Perspectives on valuing water quality improvements using stated preference methods.

Improvements to the quality of freshwater rivers and lakes can generate a wide array of benefits, from "use values" such as recreational boating, fishing, and swimming to "nonuse values" such as improved outcomes for aquatic biodiversity. Bringing these nonmarket values into decision-making is crucial to determining appropriate levels of investment in water quality improvements. However, progress in the economic valuation of water quality benefits has lagged similar efforts to value air quality benefits, with implications for water policy. New data sources, modeling techniques, and innovation in stated preference survey methods offer notable improvements to estimates of use and nonuse benefits of improved water quality. Here, we provide a perspective on how recent applications of stated preference techniques to the valuation of the nonmarket benefits of water quality improvements have advanced the field of environmental valuation. This overview is structured around four key questions: i) What is it about water quality that we seek to value? ii) How should we design and implement the surveys which elicit individuals' stated preferences? iii) How do we assess the validity of the findings provided by such studies? and iv) What are the contributions of these valuation exercises to public policy? In answering these questions, we make reference to the contributions provided by the papers in this Symposium.

Mallard landing behavior on water follows a -constant braking strategy.

Many flying animals use optic flow to control their flight. During landing maneuvers, pigeons, hummingbirds, bats, Draco lizards and bees use the -constant braking strategy. This strategy regulates the approach by keeping the ratio of distance to an object and the rate of change of that distance constant. In keeping this ratio, , constant, a variety of deceleration profiles can lead to different collision avoidance behaviors. The landing behaviors listed above all qualify as controlled collisions, where the animal is decelerating into the object. We examined whether the same regulatory strategy is employed by mallards when landing on water. Video of mallard landing behavior was recorded at a local pond and digitized. Kinematic and τ parameters were calculated for each landing (N=177). The Pearson correlation coefficient for τ with respect to time to land was 0.99±0.02, indicating mallards employ a controlled-collision strategy. This result implies regulation by the birds to fix as constant while landing (on average, 0.90±0.13). In comparison with other active flyers, mallards use a higher value of when landing (0.775±0.109, 0.710±0.132 and 0.702±0.052 for pigeons, hummingbirds and bats, respectively). This higher may reflect physical differences in substrate from solid to liquid. The higher compliance of water in comparison to a solid substrate may reduce impact forces that could be injurious on a solid substrate, thereby enabling mallards to approach faster and expend less energy for costly, slow flight.

Willingness to pay for policies to reduce health risks from COVID-19: Evidence from U.S. professional sports.

Airborne transmission of the COVID-19 virus increased the need for health policies to reduce transmission in congregate settings associated with minimal risk before the pandemic. While a large literature estimates tradeoffs between policies designed to reduce negative health outcomes, no empirical research addresses consumer willingness to pay (WTP) for health policies designed to reduce airborne virus transmission. Using survey data from 1381 fans of professional sports, we estimate consumers' WTP for reduced likelihood of coronavirus transmission through mask and social distancing policies using a stated preference approach. The results indicate increased attendance likelihood if the venue requires masks and limits attendance, with significant heterogeneity in WTP across risk scenarios and sports. We characterize consumers as casual fans who prefer a mask requirement but are indifferent to capacity constraints, strong fans who are anti-maskers and prefer capacity constraints, and a second group of casual fans with positive WTP under both mask and limited capacity requirements. For example, casual fans' WTP for masking, $38 per National Basketball Association (NBA) game attended, is more than double their WTP for capacity constraints only. Strong fans' WTP for attending capacity constrained NBA games was $490, more than 400% higher than the pre-pandemic average WTP of $105.

Combining revealed and stated preference models for artificial reef siting: A study in the Florida Keys.

This paper investigates divers' preferences for artificial reef diving and willingness to pay (WTP) for large ship, artificial reef site attributes in the Florida Keys. We investigate diver demand for existing decommissioned ships that have been sunk off the Florida Keys as well as demand for four new vessels that are available for disposal from the U.S. Department of Transportation Maritime Administration inventory. Using survey data from divers, we compare revealed preference (RP) site choices, stated preference (SP) choices from a discrete choice experiment, and joint RP/SP choices. Our analysis also incorporates stated attribute non-attendance (ANA) at the choice-task level. Our results indicate that the joint RP/SP models with stated ANA are preferred, leading to decreases in marginal WTP as well as decreases in the variability of marginal WTP estimates in the 95% confidence intervals. Results provide a framework for directing more efficient future decision making regarding sinkings at locations that will enhance welfare for divers.

