Excess burden of respiratory and abdominal conditions following COVID-19 infections during the ancestral and Delta variant periods in the United States: An EHR-based cohort study from the RECOVER program.

IMPORTANCE: The frequency and characteristics of post-acute sequelae of SARS-CoV-2 infection (PASC) may vary by SARS-CoV-2 variant. OBJECTIVE: To characterize PASC-related conditions among individuals likely infected by the ancestral strain in 2020 and individuals likely infected by the Delta variant in 2021. DESIGN: Retrospective cohort study of electronic medical record data for approximately 27 million patients from March 1, 2020-November 30, 2021. SETTING: Healthcare facilities in New York and Florida. PARTICIPANTS: Patients who were at least 20 years old and had diagnosis codes that included at least one SARS-CoV-2 viral test during the study period. EXPOSURE: Laboratory-confirmed COVID-19 infection, classified by the most common variant prevalent in those regions at the time. MAIN OUTCOME(S) AND MEASURE(S): Relative risk (estimated by adjusted hazard ratio [aHR]) and absolute risk difference (estimated by adjusted excess burden) of new conditions, defined as new documentation of symptoms or diagnoses, in persons between 31-180 days after a positive COVID-19 test compared to persons without a COVID-19 test or diagnosis during the 31-180 days after the last negative test. RESULTS: We analyzed data from 560,752 patients. The median age was 57 years; 60.3% were female, 20.0% non-Hispanic Black, and 19.6% Hispanic. During the study period, 57,616 patients had a positive SARS-CoV-2 test; 503,136 did not. For infections during the ancestral strain period, pulmonary fibrosis, edema (excess fluid), and inflammation had the largest aHR, comparing those with a positive test to those without a COVID-19 test or diagnosis (aHR 2.32 [95% CI 2.09 2.57]), and dyspnea (shortness of breath) carried the largest excess burden (47.6 more cases per 1,000 persons). For infections during the Delta period, pulmonary embolism had the largest aHR comparing those with a positive test to a negative test (aHR 2.18 [95% CI 1.57, 3.01]), and abdominal pain carried the largest excess burden (85.3 more cases per 1,000 persons). CONCLUSIONS AND RELEVANCE: We documented a substantial relative risk of pulmonary embolism and a large absolute risk difference of abdomen-related symptoms after SARS-CoV-2 infection during the Delta variant period. As new SARS-CoV-2 variants emerge, researchers and clinicians should monitor patients for changing symptoms and conditions that develop after infection.

Investigation of geographic disparities of diabetes-related hospitalizations in Florida using flexible spatial scan statistics: An ecological study.

BACKGROUND: Hospitalizations due to diabetes complications are potentially preventable with effective management of the condition in the outpatient setting. Diabetes-related hospitalization (DRH) rates can provide valuable information about access, utilization, and efficacy of healthcare services. However, little is known about the local geographic distribution of DRH rates in Florida. Therefore, the objectives of this study were to investigate the geographic distribution of DRH rates at the ZIP code tabulation area (ZCTA) level in Florida, identify significant local clusters of high hospitalization rates, and describe characteristics of ZCTAs within the observed spatial clusters. METHODS: Hospital discharge data from 2016 to 2019 were obtained from the Florida Agency for Health Care Administration through a Data Use Agreement with the Florida Department of Health. Raw and spatial empirical Bayes smoothed DRH rates were computed at the ZCTA level. High-rate DRH clusters were identified using Tango's flexible spatial scan statistic. Choropleth maps were used to display smoothed DRH rates and significant high-rate spatial clusters. Demographic, socioeconomic, and healthcare-related characteristics of cluster and non-cluster ZCTAs were compared using the Wilcoxon rank sum test for continuous variables and Chi-square test for categorical variables. RESULTS: There was a total of 554,133 diabetes-related hospitalizations during the study period. The statewide DRH rate was 8.5 per 1,000 person-years, but smoothed rates at the ZCTA level ranged from 0 to 101.9. A total of 24 significant high-rate spatial clusters were identified. High-rate clusters had a higher percentage of rural ZCTAs (60.9%) than non-cluster ZCTAs (41.8%). The median percent of non-Hispanic Black residents was significantly (p < 0.0001) higher in cluster ZCTAs than in non-cluster ZCTAs. Populations of cluster ZCTAs also had significantly (p < 0.0001) lower median income and educational attainment, and higher levels of unemployment and poverty compared to the rest of the state. In addition, median percent of the population with health insurance coverage and number of primary care physicians per capita were significantly (p < 0.0001) lower in cluster ZCTAs than in non-cluster ZCTAs. CONCLUSIONS: This study identified geographic disparities of DRH rates at the ZCTA level in Florida. The identification of high-rate DRH clusters provides useful information to guide resource allocation such that communities with the highest burdens are prioritized to reduce the observed disparities. Future research will investigate determinants of hospitalization rates to inform public health planning, resource allocation and interventions.

