Timeline of quantification of life

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This is a timeline of quantification of life, attempting to describe topics such as value of life in modern democracies, as well as measures used in economic evaluation to assess the value of medical interventions, rescue, and employment, among other areas.

Sample questions

The following are some interesting questions that can be answered by reading this timeline:

  • What are some important concepts and measures developed as a means to quantify vital human aspects?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Concept development".
    • You will see the emergence of key concepts, such as QALY and DALY, among others.
  • What are some monetary estimates of value of life assigned by entities to individuals?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Monetary estimate".
    • You will mostly see monetary estimates of value of a statistical life across diverse countries.
  • What are some notable or illustrative studies conducted on the topic of quantification of life?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Research".
  • What are some books developing content on or largely related to quantification of life?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Literature".
  • What are some notable cases of cost per life saved?
  • What are some policies set by authorities concerning the use of measures of quantification of life?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Policy".
    • You will see a number of sample cases by governmental institutions.

Other events are described under the following types: "Concept adoption", "Notable comment", "Organization", "Recommendation", "Study launch", "Tool launch", and "Value of slave life".

Numerical and visual data

The table below shows labor market studies on the value of life.[1]

Year Author VSL (in US$)
1976 V.K. Smith 5,700,000
1981 Viscusi 7,900,000
1982 Marin and Psacharopoulos 3,400,000
1984 Smith and Gilbert 800,000
1984 Leigh and Folsom 11,700,000
1985 Dillingham 1,100,000
1987 Leigh 12,600,000
1988 Garen 16,300,000
1991 Kniesner and Leith 700,000

The table below shows value of statistical life (in 2000 US$) across nations.[1][2]

Year Country VSL minimum estimate VSL maximum estimate
1989 Canada 3,900,000 4,700,000
1991 Japan 9,700,000 9,700,000
1993 South Korea 800,000 800,000
1996–1997 India 1,200,000 1,500,000
1997 Taiwan 200,000 900,000
1997 Australia 11,300,000 19,100,100
2000 United Kingdom 19,900,000 19,900,000
2006 Mexico 230,000 310,000
2011 Pakistan 321,813 775,193

The table below shows central estimate of value per statistical life, published in the U.S. Environmental Protection Agency's Final Regulatory Impact Analysis for Particulate Matter.[3]

Health Endpoint 1990 Income Level 2020 Income Level
Premature Mortality (value of a statistical life) $8,000,000 $9,600,000
Age 0–24 (heart attack at 3% discount rate) $87,000 $87,000
Age 25–44 (heart attack at 3% discount rate) $110,000 $110,000
Age 45–54 (heart attack at 3% discount rate) $120,000 $120,000
Age 55–64 (heart attack at 3% discount rate) $200,000 $200,000
Age 65 and over (heart attack at 3% discount rate) $98,000 $98,000
Age 0–24 (heart attack at 7% discount rate) $97,000 $97,000
Age 25–44 (heart attack at 7% discount rate) $110,000 $110,000
Age 45–54 (heart attack at 7% discount rate) $110,000 $110,000
Age 55–64 (heart attack at 7% discount rate) $190,000 $190,000
Age 65 and over (heart attack at 7% discount rate) $97,000 $97,000

Big picture

Time period Development summary More details
Ancient times–1981 Slavery era Period encompassing an era when slavery is legal in at least one politial state, being Mauritania the last country to abolish slavery in 1981.[4] The value of a slave life is quantified as property.
1945–1970s Human rights development and early quantification The right to life is both 'defined' and 'enumerated' in the international human rights instruments following World War Two.[5] The early 1960s see researchers becoming interested in standardizing the description of individuals' health states and scoring them in order to rank them on a scale of severity.[6][7] The Quality-adjusted life year is developed as a measure of the value of health outcomes.[8] From the late 1960s, a final key move is made towards cardinal measurements to order states of illness as well as quantify their undesirability.[6][9]
1970s Monetization and further quantification Researchers first attempt to monetize QALY in the 1970s. In the 1990s, disability-adjusted life years (DALYs) start being used.[10]