Why is it so difficult to study magnetic compass orientation in murine rodents?

A magnetic compass sense has been demonstrated in all major classes of vertebrates, as well as in many invertebrates. In mammals, controlled laboratory studies of mice have provided evidence for a robust magnetic compass that is comparable to, or exceeds, the performance of that in other animals. Nevertheless, the vast majority of laboratory studies of spatial behavior and cognition in murine rodents have failed to produce evidence of sensitivity to magnetic cues. Given the central role that a magnetic compass sense plays in the spatial ecology and cognition of non-mammalian vertebrates, and the potential utility that a global/universal reference frame derived from the magnetic field would have in mammals, the question of why responses to magnetic cues have been so difficult to demonstrate reliably is of considerable importance. In this paper, we review evidence that the magnetic compass of murine rodents shares a number of properties with light-dependent compasses in a wide variety of other animals generally believed to be mediated by a radical pair mechanism (RPM) or related quantum process. Consistent with the RPM, we summarize both published and previously unpublished findings suggesting that the murine rodent compass is sensitive to low-level radio frequency (RF) fields. Finally, we argue that the presence of anthropogenic RF fields in laboratory settings, may be an important source of variability in responses of murine rodents to magnetic cues.

Estimation of treatment effects following a sequential trial of multiple treatments.

When a clinical trial is subject to a series of interim analyses as a result of which the study may be terminated or modified, final frequentist analyses need to take account of the design used. Failure to do so may result in overstated levels of significance, biased effect estimates and confidence intervals with inadequate coverage probabilities. A wide variety of valid methods of frequentist analysis have been devised for sequential designs comparing a single experimental treatment with a single control treatment. It is less clear how to perform the final analysis of a sequential or adaptive design applied in a more complex setting, for example, to determine which treatment or set of treatments amongst several candidates should be recommended. This article has been motivated by consideration of a trial in which four treatments for sepsis are to be compared, with interim analyses allowing the dropping of treatments or termination of the trial to declare a single winner or to conclude that there is little difference between the treatments that remain. The approach taken is based on the method of Rao-Blackwellization which enhances the accuracy of unbiased estimates available from the first interim analysis by taking their conditional expectations given final sufficient statistics. Analytic approaches to determine such expectations are difficult and specific to the details of the design: instead "reverse simulations" are conducted to construct replicate realizations of the first interim analysis from the final test statistics. The method also provides approximate confidence intervals for the differences between treatments.

Altruistic and Private Values For Saving Lives With an Oyster Consumption Safety Program.

We use data from an Internet-based survey and estimate the benefits of an oyster consumption safety policy with the contingent valuation method. In addition to providing a context-specific estimate of willingness-to-pay for oyster safety, we consider an important issue in the contingent valuation mortality risk reduction literature. A number of studies find that willingness-to-pay for mortality risk reduction is not sensitive to the scope of the risk change. We present the scope test as a difference in the number of lives saved by the program, instead of small changes in risk, and find that referendum votes are responsive to scope. A third feature of this article is that we identify those at-risk respondents who would most benefit from the policy and decompose willingness-to-pay into use values and altruistic nonuse values. We find that willingness-to-pay per life saved ranges from $3.95 million to $7.69 million for the private good of lives saved when the respondent is at risk (i.e., use values). Willingness-to-pay per life saved including both use and altruistic nonuse values ranges from $6.89 million to $12.87 million.

Valuing Hemlock Woolly Adelgid Control in Public Forests: Scope Effects with Attribute Non-Attendance.

Sensitivity to the scope of public good provision is an important indication of validity for the contingent valuation method. An online survey was administered to an opt-in non-probability sample panel to estimate the willingness-to-pay to protect hemlock trees from a destructive invasive species on federal land in North Carolina. We collected survey responses from 907 North Carolina residents. We find evidence that attribute non-attendance (ANA) is a factor when testing for sensitivity to scope. When estimating the model with stated ANA, the ecologically and socially important scope coefficients become positive and statistically significant with economically significant marginal willingness-to-pay estimates.

