Valuation of human health: An integrated model of willingness to pay for mortality and morbidity risk reductions

This paper develops and applies an integrated model of mortality and morbidity valuation that is consistent with the principles of welfare economics. To obtain the integrated model, the standard one-period expected utility model of one person facing the prospect of either being alive or dead is extended to incorporate (1) a third health state (sick) with a utility level that is intermediate to utility if healthy and utility if dead, (2) a family perspective in which a parent makes choices about risk exposure both for herself and for a child, and (3) a multi-period framework that allows for possible parent/child differences in illness latency. Monetary benefits of health risk reduction obtained from the integrated model are compared with those that would be computed using the standard model. The integrated model then is applied using data obtained from two field studies of skin cancer and leukemia to demonstrate how it can be used to estimate health benefits of reduced illness and death risks.     

Accounting for Uncertainty in Risk Assessment: Case Study of Hector's Dolphin Mortality due to Gillnet Entanglement

Abstract: Uncertainties about biological data and human effects often delay decisions on management of endangered species. Some decision makers argue that uncertainty about the risk posed to a species should lead to precautionary decisions, whereas others argue for delaying protective measures until there is strong evidence that a human activity is having a serious effect on the species. We have developed a method that incorporates uncertainty into the estimate of risk so that delays in action can be reduced or eliminated. We illustrate our method with an actual situation of a deadlock over how to manage Hector's dolphin ( Cephalorhychus hectori ). The management question is whether sufficient risk is posed to the dolphins by mortalities in gillnets to warrant regulating the fisheries. In our quantitative risk assessment, we use a population model that incorporates both demographic ( between-individual) and environmental ( between-year) stochasticity. We incorporate uncertainty in estimates of model parameters by repeatedly running the model for different combinations of survival and reproductive rates. Each value is selected at random from a probability distribution that represents the uncertainty in estimating that parameter. Before drawing conclusions, we perform sensitivity analyses to see whether model assumptions alter conclusions and to recommend priorities for future research. In this example, uncertainty did not alter the conclusion that there is a high risk of population decline if current levels of gillnet mortality continue. Sensitivity analyses revealed this to be a robust conclusion. Thus, our analysis removes uncertainty in the scientific data as an excuse for inaction.     

Static modeling of dynamic recreation behavior: Implications for prediction and welfare estimation

This paper examines the consequences of using a static model of recreation trip-taking behavior when the underlying decision problem is dynamic. Specifically we examine the implications for trip forecasting and welfare estimation using a panel dataset of Lake Michigan salmon anglers for the 1996 and 1997 fishing seasons. We derive and estimate both a structural dynamic model using Bellman's equation, and a reduced-form static model with trip probability expressions mimicking those of the dynamic model. We illustrate an inherent identification problem in the reduced-form model that creates biased welfare estimates, and we discuss the general implications of this for the interpretation of preference parameters in static models. We then use both models to simulate trip taking behavior and show that although their in-sample trip forecasts are similar, their welfare estimates and out-of-sample forecasts are quite different.     

Ambiguity,reasoned determination,and climate-change policy

This paper examines climate-change benefit-cost analysis in the presence of scientific uncertainty in the form of ambiguity. The specific issue addressed is the robustness of benefit-cost analyses of climate-change policy alternatives to relaxation of Savage's original axioms. Two alternatives to subjective expected utility (SEU) are considered: maximin expected utility (MEU) and incomplete expected utility (IEU). Among other results, it is demonstrated that polar opposite recommendations can emerge in an ambiguous decision setting even if all agree on Society's rate of time preference, Society's risk attitudes, the degree of ambiguity faced, and the scientific primitives. We show that, for a simple numerical simulation of our model, an MEU decision maker favors policies which immediately tackle climate change while an IEU decision prefers “business as usual”.“Each agency shall assess the costs and benefits of the intended regulation, and recognizing that some costs and benefits are difficult to quantify, propose or adopt a regulation only upon a reasoned determination that the benefits of the intended regulation justify its cost.” Executive Order 12866 of the US President.     