Longitudinal Impacts of Precision Greenness on Alzheimer's Disease.

BACKGROUND: The potential for greenness as a novel protective factor for Alzheimer's disease (AD) requires further exploration. OBJECTIVES: This study assesses prospectively and longitudinally the association between precision greenness - greenness measured at the micro-environmental level, defined as the Census block - and AD incidence. DESIGN: Older adults living in consistently high greenness Census blocks across 2011 and 2016 were compared to those living in consistently low greenness blocks on AD incidence during 2012-2016. SETTING: Miami-Dade County, Florida, USA. PARTICIPANTS: 230,738 U.S. Medicare beneficiaries. MEASUREMENTS: U.S. Centers for Medicare and Medicaid Services Chronic Condition Algorithm for AD based on ICD-9 codes, Normalized Difference Vegetation Index, age, sex, race/ethnicity, neighborhood income, and walkability. RESULTS: Older adults living in the consistently high greenness tertile, compared to those in the consistently low greenness tertile, had 16% lower odds of AD incidence (OR=0.84, 95% CI: 0.76-0.94, p=0.0014), adjusting for age, sex, race/ethnicity, and neighborhood income. Age, neighborhood income and walkability moderated greenness' relationship to odds of AD incidence, such that younger ages (65-74), lower-income, and non-car dependent neighborhoods may benefit most from high greenness. CONCLUSIONS: High greenness, compared to low greenness, is associated with lower 5-year AD incidence. Residents who are younger and/or who reside in lower-income, walkable neighborhoods may benefit the most from high greenness. These findings suggest that consistently high greenness at the Census block-level, may be associated with reduced odds of AD incidence at a population level.

COVID-19 Pandemic and Posttraumatic Growth in Residents of a Continuing Care Retirement Community: A Mixed Methods Study.

PURPOSE: The coronavirus disease 2019 (COVID-19) pandemic impacted life for older adults living in residential settings, affecting their psychosocial well-being. Risk for COVID-19 is associated with increasing age and pre-existing health conditions. The current study aimed to describe the challenges of COVID-19 and post-traumatic growth (PTG) for residents of a continuing care retirement community (CCRC) in South Florida. METHOD: A parallel mixed methods approach was used to explore the experience of older adults with PTG. Quantitative data were analyzed using descriptive statistics. Qualitative data were analyzed using content analysis to identify emergent themes. RESULTS: Ninety-eight older adults living in a single CCRC completed a survey. Age ranged from 67 to 99 years (mean age = 86 years), with >90% identifying as non-Hispanic White and female (78%). Using the PTG theoretical framework, experiences were categorized into five dimensions: new possibilities, relating to others, personal strength, spiritual growth, and appreciation for life. CONCLUSION: The current study focused on the challenges and growth experienced by older adults, as framed by PTG theory. Findings shed light on the capacity of this demographic, with an average age of 86 years, to overcome obstacles and achieve PTG. [Journal of Gerontological Nursing, 50(6), 25-33.].

