FINANCIAL IMPACT OF MENTAL ILLNESS AND HOW TO MEASURE THE CONSEQUENCES

This article shows the economic impact of mental illness, as well as various cost-estimating approaches. To assess the burden of mental diseases, there are three different ways: the human capital, the economic growth and the value of statistical life approach. The first focuses on indirect and direct costs. Moreover, the effect of mental illness on economic development can only be approximated implicitly. Thus, the lack of production is primary estimated for somatic conditions compared to their corresponding quantity of disability-adjusted life years (DALYs). The total economic productivity drop associated with mental illnesses between 2011 and 2030 is rated to be US$16.3 trillion globally. Furthermore, the value of statistical life (VSL) method suggests that trade-offs between risks and capital should be used to assess the probability of injury or death due to psychiatric illness. This computation is equivalent to that of cardiovascular disease and bigger than that of cancer. However, greater activism is required to better the existing condition.

Estimation of the cost-effective threshold of a quality-adjusted life year in China based on the value of statistical life

Cost-effective threshold (CET) is essential for health technology assessment and decision-making based on health economic evaluations. Recently, it has been argued that the commonly used once and three times of gross domestic product (GDP) per capita CETs of a quality-adjusted life year (QALY) are not necessarily empirically supported in all countries. Therefore, we aimed to estimate the CET of a QALY as times of GDP per capita in China, of which the reimbursement coverage decisions are increasingly engaging economic evaluations. Estimates on the value of statistical life (VSL) in China were identified from several studies in the literature and converted to times of GDP per capita, the weighted average of which was used for subsequent calculation. By pooling data on population mortality, health utility, and age distribution, we estimated the value of a statistical QALY (VSQ) from VSL using an established mathematical process, which represented the theoretical upper bound of CET. The corresponding point estimate and theoretical lower bound were obtained using their numerical relationships with the upper bound. Scenarios analyses were also conducted. The estimated CET, its upper bound, and its lower bound were 1.45, 2.90, and 1.16 times of GDP per capita in China, respectively. In different scenarios, the estimated CET varied but was greater than once GDP per capita in most cases. As such, the CET of a QALY in China is close to 1.5 times of GDP per capita, which should be benchmarked for future ICER-based coverage decisions.

The value of statistical life in the context of road safety: new evidence on the contingent valuation/standard gamble chained approach

This study estimates the value of statistical life (VSL) on a road traffic accident using the Contingent Valuation/Standard Gamble chained approach. A large representative sample (n = 2020) is used to calculate a VSL for use in the evaluation of road safety programmes in Spain. The paper also makes some methodological contributions, by providing new evidence about the consistency of the chained method. Our main results are: (1) A range from 1.3 million euro to 1.7 million euro is obtained for the VSL in Spain in the context of road accidents. This range is in line with the values used in the same context in other European countries, although it is lower than those obtained in different contexts and with other methods. (2) The method performs much better in terms of scope sensitivity than the traditional contingent valuation method, which asks subjects about their willingness to pay for very small reductions in the risk of death. (3) We introduce a new ‘indirect’ chaining approach which reduces (but does not remove) the disparity between direct and indirect chaining approaches. More extreme VSL estimates are still obtained with this indirect method than with the direct one. (4) VSL estimates depend on the injury used. More specifically, we obtained a lower VSL when a more severe injury is used. (5) Framing the risk of death in the modified standard gamble question as “10n in 10,000” instead of “n in 1000” influences the value of VSL. We attribute this effect to the Ratio Bias.

Groundwater Arsenic-Attributable Cardiovascular Disease (CVD) Mortality Risks in India

Cardiovascular diseases (CVDs) have been recognized as the most serious non-carcinogenic detrimental health outcome arising from chronic exposure to arsenic. Drinking arsenic contaminated groundwaters is a critical and common exposure pathway for arsenic, notably in India and other countries in the circum-Himalayan region. Notwithstanding this, there has hitherto been a dearth of data on the likely impacts of this exposure on CVD in India. In this study, CVD mortality risks arising from drinking groundwater with high arsenic (>10 μg/L) in India and its constituent states, territories, and districts were quantified using the population-attributable fraction (PAF) approach. Using a novel pseudo-contouring approach, we estimate that between 58 and 64 million people are exposed to arsenic exceeding 10 μg/L in groundwater-derived drinking water in India. On an all-India basis, we estimate that 0.3–0.6% of CVD mortality is attributable to exposure to high arsenic groundwaters, corresponding to annual avoidable premature CVD-related deaths attributable to chronic exposure to groundwater arsenic in India of between around 6500 and 13,000. Based on the reported reduction in life of 12 to 28 years per death due to heart disease, we calculate value of statistical life (VSL) based annual costs to India of arsenic-attributable CVD mortality of between USD 750 million and USD 3400 million.