Housing prices,health effects,and valuing reductions in risk of death

By combining estimates of the effect of air pollution on both property values and human health risks, it may be possible to draw inferences about individuals' valuations of risk. Although valuations thus derived must be interpreted carefully, they may be of use in determining the welfare effects of environmental and other regulatory policies.     

Uncertainty in epidemiology and health risk and impact assessment

Environmental epidemiology and health risk and impact assessment have long grappled with problems of uncertainty in data and their relationships. These uncertainties have become more challenging because of the complex, systemic nature of many of the risks. A clear framework defining and quantifying uncertainty is needed. Three dimensions characterise uncertainty: its nature, its location and its level. In terms of its nature, uncertainty can be both intrinsic and extrinsic. The former reflects the effects of complexity, sparseness and nonlinearity; the latter arises through inadequacies in available observational data, measurement methods, sampling regimes and models. Uncertainty occurs in three locations: conceptualising the problem, analysis and communicating the results. Most attention has been devoted to characterising and quantifying the analysis—a wide range of statistical methods has been developed to estimate analytical uncertainties and model their propagation through the analysis. In complex systemic risks, larger uncertainties may be associated with conceptualisation of the problem and communication of the analytical results, both of which depend on the perspective and viewpoint of the observer. These imply using more participatory approaches to investigation, and more qualitative measures of uncertainty, not only to define uncertainty more inclusively and completely, but also to help those involved better understand the nature of the uncertainties and their practical implications.     

Coral Bleaching and Global Climate Change: Scientific Findings and Policy Recommendations

Abstract: In 1998, tropical sea surface temperatures were the highest on record, topping off a 50-year trend for some tropical oceans. In the same year, coral reefs around the world suffered the most extensive and severe bleaching ( loss of symbiotic algae) and subsequent mortality on record. These events may not be attributable to local stressors or natural variability alone but were likely induced by an underlying global phenomenon. It is probable that anthropogenic global warming has contributed to the extensive coral bleaching that has occurred simultaneously throughout the reef regions of the world. The geographic extent, increasing frequency, and regional severity of mass bleaching events are an apparent result of a steadily rising baseline of marine temperatures, combined with regionally specific El Niño and La Niña events. The repercussions of the 1998 mass bleaching and mortality events will be far-reaching. Human populations dependent on reef services face losses of marine biodiversity, fisheries, and shoreline protection. Coral bleaching events may become more frequent and severe as the climate continues to warm, exposing coral reefs to an increasingly hostile environment. This global threat to corals compounds the effects of more localized anthropogenic factors that already place reefs at risk. Significant attention needs to be given to the monitoring of coral reef ecosystems, research on the projected and realized effects of global climate change, and measures to curtail greenhouse gas emissions. Even those reefs with well-enforced legal protection as marine sanctuaries, or those managed for sustainable use, are threatened by global climate change.     

A comparison of cat‐related risk perceptions and tolerance for outdoor cats in Florida and Hawaii

Risk perceptions and attitudes toward animals often explain tolerance for wildlife and management preferences. However, little is understood about how these relationships vary across different geographic regions and stakeholder groups. To address this gap in knowledge, we compared differences in acceptance capacity, risk perceptions, perceived enjoyment from outdoor cats, and experiences with outdoor cats among 3 groups (general public, conservation community, and animal‐welfare community) in Hawaii and Florida, two states with large conservation challenges. We combined independently collected data from Florida and Hawaii, to determine how perception of the risks presented by outdoor cats, group membership, and state of residence influenced people's tolerance for outdoor cats. Florida respondents were significantly more tolerant of outdoor cats and less concerned about cat‐related risks than Hawaii respondents (p < 0.05). In both states, animal‐welfare group members reported greater enjoyment seeing cats and perceived a smaller increase in the cat population and lower levels of risk than other groups (p < 0.05). All groups exhibited similar relationships between acceptance capacity and enjoyment and the perceived increase in the cat population. Our results suggest public tolerance for cats varied due to the influence of local or geographical concerns, but that strongly held beliefs, risk perceptions, and feelings about cats explained more of the variance in stakeholder tolerance.     