Analysis of injury severity of work zone crashes on rural and urban work zones: Accounting for out-of-sample prediction and temporal instability.

This research utilizes data collected in Florida to examine the differentials in injury severities among single-vehicle drivers involved in work zone-related incidents, specifically focusing on the distinctions between rural and urban areas. The study encompasses a four-year period (2016-2019) of crash dataset. A likelihood ratio test was performed to examine model estimate's temporal consistency in datasets from rural and urban areas across several time periods throughout the year. Separate statistical models were estimated for both rural and urban datasets to understand different driver injury severity outcomes (no injury, minor injury, and severe injury) using a mixed logit approach with possible heterogeneity in mean and variance of random parameters. Out-of-sample simulations were conducted to see the effect of different parameter changes on injury severity probabilities in rural and urban work zone crashes. Over multiple years, various years in both rural and urban models have generated statistically significant random factors that effectively capture the presence of heterogeneity in means, accounting for unobservable variations within the data. Clear evidence of factors such as speed limits, work zone type, and traffic volume affecting the work zone injury severities were found to vary significantly between rural and urban work zone areas. However, despite this difference, rural and urban work zones share common safety problems and countermeasures such as driver education, improved signage, and appropriate traffic controls; combining ITS technologies and enhanced law enforcement can help mitigate crash severity in urban and rural work zone areas.

Seroprevalence of West Nile Virus in Tampa Bay Florida Patients Admitted to Hospital during 2020-2021 for Respiratory Symptoms.

West Nile virus (WNV) is an arbovirus spread primarily by Culex mosquitoes, with humans being a dead-end host. WNV was introduced to Florida in 2001, with 467 confirmed cases since. It is estimated that 80 percent of cases are asymptomatic, with mild cases presenting as a non-specific flu-like illness. Currently, detection of WNV in humans occurs primarily in healthcare settings via RT-PCR or CSF IgM when patients present with severe manifestations of disease including fever, meningitis, encephalitis, or acute flaccid paralysis. Given the short window of detectable viremia and requirement for CSF sampling, most WNV infections never receive an official diagnosis. This study utilized enzyme-linked immunosorbent assay (ELISA) to detect WNV IgG antibodies in 250 patient serum and plasma samples collected at Tampa General Hospital during 2020 and 2021. Plaque reduction neutralization tests were used to confirm ELISA results. Out of the 250 patients included in this study, 18.8% of them were IgG positive, consistent with previous WNV exposure. There was no relationship between WNV exposure and age or sex.

Using Causal Bayesian Networks to Assess the Role of Patient-Centered Care and Psychosocial Factors on Durable HIV Viral Suppression.

We assessed the role of patient-centered care on durable viral suppression (i.e., all viral load test results < 200 copies per ml during 2019) by conducting a retrospective cohort study of clients medically case managed by the Miami-Dade County Ryan White Program (RWP). Summary measures of patient-centered care practices of RWP-affiliated providers were obtained from a survey of 1352 clients. Bayesian network models analyzed the complex relationship between psychosocial and patient-centered care factors. Of 5037 clients, 4135 (82.1%) had durable viral suppression. Household income was the factor most strongly associated with durable viral suppression. Further, mean healthcare relationship score and mean "provider knows patient as a person" score were both associated with durable viral suppression. Healthcare relationship score moderated the association between low household income and lack of durable viral suppression. Although patient-centered care supports patient HIV care success, wrap around support is also needed for people with unmet psychosocial needs.

