THE HEALTH COST OF URBAN AIR POLLUTION IN COSTA RICA

1. Summary

The health cost of urban air pollution in Costa Rica amounts to about 210 Bl. Colones, or around

1.1% of the national GDP in 2010. Mortality represents roughly 0.8% of the GDP and 69% of the

total social cost of this environmental risk (see Figure 1.1 below). Around 655 premature deaths

and close to 9,000 lost DALYs were attributable to urban air pollution (PM exposure).The health

damage of urban air pollution in the country is largely concentrated in the core of the Greater

Metropolitan Area (GMA) around San Jose, the capital.

Figure 1.1. Health cost of urban air pollution in Costa Rica as a percentage of GDP in 2010

Source: estimates by the authors

The GMA presents a high concentration of economic and commercial activity in a small area. Such

concentration, along with a fast rate of motorization, ageing vehicle fleet and abundant point

sources, entails difficult challenges for an effective air quality management of the area. However,

authorities have scaled up efforts towards an effective reduction of air pollutants, in particular

those related to mobile sources. In this regard, the “Program to improve air quality in the greater

metropolitan area of Costa Rica” (2008-2013) notes the efforts of the Costa Rican government in

the reduction of congestion and improvement of mass transit systems, along with other

governmental initiatives. The guiding principles of these initiatives have been mainly the

generation of reliable information on air pollution and the gradual reduction of pollutants to levels

compliant with national standards. As for the current lines of governmental action, these

encompass six main areas of work: 1) Emissions reductions from point sources 2) Public

participation 3) Clean transportation 4) Energy efficiency 5) Renewable energies and 6) Decision

support systems. Consistently, strong efforts are being made regarding monitoring and research.

The number or monitoring stations measuring PM10 in the GAM has increased from 2 in 2005 to 5

in 2008 and up to 14 in 2010. Authorities recognize, however, that much remains to be done, in

particular regarding the monitoring of mobile sources on the road.

These and previous efforts are paying off; from a reported annual average of 62 µg/m3 in 1997

(Alfaro 1998) concentrations of PM10 have gone down to values generally below the national

standards (50 µg/m3) in the last five years. The National University (UNA) is currently conducting a

comprehensive study on the environmental, social and economic effects of air pollution involving

data including comprehensive emission sources inventories, dispersion modeling, epidemiologic

surveillance, and complete economic valuations. This evidence base will likely prove highly

valuable as a baseline reference for expected gains of an effective air quality management in the

urban areas of Costa Rica.

Similar analyses were conducted in several countries of Latin America and the Caribbean starting

in 2006 up until today, which could give some context for comparison of the findings of this report

(Figure 1.2).

Figure 1.2 Annual cost of urban air pollution as a proportion of GDP in selected LAC countries

Source: World Bank Environmental Assessment Studies, this report for Costa Rica.

The methodology in this report was shifted towards application of value of statistical life (VSL) only

for outdoor air pollution mortality valuation (as opposed to the average between human capital

approach and VSL in other studies). In the practice that means a higher value compared to the

combined HCA-VSL approach. On the other hand, no willingness-to-pay proxy was applied to the

calculation of the cost of illness of some health outcomes, which contributes to a comparatively

lower cost estimate for morbidity. A relatively high cost of hospitalization and of the value of time

lost may also contribute to explain the comparatively high health cost of urban air pollution.

2. The health impact of urban air pollution

Outdoor air pollution is a major environmental risk to public health, particularly in urban settings.

The evidence on the health effects of poor urban air quality worldwide has been substantial for

decades now, with extensive studies showing associations between certain pollutants and

respiratory and cardiovascular mortality, chronic bronchitis, respiratory infections and several

other related disorders. Of all common urban air pollutants, most studies show the strongest

association for inhalable particulate matter, specifically PM10 and PM2.5 (smaller than 10 and 2.5

microns in diameter, respectively). To the reviews by Ostro (1994) and Pope (2002, 2007) have

followed several comprehensive analyses (including cohort, case-crossover and meta-analysis

studies) involving multiple locations, mostly in Europe and North America (Samet et al. 2000).