Risk aversion and adaptive management: Insights from a multi-armed bandit model of invasive species risk

This article explores adaptive management (AM) for decision-making under environmental uncertainty. In the context of targeting invasive species inspections of agricultural imports, I find that risk aversion increases the relative value of AM and can increase the rate of exploratory action. While calls for AM in natural resource management are common, many analyses have identified modest gains from this approach. I analytically and numerically examine the distribution of outcomes from AM under risk neutrality and risk aversion. The inspection decision is framed as a multi-armed bandit problem and solved using the Lagrangian decomposition method. Results show that even when expected gains are modest, asymmetry in the distribution of outcomes has important implications. Notably, AM can serve to buffer against large losses, even if the most likely outcome is a small loss.     

Uncertainty analysis of a pharmacokinetic modeling for inorganic arsenic

This paper presents an uncertainty and sensitivity analysis of a pharmacokinetic modeling of inorganic arsenic deposition in rodents for a short‐term exposure. Efforts to develop the pharmacokinetic model are directed towards predicting the kinetic behavior of inorganic arsenic in the body, including tissue and blood concentrations, and especially, the urinary excretion of arsenic and its methylated metabolites. However, the use of the model raises an important question when fixed values of model parameters are used: how is the uncertainty in the model prediction based on the collective uncertainties in the model inputs? This study focuses on an “epistemic”; uncertainty in order to handle this problem. In this case, the uncertainty refers to an input that has a single value which cannot be known with precision due to a lack of knowledge about items or its measurement. The combination of the pharmacokinetic model and the uncertainty analysis would help understand the uncertainties in risk assessment associated with inorganic arsenic.     

Emergent conservation outcomes of shared risk perception in human-wildlife systems

Human perception of risks related to economic damages caused by nearby wildlife can be transmitted through social networks. Understanding how sharing risk information within a human community alters the spatial dynamics of human-wildlife interactions has important implications for the design and implementation of effective conservation actions. We developed an agent-based model that simulates farmer livelihood decisions and activities in an agricultural landscape shared with a population of a generic wildlife species (wildlife-human interactions in shared landscapes [WHISL]). In the model, based on risk perception and economic information, farmers decide how much labor to allocate to farming and whether and where to exclude wildlife from their farms (e.g., through fencing, trenches, or vegetation thinning). In scenarios where the risk perception of farmers was strongly influenced by other farmers, exclusion of wildlife was widespread, resulting in decreased quality of wildlife habitat and frequency of wildlife damages across the landscape. When economic losses from encounters with wildlife were high, perception of risk increased and led to highly synchronous behaviors by farmers in space and time. Interactions between wildlife and farmers sometimes led to a spillover effect of wildlife damage displaced from socially and spatially connected communities to less connected neighboring farms. The WHISL model is a useful conservation-planning tool because it provides a test bed for theories and predictions about human-wildlife dynamics across a range of different agricultural landscapes.     

Making conservation decisions under uncertainty for the persistence of multiple species.

Population models for multiple species provide one of the few means of assessing the impact of alternative management options on the persistence of biodiversity, but they are inevitably uncertain. Is it possible to use population models in multiple-species conservation planning given the associated uncertainties? We use information-gap decision theory to explore the impact of parameter uncertainty on the conservation decision when planning for the persistence of multiple species. An information-gap approach seeks robust outcomes that are most immune from error. We assess the impact of uncertainty in key model parameters for three species, whose extinction risks under four alternative management scenarios are estimated using a metapopulation model. Three methods are described for making conservation decisions across the species, taking into account uncertainty. We find that decisions based on single species are relatively robust to uncertainty in parameters, although the estimates of extinction risk increase rapidly with uncertainty. When identifying the best conservation decision for the persistence of all species, the methods that rely on the rankings of the management options by each species result in decisions that are similarly robust to uncertainty. Methods that depend on absolute values of extinction risk are sensitive to uncertainty, as small changes in extinction risk can alter the ranking of the alternative scenarios. We discover that it is possible to make robust conservation decisions even when the uncertainties of the multiple-species problem appear overwhelming. However, the decision most robust to uncertainty is likely to differ from the best decision when uncertainty is ignored, illustrating the importance of incorporating uncertainty into the decision-making process.     