RESUMEN: Evaluamos el rol de la atención centrada en el paciente en la supresión viral duradera (es decir, todos los resultados de las pruebas de carga viral < 200 copias por ml durante 2019) mediante la realización de un estudio de cohorte retrospectivo de clientes manejados médicamente por el Programa Ryan White del condado de Miami-Dade (RWP). Se obtuvieron medidas resumidas de las prácticas de atención centradas en el paciente de los proveedores afiliados a RWP usando una encuesta de 1352 clientes. Los modelos de redes bayesianos analizaron la relación compleja entre los factores psicosociales y de atención centrada en el paciente. De 5037 clientes, 4135 (82,1%) tenían una supresión viral duradera. Los ingresos del hogar fueron el factor asociado con la supresión viral duradera más fuerte. Además, la puntuación promedia de la relación con proveedores de atención médica y la puntuación promedia de "el proveedor conoce al paciente como persona" fueron asociados con una supresión viral duradera. La puntuación de la relación con proveedores de atención médica moderó la asociación entre los ingresos bajos del hogar y la falta de supresión viral duradera. Aunque la atención centrada en el paciente apoya el éxito de la atención médica del VIH, también se necesita un apoyo integral para las personas con necesidades psicosociales insatisfechas.

Highly pathogenic avian influenza A(H5N1) virus in a common bottlenose dolphin (Tursiops truncatus) in Florida.

Since late 2021, highly pathogenic avian influenza (HPAI) viruses of A/goose/Guangdong/1/1996 (H5N1) lineage have caused widespread mortality in wild birds and poultry in the United States. Concomitant with the spread of HPAI viruses in birds are increasing numbers of mammalian infections, including wild and captive mesocarnivores and carnivores with central nervous system involvement. Here we report HPAI, A(H5N1) of clade 2.3.4.4b, in a common bottlenose dolphin (Tursiops truncatus) from Florida, United States. Pathological findings include neuronal necrosis and inflammation of the brain and meninges, and quantitative real time RT-PCR reveal the brain carried the highest viral load. Virus isolated from the brain contains a S246N neuraminidase substitution which leads to reduced inhibition by neuraminidase inhibitor oseltamivir. The increased prevalence of A(H5N1) viruses in atypical avian hosts and its cross-species transmission into mammalian species highlights the public health importance of continued disease surveillance and biosecurity protocols.

DeepDynaForecast: Phylogenetic-informed graph deep learning for epidemic transmission dynamic prediction.

In the midst of an outbreak or sustained epidemic, reliable prediction of transmission risks and patterns of spread is critical to inform public health programs. Projections of transmission growth or decline among specific risk groups can aid in optimizing interventions, particularly when resources are limited. Phylogenetic trees have been widely used in the detection of transmission chains and high-risk populations. Moreover, tree topology and the incorporation of population parameters (phylodynamics) can be useful in reconstructing the evolutionary dynamics of an epidemic across space and time among individuals. We now demonstrate the utility of phylodynamic trees for transmission modeling and forecasting, developing a phylogeny-based deep learning system, referred to as DeepDynaForecast. Our approach leverages a primal-dual graph learning structure with shortcut multi-layer aggregation, which is suited for the early identification and prediction of transmission dynamics in emerging high-risk groups. We demonstrate the accuracy of DeepDynaForecast using simulated outbreak data and the utility of the learned model using empirical, large-scale data from the human immunodeficiency virus epidemic in Florida between 2012 and 2020. Our framework is available as open-source software (MIT license) at github.com/lab-smile/DeepDynaForcast.

Disparities in incidence and survival for patients with Ewing sarcoma in Florida.