Full timeline

Year Event type Details Location
≈3100 BC onwards Value of slave life Ancient Egypt male slaves are worth of approximately 32,000$ (in modern costs).[11] Egypt
27 BC–AD 395 Value of slave life A gladiator (a slave) is worth 2,080$ in the Roman Empire[11] Roman Empire
1776 Concept development Scottish economist Adam Smith introduces the concept of compensating wage differential, proposing that job characteristics influence the nature of labour market equilibrium. CWD for job risks is key when valuing fatality risks. It is the amount of money that the worker needs to pay to attain a small reduction in his risk of death. These values can be estimated from observed labour market data and can be converted to value of statistical life which are then used to value various risk reduction policies.[12][13] United Kingdom
1848 Concept development French economist Jules Dupuit publishes an article that introduces the idea of cost–benefit analysis, whose concept is later formalized in subsequent works by Alfred Marshall.[14] CBA would be used to assign a monetary value to human life (lifesaving or quality of life).[15] France
1850 Value of slave life In the United States, a 10-year-old boy (a slave) is worth $8,100.[11] United States
1931 Organization The American Medical Association Bureau of Medical Economics is established to study all economic matters affecting the medical profession.[16]
1947 Concept development The concept of years of potential life lost (YPLL) is introduced as a means of comparing mortality from tuberculosis with mortality from heart disease. YPLL refers to the total deaths in each age group being multiplied by the difference between the medium age of death in each group and the number of years of life expectancy.[17][18]
1958 Literature Selma Muskin publishes Towards the definition of health economics. At this time, in the United States health is broadly regarded as rather a consumptive branch of the economy. Muhkin’s analysis is the first understanding that health investment has long-term beneficial consequences for the community.[19][20]
1962 Literature Selma Muskin publishes Health as an Investment.[19] United States (University of Chicago Press)
1962 Research In a special conference issue of the Journal of Political Economy, Selma Mushkin articulates the case for investment in human beings through promoting better health. She argues that the return would be through future increases in labor earnings. If one more person were to live because of an investment in health, then national income would be greater by the amount that person would earn in the labor market.[21] United States
1963 Literature American economist Kenneth Arrow publishes an article that is often credited with giving rise to health economics as a discipline. His theory draws conceptual distinctions between health and other goods.[22] United States
1968 Research Klarman et al. publish a key article articulating the idea that would later be formulated as Quality-adjusted life year (QALY), a tool developed to evaluate the cost-effectiveness of treatments.[23][6] United States (Medical Care journal)
1968 Research Thomas Schelling distinguishes between earnings, which he refers to as livelihood, and value of life or living.[21] In a paper about valuing ways to reduce the risk of death, he distinguishes between identified lives and statistical lives. "Identified lives are the miners trapped in a mine or the child with a terminal disease—specific people who need help now. Statistical lives are those people, unidentifiable before the fact and often after as well, who will be saved by a new safety regulation, public health program, or environmental standard. Schelling observed that people seem to be willing to pay more to save an identified life".[24][25]
1968 Concept development Thomas Schelling introduces the "value of statistical life" terminology in his essay The Life You Save May Be Your Own.[26][27] United States
1971 Research Tony Culyer, Bob Lavers and Alan Williams, economists at the University of York, describe the idea combining painfulness and restricted activity, representing it in a diagram.[6] United Kingdom
1972 Concept development American health economist Michael Grossman publishes his model of health production[28] which would become extremely influential in health economics. Grossman's model views each individual as both a producer and a consumer of health. Health is treated as a stock which degrades over time in the absence of "investments" in health, so that health is viewed as a sort of capital. The model acknowledges that health is both a consumption good that yields direct satisfaction and utility, and an investment good, which yields satisfaction to consumers indirectly through fewer sick days. Investment in health is costly as consumers must trade off time and resources devoted to health, such as exercising at a local gym, against other goals. These factors are used to determine the optimal level of health that an individual will demand. The model makes predictions over the effects of changes in prices of healthcare and other goods, labour market outcomes such as employment and wages, and technological changes. These predictions and other predictions from models extending Grossman's 1972 paper form the basis of much of the econometric research conducted by health economists. United States
1972 Concept development Bush et al. become the first to use the term "quality-adjusted life year" (QALY).[29], which calculation can be described as the product of duration of life and a measurement of quality of life.[30] United States (University of California at San Diego)
1973 Research Pressat (and later Ryder, 1975; Fries, 1980; and Manton, 1986) attempts to estimate the maximum lifespan for males and females. Using a range of modeling methods, estimates of the difference between male and female maximum lifespan range from 1.9 to 3.2 years, with females having greater lifespans than males.[31]
1976 Research Richard Zeckhauser and Donald Shepard use the term quality-adjusted life year (QALY) to indicate a health outcome measurement unit that combines duration and quality of life.[32][33]
1976 Research Richard Thaler and Sherwin Rosen develop the modern theory of compensating wage differential in which they adopt Hedonic wage function approach.[12] United States
1977 Research Weinstein and Stason publish an article on the foundations of cost-effectiveness analysis for health care and medical practices. The authors recommend that "alternative programs or services are then ranked, from the lowest value to the highest, and selected from the top until available resources are exhausted."[8][34][8] United Sates (The New England Journal of Medicine)
1979 Concept development The Physical Quality of Life Index (PQLI) is developed by economist Morris David for 23 developed and developing countries.[35] Using three indicators: literacy, infant mortality, and life expectancy at age one, PQLI is an attempt to create a practical measure of social distribution that seeks to avoid the limitations of the Gross National Product, to minimize cultural and developmental ethnocentricity, and to be internationally comparable.[36]
1980 Research Pliskin et al. justify the QALY indicator using multiattribute utility theory: if a set of conditions pertaining to agent preferences on life years and quality of life are verified, then it is possible to express the agent's preferences about couples (number of life years/health state), by an interval (Neumannian) utility function.[37]
1980 Literature Martin Bailey publishes Reducing Risks to Life: Measurement of the Benefits, which advocates the use of individual value of life for guiding policy decisions. Bailey's publication would become an influential policy book.[21][38] United States (American Enterprise Institute for Public Policy Research)
1980 Research According to Pliskin et al., the QALY model requires utility independent, risk neutral, and constant proportional tradeoff behaviour.[37] Because of these theoretical assumptions, the meaning and usefulness of the QALY is debated.[39][40]
1982 Literature (journal) The Journal of Health Economics is launched.[41]
1982 Research Hodgson and Meiners describe cost-of-illness studies using a standardized accounting framework and methodology, enhancing the comparability of studies of different illnesses and conditions.[42]
1982 Research Mishan suggests that, according to the human capital approach, the “value of life” is the value of the individual’s market productivity, a value assumed to be reflected by the individual’s earnings.[43]
1985 Literature John Harris publishes The Value of Life: An Introduction to Medical Ethics.[44]
Mid-1980s Concept development The United States Environmental Protection Agency (EPA) begins using value of a statistical life estimates to value lives saved by environmental standards.[45][24]
1986 Concept development Kaplan and Anderson describe the quality of well-being scale, as another instrument that asks subjects to value health states on a rating scale. The instrument would have wide use in North America.[8] The Quality of Well-Being Scale is defined as "a preference-weighted measure combining three scales of functioning with a measure of symptoms and problems to produce a point-in-time expression of well-being that extends from 0 (for death) to 1.0 (for asymptomatic full function)".[46]
1986 Policy A group of healthcare politicians, health administrators, health-care personnel, and representatives of patients are commissioned by the Norwegian government to set out guidelines for prioritizing in the Norwegian National Health Service. One of the main conclusions of the committee is that severity of illness should continue to be the most important criterion for prioritizing between patients, although this criterion should be considered together with the effectiveness of treatment. Since then, similar positions would be been adopted by government-appointed commissions in several other countries, including Netherlands, New Zealand, and Sweden. Studies of population preferences support these official government positions.[8] Norway
1987 Research British economist Alan Williams suggests that treatment capacity should not be expanded where cost-per-QALY is high if there are untreated patients due to lack of capacity in technologies offering low cost QALYs.[8] United Kingdom
1989 Research Debra Froberg and Robert Kane (and later Richardson (1991)) report on many kinds of problems with QALYs, at the ethical, conceptual, and operational levels.[8]
1989 Recommendation British economist Graham Loomes and Lynda McKenzie recommend that research be conducted concerning the validity of QALYs.[47] QALY often fails to treat diverse sets of people who can benefit from health care equitably. According to some researchers, while the overall purpose of the QALY framework—utility maximization— is not always wrong, when it is activated without consideration and context, it can become a dangerously flawed tool.[48] United Kingdom
1990 Study launch The Global Burden of Disease Study begins.[49] The most comprehensive effort to date to measure epidemiological levels and trends worldwide[50], it is launched with the purpose to provide a tool to quantify health loss from hundreds of diseases, injuries, and risk factors, so that health systems can be improved and disparities can be eliminated.[51]
