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Many infectious disease forecasting models in the United States (US) are built with data partitioned into geopolitical regions centered on human activity as opposed to regions defined by natural ecosystems; although useful for data collection and intervention, this has the potential to mask biological relationships between the environment and disease. We explored this concept by analyzing the correlations between climate and West Nile virus (WNV) case data aggregated to geopolitical and ecological regions. We compared correlations between minimum, maximum, and mean annual temperature; precipitation; and annual WNV neuroinvasive disease (WNND) case data from 2005 to 2019 when partitioned into (a) climate regions defined by the National Oceanic and Atmospheric Administration (NOAA) and (b) Level I ecoregions defined by the Environmental Protection Agency (EPA). We found that correlations between climate and WNND in NOAA climate regions and EPA ecoregions were often contradictory in both direction and magnitude, with EPA ecoregions more often supporting previously established biological hypotheses and environmental dynamics underlying vector‐borne disease transmission. Using ecological regions to examine the relationships between climate and disease cases can enhance the predictive power of forecasts at various scales, motivating a conceptual shift in large‐scale analyses from geopolitical frameworks to more ecologically meaningful regions. Plain Language Summary: In the United States (US), geopolitical subdivisions like states and counties are the governing regions that collect public health data and implement health interventions like risk messaging, mask mandates, or spraying chemicals for mosquito control. These subdivisions were mostly decided by politics and other human activity, not similarities in ecosystems and climate. This can make it difficult to understand how climate affects illnesses like mosquito‐borne disease since mosquitoes will live within specific ecosystems and aren't confined to geopolitical boundaries as health data are. We explored this idea by analyzing the relationships between temperature, precipitation, and the mosquito‐borne pathogen called West Nile virus (WNV) from 2005 to 2019. We grouped our data using two different regional boundaries: (a) climate regions from the National Oceanic and Atmospheric Administration (NOAA), primarily based on state boundaries, and (b) ecoregions from the Environmental Protection Agency (EPA), based on similar ecosystems. We found that these groupings resulted in some contradictory results. The results using EPA ecoregions more often agreed with biological hypotheses, so it may be a better approach to dividing the US for similar studies. We encourage other scientists to consider this conceptual shift from analyzing data by geopolitical boundaries to more ecologically meaningful regions. Key Points: While health data is collected within geopolitical boundaries, environmental disease dynamics are influenced by ecosystem characteristicsFor West Nile virus, correlations between cases and climate were different depending on geopolitical or ecosystem regional groupings of dataWe propose a conceptual shift from analyzing climate and health data at geopolitical boundaries to more ecologically meaningful regions [ABSTRACT FROM AUTHOR]

This study explores potential adaptation approaches in planning and management that the United States Forest Service might adopt to help achieve its goals and objectives in the face of climate change. Availability of information, vulnerability of ecological and socio-economic systems, and uncertainties associated with climate change, as well as the interacting non-climatic changes, influence selection of the adaptation approach. Resource assessments are opportunities to develop strategic information that could be used to identify and link adaptation strategies across planning levels. Within a National Forest, planning must incorporate the opportunity to identify vulnerabilities to climate change as well as incorporate approaches that allow management adjustments as the effects of climate change become apparent. The nature of environmental variability, the inevitability of novelty and surprise, and the range of management objectives and situations across the National Forest System implies that no single approach will fit all situations. A toolbox of management options would include practices focused on forestalling climate change effects by building resistance and resilience into current ecosystems, and on managing for change by enabling plants, animals, and ecosystems to adapt to climate change. Better and more widespread implementation of already known practices that reduce the impact of existing stressors represents an important "no regrets" strategy. These management opportunities will require agency consideration of its adaptive capacity, and ways to overcome potential barriers to these adaptation options.

Many isolates of meticillin-resistant Staphylococcus aureus (MRSA) are indistinguishable when compared using the standard pulsed-field gel electrophoresis (PFGE) typing method. This may present a problem when investigating local outbreaks of MRSA transmission in a healthcare setting. It also impedes investigation of the widely disseminated community-acquired MRSA (USA 300-0114) in the inpatient setting, which is displacing other traditional hospital-acquired PFGE types. Combination of methods, including multiple-locus sequence typing (MLST), spa typing and staphylococcal cassette chromosome mec (SCCmec) typing, have been used with, or in place of, PFGE to characterise MRSA for epidemiological purposes. These methods are technically challenging, time-consuming and expensive and are rarely feasible except in large laboratories in tertiary care medical centres. Another method, which is simpler and with faster turnaround time, is multiple-locus variable-number tandem-repeat analysis (MLVA). We investigated the utility of MLVA to distinguish common PFGE types. The results suggest that MLVA can be used to identify unrelated strains with identical PFGE patterns or confirm close genetic composition of linked isolates. MLVA could potentially be used in conjunction with PFGE to validate relationships, but further prospective evaluation of these relationships will be required in order to define the proper role, if any, for use of this method in hospital epidemiology.

Implantation of the first automatic defibrillator occurred in February 1980. Incorporation of cardioversion capability in 1982 resulted in the AICD automatic implantable cardioverter defibrillator. Between April 1, 1982 and April 15, 1988, 3610 patients in 236 U.S. and 84 international centers received AICD pulse generators. Patient population consisted of 2904 males and 683 females with recurrent ventricular tachycardia and/or fibrillation, mean age 59 yrs. (range 9-96 yrs.). Primary diagnoses reported for the patient group were: coronary artery disease (63.5%), nonischemic cardiomyopathy (12.9%), other (6.4%) and unspecified (17.2%). Mean reported LV ejection fraction was 32.8%. Follow-up averaged 12.2 mo. (range 0-72 mo.). Of 385 deaths, 94 (24%) were sudden. Cumulative percentage survival (+/- S.E.) from sudden cardiac death (SCD) was 98.0 +/- 0.3%, 96.5 +/- 0.5%, 95.2 +/- 0.7%, 93.7 +/- 1.0%, 93.7 +/- 1.0% and 89.7 +/- 4.0% at 12, 24, 36, 48, 60 and 72 months, respectively. Operative mortality (less than or equal to 30 days) was 2.5%. Reported side effects/complications were similar to those of pacemakers. To date, 33% of the patients received spontaneous device countershocks. AICD pulse generator survival from electrical and mechanical failures was 92.8 +/- 0.5%, 88.4 +/- 0.7%, 86.7 +/- 0.8% and 86.4 +/- 0.9% at 12, 18, 24 and 30 mos. Data analysis demonstrates that the AICD has had a significant impact on patient survival from SCD.