BACKGROUND: Ewing sarcoma (ES) is a malignant bone tumor most commonly affecting non-Hispanic White (NHW) adolescent males, though recognition among Hispanic individuals is rising. Prior population-based studies in the United States (US), utilizing Surveillance, Epidemiology, and End Results (SEER) have shown higher all-cause mortality among White Hispanics, Blacks, and those of low socioeconomic status (SES). Florida is not part of SEER but is home to unique Hispanic populations including Cubans, Puerto Ricans, South Americans that contrasts with the Mexican Hispanic majority in other US states. This study aimed to assess racial/ethnic disparities on incidence and survival outcomes among this diverse Florida patient population. METHODOLOGY: Our study examined all patients diagnosed with osseous ES (2005-2018) in Florida (n = 411) based on the state's population-based cancer registry dataset. Florida Age-adjusted Incidence Rates (AAIRs) were computed by sex and race-ethnicity and compared to the equivalent populations in SEER. Cause-specific survival disparities among Florida patients were examined using Kaplan-Meier analysis. Univariable and multivariable analyses using Cox regression were performed for race/ethnicity, with adjustment for age, sex, year of diagnosis, site of disease, staging, SES, and insurance type. RESULTS: There was a significantly higher incidence of osseous ES in Florida Hispanic males (AAIR 2.6/1,000,000); (95% CI: 2.0-3.2 per 1,000,000; n = 84) compared to the SEER Hispanic males (AAIR 1.2/1,000,000;1.1-1.4 per 1,000,000; n = 382). Older age, distant metastasis, lack of chemotherapy or surgical resection were statistically significant determinants of poor survival while SES, insurance status and race-ethnicity were not. However, among nonmetastatic ES, Florida Hispanics had an increased risk of death compared to Florida NHW (adjusted Hazard Ratio 2.32; 95%CI: 1.20-4.46; p = 0.012). CONCLUSIONS: Florida Hispanic males have a higher-than-expected incidence of osseous ES compared to the US. Hispanics of both sexes show remarkably worse survival for nonmetastatic disease compared to NHW. This disparity is likely multifactorial and requires further in-depth studies.

Drug use and COVID-19 testing, vaccination, and infection among underserved, minority communities in Miami, Florida.

The Coronavirus Disease 2019 (COVID-19) pandemic has disproportionately impacted people who use drugs (PWUD). This study explored relationships between drug use, COVID-19 testing, vaccination, and infection. This cross-sectional study was conducted in Miami, Florida between March 2021 and October 2022 as part of the National Institutes of Health (NIH) Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) initiative and the Miami Adult Studies on HIV (MASH) cohort. Users of cannabis, cocaine/crack, heroin/fentanyl, methamphetamines, hallucinogens, and/or prescription drug misuse in the previous 12 months were considered PWUD. Sociodemographic data, COVID-19 testing history, and vaccination-related beliefs were self-reported. Vaccinations were confirmed with medical records and positivity was determined with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. Statistical analyses included chi-square tests and logistic regression. Of 1,780 participants, median age was 57 years, 50.7% were male, 50.2% Non-Hispanic Black, and 66.0% reported an annual income less than $15,000. Nearly 28.0% used drugs. PWUD were less likely than non-users to self-report ever testing positive for SARS-CoV-2 (14.7% vs. 21.0%, p = 0.006). However, 2.6% of participants tested positive for SARS-CoV-2, with no significant differences between PWUD and non-users (3.7% vs. 2.2%, p = 0.076). PWUD were more likely than non-users to experience difficulties accessing testing (10.2% vs. 7.1%, p = 0.033), vaccine hesitancy (58.9% vs. 43.4%, p = 0.002) and had lower odds of receiving any dose of a COVID-19 vaccine compared to non-users (aOR, 0.63; 95% CI, 0.49-0.81; p<0.001). PWUD presented with greater difficulties accessing COVID-19 testing, greater vaccine hesitancy, and lower odds of vaccination. Testing and immunization plans that are tailored to the needs of PWUD and consider access, trust-building campaigns, and education may be needed.

Machine Evaluation of Catchment Area Relevance through Text Mining.

The University of Miami Sylvester Comprehensive Cancer Center Community Outreach and Engagement Office has developed an algorithm to aid in identifying catchment area relevant trials. We have developed this tool to capture a catchment area (South Florida) that represents the most racially, ethnically, and geographically diverse region in the US. Unfortunately, the area's tumor burden is also significant with many notable disparities, necessitating a prioritization of trials within Sylvester's catchment area. These trials address the needs of the population Sylvester serves by targeting cancers that are locally prevalent.