1990 Research A study by the United States Department of Agriculture on the economic costs of congenital toxoplasmosis, estimates the value of an infant's lifetime earnings at $983,000 (1989 dollars), as one component of the indirect costs of toxopolasmosis.[42] United States
1990 Monetary estimate Roberts and Pinner use an estimate that the value of forgone lifetime earnings is $1.1 million at the time per infant to estimate the economic costs of disease caused by Listeria monocytogenes.[42]
1991 Research Froberg and Kane (and later Richardson in 1991) report on the many kinds of problems with QALYs, at the ethical, conceptual, and operational levels.[8]
1991 Research As an approach to establish equity weights that could be used to rectify biases in QALY calculations as estimations of societal value, Wagstaff specifies a social welfare function that includes a parameter that, in principle, may be estimated by asking members of a society how much they are willing to sacrifice in the total production of QALYs across individuals or groups of individuals in order to obtain a more even distribution of health among those individuals or groups.[8]
1992 Literature (journal) Peer-reviewed academic journal Health Economics is established.[52]
1993 Research A Norwegian-Australian study by Nord and Richardson et al. address the societal concern for life saving. The researchers ask subjects how they, thinking of themselves as members of parliament, would evaluate two equally expensive proposed special units A and B. Unit A would save ten people per year from dying and restore full health. Unit B would restore to full health a number of people in 34 Concerns for Fairness the following state: "sitting in a wheelchair, pain most of the time, unable to work." The question put to the subjects is: How many patients must be treated in unit B per year in order that you would find it just as valuable to spend the money on unit B as on unit A? The median responses in Norway and Australia are 50 and 40, respectively. In another group of subjects, the condition treated in unit B would be described instead as follows: "uses crutches for walking, light pain intermittently, unable to work." The median responses would be then 110 and 85.[8]
1993 Concept development The 1993 World Development Report introduces the concept of disability adjusted life years lost (DALYs) as a way to estimate and compare the burden of morbidity and premature mortality caused by widely varying conditions and states within and among countries.[53]
1993 Research Using time trade-off questions to find the relative value that people assign to life years at different stages in their own lives, Busschbach et al. in the Netherlands find the following implied relative values for ages 5, 10, 35, 60, and 70, respectively: 1.7, 1.6, 1.0, 0.7, 0.7. This study clearly suggests support for policies that favor the young over the elderly.[8]
1993 Research Fryback et al. study health-related quality of life in a random sample of 1,356 adults in a community population, using, among other instruments, a time trade-off questionnaire. "Their report includes twenty-five chronic conditions that affected a sufficient number of people to allow calculations of mean time trade-off-scores with 95 percent confidence intervals less than 15 percentage points. The willingness to sacrifice longevity in order to be cured of one specific illness is not observed directly, as the TTO refers to becoming healthy and most subjects had more than one condition. However, the authors estimate that the conditions associated with the highest disutilities are insulin dependent diabetes (WTSL = 24 percent), depression (17 percent), asthma (16 percent), and chronic bronchitis (14 percent). The willingness to sacrifice was only 5-8 percent in people with arthritis, severe back pain, migraine, angina, cataracts, ulcers, colitis, and sleep disorder".[8]
1994 Research Tolley et al. provide a comparison of the cost of illness and the value of life based on an individual’s willingness to trade money and risk.[21]
1994 Research Tsevat et al. apply the time trade-off technique in 1,438 seriously ill patients with a projected overall six-month mortality rate of 86. The patients had at least one of the following nine diseases: acute respiratory failure, acute exacerbation of severe chronic obstructive pulmonary disease, acute exacerbation of severe chronic congestive heart failure, chronic liver failure with cirrhosis, nontraumatic coma, colon cancer metastatic to the liver, metastatic non-small-cell carcinoma of the lung, multiorgan system failure with malignancy, and multiorgan system failure with sepsis. The subjects were asked to choose (hypothetically) between one year in the current state and a shorter time period healthy. Responses varied widely. Mean willingness to sacrifice time was 27 percent, corresponding to a utility score of 0.73. Thirty-five percent of the patients were unwilling to exchange any time in their current state for a shorter life in excellent health.[8] United States
1994 Research Murray et al. propose a DALY minimization objective for health systems, strictly discussing allocation of total health sector resources, regardless of financing source, in order to minimize total DALYs for society.[31]
1995 Monetary estimate In Sweden, the value of a statistical life is estimated from 9 to 98 million SEK (€0.9 - 10.6 million).[54] Sweden
1995 Research Whereas DALYs are conceptually equivalent to QALYs, inasmuch as they combine reductions in morbidity and mortality in a single value index, around this time disability weights for DALY calculations start being based on a procedure for preference measurement that is quite different from those used in the QALY field.[8]
1995 Research A study of the cost-effectiveness reviewing over 500 life-saving interventions finds that the median cost-effectiveness is $42,000 per life-year saved in the United States.[55] United States
1995 Research The Intergovernmental Panel on Climate Change calculates that a life in an industrialized country is worth $1.5 million, whereas a life in a developing country was worth only $150,000.[3]
1995 Monetary estimate A study of the cost-effectiveness reviewing over 500 life-saving interventions in the United States find that the median cost-effectiveness is $42,000 per life-year saved.[56] United States
1996 Research Using time trade-off questions to find the relative value that people assign to life years at different stages in their own lives, Tsuchiya in Japan finds the following implied relative values for ages 5, 10, 35, 60, and 70, respectively: 1.7, 1.6, 1.0, 0.7, 0.7. Like Busschbach study from 1992, this study clearly suggests support for policies that favor the young over the elderly.[8] Japan
1996 Literature Stephen R. Kellert and Stephen H. Kellert publish The Value of Life: Biological Diversity And Human Society.[57] United States (Island Press)
1996 Monetary estimate Buzby, Roberts, Lin, and MacDonald include forgone lifetime earnings in their estimate that foodborne bacteria impose between $2.9 and $6.7 billion of economic costs. In an update a year later, Buzby and Roberts include estimates of the costs of Guillain-Barré‚ syndrome related to Campylobacter jejuni infection.[42]
1997 Research The United States Environmental Protection Agency, based on an extensive review of the research literature, suggests that a reasonable estimate of the value of statistical life has a mean of US$4.8 million with a confidence interval of plus or minus $3.2 million (in 1990 dollars).[42] United States
1997 Research Williams argues that a salient ethical basis for rejecting distributive neutrality is the fair innings argument, namely, the general sentiment that everyone is entitled to a "normal" lifetime of around 70-75 years, and that anyone failing to achieve this has in some sense been cheated, while anyone getting more than this is living on "borrowed time." Williams addresses the fact that there is a significant difference between social classes in the United Kingdom with respect to quality adjusted life expectancy (QALE) at birth. Adopting a social welfare function of the kind suggested by Wagstaff (1991), Williams gives a hypothetical example of how observations of people's willingness to trade off mean QALE, for equality in QALE could be used to estimate a parameter for the strength of aversion to inequality.[8]
1997 Research Sherbourne et al. collect time trade-off and standard gamble data from 18,000 patients visiting medical centers across the United States. On average, the patients scored themselves 75 on a rating scale from 0 ("worst possible health state") to 100 ("perfect health"). However, 70 percent of the patients, including many who were very sick, were not willing to sacrifice any life expectancy to be relieved of their condition.[8]
1998 Compensation for death A U.S. Marine jet hits aerial tramway cables in Italy. As form of compensation, the United States gives close to US$2 million to each Italian victim.[5] Italy
1998 Organization The World Health Organization creates a Disease Burden Unit, which generates Global Burden of Disease (GBD) estimates, and publishing them at WHO’s annual World Health Reports.[49]
1999 Research Estimating compensating-wage differentials for risk of fatal and nonfatal injuries in India's manufacturing industry, Nathalie et al. estimate compensating-wage differentials implying a value of statistical life (VSL) in India of 6.4 million to 15 million 1990 rupees (roughly $150,000 to $360,000 at current exchange rates), a number is between 20 and 48 times forgone earnings-the human capital measure of the value of reducing the risk of death.[12][13]
1999 (May) Compensation for death After the United States Air Force kill and injure a number of people in bombing the Chinese Embassy in Belgrade, the U.S. government agree to pay US$4.5 million in damages, which amount to about US$150,000 per victim.[5]
2000 Literature (journal) The European Journal of Health Economics is first issued.[58] Germany (Springer Science+Business Media)
2001 Research Alberini et. al publish a study comparing the willingness to pay for mortality risk reductions in the United States and Canada, and conclude that with increase in size of risk reduction, willingness to pay also increases. The researchers find little evidence of variation of WTP with respondent’s age. Value of statistical life is estimated between $930,000 and $4,800,000 (2000 USD).[59][12] United States, Canada
2001 Research Nor Ghani MD. Nor and Mohd Faudzi Mohd Yusoff publish a willingness to pay study amongst young motorcyclists and accident costing on Malaysia. Findings suggest that, although young riders were initially thought to have higher valuation of lives compared to senior counterparts, this result is not robust. The study recommends adopting a value of MYR1.1 million (about $290,000 and almost five times previous estimates) per statistical life for public policy analysis involving motorcycle safety in the country. Motorcyclists constitute a large proportion of total road casualties in Asian countries.[60][12] Malaysia
