing the demographics of the enrollees recruited through community-engaged recruitment (CER) and non-CER methods. Enroll-ees indicated how they heard about the FR; CER involved direct interaction with a community member. RESULTS: Community engagement strategies incorporated approximately 1,200 people and 7 funded organizations, impacting 22 key areas of FR design and implementation. More than 50% of enrollees heard about the FR through CER methods. They were, on average, more likely to be younger, female, Black/African American, and living outside of Flint during the FWC. CONCLUSIONS: Community engagement elevated voices of those impacted by the FWC. CER methods were as effective as non-CER methods. Although there were no differences in screened measures of social vulnerability, there were in age, gender, and race. CER methods may increase participation and build trust in populations which historically are hesitant to participate in public health efforts.

Estimating the potential value of MSM-focused evidence-based implementation interventions in three Ending the HIV Epidemic jurisdictions in the United States: a model-based analysis.

INTRODUCTION: Improving the delivery of existing evidence-based interventions to prevent and diagnose HIV is key to Ending the HIV Epidemic in the United States. Structural barriers in the access and delivery of related health services require municipal or state-level policy changes; however, suboptimal implementation can be addressed directly through interventions designed to improve the reach, effectiveness, adoption or maintenance of available interventions. Our objective was to estimate the cost-effectiveness and potential epidemiological impact of six real-world implementation interventions designed to address these barriers and increase the scale of delivery of interventions for HIV testing and pre-exposure prophylaxis (PrEP) in three US metropolitan areas. METHODS: We used a dynamic HIV transmission model calibrated to replicate HIV microepidemics in Atlanta, Los Angeles (LA) and Miami. We identified six implementation interventions designed to improve HIV testing uptake ("Academic detailing for HIV testing," "CyBER/testing," "All About Me") and PrEP uptake/persistence ("Project SLIP," "PrEPmate," "PrEP patient navigation"). Our comparator scenario reflected a scale-up of interventions with no additional efforts to mitigate implementation and structural barriers. We accounted for potential heterogeneity in population-level effectiveness across jurisdictions. We sustained implementation interventions over a 10-year period and evaluated HIV acquisitions averted, costs, quality-adjusted life years and incremental cost-effectiveness ratios over a 20-year time horizon (2023-2042). RESULTS: Across jurisdictions, implementation interventions to improve the scale of HIV testing were most cost-effective in Atlanta and LA (CyBER/testing cost-saving and All About Me cost-effective), while interventions for PrEP were most cost-effective in Miami (two of three were cost-saving). We estimated that the most impactful HIV testing intervention, CyBER/testing, was projected to avert 111 (95% credible interval: 110-111), 230 (228-233) and 101 (101-103) acquisitions over 20 years in Atlanta, LA and Miami, respectively. The most impactful implementation intervention to improve PrEP engagement, PrEPmate, averted an estimated 936 (929-943), 860 (853-867) and 2152 (2127-2178) acquisitions over 20 years, in Atlanta, LA and Miami, respectively. CONCLUSIONS: Our results highlight the potential impact of interventions to enhance the implementation of existing evidence-based interventions for the prevention and diagnosis of HIV.

Methodologies for the collection of parameters to estimate dust/soil ingestion for young children.

