Health benefits of decreases in on-road transportation emissions in the United States from 2008 to 2017.

Decades of air pollution regulation have yielded enormous benefits in the United States, but vehicle emissions remain a climate and public health issue. Studies have quantified the vehicle-related fine particulate matter (PM2.5)-attributable mortality but lack the combination of proper counterfactual scenarios, latest epidemiological evidence, and detailed spatial resolution; all needed to assess the benefits of recent emission reductions. We use this combination to assess PM2.5-attributable health benefits and also assess the climate benefits of on-road emission reductions between 2008 and 2017. We estimate total benefits of $270 (190 to 480) billion in 2017. Vehicle-related PM2.5-attributable deaths decreased from 27,700 in 2008 to 19,800 in 2017; however, had per-mile emission factors remained at 2008 levels, 48,200 deaths would have occurred in 2017. The 74% increase from 27,700 to 48,200 PM2.5-attributable deaths with the same emission factors is due to lower baseline PM2.5 concentrations (+26%), more vehicle miles and fleet composition changes (+22%), higher baseline mortality (+13%), and interactions among these (+12%). Climate benefits were small (3 to 19% of the total). The percent reductions in emissions and PM2.5-attributable deaths were similar despite an opportunity to achieve disproportionately large health benefits by reducing high-impact emissions of passenger light-duty vehicles in urban areas. Increasingly large vehicles and an aging population, increasing mortality, suggest large health benefits in urban areas require more stringent policies. Local policies can be effective because high-impact primary PM2.5 and NH3 emissions disperse little outside metropolitan areas. Complementary national-level policies for NOx are merited because of its substantial impacts-with little spatial variability-and dispersion across states and metropolitan areas.

Consistent valuation of a reduction in mortality risk using values per life, life year, and quality-adjusted life year.

The monetary value of a reduction in mortality risk can be accurately characterized using the alternative concepts of value per statistical life (VSL), value per statistical life year (VSLY), and value per quality-adjusted life year (VQALY). Typically, each of these values depends on the age and other characteristics of the affected individual; at most one of the values can be independent of age. The common practice of valuing a transient or persistent risk reduction using a constant VSL, VSLY, or VQALY yields systematic differences in the calculated monetary value that depend on the age at which the risk reduction begins, its duration, time path, and whether future lives, life years, or quality-adjusted life years are discounted. Mutually consistent, age-dependent VSL, VSLY, and VQALY are derived and the large differences in valuation of illustrative transient and persistent risk reductions that can result from assuming age-independent values of each of the three concepts are illustrated.

Introduction to Special Issue on Risk Assessment, Economic Evaluation, and Decisions.

Integrating risk assessment, economic evaluation, and uncertainty to inform policy decisions is a core challenge to risk analysis. In September 2019, the Harvard Center for Risk Analysis, with support from the Society for Risk Analysis Economics and Benefits Analysis Specialty Group and others, convened a workshop to address this issue. The workshop built in part on the recommendations of the 2009 National Research Council report, Science and Decisions: Advancing Risk Assessment. It honored John S. Evans, whose thoughtful and innovative teaching and scholarship have significantly advanced thinking on these issues. This special issue features a profile of Dr. Evans and nine articles that build on work presented at the workshop.

Mortality Benefits and Control Costs of Improving Air Quality in Mexico City: The Case of Heavy Duty Diesel Vehicles.

Diesel vehicles are significant contributors to air pollution in Mexico City. We estimate the costs and mortality benefits of retrofitting heavy-duty vehicles with particulate filters and oxidation catalysts. The feasibility and cost-effectiveness of controls differ by vehicle model-year and type. We evaluate 1985 to 2014 model-year vehicles from 10 vehicle classes and five model-year groups. Our analysis shows that retrofitting all vehicles with the control that maximizes expected net benefits for that vehicle type and model-year group has the potential to reduce emissions of primary fine particles (PM2.5 ) by 950 metric tons/year; cut the population-weighted annual mean concentration of PM2.5 in Mexico City by 0.90 µg/m3 ; reduce the annual number of deaths attributable to air pollution by over 80; and generate expected annual health benefits of close to 250 million US$. These benefits outweigh expected costs of 92 million US$ per year. Diesel retrofits are but one step that should viewed in the context of other efforts--such as development of an integrated public transportation system, promotion of the rational use of cars, reduction of emissions from industrial sources and fires, and redesign of the Mexico City Metropolitan Area to reduce urban sprawl--that must be analyzed and implemented to substantially control air pollution and protect public health. Even if considering other potential public health interventions, which would offer greater benefits at the same or lower costs, only by conducting, promoting, and publishing this sort of analyses, we can make strides to improve public health cost-effectively.