2001 Research A study by Ja Fox-Rushby and K Hanson concludes that the calculation and presentation of DALYs for use in cost-effectiveness analysis should:
  • Depending on the circumstances, use relevant cohort life expectancies, locallife tables or a population model, not the standard expected years of life lost (SEYLL) method.
  • State all the assumptions used to calculate DALYs
  • Present a range of DALY estimates (at least DALYs [0,0,0] and DALYs [0.03,1,0.04])
  • Test the sensitivity of cost-effectiveness ratios to changes in the assumptions used to calculate DALYs.[61]
United Kingdom (London School of Hygiene & Tropical Medicine)
2001 Compensation for death In the United States, the next of kin of each person who died in the September 11 attacks receive some $2 million. This would spark an angry debate in the country about the respective compensation to the victims of Hurricane Rita.[5] United States
2001 Concept introduction The World Health Organization starts publishing statistics called Healthy life expectancy (HALE), defined as the average number of years that a person can expect to live in "full health" excluding the years lived in less than full health due to disease and/or injury.[62][63]
2002 Notable comment Canadian academic William Schabas observes that the right to life is "intangible in scope, and vexingly difficult to define".[64][5]
2002 Research Per-Olov Johansson suggests that the value of statistical life should track the life-cycle pattern of consumption.[43][65] Sweden (Stockholm School of Economics)
2002 Research Study by Jennifer Jelsma et al. concludes that, whereas the incorporation of the impact of disability on disease burden is validly recognized, the disability-adjusted life year is insensitive to changes in disability status. As a consequence, resource allocation to rehabilitation activities based on cost-effectiveness analysis using DALYs may be diminished. The researchers also conclude on the lack of epidemiological information relating to disability.[66]
2002 Policy The United States Environmental Protection Agency decides the value of elderly people is 38 percent less than that of people under 70. After the move becomes public, the agency reverses itself.[67] United States
2003 Research W. Kip Viscusi and Joseph E. Aldy publish study concluding that the estimates of the value of a statistical life can continue to serve as a critical input in benefit-cost analyses of proposed regulations and policies. "Refining VSLs for the specific characteristics of the affected population at risk remains an important priority for the research community and the government agencies conducting these economic analyses."[68][12] United States
2003 Research A study by Jin-Tan Liu et al. on valuation of the risk of SARS in Taiwan finds that willingness to pay for risk reduction increases with degree of risk reduction. WTP for a vaccine that protects individuals from SARS is fairly high compared to WTP for other fatal risk reduction.[69][12] Taiwan
2003 Literature Kevin M. Murphy and Robert H. Topel publish Measuring the Gains from Medical Research: An Economic Approach.[70] Its first chapter argues that the value of improved life expectancy over the last ~100 years (monetized using the value of a statistical life framework) is comparable to total measured gross domestic product growth over that time.[71] United States (University of Chicago Press)
2003 Research Alberini et al. publish a study analizing the value of a statistical life variation with age and health status in the United States and Canada, and concludes that willingness to pay does not decline much with age.[12][72] Canada, United States
2003 Research According to Viscusi, there are racial differences in labor market values of a statistical life in the United States. Implicit value of statistical life and annual compensation for fatal risks is lower for black workers compared to white workers: $9.4 - $18.8 for whites and $5.9 - $8.9 for blacks.[73][12] United States
2003 Research The income elasticity of the value of statistical life is estimated at 0.5 to 0.6.[74]
2004 Research Louis R. Eeckhoudt and James K. Hammitt publish study examining the relationship between aversion to financial risk and willingness to pay to reduce mortality risk and find that it is sensitive to what other characteristics of the utility function are held constant as risk aversion is altered. "Although aversion to financial risk increases value of a statistical life in definable cases, under many plausible assumptions the relationship between risk aversion and value of a statistical life is ambiguous".[75][12]
2004 Concept introduction Eurostat starts publishing annual statistics called Healthy Life Years (HLY) based on reported activity limitations.[76] HLY is defined as the number of years that a person is expected to continue to live in a healthy condition.[77] Europe
2004 Research Lucas W. Davis publishes an article on the effect of health risk on housing values. Analizing evidence from a cancer cluster in Nevada, the results suggest that housing values fell by 15.6 % during peak risk period, for various risk measures and size of house.[78] United States
2004 Notable comment French philosopher Jacques Derrida argues that the right to life is "highly precarious", as its "concept and axiom are more than problematic".[79][5] France
2004 Research Joseph E Aldy and W Kip Viscusi publish study on age variations in workers' value of a statistical life in the United States, and find that the value of statistical life exhibits an inverted U-shaped relationship over an individual's life cycle.[12] United States
2004 Research S. Madheswaran publishes study measuring the value of life and estimating compensating wage differentials among workers in Chennai and Mumbai Finds that job risk decreases with worker’s wealth. According to Madheswaran, "worker’s wage increases with his education level, being in union and belonging to lower caste. Fatal, nonfatal job risk and subjective risk assessment of workers had positive influence on wage." Madheswaran calculates a value of statistical life of 15 million Indian rupees.[12][80] India
2004 Policy The United States Environmental Protection Agency cuts the estimated value of a life by 8 percent, and then takes away the normal adjustment for one year's inflation. Between the two changes, the value of a life would fall 11 percent.[67] United States
2005 Research Chris Rohlfs publishes a study estimating the willingness to pay to avoid military service and fatality risk. Drawing evidence from the Vietnam Draft, Rohlfs finds WTP of white men being higher than black men. Rohlfs VSL ranging from $1.1million to $4 million (2003 USD).[12][81] United States
2005 Research Minhaj Mahmud publishes study measuring trust and the value of statistical lives in Bangladesh. Evidence shows that young people underestimate risk compared to older people. Mahmud calculates the value of statistical life ranging from $1,783 to $2,922.[12][82] Bangladesh
2005 (May) Research Viscusi and Kniesner publish study on value of a statistical life comparing relative position vs. relative age in the United States. The researchers find that, disregarding relative position of worker in wage distribution has little impact on VSL but, disregarding planned consumption of worker underestimates VSL by about 20 percent.[12][83] United States
2006 Concept adoption The United States Public Health Service’s “Healthy People Initiative,” which measures progress toward US public health goals, uses QALYs as one of its key metrics.[84] United States
2006 Research Thomas J. Kniesner, W. Kip Viscusi and James P. Ziliak publish a study on life-cycle consumption and the age-adjusted value of life. The researchers find that age pattern of consumption varies, and observe that implicit VSL increases and then declines over lifetime in a manner such that the value for aged workers is higher than the average value of young.[12][85] United States
2006 Monetary estimate Calculations on person-years of potential life lost in the United States cause by premature death are estimated at 8,628,000 person-years for cancer, 8,760,000 for heart disease and strokes, 5,873,000 for accidents and other injuries, and 13,649,000 for all other causes.[86] United States
2006 Research Mathieu suggests that the assessment of the evolving spectrum of life scenarios from an isolation of life in its biological existence through to life as apolitical expression requires a multi-disciplinary analysis.[5]
2006 Research Muhammad Rafiq and Mir Kalan Shah publish study examining the risk-wages trade off in Pakistan, and find that higher fatality risks are associated with higher wage. However, for injury risk the results are unclear. The researchewrs calculate the value of statistical life ranging from $122,047 (10.4 million PKR) to $435,294 (37 million PKR).[2] Pakistan
2006 Research Bleichrodt and Eeckhoudt assume that individuals do not evaluate probabilities linearly and show that this may affect the willingness to pay for reduction in mortality risks.[43]
2007 Organization The Institute for Health Metrics and Evaluation is founded.[87] Located at the University of Washington, it is an independent global health research center that provides measurement of the world's most important health problems and evaluates the strategies used to address them.[88][89] United States
2007 Research According to Andersson, the value of statistical life decreases with the background risk.[43] Sweden
2007 Research T. Kogut and I. Ritov find that, when the cases are presented separately, identifiable individuals receive greater contributions than identifiable groups.[90]
2007 Literature Lisa A Robinson at Harvard University publishes How U.S. Government Agencies Value Mortality Risk Reductions.[91] According to the report, at least in the United States, official bodies tend to assume that all individuals have the same value of statistical life, regardless of differences in income, status quo risk of dying, or other attributes.[90] United States
2008 Research Research by the University of York identifies that the cost per quality adjusted life year for changes in existing National Health Service expenditure in 2008 was £12,936, leading to concerns new treatments approved by National Institute for Health and Care Excellence at £30,000 per quality adjusted life year are less cost-effective than spend on existing treatments. This would mean that diverting NHS spend to new treatments would forgo more than 2 quality adjusted life years for every year gained from the new treatment. [92] United Kingdom
2009 Policy The U.K. National Institute for Health and Clinical Excellence (NICE) sets the nominal cost-per-QALY threshold at £50,000 for end-of-life care because dying patients typically benefit from any treatment for a matter of months, making the treatment's QALYs small.[93] United Kingdom
2010 Cost per life saved case An estimated $10–$20 million are spent to save 33 Chilean miners trapped during the Copiapó mining accident. This is a notable example of how identified lives are valued more highly than statistical lives.[24][94] In 2015, Cohen, Daniels and Eyal take this case as an example of allocation resources reactively rather than proactively, prioritizing treatment over prevention, and prioritizing a specific group instead of implementing more cost effective mine safety measures.[90] Chile