Experimental Treatment of Ebola Virus Disease with TKM-130803: A Single-Arm Phase 2 Clinical Trial.

BACKGROUND: TKM-130803, a small interfering RNA lipid nanoparticle product, has been developed for the treatment of Ebola virus disease (EVD), but its efficacy and safety in humans has not been evaluated. METHODS AND FINDINGS: In this single-arm phase 2 trial, adults with laboratory-confirmed EVD received 0.3 mg/kg of TKM-130803 by intravenous infusion once daily for up to 7 d. On days when trial enrolment capacity was reached, patients were enrolled into a concurrent observational cohort. The primary outcome was survival to day 14 after admission, excluding patients who died within 48 h of admission. After 14 adults with EVD had received TKM-130803, the pre-specified futility boundary was reached, indicating a probability of survival to day 14 of ≤0.55, and enrolment was stopped. Pre-treatment geometric mean Ebola virus load in the 14 TKM-130803 recipients was 2.24 × 109 RNA copies/ml plasma (95% CI 7.52 × 108, 6.66 × 109). Two of the TKM-130803 recipients died within 48 h of admission and were therefore excluded from the primary outcome analysis. Of the remaining 12 TKM-130803 recipients, nine died and three survived. The probability that a TKM-130803 recipient who survived for 48 h will subsequently survive to day 14 was estimated to be 0.27 (95% CI 0.06, 0.58). TKM-130803 infusions were well tolerated, with 56 doses administered and only one possible infusion-related reaction observed. Three patients were enrolled in the observational cohort, of whom two died. CONCLUSIONS: Administration of TKM-130803 at a dose of 0.3 mg/kg/d by intravenous infusion to adult patients with severe EVD was not shown to improve survival when compared to historic controls. TRIAL REGISTRATION: Pan African Clinical Trials Registry PACTR201501000997429.

Trial design for evaluating novel treatments during an outbreak of an infectious disease.

Tragically, the outbreak of Ebola that started in West Africa in 2014 has been far more extensive and damaging than any previous outbreaks. The duration of the outbreak has, for the first time, allowed the clinical evaluation of Ebola treatments. This article discusses the designs used for two such clinical trials which have recruited patients in Liberia and Sierra Leone. General principles are outlined for trial designs intended to be deployed quickly, adapt flexibly and provide results soon enough to influence the course of the current epidemic rather than just providing evidence for use should Ebola break out again. Lessons are drawn for the conduct of clinical research in future outbreaks of infectious diseases, where the sequence of events may or may not be similar to the West African Ebola epidemic.

Evaluating clinical trial designs for investigational treatments of Ebola virus disease.

BACKGROUND: Experimental treatments for Ebola virus disease (EVD) might reduce EVD mortality. There is uncertainty about the ability of different clinical trial designs to identify effective treatments, and about the feasibility of implementing individually randomised controlled trials during an Ebola epidemic. METHODS AND FINDINGS: A treatment evaluation programme for use in EVD was devised using a multi-stage approach (MSA) with two or three stages, including both non-randomised and randomised elements. The probabilities of rightly or wrongly recommending the experimental treatment, the required sample size, and the consequences for epidemic outcomes over 100 d under two epidemic scenarios were compared for the MSA, a sequential randomised controlled trial (SRCT) with up to 20 interim analyses, and, as a reference case, a conventional randomised controlled trial (RCT) without interim analyses. Assuming 50% 14-d survival in the population treated with the current standard of supportive care, all designs had similar probabilities of identifying effective treatments correctly, while the MSA was less likely to recommend treatments that were ineffective. The MSA led to a smaller number of cases receiving ineffective treatments and faster roll-out of highly effective treatments. For less effective treatments, the MSA had a high probability of including an RCT component, leading to a somewhat longer time to roll-out or rejection. Assuming 100 new EVD cases per day, the MSA led to between 6% and 15% greater reductions in epidemic mortality over the first 100 d for highly effective treatments compared to the SRCT. Both the MSA and SRCT led to substantially fewer deaths than a conventional RCT if the tested interventions were either highly effective or harmful. In the proposed MSA, the major threat to the validity of the results of the non-randomised components is that referral patterns, standard of care, or the virus itself may change during the study period in ways that affect mortality. Adverse events are also harder to quantify without a concurrent control group. CONCLUSIONS: The MSA discards ineffective treatments quickly, while reliably providing evidence concerning effective treatments. The MSA is appropriate for the clinical evaluation of EVD treatments.

