A framework for the assessment of US and Global Regime for Countering Infectious Diseases.
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This fact sheet highlights best practices and guidelines around HVAC, refrigeration, and space use for grocery operators.
This fact sheet highlights best practices and guidelines around HVAC, exhaust systems, BAS, elevators, and space use for retail operators.
This fact sheet examines best practices and guidelines around HVAC, exhaust systems, BAS, elevators, and space use for hotel/motel operators.
This fact sheet highlights best practices and guidelines around HVAC and space use for commercial office operators.
A fact sheet of best practices and guidelines around HVAC, refrigeration, and space use for grocery operators.
A fact sheet of best practices and guidelines around HVAC, exhaust systems, BAS, elevators, and space use for hotel/motel operators.
A fact sheet of best practices and guidelines around HVAC, exhaust systems, BAS, elevators, and space use for retail operators.
A fact sheet of best practices and guidelines around HVAC and space use for commercial office operators.
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Abstract not provided.
In one embodiment, a prefabricated container is modified as a medical isolation room by replacing an original door with a clear front door. An intake louver and an adjustable damper are disposed at a lower part of the front end. An exhaust vent is disposed at an upper part of the back wall. An exhaust fan and a HEPA filter are coupled to the exhaust vent. Washable coverings cover interior sides of the container to provide washable, nonslip interior surfaces. The exhaust fan and the adjustable damper at the intake louver are controlled to produce in the medical isolation room a negative air pressure of at least about minus 0.01 inch of water gage (approximately 2.5 pascals) and a displacement ventilation exhaust flow rate through the exhaust vent of at least about 100 cubic feet per minute (cfm) greater than an intake flow rate through the intake louver.
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Abstract Background Traditional end points used in registrational randomized, controlled trials (RCTs) often do not allow for complete interpretation of the full range of potential clinical outcomes. Desirability of outcome ranking (DOOR) is an approach to the design and analysis of clinical trials that incorporates benefits and risks of novel treatment strategies and provides a global assessment of patient experience. Methods Through a multidisciplinary committee of experts in infectious diseases, clinical trial design, drug regulation, and patient experience, we developed a DOOR end point for infectious disease syndromes and demonstrated how this could be applied to 3 registrational drug trials (ZEUS, APEKS-cUTI, and DORI-05) for complicated urinary tract infections (cUTIs). ZEUS compared fosfomycin to piperacillin/tazobactam, APEKS-cUTI compared cefiderocol to imipenem, and DORI-05 compared doripenem to levofloxacin. Using DOOR, we estimated the probability of a more desirable outcome with each investigational antibacterial drug. Results In each RCT, the DOOR distribution was similar and the probability that a patient in the investigational arm would have a more desirable outcome than a patient in the control arm had a 95% confidence interval containing 50%, indicating no significant difference between treatment arms. DOOR facilitated improved understanding of potential trade-offs between clinical efficacy and safety. Partial credit and subgroup analyses also highlight unique attributes of DOOR. Conclusions DOOR can effectively be used in registrational cUTI trials. The DOOR end point presented here can be adapted for other infectious disease syndromes and prospectively incorporated into future clinical trials.
Remotely-sensed data and observations are providing powerful new tools for addressing climate and environment-related human health problems through increased capabilities for monitoring, risk mapping, and surveillance of parameters useful to such problems as vector-borne and infectious diseases, air and water quality, harmful algal blooms, UV (ultraviolet) radiation, contaminant and pathogen transport in air and water, and thermal stress. Remote sensing, geographic information systems (GIS), global positioning systems (GPS), improved computational capabilities, and interdisciplinary research between the Earth and health science communities are being combined in rich collaborative efforts resulting in more rapid problem-solving, early warning, and prevention in global health issues. Collaborative efforts among scientists from health and Earth sciences together with local decision-makers are enabling increased understanding of the relationships between changes in temperature, rainfall, wind, soil moisture, solar radiation, vegetation, and the patterns of extreme weather events and the occurrence and patterns of diseases (especially, infectious and vector-borne diseases) and other health problems. This increased understanding through improved information and data sharing, in turn, empowers local health and environmental officials to better predict health problems, take preventive measure, and improve response actions. This paper summarizes the remote sensing systems most useful for climate, environment and health studies of the Caribbean region and provides several examples of interdisciplinary research projects in the Caribbean currently using remote sensing technologies. These summaries include the use of remote sensing of algal blooms, pollution transport, coral reef monitoring, vectorborne disease studies, and potential health effects of African dust on Trinidad and Barbados.
The interplay of a rapidly changing climate and infectious disease occurrence is emerging as a critical topic, requiring investigation of possible direct, as well as indirect, connections between disease processes and climate-related variation and phenomena. First, we introduce and overview three infectious disease exemplars (dengue, influenza, valley fever) representing different transmission classes (insect-vectored, human-to-human, environmentally-transmitted) to illuminate the complex and significant interplay between climate disease processes, as well as to motivate discussion of how Sandia can transform the field, and change our understanding of climate-driven infectious disease spread. We also review state-of-the-art epidemiological and climate modeling approaches, together with data analytics and machine learning methods, potentially relevant to climate and infectious disease studies. We synthesize the modeling and disease exemplars information, suggesting initial avenues for research and development (R&D) in this area, and propose potential sponsors for this work. Whether directly or indirectly, it is certain that a rapidly changing climate will alter global disease burden. The trajectory of climate change is an important control on this burden, from local, to regional and global scales. The efforts proposed herein respond to the National Research Councils call for the creation of a multidisciplinary institute that would address critical aspects of these interlocking, cascading crises.
The teaching hospital of the Faculty of Veterinary Medicine at the University of Lisbon hosts a Biological Isolation and Containment Unit (BICU) for the hospitalization of both confirmed and suspected animals of an infectious disease. This study targets the BICU dog population to identify and characterize the most frequent infectious diseases recorded in a 7-year period. Several epidemiologic factors were analyzed for their significance to triage infected cases. During the study period, 534 dogs were admitted, of which 263 (49.3%) had a confirmed infectious disease diagnosis: parvovirosis (49.4%; n = 130); leptospirosis (21.7%; n = 57); multidrug-resistant (MDR) bacterial infection; (10.6%; n = 28), and canine distemper (9.9%; n = 26). Several potential risk factors for these diseases were identified: age under 2 years old (p < 0.001), incomplete vaccination for parvovirosis (p < 0.001), age ≥ 10 years old (p < 0.001), and the presence of concomitant disorders for MDR-infected cases (p = 0.03). Logistic regression models were constructed to classify cases and controls. The sensitivity and specificity estimates were very high (>0.83) for parvovirosis, MDR, and distemper infections. A lower sensitivity (0.77) was obtained for identifying cases with leptospirosis. In conclusion, infectious diseases are frequent, hence, it is essential to decrease their occurrence through effective preventive measures such as vaccination. The constructed logistic models can also help in triaging admitted dogs with a potential infectious disease.