Background: Heavy metals, pesticides and a host of contaminants found in dust and soil pose a health risk to young children through ingestion. Dust/soil ingestion rates for young children can be estimated using micro-level activity time series (MLATS) as model inputs. MLATS allow for the generation of frequency and duration of children's contact activities, along with sequential contact patterns. Models using MLATS consider contact types, and transfer dynamics to assign mechanisms of contact and appropriate exposure factors for cumulative estimates of ingestion rates. Objective: The objective of this study is to describe field implementation, data needs, advanced field collection, laboratory methodologies, and challenges for integrating into and updating a previously validated physical-stochastic MLATS-based model framework called the Child-Specific Aggregate Cumulative Human Exposure and Dose (CACHED) model. The manuscript focuses on describing the methods implemented in the current study. Methods: This current multidisciplinary study (Dust Ingestion childRen sTudy [DIRT]) was implemented across three US regions: Tucson, Arizona; Miami, Florida and Greensboro, North Carolina. Four hundred and fifty participants were recruited between August 2021 to June 2023 to complete a 4-part household survey, of which 100 also participated in a field study. Discussion: The field study focused on videotaping children's natural play using advanced unattended 360° cameras mounted for participants' tracking and ultimately conversion to MLATS. Additionally, children's hand rinses were collected before and after recording, along with indoor dust and outdoor soil, followed by advanced mass analysis. The gathered data will be used to quantify dust/soil ingestion by region, sociodemographic variables, age groups (from 6 months to 6 years), and other variables for indoor/outdoor settings within an adapted version of the CACHED model framework. Significance: New innovative approaches for the estimation of dust/soil ingestion rates can potentially improve modeling and quantification of children's risks to contaminants from dust exposure.

Geographic disparities and temporal changes of diabetes-related mortality risks in Florida: a retrospective study.

Background: Over the last few decades, diabetes-related mortality risks (DRMR) have increased in Florida. Although there is evidence of geographic disparities in pre-diabetes and diabetes prevalence, little is known about disparities of DRMR in Florida. Understanding these disparities is important for guiding control programs and allocating health resources to communities most at need. Therefore, the objective of this study was to investigate geographic disparities and temporal changes of DRMR in Florida. Methods: Retrospective mortality data for deaths that occurred from 2010 to 2019 were obtained from the Florida Department of Health. Tenth International Classification of Disease codes E10-E14 were used to identify diabetes-related deaths. County-level mortality risks were computed and presented as number of deaths per 100,000 persons. Spatial Empirical Bayesian (SEB) smoothing was performed to adjust for spatial autocorrelation and the small number problem. High-risk spatial clusters of DRMR were identified using Tango's flexible spatial scan statistics. Geographic distribution and high-risk mortality clusters were displayed using ArcGIS, whereas seasonal patterns were visually represented in Excel. Results: A total of 54,684 deaths were reported during the study period. There was an increasing temporal trend as well as seasonal patterns in diabetes mortality risks with high risks occurring during the winter. The highest mortality risk (8.1 per 100,000 persons) was recorded during the winter of 2018, while the lowest (6.1 per 100,000 persons) was in the fall of 2010. County-level SEB smoothed mortality risks varied by geographic location, ranging from 12.6 to 81.1 deaths per 100,000 persons. Counties in the northern and central parts of the state tended to have high mortality risks, whereas southern counties consistently showed low mortality risks. Similar to the geographic distribution of DRMR, significant high-risk spatial clusters were also identified in the central and northern parts of Florida. Conclusion: Geographic disparities of DRMR exist in Florida, with high-risk spatial clusters being observed in rural central and northern areas of the state. There is also evidence of both increasing temporal trends and Winter peaks of DRMR. These findings are helpful for guiding allocation of resources to control the disease, reduce disparities, and improve population health.

Evolution of serious and life-threatening COVID-19 pneumonia as the SARS-CoV-2 pandemic progressed: an observational study of mortality to 60 days after admission to a 15-hospital US health system.