Bayesian methods for setting sample sizes and choosing allocation ratios in phase II clinical trials with time-to-event endpoints.

Conventional phase II trials using binary endpoints as early indicators of a time-to-event outcome are not always feasible. Uveal melanoma has no reliable intermediate marker of efficacy. In pancreatic cancer and viral clearance, the time to the event of interest is short, making an early indicator unnecessary. In the latter application, Weibull models have been used to analyse corresponding time-to-event data. Bayesian sample size calculations are presented for single-arm and randomised phase II trials assuming proportional hazards models for time-to-event endpoints. Special consideration is given to the case where survival times follow the Weibull distribution. The proposed methods are demonstrated through an illustrative trial based on uveal melanoma patient data. A procedure for prior specification based on knowledge or predictions of survival patterns is described. This enables investigation into the choice of allocation ratio in the randomised setting to assess whether a control arm is indeed required. The Bayesian framework enables sample sizes consistent with those used in practice to be obtained. When a confirmatory phase III trial will follow if suitable evidence of efficacy is identified, Bayesian approaches are less controversial than for definitive trials. In the randomised setting, a compromise for obtaining feasible sample sizes is a loss in certainty in the specified hypotheses: the Bayesian counterpart of power. However, this approach may still be preferable to running a single-arm trial where no data is collected on the control treatment. This dilemma is present in most phase II trials, where resources are not sufficient to conduct a definitive trial.

Bayesian sample sizes for exploratory clinical trials comparing multiple experimental treatments with a control.

In this paper, a Bayesian approach is developed for simultaneously comparing multiple experimental treatments with a common control treatment in an exploratory clinical trial. The sample size is set to ensure that, at the end of the study, there will be at least one treatment for which the investigators have a strong belief that it is better than control, or else they have a strong belief that none of the experimental treatments are substantially better than control. This criterion bears a direct relationship with conventional frequentist power requirements, while allowing prior opinion to feature in the analysis with a consequent reduction in sample size. If it is concluded that at least one of the experimental treatments shows promise, then it is envisaged that one or more of these promising treatments will be developed further in a definitive phase III trial. The approach is developed in the context of normally distributed responses sharing a common standard deviation regardless of treatment. To begin with, the standard deviation will be assumed known when the sample size is calculated. The final analysis will not rely upon this assumption, although the intended properties of the design may not be achieved if the anticipated standard deviation turns out to be inappropriate. Methods that formally allow for uncertainty about the standard deviation, expressed in the form of a Bayesian prior, are then explored. Illustrations of the sample sizes computed from the new method are presented, and comparisons are made with frequentist methods devised for the same situation.

Bayesian adaptive dose-escalation procedures for binary and continuous responses utilizing a gain function.

One of the main aims of early phase clinical trials is to identify a safe dose with an indication of therapeutic benefit to administer to subjects in further studies. Ideally therefore, dose-limiting events (DLEs) and responses indicative of efficacy should be considered in the dose-escalation procedure. Several methods have been suggested for incorporating both DLEs and efficacy responses in early phase dose-escalation trials. In this paper, we describe and evaluate a Bayesian adaptive approach based on one binary response (occurrence of a DLE) and one continuous response (a measure of potential efficacy) per subject. A logistic regression and a linear log-log relationship are used respectively to model the binary DLEs and the continuous efficacy responses. A gain function concerning both the DLEs and efficacy responses is used to determine the dose to administer to the next cohort of subjects. Stopping rules are proposed to enable efficient decision making. Simulation results shows that our approach performs better than taking account of DLE responses alone. To assess the robustness of the approach, scenarios where the efficacy responses of subjects are generated from an Emax model, but modelled by the linear log-log model are also considered. This evaluation shows that the simpler log-log model leads to robust recommendations even under this model showing that it is a useful approximation to the difficulty in estimating Emax model. Additionally, we find comparable performance to alternative approaches using efficacy and safety for dose-finding.

One-stage and two-stage designs for phase II clinical trials with survival endpoints.