Several large cohort studies have confirmed significant effects of inhalable particles on public

health, in different age groups (Eftim et al. 2008, Samet et al. 2007a, 2007b). A recent

comprehensive review (Brook et al. 2010) that pooled together many large scale studies on the

association between cardiovascular disease and PM confirmed that short-term exposure to PM2.5

can trigger health effects from mild to increased risk of cardiovascular disease-related premature

death, and that long term exposure increases the risk of cardiovascular mortality and reduces life

expectancy. Though not the only outcomes related to air pollution, cardiovascular and respiratory

health effects are the most important in magnitude and strength of the association. Besides the

well-established evidence in Europe and North America, a substantial body of evidence is now

available from cities in developing countries of Asia (E.g. HEI 2008) and, most importantly for this

update, from cities in Latin American countries (Gouveia et al. 2004, Martins et al. 2004, Bell et al.

2006, O´Neill et al. 2008, Bell et al. 2011, among others).

Inhalable particulate matter has the strongest effect of all common urban air pollutants and it is

used in this report as the environmental exposure representing urban air pollution in Costa Rica.

However, many other anthropogenic pollutants have proven to be associated with adverse health

outcomes, including (but not limited to) Sulphur oxides, Nitrogen oxides, Volatile organic

compounds, Lead, Carbon monoxide, and –notably- Ozone (USEPA 2011a). Tropospheric (I.e.

ground level) Ozone can trigger a large number of respiratory effects and aggravate certain

chronic diseases, thus increasing societally costly outcomes like increased healthcare usage or

absenteeism from work and school (USEPA 2011b). Moreover, an association between Ozone

concentrations and long term mortality has been found, albeit it was statistically significant only

when PM2.5 concentrations were taken into account (Jerrett et al. 2009). A detailed discussion on

the epidemiology of air pollution is beyond the scope of this report, and a large body of evidence

is widely available both in academic journals and in governmental sources worldwide. In general,

evidence shows that the strongest association and magnitude of effect in the interaction between

air pollutants and premature mortality/health is related to fine particulate matter, and in

particular the smallest diameter fraction. The analytical approach to the estimation of the damage

value of air pollution follows the same main steps used in most World Bank Country

Environmental Analyses including air pollution: 1) Identification of air pollutants and

determination of concentrations 2) Population exposed and their baseline vulnerability 3)

Calculation of the health impact of the exposure to air pollution based on epidemiologic

techniques and 4) Estimation of the value of that health impact.

3. Baseline population and dose-response coefficients

In Costa Rica, most of the population exposed to significant levels of urban air pollution lives in the

Greater Metropolitan Area (GMA), which represents only 4% of the national territory, but

concentrates more than 60% of the population along with roughly 75% of the vehicle fleet and a

large proportion of the industry (INEC 2011). As per consultations with the Costa Rican Ministry of

the Environment, the network of air pollution monitoring stations covers the majority of districts

within the GMA where air pollution is of significant concern, comprising 31 municipalities (see

Map 3.1.). The total population within this area amounts to roughly 2.3 Million people, a sizeable

proportion of the total national population of 4.3 Million. Some of these municipalities (notably

Heredia, Alajuela and Cartago) are on a net population growth path, largely based on internal

migration (INEC 2011). Overall, more than 65% of Costa Rica’s population lives in urban areas.

Map 3.1. Municipalities within the GMA covered in the analysis

Source: adapted from INEC data with ArcGIS™ 10.1

The inhalable particles exposure assessment is based on annual average data from fourteen

monitoring stations placed in nine municipalities within the GMA (4 in San Jose, 2 in Belen and 1

each in Heredia, Moravia, Santa Ana, Escazu, Heredia, Santo Domingo, Alajuela and Cartago). We

pondered measurements by exposure category based on simple interpolation (Kriging and Inverse

Distance Weighting). Results are summarized in Table 3.1. A complete dispersion modeling would

be appropriate in this case, but time and data availability constraints determined our analytical

choice. The ratio PM2.5/PM10 of 0.67 is based on the average measurements in the monitoring

stations that measure PM2.5.

Table 3.1. Population and weighted average concentration of PM10 and PM2.5 in 2010 in the

Greater Metropolitan Area of Costa Rica

PM2.5 Annual Avg. Concentration intervals, µg/m3

Population exposeda

Annual Avg. PM2.5 concentration, µg/m3

Population exposedc

Up to 15 664,878 21 2,329,410

16 - 20 927,824

21 - 25 296,573

26 - 30 378,695

30 - 35 61,440

Total 2,329,410

PM10 Annual Avg. Concentration intervals, µg/m3

Population exposedb

Annual Avg. PM10 concentration, µg/m3

Population exposedc

Up to 20 135,574 31 2,329,410

21 - 25 904,301

26 - 30 495,479

30 - 35 218,724

36 - 40 273,675

41 - 45 225,883

46 - 50 56,834

51 - 55 18,940

Total 2,329,410 aKriging interpolation using ArcGIS™ bIDW interpolation using ArcGIS™ cTotal population of GMA

