Developmental framework for a desktop hydrogeomorphic wetland functional assessment derived from field-based data.

With loss of wetlands and their associated ecosystem services within landscapes, it is imperative to be able to understand the change in ecological functions underlying these services. Field-based functional assessments can produce a range of specific scores among a robust set of functions but are time and cost prohibitive as the number of wetlands assessed increases. Remote-based functional assessments are an alternative for broad scale assessments, but trade-off cost for limitations in scoring and functional assemblage. To address these concerns, we created a framework for the development of the Hydrogeomorphic Remote Assessment of Wetland Function (HGM-RAWF). Rooted in the hydrogeomorphic approach of an existing field-based functional assessment and its underlying models, this remote functional assessment substitutes field-based assessment methods with remotely assessed proxies. As potential remote proxies were determined through literature review and statistically screened for use in the remote assessment, a field-based reference wetland database of 222 freshwater wetlands in the Mid-Atlantic Region provided a baseline by which remote data could be compared and calibrated. The resulting HGM-RAWF protocol remotely assesses seven hydrology and biogeochemistry functions in the Mid-Atlantic with assessment scores similar to its field-based counterparts. With noted limitations, the HGM-RAWF framework provides the means to create desktop functional assessments across broad geographic scales with the diversity and specificity of field-based assessments at the reduced costs associated with remote assessments. Its basis in the HGM approach and use of public spatial datasets allows the framework to be adopted regionally and can be used as a model for national wetland functional assessment.

Designing for caregiving networks: a case study of primary caregivers of children with medical complexity.

OBJECTIVE: The study aimed to characterize the experiences of primary caregivers of children with medical complexity (CMC) in engaging with other members of the child's caregiving network, thereby informing the design of health information technology (IT) for the caregiving network. Caregiving networks include friends, family, community members, and other trusted individuals who provide resources, information, health, or childcare. MATERIALS AND METHODS: We performed a secondary analysis of two qualitative studies. Primary studies conducted semi-structured interviews (n = 50) with family caregivers of CMC. Interviews were held in the Midwest (n = 30) and the mid-Atlantic region (n = 20). Interviews were transcribed verbatim for thematic analysis. Emergent themes were mapped to implications for the design of future health IT. RESULTS: Thematic analysis identified 8 themes characterizing a wide range of primary caregivers' experiences in constructing, managing, and ensuring high-quality care delivery across the caregiving network. DISCUSSION: Findings evidence a critical need to create flexible and customizable tools designed to support hiring/training processes, coordinating daily care across the caregiving network, communicating changing needs and care updates across the caregiving network, and creating contingency plans for instances where caregivers are unavailable to provide care to the CMC. Informaticists should additionally design accessible platforms that allow primary caregivers to connect with and learn from other caregivers while minimizing exposure to sensitive or emotional content as indicated by the user. CONCLUSION: This article contributes to the design of health IT for CMC caregiving networks by uncovering previously underrecognized needs and experiences of CMC primary caregivers and drawing direct connections to design implications.

Phosphorus speciation in manure and fertilizer impacted Mid-Atlantic coastal plain soils.

Historical applications of manures and fertilizers at rates exceeding crop P removal in the Mid-Atlantic region (United States) have resulted in decades of increased water quality degradation from P losses in agricultural runoff. As such, many growers in this region face restrictions on future P applications. An improved understanding of the fate, transformations, and availability of P is needed to manage P-enriched soils. We paired chemical extractions (i.e., Mehlich-3, water extractable P, and chemical fractionation) with nondestructive methods (i.e., x-ray absorption near edge structure [XANES] spectroscopy and x-ray fluorescence [XRF]) to investigate P dynamics in eight P-enriched Mid-Atlantic soils with various management histories. Chemical fractionation and XRF data were used to support XANES linear combination fits, allowing for identification of various Al, Ca, and Fe phosphates and P sorbed phases in soils amended with fertilizer, poultry litter, or dairy manure. Management history and P speciation were used to make qualitative comparisons between the eight legacy P soils; we also speculate about how P speciation may affect future management of these soils with and without additional P applications. With continued P applications, we expect an increase in semicrystalline Al and Fe-P, P sorbed to Al (hydro)oxides, and insoluble Ca-P species in these soils for all P sources. Under drawdown scenarios, we expect plant P uptake first from semicrystalline Al and Fe phosphates followed by P sorbed phases. Our results can help guide management decisions on coastal plain soils with a history of P application.

Mapping the distribution of Lyme disease at a mid-Atlantic site in the United States using electronic health data.

Lyme disease is a spatially heterogeneous tick-borne infection, with approximately 85% of US cases concentrated in the mid-Atlantic and northeastern states. Surveillance for Lyme disease and its causative agent, including public health case reporting and entomologic surveillance, is necessary to understand its endemic range, but currently used case detection methods have limitations. To evaluate an alternative approach to Lyme disease surveillance, we have performed a geospatial analysis of Lyme disease cases from the Johns Hopkins Health System in Maryland. We used two sources of cases: a) individuals with both a positive test for Lyme disease and a contemporaneous diagnostic code consistent with a Lyme disease-related syndrome; and b) individuals referred for a Lyme disease evaluation who were adjudicated to have Lyme disease. Controls were individuals from the referral cohort judged not to have Lyme disease. Residential address data were available for all cases and controls. We used a hierarchical Bayesian model with a smoothing function for a coordinate location to evaluate the probability of Lyme disease within 100 km of Johns Hopkins Hospital. We found that the probability of Lyme disease was greatest in the north and west of Baltimore, and the local probability that a subject would have Lyme disease varied by as much as 30-fold. Adjustment for demographic and ecological variables partially attenuated the spatial gradient. Our study supports the suitability of electronic medical record data for the retrospective surveillance of Lyme disease.