2010 Research Study by Abdelaziz Benkhalifa on the value of mortality risk reductions in the Tunisian building and manufacturing industries, finds positive and significant fatal risk premium implying higher value of mortality risk in the building and manufacturing industries. Benkhalifa calculates the value of statistical life ranging from 448663.32 Dinnars (manufacturing) to 689280.5 (building).[12][95] Tunisia
2010 Research With funding from the European Commission, the European Consortium in Healthcare Outcomes and Cost-Benefit Research (ECHOUTCOME) begins a major study on QALYs as used in health technology assessment.[96]
2010 Research R. Kirkdale et al. note that Quality-adjusted life year only considers the quality of life when patients may choose to suffer negative side-effects to live long enough to attend a milestone event, such as a wedding or graduation.[97] United Kingdom
2011 Research A study by K. R. Shanmugam and S. Madheswaran on the compensating wage differentials for job risks shows that fatal, non-fatal and subjective job risk positively and significantly affect worker’s wage. Age and VSL show an inverted-U shaped relation. Union and backward community workers have higher wage. The researchers estimate a statistical value of life of $3.74 million (1990 USD).[12] India
2011 Tool launch The Institute for Health Metrics and Evaluation launches the Global Health Data Exchange, which indexes and hosts information about microdata, aggregated data, and research results with a focus on health-related and demographic datasets.[98] It is the world's most comprehensive catalog of surveys, censuses, vital statistics, and other health-related data.[99] United States
2011 (November) Cost per life saved case Charity evaluator GiveWell, in its analysis of cost-effectiveness, estimates that the “cost per life saved” for long-lasting insecticidal net distribution is about $1,600 (using marginal cost) and $1,700 (using total cost)[100], figures that would increase over the years[101][102][103][104], in contrast with the estimated cost per long-lasting insecticide net distributed, which would decrease. See Timeline of Against Malaria Foundation.
2012 (February 10) Literature The OECD publishes Mortality Risk Valuation in Environment, Health and Transport Policies, which attempts to provide with a meta-analysis of value of a statistical life estimates drawn from surveys where people around the world have been asked about their willingness to pay for small reduction in mortality risks.[105]
2012 Monetary estimate A wage-risk study estimates values of $4–$10 million per life saved (2001 dollars) for a sample of employed men with an average age of 40. Using the Consumer Price Index to adjust the value of statistical life estimates to 2007 raises the range to $4.7–$11.7 million, almost 5–12 times as large as future discounted earnings.[24][106]
2012 Monetary estimate Studies by Hacettepe University estimate the value of statistical life at about half a million purchasing power parity adjusted 2012 US dollars,[107] the value of a healthier and longer life (VHLL) for Turkey at about 42,000 lira (about $27,600 in PPP-adjusted 2012 USD), and the value of a life year (VOLY) as about 10,300 TL (about $6,800 in PPP-adjusted 2012 USD).[108] Turkey
2013 Research A review reports that there are well over a hundred value of a statistical life (VSL) studies.[109][24]
2013 (June) Research A study by Jie He and Hua Wang on the value of statistical life in China, uses data on the incidence of cancer illness and death in the population, and finds that the willingness to pay figures imply that "the marginal value of reducing the anticipated incidence of cancer mortality by one in the population is 73,000 yuan and an average value of 795,000 yuan, which are about six and 60 times average household annual income, respectively."[110] China
2014 Research According to Kniesner, Viscusi, and Ziliak, willingness to pay (WTP) refers to the underlying principle for valuing the benefits of fatal risk reduction policies.[111][12] United States
2015 Research According to Yates and Doerr, the "metrification" or quantification of life comes with the suggestion that there is a calculable and controllable way of achieving a goal. "Taking in X calories while expending Y calories through exercise, for example, would result in weight loss if Y is larger than X."[112][113]
2015 Monetary estimate On the results of opinion poll life value (as the cost of financial compensation for the death) in the beginning of this year, the value of life in Russia is estimated at about $71,500.[114] Russia
2015 Research A study suggests the global 'mean loss of life expectancy' (LLE) from all forms of direct violence is about 0.3 years, while air pollution accounts for about 2.9 years in the year.[115] Worldwide
2015 Research John Brazier and Aki Tsuchiya propose improvements for quality-adjusted life years by extending the data used to calculate them (e.g., by using different survey instruments), using well-being to value outcomes (e.g., by developing a "well-being-adjusted life-year"), and by value outcomes in monetary terms.[116] United Kingdom
2015 Literature I. Glenn Cohen, Norman Daniels, and Nir Eyal publish Identified versus Statistical Lives: An Interdisciplinary Perspective, which attempts to explian why people tend to demonstrate a stronger inclination to assist persons and groups identified as at high risk of great harm than those who will or already suffer similar harm, but endure unidentified.[90] United Kingdom (Oxford University Press)
2016 Research American health economist Louis Preston Garrison reports in his article that US private payers, with a few limited exceptions, rarely explicitly use costutility analyses (CUAs), the cost-effectiveness studies that rely on QALYs, in their benefits and reimbursement decisions. Garrison states that it is a “puzzle” that the United States has so many competent health economists who made so many CUAs, but that US private and public payers rarely make direct use of their material.[84] United States
2016 (May 28) Cost per life saved case The killing of Harambe occurs after a 3-year-old boy fell into the animal's enclosure and began to be dragged around by the Western lowland gorilla. Fearing for the boy's life, a zoo worker shot and killed Harambe.[117] This case would trigger ethical dilemmas over the value of human versus non-human life.[118] United States
2016 Policy The U.K. National Institute for Health and Care Excellence sets the cost-per-QALY threshold at £100,000 for treatments for rare conditions because, otherwise, drugs for a small number of patients would not be profitable.[119] United Kingdom
2016 (August 4) Literature Dmitry A. Kondrashov publishes Quantifying Life: A Symbiosis of Computation, Mathematics, and Biology, which attempts to introduce mathematical modeling used in biology.[120] United States (University of Chicago Press)
2016 Monetary estimate The U.S. Department of Transportation uses a value of $9.6 million for a statistical life[121], which is considered on the high side relative to other estimates.[122] United States
2016 (October) Research A study attempting to estimate the social value of statistical life in the city of Nanjing in China concludes that, after using the tax system to illustrate the contribution of different income groups to social funds, the average social value of statistical life is found to be 7,184,406 RMB (US$1,130,032).[123] China
2018 (September) Cost per life saved case An article by Jye Sawtell-Rickson, titled Quantifying The Thai Cave Rescue, analizes the cost to save 12 Thai boys during the Tham Luang cave rescue. Sawtell-Rickson writes "At a cost of over $500,000, the money could have been allocated to other sources which could have without a doubt saved more lives (...) In particular, over 100 lives could have been saved in Africa with this funding."[124] Thailand
2018 (December) Concept development The Institute for Clinical and Economic Review (ICER) introduces the Equal Value of Life Years Gained (evLYG) metric and incorporates it in its 2020-2023 Value Assessment Framework to be a component of all their new health technology assessments.[125] evLYG is a generic measure used to determine how much a medical treatment can extend the life of the patient. United States
2019 (April) Research Mark H. Bernstein publishes an article aiming to show that there is no good reason to sustain the common belief in the hierarchy of value concerning animal lives.[126]
2019 (June) Research Keller et al., searching databases to identify methodological and empirical studies, conclude that estimates for the value of a statistical life varies substantially by context (sector, developed/developing country, socio-economic status, etc), with the median of midpoint purchasing power parity–adjusted estimates of 2019 US$5.7 million ($6.8 million, $8.7 million, and $5.3 million for health, labor market, and transportation safety sectors, respectively).[127]
2019 (July) Research Non-profit Open Philanthropy publishes a study describing how they think about the “bar” for charitable giving and how they compare different kinds of interventions using back-of-the-envelope calculations. In some cases, in addition to looking at monetary savings or gains, Open Philanthropy also uses “value of a statistical life” techniques to try to account for health and quality-of-life benefits, and yield more cost-effectiveness estimates. Among the several findings, the study concludes that, if the lives of children are to be saved by GiveWell’s global health charities the same way the U.S. Department of Transportation values lives lost in car crashes in the United States, there would be estimated ~5,000x returns ($9.6 million benefit/~$2,000 cost per life saved equivalent).[122] United States
2019 (September) Research A study is published providing evidence that support a constant value of a QALY and indicates that the primary cause of variation in the value of a QALY is not caused by the size of the QALY gain. "The source of variation is, instead, likely to be found in budget constraints and diminishing marginal returns. The original chained approach was found to be sensitive to injury severity and duration and shown to be mostly internally consistent. The method could be a valid alternative approach for estimating the value of major health loss."[128]
2020 Monetary estimate The United States Federal Emergency Management Agency estimates the value of a statistical life at US$7.5 million in the year.[129] United States
2021 (January) Research A study by M. Wilks et al. finds that children lack the “speciesism” bias of adults, and value animal life much more than the latter do. This suggests that speciesism is a learned attitude, and that the common view that humans are far more morally important than animals appears late in development and is likely socially acquired.[130][131] United States
2021 Monetary estimate In Australia, the value of a statistical life is set at AU$5.1 million (about US$3.8 million), and the value of statistical life year is set at $222,000 (about US$165,000).[132] Australia