There has been a substantial increase in available evidence on the links between air pollution and

mortality in Latin America in the last decade, although most studies have dealt with short term

effects. A recent study (O´Neill et al. 2009) analyzed the effect of education in the association

between PM10 concentrations and short term mortality in Mexico city, Sao Paulo and Santiago de

Chile, and found 1-day lagged increases of 0.39%, 1.04% and 0.61% respectively of total non-

accidental adult mortality for an increase of 10- µg/m3 in concentration. In Brazil, studies have

found associations between exposure to PM10 and low birth weight (Gouveia et al. 2004) and also

with elderly respiratory mortality (Martins et al. 2004)

While the accurate determination of air pollutants’ concentrations and distribution has improved

greatly in Costa Rica in the last years (Herrera and Rodriguez 2009, 2010), the evidence base for

health risks of air pollution is still under development. While ongoing local studies are needed to

obtain a greater understanding of the health effects of urban air pollution in Costa Rica, a large

body of evidence is required to provide reliable estimates of health effects applicable at the

national level. In the absence of local data, for the association between exposure to inhalable

particulate matter and mortality, the coefficients of Pope et al. (2002) continue to be among the

most solid results for long term effects. Pope et al (2002) utilized ambient air quality data from

metropolitan areas across the United States for the two periods 1979-83 and 1999-2000, and

information on certified causes of mortality of adults in the American Cancer Society (ACS)

database over a period of 16 years. The details of the study (which confirms previous

observations, E.g. Dockery et al. 1993, Pope et al. 1995) have been discussed extensively

elsewhere, and the results still stand as the best available evidence for the association between

exposure to inhalable particulate matter and mortality. Although the locally relevant evidence of

health effects from air pollution has increased greatly in the last decade, new results are not

significantly changing the estimates of relative risk associated to PM exposure. In the context of

Latin America and the Caribbean there are not enough local studies to constitute a body of

evidence solid enough to displace (at least for long-term risk) the risk ratios and dose response

coefficients from Pope et al. (2002, 2007) (mortality effects of PM2.5) and from Ostro (1994, 2004)

and Abbey et al. (1995) (morbidity effects of PM10 and Chronic Bronchitis attributable to PM10,

respectively). These are summarized in table 3.2.

Table 3.2. Urban Air Pollution Dose-response coefficients

Annual Health Effect Dose-response

coefficient

Per 1 µg/m3 annual average

ambient concentration of:

Mortality (% change in cardiopulmonary

and lung cancer mortality)

0.8% PM 2.5

Chronic bronchitis (% change in annual

incidence)

0.9% PM 10

Respiratory hospital admissions (per

100,000 population)

1.2 PM 10

Emergency room visits (per 100,000

population)

24 PM 10

Restricted activity days (per 100,000

adults)

5,750 PM 10

Lower respiratory illness in children (per

100,000 children)

169 PM 10

Respiratory symptoms (per 100,000

adults)

18,300 PM 10

Source: Pope et al (2002) for the mortality coefficient. Ostro (1994, 2004) and Abbey et al (1995)

for the morbidity coefficients.

4. The health impact of inhalable particles in Costa Rica

In order to ascertain the share of mortality that is attributable to air pollution, baseline data on

certain causes of mortality are required. These are routinely collected and reported by Costa Rica’s

National Institute of Statistics on a yearly basis. The baseline mortality considered is the total non-

accidental and the types for determination of attributable mortality are cardiopulmonary causes

and lung cancer. It is also necessary to establish a lower threshold level for PM 2.5, below which it

is assumed there are no mortality effects. WHO (2002) recommended this threshold to be 7.5

µg/m3 in the World Health Report for mortality. However, a recent review by Krewski et al. (2009)

lowers the threshold to 5 µg/m3. Although there is much debate about the usefulness of these

lower limits (WHO recognizes there is no safe threshold for inhalable particles), they are widely

regarded as necessary for practical matters regarding air quality management. We applied the 5

µg/m3 threshold, more consistent with epidemiologic evidence.