Estimating the Potential Health Benefits of Air Quality Warnings.

National, state, and local air quality authorities issue warnings urging residents to stay indoors or to take other precautions when pollutant levels are expected to exceed defined thresholds. Previous work explores the impact of warnings on specific activities but not the health improvements that might result if individuals fully responded to the recommendations. We estimate these potential health impacts using recent pollution data in three U.S. locations: Denver, Colorado; Los Angeles, California; and Pittsburgh, Pennsylvania. We focus on mortality risks among the elderly, who are particularly vulnerable. Under the strong assumptions of no infiltration and no offsetting indoor sources, we estimate that the benefits associated with avoiding ambient ozone and fine particle exposure are generally less than $14 per person for one additional hour spent indoors on days when air quality thresholds are exceeded. These estimates are sensitive to assumptions regarding the relationship between decreased exposure and mortality risks. Individuals' decisions to stay indoors likely depend on the value of the health benefits compared with the value of forgone work and leisure activities. While the national warning system provides flexibility and allows individuals to tailor their responses to personal circumstances, our analysis suggests that its benefits under typical conditions are small. The benefits of warnings under wildfire or other extreme conditions may be much greater.

Premature Deaths, Statistical Lives, and Years of Life Lost: Identification, Quantification, and Valuation of Mortality Risks.

Mortality effects of exposure to air pollution and other environmental hazards are often described by the estimated number of "premature" or "attributable" deaths and the economic value of a reduction in exposure as the product of an estimate of "statistical lives saved" and a "value per statistical life." These terms can be misleading because the number of deaths advanced by exposure cannot be determined from mortality data alone, whether from epidemiology or randomized trials (it is not statistically identified). The fraction of deaths "attributed" to exposure is conventionally derived as the hazard fraction (R - 1)/R, where R is the relative risk of mortality between high and low exposure levels. The fraction of deaths advanced by exposure (the "etiologic" fraction) can be substantially larger or smaller: it can be as large as one and as small as 1/e (≈0.37) times the hazard fraction (if the association is causal and zero otherwise). Recent literature reveals misunderstanding about these concepts. Total life years lost in a population due to exposure can be estimated but cannot be disaggregated by age or cause of death. Economic valuation of a change in exposure-related mortality risk to a population is not affected by inability to know the fraction of deaths that are etiologic. When individuals facing larger or smaller changes in mortality risk cannot be identified, the mean change in population hazard is sufficient for valuation; otherwise, the economic value can depend on the distribution of risk reductions.

Trading Bankruptcy for Health: A Discrete-Choice Experiment.

BACKGROUND: Although nearly two-third of bankruptcy in the United States is medical in origin, a common assumption is that individuals facing a potentially lethal disease opt for cure at any cost. This assumption has never been tested, and knowledge of how the American population values a trade-off between cure and bankruptcy is unknown. OBJECTIVES: To determine the relative importance among the general American population of improved health versus improved financial risk protection, and to determine the impact of demographics on these preferences. METHODS: A discrete-choice experiment was performed with 2359 members of the US population. Respondents were asked to value treatments with varying chances of cure and bankruptcy in the presence of a lethal disease. Latent class analysis with concomitant variables was performed, weighted for national representativeness. Sensitivity analyses were undertaken to test the robustness of the results. RESULTS: It was found that 31.3% of the American population values cure at all costs. Nevertheless, for 8.5% of the US population, financial solvency dominates concerns for health in medical decision making. Individuals who value cure at all costs are more likely to have had experience with serious disease and to be women. No demographic characteristics significantly predicted individuals who value solvency over cure. CONCLUSIONS: Although the average American values cure more than financial solvency, a cure-at-all-costs rubric describes the preferences of a minority of the population, and 1 in 12 value financial protection over any chances of cure. This study provides empirical evidence for how the US population values a trade-off between avoiding adverse health outcomes and facing bankruptcy. These findings bring to the fore the decision making that individuals face in balancing the acute financial burden of health care access.