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  1. 1.0 1.1 Sunstein, Cass R. (2004). "Valuing Life: A Plea for Disaggregation". Duke Law Journal. 54 (2): 385–445. ISSN 0012-7086. 
  2. 2.0 2.1 "How Much is a Life Worth? Examining the Risk-Wages Trade Off in Pakistan" (PDF). 
  3. 3.0 3.1 Sunstein, Cass R. (5 September 2014). Valuing Life: Humanizing the Regulatory State. University of Chicago Press. ISBN 978-0-226-78017-7. 
  4. CNN, John D. Sutter, Edythe McNamee. "Slavery's last stand - CNN.com". CNN. Retrieved 19 June 2022. 
  5. 5.0 5.1 5.2 5.3 5.4 5.5 5.6 Yorke, Dr Jon (28 February 2013). The Right to Life and the Value of Life: Orientations in Law, Politics and Ethics. Ashgate Publishing, Ltd. ISBN 978-1-4094-9715-8. 
  6. 6.0 6.1 6.2 6.3 MacKillop, Eleanor; Sheard, Sally (August 2018). "Quantifying life: Understanding the history of Quality-Adjusted Life-Years (QALYs)". Social Science & Medicine. 211: 359–366. doi:10.1016/j.socscimed.2018.07.004. 
  7. Katz, Sidney (21 September 1963). "Studies of Illness in the Aged: The Index of ADL: A Standardized Measure of Biological and Psychosocial Function". JAMA. 185 (12): 914. doi:10.1001/jama.1963.03060120024016. 
  8. 8.00 8.01 8.02 8.03 8.04 8.05 8.06 8.07 8.08 8.09 8.10 8.11 8.12 8.13 8.14 8.15 8.16 Nord, Erik (28 September 1999). Cost-Value Analysis in Health Care: Making Sense out of QALYS. Cambridge University Press. ISBN 978-0-521-64434-1. 
  9. Rosser R. Issues of measurement in the design of health indicators: a review. In: Culyer A.J., editor. Health Indicators. Martin Robertson; Oxford: 1983. pp. 34–81.
  10. Harris, John P; Iturriza-Gomara, Miren; O’Brien, Sarah J (21 February 2019). "Estimating Disability-Adjusted Life Years (DALYs) in Community Cases of Norovirus in England". Viruses. 11 (2): 184. doi:10.3390/v11020184. 
  11. 11.0 11.1 11.2 Vilks, Andrejs (2018). "Price of human life: Medical, legal and social aspects". SHS Web of Conferences. 51: 01016. doi:10.1051/shsconf/20185101016. 
  12. 12.00 12.01 12.02 12.03 12.04 12.05 12.06 12.07 12.08 12.09 12.10 12.11 12.12 12.13 12.14 12.15 12.16 12.17 12.18 Majumder, Agamoni (2016). Value of statistical life : a meta-analysis with mixed effects regression model. Bangalore. ISBN 978-81-7791-218-0. 
  13. 13.0 13.1 Simon, Nathalie B.; Cropper, Maureen L.; Alberini, Anna; Arora, Seema (31 January 1999). "Valuing mortality reductions in India : a study of compensating wage differentials". The World Bank. 
  14. Livermore, Michael A.; Revesz, Richard L. (21 February 2013). The Globalization of Cost-Benefit Analysis in Environmental Policy. OUP USA. ISBN 978-0-19-993438-6. 
  15. "Human cost as a factor used in the cost-benefit analysis". researchgate. Retrieved 10 June 2022. 
  16. Rebelo, LP (2007). The Origins and the Evolution of Health Economics: A Discipline by Itself?. 
  17. "Years of Potential Life Lost-Brazil, 1980" (PDF). 
  18. Cavazos-Ortega, N.; del Río-Zolezzi, A.; Izazola-Licea, J. A.; Lezana-Fernández, M. A.; Valdespino-Gómez, J. L. (September 1989). "[Years of potential life lost: their usefulness in the analysis of mortality in Mexico]". Salud Publica De Mexico. 31 (5): 610–624. ISSN 0036-3634. 
  19. 19.0 19.1 Mihajlo, Jakovljevic; Seiritsu, Ogura (1999). "Health Economics at the Crossroads of Centuries – From the Past to the Future.". Frontiers in Public Health. 4: 115. PMC 4899886Freely accessible. PMID 27376055. doi:10.3389/fpubh.2016.00115Freely accessible. 
  20. Uncertainty and the welfare economics of medical care. 1963. 
  21. 21.0 21.1 21.2 21.3 Blomquist, G.C. (2001). "Value of Life, Economics of". International Encyclopedia of the Social & Behavioral Sciences: 16133–16139. doi:10.1016/B0-08-043076-7/02278-6. 
  22. Arrow, Kenneth (1963). "Uncertainty and the Welfare Economics of Medical Care". The American Economic Review. 53 (5): 941–973. JSTOR 1812044. 
  23. Klarman, Herbert E.; Francis, Jhon O??S.; Rosenthal, Gerald D. (January 1968). "Cost Effectiveness Analysis Applied to the Treatment of Chronic Renal Disease:". Medical Care. 6 (1): 48–54. doi:10.1097/00005650-196801000-00005. 
  24. 24.0 24.1 24.2 24.3 24.4 Russell, Louise B. (July 2014). "Do We Really Value Identified Lives More Highly Than Statistical Lives?". Medical Decision Making. 34 (5): 556–559. doi:10.1177/0272989X13512183. 
  25. Schelling, TC . The life you save may be your own. Reprinted in Choice and Consequence: Perspectives of an Errant Economist. Cambridge (MA): Harvard University Press; 1984. p 113–46. Originally published in Chase, SB ., ed. Problems in Public Expenditure Analysis. Washington (DC): The Brookings Institution; 1968. p 127–61.
  26. Banzhaf, H. Spencer (November 2014). "Retrospectives: The Cold-War Origins of the Value of Statistical Life". Journal of Economic Perspectives. pp. 213–226. doi:10.1257/jep.28.4.213. Retrieved 8 May 2022. 
  27. Schelling, T. C. (1968). "The Life You Save May Be Your Own". eweb:1577. 
  28. Grossman, Michael (March 1972). "On the Concept of Health Capital and the Demand for Health". Journal of Political Economy. 80 (2): 223–255. doi:10.1086/259880. 
  29. Bush, J.W.; Fanshel, S.; Chen, M.M. (February 1972). "Analysis of a tuberculin testing program using a health status index". Socio-Economic Planning Sciences. 6 (1): 49–68. doi:10.1016/0038-0121(72)90006-7. 
  30. "Quality Adjusted Life Year - an overview | ScienceDirect Topics". www.sciencedirect.com. Retrieved 19 June 2022. 
  31. 31.0 31.1 Murray, Christopher J.L.; Acharya, Arnab K. (December 1997). "Understanding DALYs". Journal of Health Economics. 16 (6): 703–730. doi:10.1016/s0167-6296(97)00004-0. 
  32. Sassi, F. (28 July 2006). "Calculating QALYs, comparing QALY and DALY calculations". Health Policy and Planning. 21 (5): 402–408. doi:10.1093/heapol/czl018. 
  33. Zeckhauser, Richard; Shepard, Donald (1976). "Where Now for Saving Lives?". Law and Contemporary Problems. 40 (4): 5–45. ISSN 0023-9186. JSTOR 1191310. doi:10.2307/1191310. 
  34. Weinstein, Milton C.; Stason, William B. (31 March 1977). "Foundations of Cost-Effectiveness Analysis for Health and Medical Practices". New England Journal of Medicine. 296 (13): 716–721. doi:10.1056/NEJM197703312961304. 
  35. "Physical Quality of Life Index (PQLI)". HPPSC HAS Exam Free Notes. 13 June 2019. Retrieved 22 June 2022. 
  36. Morris, Morris D. (1 November 1978). "A physical quality of life index". Urban Ecology. 3 (3): 225–240. ISSN 0304-4009. doi:10.1016/0304-4009(78)90015-3. 
  37. 37.0 37.1 Pliskin, J. S.; Shepard, D. S.; Weinstein, M. C. (1980). "Utility Functions for Life Years and Health Status". Operations Research. 28 (1): 206–24. JSTOR 172147. doi:10.1287/opre.28.1.206. 
  38. Bailey, Martin J. (1980). Reducing Risks to Life: Measurement of the Benefits. American Enterprise Institute for Public Policy Research. ISBN 978-0-8447-3346-3. 
  39. Prieto, Luis; Sacristán, José A (2003). "[No title found]". Health and Quality of Life Outcomes. 1 (1): 80. doi:10.1186/1477-7525-1-80. 
  40. Mortimer, Duncan; Segal, Leonie (January 2008). "Comparing the Incomparable? A Systematic Review of Competing Techniques for Converting Descriptive Measures of Health Status into QALY-Weights". Medical Decision Making. 28 (1): 66–89. doi:10.1177/0272989X07309642. 
  41. "Journal of Health Economics | Vol 1, Issue 3, Pages 217-309 (December 1982) | ScienceDirect.com by Elsevier". www.sciencedirect.com. Retrieved 18 May 2022. 