The Florida Scoring System for stratifying children with suspected Sjögren's disease: a cross-sectional machine learning study.

BACKGROUND: Childhood Sjögren's disease is a rare, underdiagnosed, and poorly-understood condition. By integrating machine learning models on a paediatric cohort in the USA, we aimed to develop a novel system (the Florida Scoring System) for stratifying symptomatic paediatric patients with suspected Sjögren's disease. METHODS: This cross-sectional study was done in symptomatic patients who visited the Department of Pediatric Rheumatology at the University of Florida, FL, USA. Eligible patients were younger than 18 years or had symptom onset before 18 years of age. Patients with confirmed diagnosis of another autoimmune condition or infection with a clear aetiological microorganism were excluded. Eligible patients underwent comprehensive examinations to rule out or diagnose childhood Sjögren's disease. We used latent class analysis with clinical and laboratory variables to detect heterogeneous patient classes. Machine learning models, including random forest, gradient-boosted decision tree, partial least square discriminatory analysis, least absolute shrinkage and selection operator-penalised ordinal regression, artificial neural network, and super learner were used to predict patient classes and rank the importance of variables. Causal graph learning selected key features to build the final Florida Scoring System. The predictors for all models were the clinical and laboratory variables and the outcome was the definition of patient classes. FINDINGS: Between Jan 16, 2018, and April 28, 2022, we screened 448 patients for inclusion. After excluding 205 patients due to symptom onset later than 18 years of age, we recruited 243 patients into our cohort. 26 patients were excluded because of confirmed diagnosis of a disorder other than Sjögren's disease, and 217 patients were included in the final analysis. Median age at diagnosis was 15 years (IQR 11-17). 155 (72%) of 216 patients were female and 61 (28%) were male, 167 (79%) of 212 were White, and 20 (9%) of 213 were Hispanic, Latino, or Spanish. The latent class analysis identified three distinct patient classes: class I (dryness dominant with positive tests, n=27), class II (high symptoms with negative tests, n=98), and class III (low symptoms with negative tests, n=92). Machine learning models accurately predicted patient class and ranked variable importance consistently. The causal graphical model discovered key features for constructing the Florida Scoring System. INTERPRETATION: The Florida Scoring System is a paediatrician-friendly tool that can be used to assist classification and long-term monitoring of suspected childhood Sjögren's disease. The resulting stratification has important implications for clinical management, trial design, and pathobiological research. We found a highly symptomatic patient group with negative serology and diagnostic profiles, which warrants clinical attention. We further revealed that salivary gland ultrasonography can be a non-invasive alternative to minor salivary gland biopsy in children. The Florida Scoring System requires validation in larger prospective paediatric cohorts. FUNDING: National Institute of Dental and Craniofacial Research, National Institute of Arthritis, Musculoskeletal and Skin Diseases, National Heart, Lung, and Blood Institute, and Sjögren's Foundation.

Autochthonous Plasmodium vivax Infections, Florida, USA, 2023.

During May-July 2023, a cluster of 7 patients at local hospitals in Florida, USA, received a diagnosis of Plasmodium vivax malaria. Whole-genome sequencing of the organism from 4 patients and phylogenetic analysis with worldwide representative P. vivax genomes indicated probable single parasite introduction from Central/South America.

Investigating Disparities in Hypopharyngeal/Laryngeal Cancer Survival in Florida With Geospatial Mapping Analysis.