OBJECTIVE: In order to predict at hospital admission the prognosis of patients with serious and life-threatening COVID-19 pneumonia, we sought to understand the clinical characteristics of hospitalised patients at admission as the SARS-CoV-2 pandemic progressed, document their changing response to the virus and its variants over time, and identify factors most importantly associated with mortality after hospital admission. DESIGN: Observational study using a prospective hospital systemwide COVID-19 database. SETTING: 15-hospital US health system. PARTICIPANTS: 26 872 patients admitted with COVID-19 to our Northeast Ohio and Florida hospitals from 1 March 2020 to 1 June 2022. MAIN OUTCOME MEASURES: 60-day mortality (highest risk period) after hospital admission analysed by random survival forests machine learning using demographics, medical history, and COVID-19 vaccination status, and viral variant, symptoms, and routine laboratory test results obtained at hospital admission. RESULTS: Hospital mortality fell from 11% in March 2020 to 3.7% in March 2022, a 66% decrease (p<0.0001); 60-day mortality fell from 17% in May 2020 to 4.7% in May 2022, a 72% decrease (p<0.0001). Advanced age was the strongest predictor of 60-day mortality, followed by admission laboratory test results. Risk-adjusted 60-day mortality had all patients been admitted in March 2020 was 15% (CI 3.0% to 28%), and had they all been admitted in May 2022, 12% (CI 2.2% to 23%), a 20% decrease (p<0.0001). Dissociation between observed and predicted decrease in mortality was related to temporal change in admission patient profile, particularly in laboratory test results, but not vaccination status or viral variant. CONCLUSIONS: Hospital mortality from COVID-19 decreased substantially as the pandemic evolved but persisted after hospital discharge, eclipsing hospital mortality by 50% or more. However, after accounting for the many, even subtle, changes across the pandemic in patients' demographics, medical history and particularly admission laboratory results, a patient admitted early in the pandemic and predicted to be at high risk would remain at high risk of mortality if admitted tomorrow.

Fitting in? Physician practice style after forced relocation.

OBJECTIVE: This study aims to examine how variation in physicians' treatment decisions for newborn deliveries responds to changes in the hospital-level norms for obstetric clinical decision-making. DATA SOURCES: All hospital-based births in Florida from 2003 through 2017. STUDY DESIGN: Difference-in-differences approach is adopted that leverages obstetric unit closures as the source of identifying variation to exogenously shift obstetricians to a new, nearby hospital with different propensities to approach newborn deliveries less intensively. DATA EXTRACTION: Births attributed to physicians continuously observed 2 years before the closure event and 2 years after the closure event (treatment group physicians) or for identical time periods around a randomly assigned placebo closure date (control group physicians). PRINCIPAL FINDINGS: All of the physicians meeting our inclusion criteria shifted their births to a new hospital less than 20 miles from the hospital shuttering its obstetric unit. The new hospitals approached newborn births more conservatively, and treatment group physicians sharply became less aggressive in their newborn birth clinical management (e.g., use of C-section). The immediate 11-percentage point (33%) increase in delivering newborns without any procedure behavior change is statistically significant (p value <0.01) and persistent after the closure event; however, the physicians' payer and patient mix are unchanged. CONCLUSIONS: Obstetric physician behavior change appears highly malleable and sensitive to the practice patterns of other physicians delivering newborns at the same hospital. Incentives and policies that encourage more appropriate clinical care norms hospital-wide could sharply improve physician treatment decisions, with benefits for maternal and infant outcomes.

Integrating temporal decomposition and data-driven approaches for predicting coastal harmful algal blooms.

Frequent coastal harmful algal blooms (HABs) threaten the ecological environment and human health. Biscayne Bay in southeastern Florida also faces algal bloom issues; however, the mechanisms driving these blooms are not fully understood, emphasizing the importance of HAB prediction for effective environmental management. The overarching goal of this study is to offer a robust HAB predictive framework and try to enhance the understanding of HAB dynamics. This study established three scenarios to predict chlorophyll-a concentrations, a recognized representative of HABs: Scenario 1 (S1) using single nonlinear machine learning (ML) algorithms, hybrid Scenario 2 (S2) combining linear models and nonlinear ML algorithms, and hybrid Scenario 3 (S3) combining temporal decomposition and ML (TD-ML) algorithms. The novel-developed S3 TD-ML hybrid models demonstrated superior predictive capabilities, achieving all R2 values above 0.9 and MAPE under 30% in tests, significantly outperforming the S1 with an average R2 of 0.16 and the S2 with an R2 of -0.06. S3 models effectively captured the algal dynamics, successfully predicting complex time series with extremes and noise. In addition, we unveiled the relationship between environmental variables and chlorophyll-a through correlation analysis and found that climate change might intensify the HABs in Biscayne Bay. This research developed a precise predictive framework for early warning and proactive management of HABs, offering potential global applicability and improved prediction accuracy to address HAB challenges.