Evidence of variable discount rates and non-standard discounting in mortality risk valuation

Time discounting is central to the valuation of future health and mortality risks in public sector allocative decision-making, particularly for environmental policies with delayed health impacts. Using a Risk-Risk trade-off survey, we elicit discount rates for fatality risks and establish discounting functional forms on both a sample and an individual level. We find wide variation in implicit discount rates for fatality risk between individuals, as well as between-individual heterogeneity in discounting functional forms. In aggregate, the sample is best characterised by subadditive discounting. Our work has implications for the academic investigation of intertemporal choice involving mortality risks, and potentially for the evaluation of policy options with delayed mortality risk outcomes. A thought experiment cautions against the standard practice of assuming that exponential discounting characterises society's time preferences.     

环境风险知觉和评价的整体框架

环境风险通常发生在一定时间之后,以某种可能性发生在某个特定的地方,使得某些人群受到影响。因此,环境风险是典型的多维度事件,它涵盖四个基本的偏好维度：时间、空间、概率与社会性,每个维度都可能导致环境风险知觉和评价出现折扣（discount）现象。但是,传统视角往往关注单一维度,主要是时间,因而割裂了维度的整体性。基于环境风险的多维度特征,提出了一个统一的多维度偏好框架,为环境风险知觉及评价提供整体性视角。这四个偏好维度统一的内在原因是心理距离。维度共性意味着时间维度上的折现机制能够应用到其它维度,为此,对环境风险跨期评价中关于折现率热点问题的研究进展进行了一个关键的梳理。未来有必要在此整体框架下,重点关注三个方面的问题：（1）环境折现率,对环境折现率的要素及其关系进行规范性分析,进而分析环境贴现率与经济贴现率之间的关系,及双率折现对可持续发展的涵义;（2）基于维度共性,将时间维度上的研究结论应用到其它维度;（3）研究多重维度复合情形下的偏好和评价问题,建立综合性描述模型,依托具体案例探讨有效的环境风险沟通策略、环境政策和制度设计。     

An anatomy of a groundwater contamination episode

Using the contamination episode at Price Landfill, New Jersey, as a case study, major analytical and informational issues characterizing groundwater pollution, with special emphasis on uncertainty associated with the environmental medium, especially solute-transport processes, and the valuation of health risks, principally dose-response relationships, are addressed. Alternative approaches to modeling the physical-chemical processes are described and subsequently coupled with mortality risk predictions to derive estimates of expected pollution costs: reduced longevity (pollution damage costs) and cost of control and remedial measures (damage reduction costs).     

Controlling the monopolistic polluter: Nihilism or eclecticism?

This paper is concerned with the consequences of pollution control when the polluter is a monopolist who can choose between abating pollution by reducing output and by adopting a less-polluting technology. It is suggested that the risk of welfare losses resulting from control policy is lower when technology is flexible than when it is rigid. Nevertheless some risk does remain, so the paper concludes with a discussion of the possible use of selective control instruments to keep the risk to a minimum.     

Incorporating Uncertainty into Management Models for Marine Mammals

Abstract: Good management models and good models for understanding biology differ in basic philosophy. Management models must facilitate management decisions despite large amounts of uncertainty about the managed populations. Such models must be based on parameters that can be estimated readily, must explicitly account for uncertainty, and should be simple to understand and implement. In contrast, biological models are designed to elucidate the workings of biology and should not be constrained by management concerns. We illustrate the need to incorporate uncertainty in management models by reviewing the inadequacy of using standard biological models to manage marine mammals in the United States. Past management was based on a simple model that, although it may have represented population dynamics adequately, failed as a management tool because the parameter that triggered management action was extremely difficult to estimate for the majority of populations. Uncertainty in parameter estimation resulted in few conservation actions. We describe a recently adopted management scheme that incorporates uncertainty and its resulting implementation. The approach used in this simple management scheme, which was tested by using simulation models, incorporates uncertainty and mandates monitoring abundance and human-caused mortality. Although the entire scheme may be suitable for application to some terrestrial and marine problems, two features are broadly applicable: the incorporation of uncertainty through simulations of management and the use of quantitative management criteria to translate verbal objectives into levels of acceptable risk.     