  42. 42.0 42.1 42.2 42.3 42.4 "Using Estimates of the Value of a Statistical Life in Evaluating Regulatory Effects" (PDF). ers.usda.gov. Retrieved 4 May 2022. 
  43. 43.0 43.1 43.2 43.3 Andersson, Henrik; Treich, Nicolas. "The Value of a Statistical Life" (PDF). 
  44. Harris, John (5 December 2006). The Value of Life: An Introduction to Medical Ethics. Routledge. ISBN 978-1-134-95420-9. 
  45. US Environmental Protection Agency, National Center for Environmental Economics . Frequently asked questions on mortality risk valuation.
  46. Button, Brenda (2014). "Quality of Well-Being (QWB) Scale". Encyclopedia of Quality of Life and Well-Being Research: 5314–5320. doi:10.1007/978-94-007-0753-5_654. 
  47. Loomes, Graham; McKenzie, Lynda (1989). "The use of QALYs in health care decision making". Social Science & Medicine. 28 (4): 299–308. ISSN 0277-9536. PMID 2649989. doi:10.1016/0277-9536(89)90030-0. 
  48. John Browne, PhD; Donna R. Cryer, J. D.; Warren Stevens, PhD (14 July 2021). "Is the QALY Fit for Purpose?". The American Journal of Accountable Care. 9 (2). 
  49. 49.0 49.1 "GBD History". Institute for Health Metrics and Evaluation. 18 April 2014. Retrieved 4 May 2022. 
  50. "Global Burden of Disease (GBD 2019)". Institute for Health Metrics and Evaluation. 17 March 2014. Retrieved 27 May 2022. 
  51. "About GBD". Institute for Health Metrics and Evaluation. 18 April 2014. Retrieved 27 May 2022. 
  52. "Health economics.". worldcat. 1992. Retrieved 14 May 2022. 
  53. Larson, Bruce A. (8 August 2013). "Calculating disability-adjusted-life-years lost (DALYs) in discrete-time". Cost Effectiveness and Resource Allocation. p. 18. doi:10.1186/1478-7547-11-18. Retrieved 5 May 2022. 
  54. Hultkrantz, Lars; Svensson, Mikael (1 December 2012). "The value of a statistical life in Sweden: A review of the empirical literature". Health Policy. 108 (2): 302–310. doi:10.1016/j.healthpol.2012.09.007. 
  55. Tengs, Tammy O.; Adams, Miriam E.; Pliskin, Joseph S.; Safran, Dana Gelb; Siegel, Joanna E.; Weinstein, Milton C.; Graham, John D. (June 1995). "Five-Hundred Life-Saving Interventions and Their Cost-Effectiveness". Risk Analysis. 15 (3): 369–390. doi:10.1111/j.1539-6924.1995.tb00330.x. 
  56. "Five-Hundred Life-Saving Interventions and Their Cost Effectiveness" (PDF). 
  57. Kellert, Stephen R.; Kellert, Stephen H. (1996). The Value of Life: Biological Diversity And Human Society. Island Press. ISBN 978-1-55963-317-8. 
  58. "HEPAC = Health economics in prevention and care, the European journal of health economics.". worldcat. 2000. Retrieved 14 May 2022. 
  59. Alberini, Anna; Krupnick, Alan; Cropper, Maureen L.; Simon, Nathalie B.; Cook, Joseph (2001). "The Willingness to Pay for Mortality Risk Reductions: A Comparison of the United States and Canada". SSRN Electronic Journal. doi:10.2139/ssrn.293662. 
  60. Mohd Fauzi, Mohd Y.; Nor Ghani, Mohd N.; Radin Umar, Radin S.; Ahmad Hariza, Hashim (1 March 2004). "The value of life and accident costing". Applied Health Economics and Health Policy. 3 (1): 5–8. doi:10.2165/00148365-200403010-00003. 
  61. Rushby, J. F. (1 September 2001). "Calculating and presenting disability adjusted life years (DALYs) in cost-effectiveness analysis". Health Policy and Planning. 16 (3): 326–331. doi:10.1093/heapol/16.3.326. 
  62. "Indicator Metadata Registry Details". www.who.int. Retrieved 22 June 2022. 
  63. "WHO | Health Status Statistics: Mortality". web.archive.org. 4 July 2012. Retrieved 22 June 2022. 
  64. Schabas 2002
  65. Johansson, Per-Olov (2002). "The value of a statistical life: theoretical and empirical evidence". Applied Health Economics and Health Policy. 1 (1): 33–41. ISSN 1175-5652. 
  66. Jelsma, Jennifer; De Weerdt, Willy; De Cock, Paul (10 May 2002). "Disability Adjusted Life Years (DALYs) and rehabilitation". Disability and Rehabilitation. 24 (7): 378–382. ISSN 0963-8288. doi:10.1080/09638280110096269. 
  67. 67.0 67.1 "How to value life? EPA devalues its estimate". NBC News. Retrieved 25 March 2022. 
  68. Viscusi, W. Kip; Aldy, Joseph E. (2003). "[No title found]". Journal of Risk and Uncertainty. 27 (1): 5–76. doi:10.1023/A:1025598106257. 
  69. Liu, Jin-Tan; Hammitt, James K.; Wang, Jung-Der; Tsou, Meng-Wen (October 2003). "Valuation of the Risk of SARS in Taiwan". National Bureau of Economic Research, Inc. 
  70. Murphy, Kevin M.; Topel, Robert H. (15 April 2010). Measuring the Gains from Medical Research: An Economic Approach. University of Chicago Press. ISBN 978-0-226-55179-1. 
  71. "Returns to Life Sciences Funding - Open Philanthropy". Open Philanthropy -. 15 January 2014. Retrieved 27 June 2022. 
  72. Alberini, Anna; Cropper, Maureen; Krupnick, Alan; Simon, Nathalie B. (July 2004). "Does the value of a statistical life vary with age and health status? Evidence from the US and Canada". Journal of Environmental Economics and Management. 48 (1): 769–792. doi:10.1016/j.jeem.2003.10.005. 
  73. VISCUSI, W. KIP (2003). "Racial Differences in Labor Market Values of a Statistical Life". Journal of Risk and Uncertainty. 27 (3): 239–256. ISSN 0895-5646. 
  74. Viscusi, W. Kip; Aldy, Joseph E. (2003). "[No title found]". Journal of Risk and Uncertainty. 27 (1): 5–76. doi:10.1023/A:1025598106257. 
  75. Eeckhoudt, Louis R; Hammitt, James K (January 2004). "Does risk aversion increase the value of mortality risk?". Journal of Environmental Economics and Management. 47 (1): 13–29. doi:10.1016/S0095-0696(03)00076-7. 
  76. "Healthy life years by sex (from 2004 onwards) (hlth_hlye)". ec.europa.eu. Retrieved 24 June 2022. 
  77. "Glossary:Healthy life years (HLY)". ec.europa.eu. Retrieved 27 June 2022. 
  78. Davis, Lucas W. (2004). "The Effect of Health Risk on Housing Values: Evidence from a Cancer Cluster". The American Economic Review. 94 (5): 1693–1704. ISSN 0002-8282. 
  79. Derrida and Roudinesco 2004
  80. Madheswaran, by S. "Measuring the value of life and limb: Estimating compensating wage differentials among workers in Chennai and Mumbai". The South Asian Network for Development and Environmental Economics. 
  81. "Estimates of the Willingness-to-Pay to Avoid Military Service and Free pdf download - 639558 - DocDatabase.net". www.docdatabase.net. 
  82. Mahmud, Minhaj (2005). "Measuring Trust and the Value of Statistical Lives: Evidence from Bangladesh". 
  83. Kniesner, Thomas J.; Viscusi, W. Kip (2005). "Value of a Statistical Life: Relative Position vs. Relative Age". The American Economic Review. 95 (2): 142–146. ISSN 0002-8282. 
  84. 84.0 84.1 "Quality-Adjusted Life Years and the Devaluation of Life with Disability: Part of the Bioethics and Disability Series" (PDF). ncd.gov. Retrieved 12 May 2022. 
  85. Kniesner, Thomas; Ziliak, James; Viscusi, W. Kip (February 2004). "Life-Cycle Consumption and the Age-Adjusted Value of Life": w10266. doi:10.3386/w10266. 
  86. "Cancer Trends Progress Report - Person-Years of Life Lost". web.archive.org. 1 July 2011. Retrieved 16 June 2022. 
  87. "History". Institute for Health Metrics and Evaluation. 9 May 2014. Retrieved 16 June 2022. 
  88. "Institute for Health Metrics and Evaluation". Institute for Health Metrics and Evaluation. Retrieved 16 June 2022. 
  89. "Institute for Health Metrics and Evaluation". linkedin. Retrieved 16 June 2022. 