OBJECTIVE: Identify predictors of overall survival (OS) after hypopharyngeal/laryngeal cancer in Florida. MATERIAL AND METHODS: We conducted a retrospective cohort study using data from the Florida Cancer Data System (FCDS) on patients diagnosed with hypopharyngeal or laryngeal cancer from 2010-2017. Primary outcome was OS. Hazard ratios (HRs) were estimated from univariable and multivariable Cox regression models for OS. Data was analyzed from November 1, 2022, to June 30, 2023. RESULTS: We analyzed 6771 patients, who were primarily male (81.2%), White non-Hispanic (WNH) (78.2%), publicly insured (70.1%), married (51.8%), and residents of urban counties (73.6%). Black patients were more likely to be younger at diagnosis (38.9%), single (43.4%), to have distant SEER stage disease (25.6%). Median OS were lowest among patients who were uninsured (34 months), with hypopharyngeal site disease (18 months), and a smoking history (current: 34 months, former: 46 months, no smoking: 63 months). Multivariable Cox regression analysis showed worse OS for single/unmarried vs married (HR 1.47 [95%CI: 1.36-1.59], P < .001), history of tobacco use (current: HR 1.62 [95%CI: 1.440-1.817], P < .001; former smokers: (HR 1.28 [95%CI: 1.139-1.437], P < .001) vs no history). Improved OS was observed among White Hispanics (WH) vs WNH (HR .73 [95%CI: .655-.817], P < .001) and women vs men (HR .88 [95%CI: .807-.954], P = .002). Geographical mapping showed that mortality rates were highest in census tracts with low income and education. CONCLUSION: Our findings suggest that sociodemographic and clinical factors impact OS from hypopharyngeal/laryngeal cancer in Florida and vary geographically within the state. These results will help guide future public health interventions.

Concurrent Outbreaks of Hepatitis A, Invasive Meningococcal Disease, and Mpox, Florida, USA, 2021-2022.

In 2022, concurrent outbreaks of hepatitis A, invasive meningococcal disease (IMD), and mpox were identified in Florida, USA, primarily among men who have sex with men. The hepatitis A outbreak (153 cases) was associated with hepatitis A virus genotype IA. The IMD outbreak (44 cases) was associated with Neisseria meningitidis serogroup C, sequence type 11, clonal complex 11. The mpox outbreak in Florida (2,845 cases) was part of a global epidemic. The hepatitis A and IMD outbreaks were concentrated in Central Florida and peaked during March--June, whereas mpox cases were more heavily concentrated in South Florida and had peak incidence in August. HIV infection was more common (52%) among mpox cases than among hepatitis A (21%) or IMD (34%) cases. Where feasible, vaccination against hepatitis A, meningococcal disease, and mpox should be encouraged among at-risk groups and offered along with program services that target those groups.

Spatial and temporal analysis of HIV clinical outcomes in Florida reveals counties with persistent racial and ethnic disparities during 2012-2019.

BACKGROUND: Racial/ethnic disparities in the HIV care continuum have been well documented in the US, with especially striking inequalities in viral suppression rates between White and Black persons with HIV (PWH). The South is considered an epicenter of the HIV epidemic in the US, with the largest population of PWH living in Florida. It is unclear whether any disparities in viral suppression or immune reconstitution-a clinical outcome highly correlated with overall prognosis-have changed over time or are homogenous geographically. In this analysis, we 1) investigate longitudinal trends in viral suppression and immune reconstitution among PWH in Florida, 2) examine the impact of socio-ecological factors on the association between race/ethnicity and clinical outcomes, 3) explore spatial and temporal variations in disparities in clinical outcomes. METHODS: Data were obtained from the Florida Department of Health for 42,369 PWH enrolled in the Ryan White program during 2008-2020. We linked the data to county-level socio-ecological variables available from County Health Rankings. GEE models were fit to assess the effect of race/ethnicity on immune reconstitution and viral suppression longitudinally. Poisson Bayesian hierarchical models were fit to analyze geographic variations in racial/ethnic disparities while adjusting for socio-ecological factors. RESULTS: Proportions of PWH who experienced viral suppression and immune reconstitution rose by 60% and 45%, respectively, from 2008-2020. Odds of immune reconstitution and viral suppression were significantly higher among White [odds ratio =2.34, 95% credible interval=2.14-2.56; 1.95 (1.85-2.05)], and Hispanic [1.70 (1.54-1.87); 2.18(2.07-2.31)] PWH, compared with Black PWH. These findings remained unchanged after accounting for socio-ecological factors. Rural and urban counties in north-central Florida saw the largest racial/ethnic disparities. CONCLUSIONS: There is persistent, spatially heterogeneous, racial/ethnic disparity in HIV clinical outcomes in Florida. This disparity could not be explained by socio-ecological factors, suggesting that further research on modifiable factors that can improve HIV outcomes among Black and Hispanic PWH in Florida is needed.