Psychosocial and socioeconomic changes among low-income people with HIV during the COVID-19 pandemic in Miami-Dade County, Florida: racial/ethnic and gender differences.

BACKGROUND: COVID-19 profoundly and uniquely impacted people with HIV. People with HIV experienced significant psychosocial and socioeconomic impacts, yet a limited amount of research has explored potential differences across gender and racial/ethnic groups of people with HIV. OBJECTIVE: The objective of this study was to examine psychosocial and socioeconomic stressors related to the COVID-19 pandemic among a diverse sample of people with HIV in South Florida and to determine if the types of stressors varied across gender and racial/ethnic groups. METHODS: We analyzed data from a cross-sectional survey with Miami-Dade County, Ryan White Program recipients. Outcomes included mental health, socioeconomic, drug/alcohol, and care responsibility/social support changes. Weighted descriptive analyses provided an overview of stressors by gender and racial/ethnic group and logistic regressions estimated associations between demographics and stressors. RESULTS: Among 291 participants, 39% were Non-Hispanic Black, 18% were Haitian, and 43% were Hispanic. Adjusting for age, sex, language, and foreign-born status, Hispanics were more likely to report several worsened mental health (i.e. increased loneliness, anxiety) and socioeconomic stressors (i.e. decreased income). Spanish speakers were more likely to report not getting the social support they needed. Women were more likely to report spending more time caring for children. CONCLUSIONS: Findings highlight ways in which cultural and gender expectations impacted experiences across people with HIV and suggest strategies to inform interventions and resources during lingering and future public health emergencies. Results suggest that public health emergencies have different impacts on different communities. Without acknowledging and responding to differences, we risk losing strides towards progress in health equity.

Overdose deaths before and during the COVID-19 pandemic in a US county.

Introduction: Globally, overdose deaths increased near the beginning of the COVID-19 pandemic, which created availability and access barriers to addiction and social services. Especially in times of a crisis like a pandemic, local exposures, service availability and access, and system responses have major influence on people who use drugs. For policy makers to be effective, an understanding at the local level is needed. Methods: This retrospective epidemiologic study from 2019 through 2021 compares immediate and 20-months changes in overdose deaths from the pandemic start to 16 months before its arrival in Pinellas County, FL We examine toxicologic death records of 1,701 overdoses to identify relations with interdiction, and service delivery. Results: There was an immediate 49% increase (95% CI 23-82%, p < 0.0001) in overdose deaths in the first month following the first COVID deaths. Immediate increases were found for deaths involving alcohol (171%), heroin (108%), fentanyl (78%), amphetamines (55%), and cocaine (45%). Overdose deaths remained 27% higher (CI 4-55%, p = 0.015) than before the pandemic through 2021.Abrupt service reductions occurred when the pandemic began: in-clinic methadone treatment dropped by two-thirds, counseling by 38%, opioid seizures by 29%, and drug arrests by 56%. Emergency transport for overdose and naloxone distributions increased at the pandemic onset (12%, 93%, respectively) and remained higher through 2021 (15%, 377%,). Regression results indicate that lower drug seizures predicted higher overdoses, and increased 911 transports predicted higher overdoses. The proportion of excess overdose deaths to excess non-COVID deaths after the pandemic relative to the year before was 0.28 in Pinellas County, larger than 75% of other US counties. Conclusions: Service and interdiction interruptions likely contributed to overdose death increases during the pandemic. Relaxing restrictions on medical treatment for opioid addiction and public health interventions could have immediate and long-lasting effects when a major disruption, such as a pandemic, occurs. County level data dashboards comprised of overdose toxicology, and interdiction and service data, can help explain changes in overdose deaths. As a next step in predicting which policies and practices will best reduce local overdoses, we propose using simulation modeling with agent-based models to examine complex interacting systems.