Substitution and the control of pollution : A comparison of effluent charges and quantity standards under uncertainty

Single-valued price and quantity controls of a polluting activity are compared under uncertainty. The ability to substitute other inputs for the pollutant in the production of a positively valued final good, and the usual discrepancy between the amount of pollution actually consumed and the amount emitted are carefully incorporated. The first is found to influence the degree to which cost fluctuation is reflected in the output of the final good. The second concern alters the region of the benefit function into which output is inserted. Both change the welfare losses associated with random fluctuation in the costs of reducing pollution.     

A multi-event model to study stage-dependent dispersal in radio-collared hares: when hunting promotes costly transience

Behavioral ecologists have often assumed that dispersal is costly mainly because of unfamiliarity with traversed habitats during dispersal and energy costs of the movement per se; thus, dispersers that have successfully settled should experience survival rates comparable to those of philopatric individuals. In this paper, we tested that hypothesis using 152 radio-collared European hares in a harvested population. We developed a multi-event capture recapture model, combining telemetry data and recoveries and separately modeling the foray probability, the settlement probability, and the permanent dispersal probability. The parameterization introduced here raises the possibility of separately testing effects on survival and dispersal probabilities at each stage of dispersal (departure, transience, and settlement). In accordance with our expectations, we reveal that dispersers incur higher mortality risks during transience and the early settlement period than philopatric individuals or settled dispersers. We also found that dispersers suffer from higher risks of being shot. Those results illustrate that unfamiliarity with the habitat during transience makes dispersal costly and that settled dispersers may enjoy survival rates comparable to those of philopatric individuals. Surprisingly, we also found that individuals have a higher probability of foraying during the hunting season. We suggest that hunting and related disturbances increase dispersal costs both by increasing mortality risk during transience and (perhaps) by increasing movement rates. We emphasize the need to take human pressures into account as factors that may drive the demographics of movements in populations.     

Fuzzy experts on recreational vessels, a risk modelling approach for marine invasions

Understanding risks from the human-mediated spread of non-indigenous species (NIS) is a critical component of marine biosecurity management programmes. Recreational boating is well-recognised as a NIS pathway, especially at a regional scale. Assessment of risks from this pathway is therefore desirable for coastal environments where recreational boating occurs. However, formal or quantitative risk assessment for the recreational vessel pathway is often hampered by lack of data, hence often relies on expert opinion. The use of expert opinion itself is sometimes limited by its inherent vagueness, which can be an important source of uncertainty that reduces the validity and applicability of the assessment. Fuzzy logic, specifically interval type-2 fuzzy logic, is able to model and propagate this type of uncertainty, and is a useful technique in risk assessment where expert opinion is relied upon. The present paper describes the implementation of a NIS fuzzy expert system (FES) for assessing the risk of invasion in marine environments via recreational vessels. The FES was based on expert opinion gathered through systematic elicitation exercises, designed to acknowledge important uncertainty sources (e.g., underspecificity and ambiguity). The FES, using interval type-2 fuzzy logic, calculated an invasion risk value (integrating NIS infection and detection probabilities) for a range of invasion scenarios. These scenarios were defined by all possible combinations of two vessel types (moored and trailered), five vessel components (hull, deck, internal spaces, anchor, fishing gear), two infection modes (fouling, water/sediment retention) and six frequently visited marine habitats (marina, mooring, farm, ramp, wharf, anchorage). Although invasion risk values determined using the FES approach was scenario-specific, general patterns were identified. Moored vessels consistently showed higher invasion risk values than trailered vessels. Invasion risk values were higher for anchorages, moorings and wharves. Similarly, hull-fouling was revealed as the highest infection risk mode after pooling results across all habitats. The NIS fuzzy expert system presented here appears as a valuable prioritising and decision-making tool for NIS research, prevention and control activities. Its easy implementation and wide applicability should encourage the development and application of this type of system as an integral part of biosecurity, and other environmental management plans.