Study on Motorcycle Crash Cost in Bandung City

Crash cost is an important component for conducting economic analysis in selecting countermeasures for crash locations. It is used to convert the benefit of crash or fatality reduction into monetary terms. Many research on crash cost have been carried out in Indonesia. Most of the research utilized gross output/human capital approach. However, this approach has been widely criticized for not being able to describe the quality of life of crash casualties and the costs of pain, grief and suffering (i.e. human cost). The concept of Value of Statistical Life (VoSL) has been introduced by InDeV (2016) to calculate the human cost, which is assessed by using willingness to pay approach. To obtain a more reliable estimation of crash cost for Indonesia, it is necessary to conduct a study on crash cost involving motorcycles which incorporates the estimation of human cost. The VoSL is obtained by interviewing motorcycle users for willingness to pay with safety equipment. Based on the analysis, it is obtained that the value of statistical life (VoSL) for fatality in a road crash was estimated to be Rp.2.3 billion. The unit cost of fatal injury is Rp.3.08 billion, serious injury is Rp.333 million and slight injury is Rp.24.9 million. The unit cost of fatal crash on arterial roads is Rp.3.23 billion, serious crash is Rp.451 million and the slight crash is Rp.114 million. The unit cost of fatal crash on collector roads is Rp.3.16 billion, serious crashes is Rp.381 million and minor crash is Rp.69.4 million. The unit cost of fatal crash on local roads is Rp.3.09 billion, serious crash is Rp.338 million, and minor crash is Rp.29.8 million. Keywords: Motorcycle crash cost, gross output approach, human capital approach, willingness to pay approach

Health and economic costs of early and delayed suppression and the unmitigated spread of COVID-19: The case of Australia

We compare the health and economic costs of early and delayed mandated suppression and the unmitigated spread of ‘first-wave’ COVID-19 infections in Australia in 2020. Using a fit-for-purpose SIQRM-compartment model for susceptible, infected, quarantined, recovered and mortalities on active cases, that we fitted from recorded data, a value of a statistical life year (VSLY) and an age-adjusted value of statistical life (A-VSL), we find that the economic costs of unmitigated suppression are multiples more than for early mandated suppression. We also find that using an equivalent VSLY welfare loss from fatalities to estimated GDP losses, drawn from survey data and our own estimates of the impact of suppression measures on the economy, means that for early suppression not to be the preferred strategy requires that Australia would have to incur more than 12,500–30,000 deaths, depending on the fatality rate with unmitigated spread, to the economy costs of early mandated suppression. We also find that early rather than delayed mandated suppression imposes much lower economy and health costs and conclude that in high-income countries, like Australia, a ‘go early, go hard’ strategy to suppress COVID-19 results in the lowest estimated public health and economy costs.

Estimating the Value of Statistical Life in China: A Contingent Valuation Study in Six Representative Cities

Incorporating the health impacts into all kinds of policy decisions has become the shared expectations of policymakers and the public, hoping to obtain the most significant health benefits with the least policy costs. The value of statistical life (VSL), which represents the additional cost that individuals are willing to reduce the risk of death, is a core tool for monetizing health impacts. Though VSL has been widely studied internationally, the existing VSL research in China has limitations on regional representativeness, questionnaire design, and discussion of influencing factors. To fill these research gaps, we selected six representative cities in six typical provinces based on cluster analysis and conducted a face-to-face contingent valuation interview (n=3936) from March 7, 2019, to September 30, 2019, using the hypothetical vaccine as the payment tool followed by double-bounded dichotomous choice questions. The respondents' willingness to pay (WTP) to reduce the death risk from air pollution was elicited and used to quantify the VSL of typical urban residents. Also, we discussed the determinants of WTP and VSL in comparison with previous studies. Results showed that the WTP varied from 455-763 yuan, corresponding to a VSL range of 3.79-6.36 million yuan (price in 2019) in different cities. Therefore, the VSL in China in 2019 was estimated to be 5.10 million yuan, which was 1.2-41 times of the previous studies (in 2019 price). It was also proven that influencing factors such as monthly expenditure levels, environmental concerns, risk attitudes, and assumed market acceptance, which had been seldom discussed in previous studies, had significant impacts on the WTP and the VSL. There were substantial differences in the influencing factors of residents' WTP in different cities, which provided a reasonable explanation for the large gap of the VSL among six representative cities.