Climate change anxiety, hurricane exposure, and climate change actions and attitudes: results from a representative, probability-based survey of US Gulf Coast residents.

BACKGROUND: Exposure to climate change-related threats (eg, hurricanes) has been associated with mental health symptoms, including post-traumatic stress symptoms. Yet it is unclear whether climate change anxiety, which is understudied in representative samples, is a specific mental health threat, action motivator, or both, particularly in populations exposed to climate-change related disasters. We sought to examine the associations between exposure to hurricanes, climate change anxiety, and climate change actions and attitudes in a representative sample of US Gulf Coast residents. METHODS: This study used data from a 5-year, representative, prospectively assessed, probability-based, longitudinal cohort sample of residents in Texas and Florida (USA) exposed to exogenous catastrophic hurricanes rated category 3 or greater. Participants were adults aged 18 years and older and were initially recruited from the Ipsos KnowledgePanel in the 60 h before Hurricane Irma (Sept 8-11, 2017). Relationships between climate change anxiety, hurricane exposure, hurricane-related post-traumatic stress symptoms, general functional impairment, and climate change-related individual-level actions (eg, eating a plant-based diet and driving more fuel efficient cars) and collective-level actions (eg, petition signing and donating money) and climate change action attitudes were evaluated using structural equation modelling. FINDINGS: The final survey was completed by 1479 individuals (787 [53·2%] women and 692 [46·8%] men). Two climate change anxiety subscales (cognitive-emotional impairment and perceived experience of climate change) were confirmed using confirmatory factor analysis. Mean values were low for both climate change anxiety subscales: cognitive-emotional impairment (mean 1·31 [SD 0·63], range 1-5) and perceived climate change experience (mean 1·67 [SD 0·89], range 1-5); these subscales differentially predicted outcomes. The cognitive-emotional impairment subscale did not significantly correlate with actions or attitudes; its relationship with general functional impairment was attenuated by co-occurring hurricane-related post-traumatic stress symptoms, which were highly correlated with general functional impairment in all three models (all p<0·0001). The perceived climate change experience subscale correlated with climate change attitudes (b=0·57, 95% CI 0·47-0·66; p<0·0001), individual-level actions (b=0·34, 0·21-0·47; p<0·0001), and collective-level actions (b=0·22, 0·10-0·33; p=0·0002), but was not significantly associated with general functional impairment in any of the final models. Hurricane exposure correlated with climate change-related individual-level (b=0·26, 0·10-0·42; p=0·0011) and collective-level (b=0·41, 0·26-0·56; p<0·0001) actions. INTERPRETATION: Expanded treatment for post-traumatic stress symptoms after disasters could help address climate change-related psychological distress; experiences with climate change and natural hazards could be inflection points to motivate action. FUNDING: National Science Foundation and the National Center for Atmospheric Research.

Environmental variables driving horseshoe crab spawning behavior in a microtidal lagoon in Florida.

The timing of American horseshoe crab (Limulus polyphemus) spawning behavior along the coast of Florida (United States) is generally associated with the highest tides during the spring and fall lunar cycles. All Florida estuaries support horseshoe crab populations, but tidal characteristics vary markedly among locations, which may influence the timing of horseshoe crab spawning behavior. The Indian River Lagoon is a large microtidal estuary on Florida's east coast. Given the microtidal nature of the lagoon, it is unclear which environmental factors affect horseshoe spawning. In 2019, volunteers of Florida Horseshoe Crab Watch conducted daily surveys at two sites in the northern Indian River Lagoon during peak spawning months (February-April). During each survey, volunteers counted all spawning horseshoe crabs and recorded environmental variables, including water temperature, air temperature, wind speed, wind direction, salinity, and tide height. We developed a suite of negative-binomial regression models to quantify relationships between the number of spawning horseshoe crabs and environmental factors. Modeling results indicated a positive relationship between onshore wind speed and number of spawning horseshoe crabs. Our study suggests that in the absence of tidal cues, onshore wind speed may be an important driver of horseshoe crab spawning activity in microtidal estuarine systems.

