Electronic Nicotine Delivery Systems (ENDS) use Among Members of a Community Engagement Program.

Electronic nicotine delivery systems (ENDS) are relatively new and ENDS use data from community engagement programs may help us understand usage patterns and facilitate targeted longitudinal studies. Community members in Florida, USA, were asked about ENDS use, tobacco use, and health history/concerns by Community Health Workers. Among 7253 members recruited during 2014 to 2021 into our HealthStreet program, 1177 had ever used ENDS; the proportion increased from 12 to 27% from 2014 to 2021 (adjusted odds ratio (aOR) 2.5; 95% CI 1.7-3.5; Ever versus never used ENDS). Ever tobacco use was strongly associated with ENDS use; 69% of ever users were current tobacco users. Demographic determinants (sex, age, race) and food insecurity were strongest predictors of ENDS use. Most who had ever used ENDS were aged 18-25 (aOR 5.9; 95% CI 4.6-7.6; vs. aged 60 + years), White (aOR 3.7; 95% CI 3.2-4.3; vs. Black/African American), male (aOR 1.5; 95% CI 1.3-1.7; vs. female), and recently food insecure (aOR 1.8; 95% CI 1.5-2.0; vs. not recently food insecure). Those with respiratory issues were more likely to have used ENDS compared to those without (aOR 2.0; 95% CI 1.6-2.6; aOR 1.3; 95% CI 1.1-1.5). Members concerned about hypertension were less likely to have used ENDS (aOR 0.7; 95% CI 0.5-0.9). In this relatively rural, micropolitan sample, tobacco use, socio-economic determinants, and certain health history/concerns were strongly associated with ENDS use. Community outreach approaches are needed to further understand these factors and implement interventions.

Evaluation of NEON Data to Model Spatio-Temporal Tick Dynamics in Florida.

In 2013, the National Ecological Observatory Network (NEON) started collecting 30-year multi-faceted ecological data at various spatial and temporal scales across the US including ticks. Understanding the abundance and dynamics of disease vectors under changing environmental conditions in the long-term is important to societies, but sustained long-term collection efforts are sparse. Using hard-bodied tick data collected by NEON, the vegetation and atmospheric data and a statistical state-space model, which included a detection probability component, this study estimated the abundance of tick nymphs and adult ticks across a Florida NEON location. It took into account the spatial and temporal variation, and factors affecting detection. Its purpose was to test the applicability of data collected thus far and evaluate tick abundance. The study found an increase in tick abundance at this Florida location, and was able to explain spatial and temporal variability in abundance and detection. This approach shows the potential of NEON data. The NEON data collection is unique in scale, and promises to be of great value to understand tick and disease dynamics across the US. From a public health perspective, the detection probability of vectors can be interpreted as the probability of encountering that vector, making these types of analyses useful for estimating disease risk.

A spatiotemporal natural-human database to evaluate road development impacts in an Amazon trinational frontier.

Road construction and paving bring socio-economic benefits to receiving regions but can also be drivers of deforestation and land cover change. Road infrastructure often increases migration and illegal economic activities, which in turn affect local hydrology, wildlife, vegetation structure and dynamics, and biodiversity. To evaluate the full breadth of impacts from a coupled natural-human systems perspective, information is needed over a sufficient timespan to include pre- and post-road paving conditions. In addition, the spatial scale should be appropriate to link local human activities and biophysical system components, while also allowing for upscaling to the regional scale. A database was developed for the tri-national frontier in the Southwestern Amazon, where the Inter-Oceanic Highway was constructed through an area of high biological value and cultural diversity. Extensive socio-economic surveys and botanical field work are combined with remote sensing and reanalysis data to provide a rich and unique database, suitable for coupled natural-human systems research.

Using Cluster Analysis to Compartmentalize a Large Managed Wetland Based on Physical, Biological, and Climatic Geospatial Attributes.

Hierarchical and partitional cluster analyses were used to compartmentalize Water Conservation Area 1, a managed wetland within the Arthur R. Marshall Loxahatchee National Wildlife Refuge in southeast Florida, USA, based on physical, biological, and climatic geospatial attributes. Single, complete, average, and Ward's linkages were tested during the hierarchical cluster analyses, with average linkage providing the best results. In general, the partitional method, partitioning around medoids, found clusters that were more evenly sized and more spatially aggregated than those resulting from the hierarchical analyses. However, hierarchical analysis appeared to be better suited to identify outlier regions that were significantly different from other areas. The clusters identified by geospatial attributes were similar to clusters developed for the interior marsh in a separate study using water quality attributes, suggesting that similar factors have influenced variations in both the set of physical, biological, and climatic attributes selected in this study and water quality parameters. However, geospatial data allowed further subdivision of several interior marsh clusters identified from the water quality data, potentially indicating zones with important differences in function. Identification of these zones can be useful to managers and modelers by informing the distribution of monitoring equipment and personnel as well as delineating regions that may respond similarly to future changes in management or climate.