Valuing Reductions in Fatal Illness Risks: Implications of Recent Research.

The value of mortality risk reductions, conventionally expressed as the value per statistical life, is an important determinant of the net benefits of many government policies. US regulators currently rely primarily on studies of fatal injuries, raising questions about whether different values might be appropriate for risks associated with fatal illnesses. Our review suggests that, despite the substantial expansion of the research base in recent years, few US studies of illness-related risks meet criteria for quality, and those that do yield similar values to studies of injury-related risks. Given this result, combining the findings of these few studies with the findings of the more robust literature on injury-related risks appears to provide a reasonable range of estimates for application in regulatory analysis. Our review yields estimates ranging from about $4.2 million to $13.7 million with a mid-point of $9.0 million (2013 dollars). Although the studies we identify differ from those that underlie the values currently used by Federal agencies, the resulting estimates are remarkably similar, suggesting that there is substantial consensus emerging on the values applicable to the general US population. Copyright © 2015 John Wiley & Sons, Ltd.

Effect of the Fukushima nuclear accident on the risk perception of residents near a nuclear power plant in China.

We assessed the influence of the Fukushima nuclear accident (FNA) on the Chinese public's attitude and acceptance of nuclear power plants in China. Two surveys (before and after the FNA) were administered to separate subsamples of residents near the Tianwan nuclear power plant in Lianyungang, China. A structural equation model was constructed to describe the public acceptance of nuclear power and four risk perception factors: knowledge, perceived risk, benefit, and trust. Regression analysis was conducted to estimate the relationship between acceptance of nuclear power and the risk perception factors while controlling for demographic variables. Meanwhile, we assessed the median public acceptable frequencies for three levels of nuclear events. The FNA had a significant impact on risk perception of the Chinese public, especially on the factor of perceived risk, which increased from limited risk to great risk. Public acceptance of nuclear power decreased significantly after the FNA. The most sensitive groups include females, those not in public service, those with lower income, and those living close to the Tianwan nuclear power plant. Fifty percent of the survey respondents considered it acceptable to have a nuclear anomaly no more than once in 50 y. For nuclear incidents and serious incidents, the frequencies are once in 100 y and 150 y, respectively. The change in risk perception and acceptance may be attributed to the FNA. Decreased acceptance of nuclear power after the FNA among the Chinese public creates additional obstacles to further development of nuclear power in China and require effective communication strategies.

Research Synthesis and the Value per Statistical Life.

The value of small changes in mortality risk, conventionally expressed as the value per statistical life (VSL), is a major determinant of the benefits of many environmental, health, and safety regulations and other policies. However, selecting an appropriate value is challenging. Different studies yield different results and analysts often find they lack estimates that are directly applicable to the policy they are assessing. Research-synthesis methods are widely used to address these concerns in many fields, yet we find only limited applications to estimating VSL. More structured, criteria-driven review of the available studies is an important first step. Additional meta-analyses that use such review as a starting point are needed to explore variation across studies as well as to adjust estimates to better fit different policy contexts. Carefully designed expert elicitation is significantly underutilized and is particularly important when the available research is limited or inconsistent. Although greater use of such methods is likely to enhance the credibility of the VSL estimates applied in policy analyses, as well as provide greater insights into the advantages and limitations of the available research, it is not clear how much the resulting estimates will vary from those currently used. In the United States, these estimates are generally around $9 million.

Introduction to the Special Series on Research Synthesis: A Cross-Disciplinary Approach.

To estimate the effects of a policy change, analysts must often rely on available data as time and resource constraints limit their ability to commission new primary research. Research synthesis methods-including systematic review, meta-analysis, and expert elicitation-play an important role in ensuring that this evidence is appropriately weighed and considered. We present the conclusions of a multidisciplinary Harvard Center for Risk Analysis project that evaluated and applied these methods, and introduce the resulting series of articles. The first step in any analysis is to clearly define the problem to be addressed; the second is a systematic review of the literature. Whether additional analysis is needed depends on the quality and relevance of the available data to the policy question, and the likely effect of uncertainty on the policy decision. Meta-analysis promotes understanding the variation between studies and may be used to combine the estimates to develop values for application in policy analysis. Formal, structured expert elicitation promotes careful consideration of the evidence when data are limited or inconsistent, and aids in extrapolating to the policy context. Regardless of the methods used, clear communication of the approach, assumptions, and uncertainty is essential.

