Evaluation of Microwave Steam Bags for the Decontamination of Filtering Facepiece Respirators

Reusing filtering facepiece respirators (FFRs) has been suggested as a strategy to conserve available supplies for home and healthcare environments during an influenza pandemic. For reuse to be possible, used FFRs must be decontaminated before redonning to reduce the risk of virus transmission; however, there are no approved methods for FFR decontamination. An effective method must reduce the microbial threat, maintain the function of the FFR, and present no residual chemical hazard. The method should be readily available, inexpensive and easily implemented by healthcare workers and the general public. Many of the general decontamination protocols used in healthcare and home settings are unable to address all of the desired qualities of an efficient FFR decontamination protocol. The goal of this study is to evaluate the use of two commercially available steam bags, marketed to the public for disinfecting infant feeding equipment, for FFR decontamination. The FFRs were decontaminated with microwave generated steam following the manufacturers' instructions then evaluated for water absorption and filtration efficiency for up to three steam exposures. Water absorption of the FFR was found to be model specific as FFRs constructed with hydrophilic materials absorbed more water. The steam had little effect on FFR performance as filtration efficiency of the treated FFRs remained above 95%. The decontamination efficacy of the steam bag was assessed using bacteriophage MS2 as a surrogate for a pathogenic virus. The tested steam bags were found to be 99.9% effective for inactivating MS2 on FFRs; however, more research is required to determine the effectiveness against respiratory pathogens

Time preferences and risk aversion: tests on domain differences

The design and evaluation of environmental policy requires the incorporation of time and risk elements as many environmental outcomes extend over long time periods and involve a large degree of uncertainty. Understanding how individuals discount and evaluate risks with respect to environmental outcomes is a prime component in designing effective environmental policy to address issues of environmental sustainability, such as climate change. Our objective in this study is to investigate whether subjects' time preferences and risk aversion across the monetary domain and the environmental domain differ. Crucially, our experimental design is incentivized: in the monetary domain, time preferences and risk aversion are elicited with real monetary payoffs, whereas in the environmental domain, we elicit time preferences and risk aversion using real (bee-friendly) plants. We find that subjects' time preferences are not significantly different across the monetary and environmental domains. In contrast, subjects' risk aversion is significantly different across the two domains. More specifically, subjects (men and women) exhibit a higher degree of risk aversion in the environmental domain relative to the monetary domain. Finally, we corroborate earlier results, which document that women are more risk averse than men in the monetary domain. We show this finding to, also, hold in the environmental domain

Is imprecise knowledge better than conflicting expertise? Evidence from insurers’ decisions in the United States

This paper reports the results of the first experiment in the United States designed to distinguish between two sources of ambiguity: imprecise ambiguity (expert groups agree on a range of probability, but not on any point estimate) versus conflict ambiguity (each expert group provides a precise probability estimate which differs from one group to another). The specific context is whether risk professionals (here, insurers) behave differently under risk (when probability is well-specified) and different types of ambiguity in pricing catastrophic risks (floods and hurricanes) and non-catastrophic risks (house fires). The data show that insurers charge higher premiums when faced with ambiguity than when the probability of a loss is well specified (risk). Furthermore, they tend to charge more for conflict ambiguity than imprecise ambiguity for flood and hurricane hazards, but less in the case of fire. The source of ambiguity also impacts causal inferences insurers make to reduce their uncertainty