Returners and explorers dichotomy in the face of natural hazards.

Understanding human mobility patterns amid natural hazards is crucial for enhancing urban emergency responses and rescue operations. Existing research on human mobility has delineated two primary types of individuals: returners, who exhibit a tendency to frequent a limited number of locations, and explorers, characterized by a more diverse range of movement across various places. Yet, whether this mobility dichotomy endures in the context of natural hazards remains underexplored. This study addresses this gap by examining anonymized high-resolution mobile phone location data from Lee County, Florida residents, aiming to unravel the dynamics of these distinct mobility groups throughout different phases of Hurricane Ian. The results indicate that returners and explorers maintained their distinct mobility characteristics even during the hurricane, showing increased separability. Before the hurricane, returners favored shorter trips, while explorers embarked on longer journeys, a trend that continued during the hurricane. However, the hurricane heightened people's inclination to explore, leading to a notable increase in longer-distance travel for both groups, likely influenced by evacuation considerations. Spatially, both groups exhibited an uptick in trips towards the southern regions, away from the hurricane's path, particularly converging on major destinations such as Miami, Fort Lauderdale, Naples, and West Palm Beach during the hurricane.

Hurricanes enhance coral connectivity but also superspread coral diseases.

Climate change poses an existential threat to coral reefs. A warmer and more acidic ocean weakens coral ecosystems and increases the intensity of hurricanes. The wind-wave-current interactions during a hurricane deeply change the ocean circulation patterns and hence potentially affect the dispersal of coral larvae and coral disease agents. Here, we modeled the impact of major hurricane Irma (September 2017) on coral larval and stony coral tissue loss disease (SCTLD) connectivity in Florida's Coral Reef. We coupled high-resolution coastal ocean circulation and wave models to simulate the dispersal of virtual coral larvae and disease agents between thousands of reefs. While being a brief event, our results suggest the passage of hurricane Irma strongly increased the probability of long-distance exchanges while reducing larval supply. It created new connections that could promote coral resilience but also probably accelerated the spread of SCTLD by about a month. As they become more intense, hurricanes' double-edged effect will become increasingly pronounced, contributing to increased variability in transport patterns and an accelerated rate of change within coral reef ecosystems.

Mammalian lures monitored with time-lapse cameras increase detection of pythons and other snakes.

Background: Enhancing detection of cryptic snakes is critical for the development of conservation and management strategies; yet, finding methods that provide adequate detection remains challenging. Issues with detecting snakes can be particularly problematic for some species, like the invasive Burmese python (Python bivittatus) in the Florida Everglades. Methods: Using multiple survey methods, we predicted that our ability to detect pythons, larger snakes and all other snakes would be enhanced with the use of live mammalian lures (domesticated rabbits; Oryctolagus cuniculus). Specifically, we used visual surveys, python detection dogs, and time-lapse game cameras to determine if domesticated rabbits were an effective lure. Results: Time-lapse game cameras detected almost 40 times more snakes (n = 375, treatment = 245, control = 130) than visual surveys (n = 10). We recorded 21 independent detections of pythons at treatment pens (with lures) and one detection at a control pen (without lures). In addition, we found larger snakes, and all other snakes were 165% and 74% more likely to be detected at treatment pens compared to control pens, respectively. Time-lapse cameras detected almost 40 times more snakes than visual surveys; we did not detect any pythons with python detection dogs. Conclusions: Our study presents compelling evidence that the detection of snakes is improved by coupling live mammalian lures with time-lapse game cameras. Although the identification of smaller snake species was limited, this was due to pixel resolution, which could be improved by changing the camera focal length. For larger snakes with individually distinctive patterns, this method could potentially be used to identify unique individuals and thus allow researchers to estimate population dynamics.