Changing COVID-19 cases and deaths detection in Florida.

Epidemic data are often difficult to interpret due to inconsistent detection and reporting. As these data are critically relied upon to inform policy and epidemic projections, understanding reporting trends is similarly important. Early reporting of the COVID-19 pandemic in particular is complicated, due to changing diagnostic and testing protocols. An internal audit by the State of Florida, USA found numerous specific examples of irregularities in COVID-19 case and death reports. Using case, hospitalization, and death data from the the first year of the COVID-19 pandemic in Florida, we present approaches that can be used to identify the timing, direction, and magnitude of some reporting changes. Specifically, by establishing a baseline of detection probabilities from the first (spring) wave, we show that transmission trends among all age groups were similar, with the exception of the second summer wave, when younger people became infected earlier than seniors, by approximately 2 weeks. We also found a substantial drop in case-fatality risk (CFR) among all age groups over the three waves during the first year of the pandemic, with the most drastic changes seen in the 0 to 39 age group. The CFR trends provide useful insights into infection detection that would not be possible by relying on the number of tests alone. During the third wave, for which we have reliable hospitalization data, the CFR was remarkably stable across all age groups. In contrast, the hospitalization-to-case ratio varied inversely with cases while the death-to-hospitalization ratio varied proportionally. Although specific trends are likely to vary between locales, the approaches we present here offer a generic way to understand the substantial changes that occurred in the relationships among the key epidemic indicators.

Recent Latinx immigrants to Miami/Dade County (FL): Travel patterns before, during, and one year after the COVID-19 pandemic lockdown.

INTRODUCTION: Understanding the transportation needs of immigrants is crucial for the design and promotion of safe, equitable, and sustainable living environments. This study examines the transportation patterns from a sample of Recent Latinx Immigrants (RLIs) upon arrival to Miami/Dade Co (MDC), Florida. METHODS: Collected between 2018 and 2021, data came from a longitudinal study examining drinking and driving trajectories among 540 RLIs to MDC. Retrospective pre-immigration data (T0) were obtained simultaneously with the first-year post-immigration data (T1). Follow up surveys were conducted one year later, before (T2-BC) or during a pandemic lockout (T2-DC), and two years later (T3). Descriptive and repeated measures mixed-model regression were used to examine the data. RESULTS: Driving declined from T0 to T1, although remained higher than previously reported for other locations. Not having a valid driver's license was the main reason for the decline. The initial reduction in driving was paralleled by an increase in the use of transit, riding as passengers in private vehicles, and walking. A year later (T2), as RLIs' income and access to a driver's license grew, driving rates increased (even during the pandemic lockdown), while the use of other transportation modes decreased. A year after the pandemic lockdown (T3), driving as well as the use of other transportation modes receded. Reasons for this decline are unclear. CONCLUSIONS: RLIs reported elevated driving rates upon their arrival to MDC. The COVID-19 pandemic seems to have altered the RLIs' transportation patterns, provoking an overall decline in mobility that lasted even after the pandemic lockdown ceased. PRACTICAL APPLICATIONS: Transportation planners working on developing safe and equitable transportation systems in MDC should: (1) identify and address barriers to the use of transportation modes other than driving by RLIs; and (2) understand reasons for the broad decline in transportation modes after the pandemic lockdown.