This work is motivated by trials in rapidly lethal cancers or cancers for which measuring shrinkage of tumours is infeasible. In either case, traditional phase II designs focussing on tumour response are unsuitable. Usually, tumour response is considered as a substitute for the more relevant but longer-term endpoint of death. In rapidly lethal cancers such as pancreatic cancer, there is no need to use a surrogate, as the definitive endpoint is (sadly) available so soon. In uveal cancer, there is no counterpart to tumour response, and so, mortality is the only realistic response available. Cytostatic cancer treatments do not seek to kill tumours, but to mitigate their effects. Trials of such therapy might also be based on survival times to death or progression, rather than on tumour shrinkage. Phase II oncology trials are often conducted with all study patients receiving the experimental therapy, and this approach is considered here. Simple extensions of one-stage and two-stage designs based on binary responses are presented. Outcomes based on survival past a small number of landmark times are considered: here, the case of three such times is explored in examples. This approach allows exact calculations to be made for both design and analysis purposes. Simulations presented here show that calculations based on normal approximations can lead to loss of power when sample sizes are small. Two-stage versions of the procedure are also suggested.

Bayesian methods for the design and interpretation of clinical trials in very rare diseases.

This paper considers the design and interpretation of clinical trials comparing treatments for conditions so rare that worldwide recruitment efforts are likely to yield total sample sizes of 50 or fewer, even when patients are recruited over several years. For such studies, the sample size needed to meet a conventional frequentist power requirement is clearly infeasible. Rather, the expectation of any such trial has to be limited to the generation of an improved understanding of treatment options. We propose a Bayesian approach for the conduct of rare-disease trials comparing an experimental treatment with a control where patient responses are classified as a success or failure. A systematic elicitation from clinicians of their beliefs concerning treatment efficacy is used to establish Bayesian priors for unknown model parameters. The process of determining the prior is described, including the possibility of formally considering results from related trials. As sample sizes are small, it is possible to compute all possible posterior distributions of the two success rates. A number of allocation ratios between the two treatment groups can be considered with a view to maximising the prior probability that the trial concludes recommending the new treatment when in fact it is non-inferior to control. Consideration of the extent to which opinion can be changed, even by data from the best feasible design, can help to determine whether such a trial is worthwhile.

A revealed preference approach to valuing non-market recreational fishing losses from the Deepwater Horizon oil spill.

At an estimated 206 million gallons, the Deepwater Horizon (DWH) is the largest marine oil spill in the history of the United States. In this paper we develop a series of random utility models of site choice by saltwater anglers in the Southeast US and estimate monetary compensation for recreational losses due to the DWH oil spill. Heterogeneity in angler preferences is accounted for by using mixed logit models, and different compensation measures for shore-based, private boat, and for-hire anglers are estimated. Results indicate that willingness to pay for oil spill prevention varies by fishing mode and anglers fishing from shore and private boats exhibit heterogeneous preferences for oil spill avoidance. In addition, the total monetary compensation due to anglers is estimated at USD 585 million.

Designing exploratory cancer trials using change in tumour size as primary endpoint.

In phase III cancer clinical trials, overall survival is commonly used as the definitive endpoint. In phase II clinical trials, however, more immediate endpoints such as incidence of complete or partial response within 1 or 2 months or progression-free survival (PFS) are generally used. Because of the limited ability to detect change in overall survival with response, the inherent variability of PFS and the long wait for progression to be observed, more informative and immediate alternatives to overall survival are desirable in exploratory phase II trials. In this paper, we show how comparative trials can be designed and analysed using change in tumour size as the primary endpoint. The test developed is based on the framework of score statistics and will formally incorporate the information of whether patients survive until the time at which change in tumour size is assessed. Using an example in non-small cell lung cancer, we show that the sample size requirements for a trial based on change in tumour size are favourable compared with alternative randomized trials and demonstrate that these conclusions are robust to our assumptions.

Inverted laser sintering of metal powders.

We demonstrate the ability of the inverted laser sintering process to manufacture parts composed of metal powder. We fabricate a 10-layer part by depositing a layer of copper powder onto a sapphire plate, then pressing the plate against the part being built and sintering the powder onto the part by shining a 14W 445 nm laser through the glass. The process was then repeated multiple times, each time adding a new layer to the component being printed until completion. We discuss the potential applications and impacts of this process, including the ability to directly fabricate multi-material metallic parts without the use of a powder bed.