Sediment source and dose influence the larval performance of the threatened coral Orbicella faveolata.

The effects of turbidity and sedimentation stress on early life stages of corals are poorly understood, particularly in Atlantic species. Dredging operations, beach nourishment, and other coastal construction activities can increase sedimentation and turbidity in nearby coral reef habitats and have the potential to negatively affect coral larval development and metamorphosis, reducing sexual reproduction success. In this study, we investigated the performance of larvae of the threatened Caribbean coral species Orbicella faveolata exposed to suspended sediments collected from a reef site in southeast Florida recently impacted by dredging (Port of Miami), and compared it to the performance of larvae exposed to sediments collected from the offshore, natal reef of the parent colonies. In a laboratory experiment, we tested whether low and high doses of each of these sediment types affected the survival, settlement, and respiration of coral larvae compared to a no-sediment control treatment. In addition, we analyzed the sediments used in the experiments with 16S rRNA gene amplicon sequencing to assess differences in the microbial communities present in the Port versus Reef sediments, and their potential impact on coral performance. Overall, only O. faveolata larvae exposed to the high-dose Port sediment treatment had significantly lower survival rates compared to the control treatment, suggesting an initial tolerance to elevated suspended sediments. However, significantly lower settlement rates were observed in both Port treatments (low- and high-dose) compared to the control treatment one week after exposure, suggesting strong latent effects. Sediments collected near the Port also contained different microbial communities than Reef sediments, and higher relative abundances of the bacteria Desulfobacterales, which has been associated with coral disease. We hypothesize that differences in microbial communities between the two sediments may be a contributing factor in explaining the observed differences in larval performance. Together, these results suggest that the settlement success and survival of O. faveolata larvae are more readily compromised by encountering port inlet sediments compared to reef sediments, with potentially important consequences for the recruitment success of this species in affected areas.

A Novel Summer Camp Integrating Physical, Psychological, and Educational Health in Youth: The THINK Program.

Numerous youth summer programs focus upon physical fitness, nutritional health, psychological well-being, or education. Few, however, have integrated all of these elements into a single program. The Translational Health in Nutrition and Kinesiology (THINK) program provides an integrative nutrition and exercise science curriculum that is interfaced with social emotional learning (SEL) and STEM education to enhance healthy behaviors in youth. The purpose of this study was to determine whether the THINK program could improve physical fitness, nutrition habits, SEL, and STEM education in a 6-week summer program covering a 3-year period. Participants from South Miami were enrolled in THINK (n = 108, 58 males, 50 females, 12.03 + 0.56 years). Physical fitness assessments, the Positive Youth Development Inventory (PYDI), the Students' Attitude Towards STEM Survey, and the Adolescent Food Habits Checklist (ADFH) were recorded at baseline and post-testing. Means and standard error values were evaluated for all dependent variables. Paired samples t-tests (SPSS version 27) were used to determine changes. Improvements in cardiorespiratory fitness (p < 0.001), power (p < 0.006), flexibility (p < 0.001), agility (p < 0.001), muscular endurance (p < 0.001), lean body mass (p < 0.001), ADFH (p < 0.001), and PYDI (p = 0.038) were found. An integrative summer fitness program can result in improvements in physical fitness, nutrition habits, and SEL in as little as six weeks.

Engaging School Champions in the Implementation of a Research Study in Historically Marginalized School Communities.

Community engagement in research improves uptake of health interventions and health outcomes among marginalized populations. Researchers from school-based health centers serving marginalized communities in Miami, Florida fostered community engagement in COVID-19 research and health education through collaboration with school staff and student "champions" from June 2021 to June 2023. Evaluations completed by champions assessed acceptability, feasibility, and recommendations for improvements. Overall satisfaction was high among champions. We elaborate on lessons learned and future directions for this type of research collaboration. (Am J Public Health. 2024;114(8):789-793. https://doi.org/10.2105/AJPH.2024.307711).