Major factors influencing the health impacts from controlling air pollutants with nonlinear chemistry: an application to China.

Predicting the human-health effects of reducing atmospheric emissions of nitrogen oxide (NOx) emissions from power plants, motor vehicles, and other sources is complex because of nonlinearity in the relevant atmospheric processes. We estimate the health impacts of changes in fine particulate matter (PM2.5) and ozone concentrations that result from control of NOx emissions alone and in conjunction with other pollutants in and outside the mega-city of Shanghai, China. The Community Multiscale Air Quality (CMAQ) Modeling System is applied to model the effects on atmospheric concentrations of emissions from different economic sectors and geographic locations. Health impacts are quantified by combining concentration-response functions from the epidemiological literature with pollutant concentration and population distributions. We find that the health benefits per ton of emission reduction are more sensitive to the location (i.e., inside vs. outside of Shanghai) than to the sectors that are controlled. For eastern China, we predict between 1 and 20 fewer premature deaths per year per 1,000 tons of NOx emission reductions, valued at $300-$6,000 per ton. Health benefits are sensitive to seasonal variation in emission controls. Policies to control NOx emissions need to consider emission location, season, and simultaneous control of other pollutants to avoid unintended consequences.

Combining experts' judgments: comparison of algorithmic methods using synthetic data.

Expert judgment (or expert elicitation) is a formal process for eliciting judgments from subject-matter experts about the value of a decision-relevant quantity. Judgments in the form of subjective probability distributions are obtained from several experts, raising the question how best to combine information from multiple experts. A number of algorithmic approaches have been proposed, of which the most commonly employed is the equal-weight combination (the average of the experts' distributions). We evaluate the properties of five combination methods (equal-weight, best-expert, performance, frequentist, and copula) using simulated expert-judgment data for which we know the process generating the experts' distributions. We examine cases in which two well-calibrated experts are of equal or unequal quality and their judgments are independent, positively or negatively dependent. In this setting, the copula, frequentist, and best-expert approaches perform better and the equal-weight combination method performs worse than the alternative approaches.

Monetary values of increasing life expectancy: Sensitivity to shifts of the survival curve.

Individuals' monetary values of decreases in mortality risk depend on the magnitude and timing of the risk reduction. We elicited stated preferences among three time paths of risk reduction yielding the same increase in life expectancy (decreasing risk for the next decade, subtracting a constant from or multiplying risk by a constant in all future years) and willingness to pay (WTP) for risk reductions differing in timing and life-expectancy gain. Respondents exhibited heterogeneous preferences over the alternative time paths, with almost 90 percent reporting transitive orderings. WTP is statistically significantly associated with life-expectancy gain (between about 7 and 28 days) and with respondents' stated preferences over the alternative time paths. Estimated value per statistical life year (VSLY) can differ by time path and averages about $500,000, roughly consistent with conventional estimates obtained by dividing estimated value per statistical life by discounted life expectancy.

Reappraising the public health benefits conferred by environmental policy: Considerations for an aging society.

Although addressing environmental pollution and unprecedented societal aging are concurrent public health challenges, rarely is the relationship between the two considered. Current approaches to valuing the public health benefits conferred by environmental policy may be ill-suited to aging populations. We describe the limitations of the age-invariant approach used by the United States Environmental Protection Agency to estimate the public health benefits corresponding to environmental regulation. These include the poor age-representativeness of the samples informing the valuation of mortality risk reduction, the exclusion of age-related outcomes from valuation, and the omission of age-related third-party expenditures. We offer an empirical framework that could address these limitations. Our recommendations could improve the calibration of environmental regulatory analysis to the changing age distribution of the United States population.

National HIV prevalence estimates for sub-Saharan Africa: controlling selection bias with Heckman-type selection models.

