RESUMEN
BACKGROUND: The novel coronavirus disease (COVID-19) has afflicted millions of people worldwide since its first case was reported in December 2019. Personal protective equipment (PPE) has been tailored accordingly, but as of April 2020, close to 10 000 health care workers in the United States have contracted COVID-19 despite wearing recommended PPE. As such, standard guidelines for PPE may be inadequate for the health care worker performing high-risk aerosolizing procedures such as endotracheal intubation. In this brief technical report, we describe the integration of an orthopedic hood cover as an item for full barrier protection against COVID-19 transmission. TECHNICAL DESCRIPTION: The Coronavirus Airway Task Force at Virginia Commonwealth University Medical Center approved this initiative and went live with the full barrier suit during the last week of March 2020. The PPE described in this report includes a Stryker T4 Hood, normally used in conjunction with the Stryker Steri-Shield T4 Helmet. Instead of the helmet, the hood is secured to the head via a baseball cap and binder clip. This head covering apparatus is to be used as an accessory to other PPE items that include an N95 mask, waterproof gown, and disposable gloves. The motor ventilation system is not used in order to prevent airborne viral entry into the hood. DISCUSSION: An advantage of the full barrier suit is an additional layer of droplet protection during intubation. The most notable disadvantage is the absence of a ventilation system within the hood covering. CONCLUSION: Modification of existing PPE may provide protection for health care workers during high-risk aerosolizing procedures such as endotracheal intubation. Although the integration of this medical equipment meets the immediate needs of an escalating crisis, further innovation is on the horizon. More research is needed to confirm the safety of modified PPE.
RESUMEN
Common goals of ecological fire management are to sustain biodiversity and minimize extinction risk. A novel approach to achieving these goals determines the relative proportions of vegetation growth stages (equivalent to successional stages, which are categorical representations of time since fire) that maximize a biodiversity index. The method combines data describing species abundances in each growth stage with numerical optimization to define an optimal growth-stage structure that provides a conservation-based operational target for managers. However, conservation targets derived from growth-stage optimization are likely to depend critically on choices regarding input data. There is growing interest in the use of growth-stage optimization as a basis for fire management, thus understanding of how input data influence the outputs is crucial. Simulated data sets provide a flexible platform for systematically varying aspects of survey design and species inclusions. We used artificial data with known properties, and a case-study data set from southeastern Australia, to examine the influence of (1) survey design (total number of sites and their distribution among growth stages) and (2) species inclusions (total number of species and their level of specialization) on the precision of conservation targets. Based on our findings, we recommend that survey designs for precise estimates would ideally involve at least 80 sites, and include at least 80 species. Greater numbers of sites and species will yield increasingly reliable results, but fewer might be sufficient in some circumstances. An even distribution of sites among growth stages was less important than the total number of sites, and omission of species is unlikely to have a major influence on results as long as several species specialize on each growth stage. We highlight the importance of examining the responses of individual species to growth stage before feeding survey data into the growth-stage optimization black box, and advocate use of a resampling procedure to determine the precision of results. Collectively, our findings form a reproducible guide to designing ecological surveys that yield precise conservation targets through growth-stage optimization, and ultimately help sustain biodiversity in fire-prone systems.