Public perceptions of artificial intelligence in healthcare: ethical concerns and opportunities for patient-centered care.

BACKGROUND: In an effort to improve the quality of medical care, the philosophy of patient-centered care has become integrated into almost every aspect of the medical community. Despite its widespread acceptance, among patients and practitioners, there are concerns that rapid advancements in artificial intelligence may threaten elements of patient-centered care, such as personal relationships with care providers and patient-driven choices. This study explores the extent to which patients are confident in and comfortable with the use of these technologies when it comes to their own individual care and identifies areas that may align with or threaten elements of patient-centered care. METHODS: An exploratory, mixed-method approach was used to analyze survey data from 600 US-based adults in the State of Florida. The survey was administered through a leading market research provider (August 10-21, 2023), and responses were collected to be representative of the state's population based on age, gender, race/ethnicity, and political affiliation. RESULTS: Respondents were more comfortable with the use of AI in health-related tasks that were not associated with doctor-patient relationships, such as scheduling patient appointments or follow-ups (84.2%). Fear of losing the 'human touch' associated with doctors was a common theme within qualitative coding, suggesting a potential conflict between the implementation of AI and patient-centered care. In addition, decision self-efficacy was associated with higher levels of comfort with AI, but there were also concerns about losing decision-making control, workforce changes, and cost concerns. A small majority of participants mentioned that AI could be useful for doctors and lead to more equitable care but only when used within limits. CONCLUSION: The application of AI in medical care is rapidly advancing, but oversight, regulation, and guidance addressing critical aspects of patient-centered care are lacking. While there is no evidence that AI will undermine patient-physician relationships at this time, there is concern on the part of patients regarding the application of AI within medical care and specifically as it relates to their interaction with physicians. Medical guidance on incorporating AI while adhering to the principles of patient-centered care is needed to clarify how AI will augment medical care.

Agent-based modeling of the COVID-19 pandemic in Florida.

The onset of the COVID-19 pandemic drove a widespread, often uncoordinated effort by research groups to develop mathematical models of SARS-CoV-2 to study its spread and inform control efforts. The urgent demand for insight at the outset of the pandemic meant early models were typically either simple or repurposed from existing research agendas. Our group predominantly uses agent-based models (ABMs) to study fine-scale intervention scenarios. These high-resolution models are large, complex, require extensive empirical data, and are often more detailed than strictly necessary for answering qualitative questions like "Should we lockdown?" During the early stages of an extraordinary infectious disease crisis, particularly before clear empirical evidence is available, simpler models are more appropriate. As more detailed empirical evidence becomes available, however, and policy decisions become more nuanced and complex, fine-scale approaches like ours become more useful. In this manuscript, we discuss how our group navigated this transition as we modeled the pandemic. The role of modelers often included nearly real-time analysis, and the massive undertaking of adapting our tools quickly. We were often playing catch up with a firehose of evidence, while simultaneously struggling to do both academic research and real-time decision support, under conditions conducive to neither. By reflecting on our experiences of responding to the pandemic and what we learned from these challenges, we can better prepare for future demands.

Treatment of Brachioradial Pruritus: A Tertiary Center Retrospective Analysis.

This retrospective study investigates the efficacy of 2 treatment regimens, pregabalin alone versus pregabalin combined with ketamine, amitriptyline, and lidocaine cream, in reducing itch in patients with brachioradial pruritus at a tertiary care center. Electronic medical records of 64 brachioradial pruritus patients seen at the University of Miami Itch Center were analyzed. A significant reduction in itch scores was seen with both treatments, with no significant difference between the groups. A small number of patients experienced adverse effects, including drowsiness and weight gain with pregabalin and skin irritation with ketamine, amitriptyline, and lidocaine cream. Ultimately, our findings underscore the potential of utilizing combined therapy for difficult-to-treat brachioradial pruritus cases and implementing individualized approaches for managing neuropathic pruritus. Further controlled clinical trials are needed to establish optimal treatment protocols.