OBJECTIVES: Population-based HIV testing surveys have become central to deriving estimates of national HIV prevalence in sub-Saharan Africa. However, limited participation in these surveys can lead to selection bias. We control for selection bias in national HIV prevalence estimates using a novel approach, which unlike conventional imputation can account for selection on unobserved factors. METHODS: For 12 Demographic and Health Surveys conducted from 2001 to 2009 (N=138 300), we predict HIV status among those missing a valid HIV test with Heckman-type selection models, which allow for correlation between infection status and participation in survey HIV testing. We compare these estimates with conventional ones and introduce a simulation procedure that incorporates regression model parameter uncertainty into confidence intervals. RESULTS: Selection model point estimates of national HIV prevalence were greater than unadjusted estimates for 10 of 12 surveys for men and 11 of 12 surveys for women, and were also greater than the majority of estimates obtained from conventional imputation, with significantly higher HIV prevalence estimates for men in Cote d'Ivoire 2005, Mali 2006 and Zambia 2007. Accounting for selective non-participation yielded 95% confidence intervals around HIV prevalence estimates that are wider than those obtained with conventional imputation by an average factor of 4.5. CONCLUSIONS: Our analysis indicates that national HIV prevalence estimates for many countries in sub-Saharan African are more uncertain than previously thought, and may be underestimated in several cases, underscoring the need for increasing participation in HIV surveys. Heckman-type selection models should be included in the set of tools used for routine estimation of HIV prevalence.

Risk trade-offs in fish consumption: a public health perspective.

Fish consumption advisories instruct vulnerable consumers to avoid high mercury fish and to limit total fish intake to reduce neurotoxic risk. Consumption data from the U.S. suggest that nontarget consumers also respond to such advice. These consumers reduce exposure to mercury and other toxicants at the cost of reduction in cardioprotective fatty acids. We present a probabilistic model to assess these risk trade-offs. We use NHANES consumption data to simulate exposure to contaminants and nutrients in fish, employ dose-response relationships to convert exposure to health end points, and monetize them using benefit transfer. Our results suggest that newborns gained on average 0.033 IQ points from their mothers' compliance with the prominent FDA/EPA advisory. The welfare gain for a birth cohort is estimated at $386 million. This gain could be fully offset by increments in cardiovascular risk if 0.6% of consumers aged 40 and older reduced fish intake by one monthly meal until they reached the age of 60 or if 0.1% of them permanently reduced fish intake.

Discounting health and cost-effectiveness analysis: a response to Nord.

Nord (2011) criticizes standard arguments which assert that consistency requires that future health benefits must be discounted at the same rate as future costs in cost-effectiveness analysis (CEA). He suggests these arguments are misguided because they require transitivity of preferences across decision contexts and that it can be appropriate to discount health at different rates depending on the programs to be compared. I claim that rejecting transitivity is unwarranted and would sharply diminish the utility of CEA. Factors that tempt Nord to reject consistency can be accommodated by recognizing that CEA does not perfectly mimic normative social preferences because it omits factors (like distribution of health in a population) that can be normatively significant. A better approach is to maintain consistency in application of CEA but authorize decision makers to depart from rankings implied by CEA when justified and to explain which specific factors justify the decision. Finally, the assertion that health must be discounted at the same rate as costs requires the additional assumption that the dollar value of health does not change over time, a point that is not always recognized in standard arguments.

Willingness-to-pay for predictive tests with no immediate treatment implications: a survey of US residents.

We assessed how much, if anything, people would pay for a laboratory test that predicted their future disease status. A questionnaire was administered via an internet-based survey to a random sample of adult US respondents. Each respondent answered questions about two different scenarios, each of which specified: one of four randomly selected diseases (Alzheimer's, arthritis, breast cancer, or prostate cancer); an ex ante risk of developing the disease (randomly designated 10 or 25%); and test accuracy (randomly designated perfect or 'not perfectly accurate'). Willingness-to-pay (WTP) was elicited with a double-bounded, dichotomous-choice approach. Of 1463 respondents who completed the survey, most (70-88%, depending on the scenario) were inclined to take the test. Inclination to take the test was lower for Alzheimer's and higher for prostate cancer compared with arthritis, and rose somewhat with disease prevalence and for the perfect versus imperfect test [Correction made here after initial online publication.]. Median WTP varied from $109 for the imperfect arthritis test to $263 for the perfect prostate cancer test. Respondents' preferences for predictive testing, even in the absence of direct treatment consequences, reflected health and non-health related factors, and suggests that conventional cost-effectiveness analyses may underestimate the value of testing.