Regarding nonfatal outcomes with known associations to air pollution, perhaps the most

burdensome for patients and health systems is Chronic Bronchitis (CB).Largely (but not

completely) attributable to tobacco use, not only does this disease entail intense suffering for the

patient (Nicolson & Anderson 2000), but it also constitutes a large-bill item for healthcare systems

(Blanchette et al. 2011). However, estimates of incidence are as yet not widespread, and are

exceedingly rare in non-OECD countries. There are no general estimates on either prevalence or

incidence of the disease in Costa Rica. The country´s efficient health information systems capture

all hospital discharges from the disease; however, estimating incidence from those would be

inaccurate on two accounts: firstly, not all (or even the majority) of CB patients would necessarily

require or seek hospitalization; and secondly, the discharge records did not reflect whether the

patient was firstly diagnosed or it was a recurrent event. Therefore, the rates applied are those

from WHO (2001) and Shibuya (2001) for the AMRO-B sub-region within the WHO region of the

Americas. A PM10 concentration threshold of 10 µg/m3 is used for the determination of

attributable CB (Abbey et al. 1995).

Aside from Chronic Bronchitis, the other health endpoints considered in this update are listed in

Table 4.1. below. These specific health effects have become standard health endpoints considered

in several worldwide studies on air pollution. In order to facilitate magnitude comparisons with

other risk factors, health effects can be converted to disability adjusted life years (DALYs)1. To do

so, disability weights and average duration of each outcome are assigned to each health effect.

Larsen (2004) used weights from the USNIH for lower respiratory illness (LRI) and chronic

bronchitis (CB) in the LAC region, and came up with his own estimates for other weights and

duration of illnesses. Years lost to premature mortality from air pollution were estimated from

age-specific mortality data for cardiopulmonary and lung cancer deaths, discounted at 3 percent

1 DALYs are the sum of the present value of future years of lifetime lost to premature mortality (referred to

life expectancy) and the present value of future years of lifetime adjusted by the severity of a disability caused

by disease or injury. For further details on DALY calculation, details can be found at (Fox-Rushby & Hanson

2001) and at the WHO website on the matter

http://www.who.int/healthinfo/global_burden_disease/metrics_daly/en/

per year with full age weighting. This approach is not free from controversy, since there is

considerable uncertainty to duration estimates and weights include a substantial subjective

component. However, it is widely used for convenience in this type of calculations. No threshold is

applied for morbidity effects other than CB.

Table 4.1. Calculation of DALYs per case of health Effect

Disability weight Average duration of illness

Mortality 1.0 (7.5 years lost)

Lower respiratory illness - children 0.28 10 days

Respiratory iymptoms – adults 0.05 0.5 days

Restricted activity aays – adults 0.1 1 day

Emergency room visits 0.30 5 days

Hospital admissions 0.40 14 days*

Chronic Bronchitis 0.2 20 years

Source: Larsen (2004) * Includes days of hospitalization and recovery period after hospitalization.

Once health effects of air pollution are converted to disability adjusted life years (DALYs), we can

make quick comparisons with regard to health effects from other environmental risk factors. A

calculation of DALYs lost per 10 thousand cases of the considered health end-points is presented

in Table 4.2.

Table 4.2. DALYs lost per selected health effect attributable to air pollution

Health effect DALYs lost per 10,000 cases

Mortality 75,000

Chronic Bronchitis (adults) 22,000

Respiratory hospital admissions 160

Emergency Room visits 45

Restricted activity days (adults) 3

Lower respiratory illness in children 65

Respiratory symptoms (adults) 0.75

Source: Larsen 2004

The estimated health impact of urban air pollution in Costa Rican cities is in table 4.3. The values

are calculated by applying relative risks and particle concentrations (minus thresholds, where

applicable) to population exposed, adjusting for age groups when necessary and extracting the

fraction of these health outcomes that is attributable to this specific exposure. DALYs are

calculated simply by multiplying the number of cases by the factors in table 4.2.

Table 4.3. Estimated Health Impact of Urban Air Pollution in cities with PM monitoring data

Health categories Total cases Total DALYs

Premature mortality 655 4,909

Chronic bronchitis 353 776

Hospital admissions 881 14

Emergency room /Outpatient hospital visits 17,275 78

Restricted activity days 4,219,757 1,266

Lower respiratory illness in children 124,024 806

Respiratory symptoms 13,429,835 1,007

TOTAL N/A 8,857

Source: estimates by the authors

Around 655 premature deaths and close to 9,000 lost DALYs were attributable to urban air

pollution (PM exposure) in the Greater Metropolitan Area of Costa Rica in 2010. The only available

previous results for comparison come from a similar study conducted in the mid 2000s by the

Ministry of Health (Allen et al. 2005). Reported premature mortality related to PM was of over

3,400 attributable deaths annually. However, some factors preclude a direct comparison. Firstly,

the calculation was made in relation with PM10, not PM2.5 (for which there was no measurement

at the time). Secondly, the considered exposure was far greater; with their data, over 68% of the

population in the GMA was exposed to PM10 concentrations of over 60 µg/m3. At the time, only

two monitoring stations measured PM10. In our dataset, the maximum exposure category is over

55 µg/m3, and less than 1% of the population in the GMA is in that category. Exposure was

possibly overestimated in the mentioned study, probably in relation with scarce data availability.