  90. 90.0 90.1 90.2 90.3 Cohen, I. Glenn; Daniels, Norman; Eyal, Nir (9 March 2015). Identified versus Statistical Lives: An Interdisciplinary Perspective. Oxford University Press. ISBN 978-0-19-021749-5. 
  91. Robinson, Lisa A. "How U.S. Government Agencies Value Mortality Risk Reductions". 
  92. Claxton K, Martin S, Soares M, Rice N, Spackman E, Hinde S, Devlin N, Smith PC, Sculpher M (2015). "Methods for the estimation of the NICE cost effectiveness threshold.". Health Technology Assessment. 19 (14): 1–503, v–vi. PMC 4781395Freely accessible. PMID 25692211. doi:10.3310/hta19140Freely accessible. 
  93. "Three NICE thresholds for cost-effectiveness: does that make sense? -". pharmaphorum.com. 25 November 2016. Retrieved 9 May 2022. 
  94. Epatko, L . Chile’s mine rescue: costs and benefits. PBS Newshour/The Rundown: a blog of news and insight. October 14, 2010.
  95. Benkhalifa, Abdelaziz (2 February 2010). "The value of mortality risk reductions in the Tunisian building and manufacturing industries". University Library of Munich, Germany. 
  96. "Echoutcome". web.archive.org. 8 October 2016. Retrieved 4 May 2022. 
  97. Kirkdale, R.; Krell, J.; O'Hanlon Brown, C.; Tuthill, M.; Waxman, J. (1 September 2010). "The cost of a QALY". QJM. 103 (9): 715–720. doi:10.1093/qjmed/hcq081. 
  98. "Institute for Health Metrics and Evaluation to launch new Global Health Data Exchange (GHDx) at upcoming global health conference (Media Advisory)". healthdata. 9 May 2014. Retrieved 14 May 2022. 
  99. "Global Health Data Exchange | GHDx". ghdx.healthdata.org. Retrieved 10 June 2022. 
  100. "Against Malaria Foundation (AMF) - 2012 Review | GiveWell". www.givewell.org. Retrieved 27 July 2022. 
  101. "Against Malaria Foundation (AMF) - 2013 Review | GiveWell". www.givewell.org. Retrieved 27 July 2022. 
  102. "Against Malaria Foundation (AMF) - 2014 Review | GiveWell". www.givewell.org. Retrieved 27 July 2022. 
  103. "Against Malaria Foundation (AMF) – 2015 Review, Updated January 2016 | GiveWell". www.givewell.org. Retrieved 27 July 2022. 
  104. "Against Malaria Foundation (AMF) – June 2016 version | GiveWell". www.givewell.org. Retrieved 27 July 2022. 
  105. "Mortality Risk Valuation in Environment, Health and Transport Policies - OECD". www.oecd.org. Retrieved 17 March 2022. 
  106. Kniesner, TJ, Viscusi, WK, Woock, C. The value of a statistical life: evidence from panel data. Rev Econ Stat. 2012;94:74–87.
  107. Ara, Shihomi; Tekeşin, Cem (4 July 2014). "Measuring the Value of Mortality Risk Reductions in Turkey". International Journal of Environmental Research and Public Health. 11 (7): 6890–6922. PMC 4113852Freely accessible. PMID 25000150. doi:10.3390/ijerph110706890Freely accessible. 
  108. Tekeşin, Cem; Ara, Shihomi (29 September 2017). "The Monetary Valuation of Lifetime Health Improvement and Life Expectancy Gains in Turkey". International Journal of Environmental Research and Public Health. 14 (10): 1151. PMC 5664652Freely accessible. PMID 28961227. doi:10.3390/ijerph14101151Freely accessible. 
  109. Robinson, LA, Hammitt, JK. Skills of the trade: valuing health risk reductions in benefit-cost analysis. J Benefit-Cost Anal. 2013;4:107–30.
  110. He, Jie; Wang, Hua (29 September 2010). "The value of statistical life : a contingent investigation in China". The World Bank. doi:10.1596/1813-9450-5421. 
  111. Kniesner, Thomas J.; Viscusi, W. Kip; Ziliak, James P. (2012). "Willingness to Accept Equals Willingness to Pay for Labor Market Estimates of the Value of Statistical Life". SSRN Electronic Journal. doi:10.2139/ssrn.2221038. 
  112. Pols, Jeannette; Willems, Dick; Aanestad, Margunn (October 2019). "Making sense with numbers. Unravelling ethico‐psychological subjects in practices of self‐quantification". Sociology of Health & Illness. 41 (Suppl 1): 98–115. ISSN 0141-9889. doi:10.1111/1467-9566.12894. 
  113. Yates-Doerr, Emily (31 December 2019). "The Weight of Obesity: Hunger and Global Health in Postwar Guatemala". doi:10.1525/9780520961906. 
  114. "Стоимость человеческой жизни в России в 2015 году составила 4,5 млн. рублей" (PDF). Center for Strategic Researches RGS. 
  115. Lelieveld, Jos; Pozzer, Andrea; Pöschl, Ulrich; Fnais, Mohammed; Haines, Andy; Münzel, Thomas (1 September 2020). "Loss of life expectancy from air pollution compared to other risk factors: a worldwide perspective". Cardiovascular Research. 116 (11): 1910–1917. doi:10.1093/cvr/cvaa025. 
  116. Brazier, John; Tsuchiya, Aki (December 2015). "Improving Cross-Sector Comparisons: Going Beyond the Health-Related QALY". Applied Health Economics and Health Policy. 13 (6): 557–565. doi:10.1007/s40258-015-0194-1. 
  117. Project, Nonhuman Rights (27 May 2021). "Why We Fight for Nonhuman Rights: Harambe's Story". Nonhuman Rights Project. Retrieved 7 June 2022. 
  118. Bastian, Brock; Crimston, Charlie; Hornsey, Matthew; Bain, Paul. "How do we weigh the moral value of human lives against animal ones?". The Conversation. Retrieved 17 June 2022. 
  119. "Three NICE thresholds for cost-effectiveness: does that make sense? -". pharmaphorum.com. 25 November 2016. Retrieved 1 June 2022. 
  120. Kondrashov, Dmitry A. (4 August 2016). Quantifying Life: A Symbiosis of Computation, Mathematics, and Biology. University of Chicago Press. ISBN 978-0-226-37193-1. 
  121. "2016 Revised Value of a Statistical Life Guidance" (PDF). Retrieved 25 June 2022. 
  122. 122.0 122.1 "GiveWell's Top Charities Are (Increasingly) Hard to Beat - Open Philanthropy". Open Philanthropy -. 1 July 2019. Retrieved 25 June 2022. 
  123. Yang, Zhao; Liu, Pan; Xu, Xin (October 2016). "Estimation of social value of statistical life using willingness-to-pay method in Nanjing, China". Accident Analysis & Prevention. 95: 308–316. doi:10.1016/j.aap.2016.04.026. 
  124. Sawtell-Rickson, Jye (29 September 2018). "Quantifying The Thai Cave Rescue". Medium. Retrieved 25 June 2022. 
  125. "Demystifying ICER's Equal Value of Life Years Gained Metric". ISPOR | International Society For Pharmacoeconomics and Outcomes Research. Retrieved 13 June 2022. 
  126. Bernstein, Mark H. (1 April 2019). "Evaluating the Value of Animals and Humans". Journal of Animal Ethics. 9 (1): 66–75. doi:10.5406/janimalethics.9.1.0066. 
  127. Keller, Elena; Newman, Jade E.; Ortmann, Andreas; Jorm, Louisa R.; Chambers, Georgina M. (1 October 2021). "How Much Is a Human Life Worth? A Systematic Review". Value in Health. 24 (10): 1531–1541. ISSN 1098-3015. doi:10.1016/j.jval.2021.04.003. 
  128. Olofsson, S.; Gerdtham, U.-G.; Hultkrantz, L.; Persson, U. (September 2019). "Value of a QALY and VSI estimated with the chained approach". The European Journal of Health Economics. 20 (7): 1063–1077. doi:10.1007/s10198-019-01077-8. 
  129. "FEMA Benefit‐Cost Analysis (BCA) Toolkit 6.0 Release Notes" (PDF). 2020-07-31. Retrieved 2022-03-23. 
  130. Wilks, Matti; Caviola, Lucius; Kahane, Guy; Bloom, Paul (January 2021). "Children Prioritize Humans Over Animals Less Than Adults Do". Psychological Science. 32 (1): 27–38. ISSN 1467-9280. doi:10.1177/0956797620960398. 
  131. "New research finds that kids value animal life a lot more than adults do". psychnewsdaily. 6 January 2021. Retrieved 28 June 2022. 
  132. "Best Practice Regulation Guidance Note Value of statistical life" (PDF). obpr.pmc.gov.au. Retrieved 16 June 2022.