5. Estimated Cost of Health Impacts

The estimated annual cost of health impacts from urban air pollution is presented in Table 5.1. The

cost of mortality is based on the Value of a Statistical Life (VSL). We are not reporting a cost based

on the Human Capital Approach, since we feel that an indicator based on foregone income due to

premature mortality severely underestimates the true cost to society of that excess mortality

represents in a setting like Costa Rica. There are no primary studies on the Willingness To Pay

(WTP) to avoid mortality or morbidity risks related to air pollution in Costa Rica. A VSL was recently

obtained through a primary survey (Schram 2009) but the risks of focus in the study were of

difficult application for the case of air pollution. Instead, we extrapolated an estimate from a

recent study (Ortiz et al. 2009) that estimated the population’s WTP to reduce risks of death

associated with “typical” air pollution policies and, consequently, the value of a statistical life in

São Paulo, Brazil. Details on the extrapolation are available in Annex 1.

Table 5.1. Estimated Annual Cost of Health Impacts (Billion LCU)

Health categories Total annual cost

(Billion Colon)

Percent of total cost*

(Mean)

Mortality 130 - 162 69

Morbidity:

Chronic bronchitis 3 1

Hospital admissions 7 3

ER visits/Outpatient hospital visits 9 4

Restricted activity days (adults) 21 10

Lower respiratory illness in children 20 10

Respiratory symptoms (adults) 4 2

Total cost of Morbidity 64 31

TOTAL COST (Mortality and Morbidity) 194 - 226 100

* Annual cost is rounded to nearest billion, and percentages are rounded to nearest percent.

The total cost of air pollution in Costa Rica in 2010 was around 210 Billion Colones on average,

which represented roughly 1.1% of the GDP. Almost 70% of the cost was related to premature

mortality, and the rest distributed among several health outcomes. Such high mortality-related

proportion of costs is consistent with most international studies (Hunt 2011).

The cost of morbidity was estimated through the cost of illness (comprising the cost of treatment

and the opportunity cost of time lost to illness). The calculated cost of treatment was based on

consultations with health authorities and the upper bound of the publicly listed prices that the

public healthcare financing authority pays to healthcare providers, which in turn are deemed the

most adequate reflection of the true cost of treatment in Costa Rica. Some explanation on

healthcare financing and provision in Costa Rica is useful to understand the cost of treatment

values for health effects attributable to air pollution used in this report. Such costs are based on

public prices for medical and hospital services as reported by the Costa Rican Social Security

Administration (Caja Costarricense del Seguro Social - CCSS). More so than in other Latin American

countries, public prices for medical and healthcare services are in Costa Rica an accurate reflection

of the cost of treatment for the society. The CCSS pays for and administers a large proportion of

healthcare services provided in the country (Giedion et al. 2010). The small and decreasing

percentage of uninsured population usually has publicly paid healthcare alternatives. Moreover,

evidence suggests that the widespread usage of public healthcare services in Costa Rica is not

affected by income, so high income groups are not necessarily more likely to use private

healthcare (ECLAC 2001). Whereas public healthcare services prices may represent a distorted

indicator for the valuation of the true health cost of environmental risks in certain markets, they

are an accurate and readily available indicator in several Latin American countries, and specifically

in Costa Rica.

Beyond the actual cost of treating illness, there is sound evidence that individuals place a much

higher value on avoiding pain and discomfort associated to illness than that reflected solely in

medical costs; this has been observed also specifically in connection with air pollution risks

(Cropper and Oates 1992, Alberini and Krupnick 2000, Arigoni et al. 2009). Therefore, we apply a

WTP proxy based on various estimates (PDDB 2009, Cifuentes et al. 2005, Lozano 2004, Alberini

and Krupnick 2000) which used Benefit transfer to calculate the WTP value. Alberini and Krupnick

also note that such ratios are similar to those for the United States, despite the differences

between countries, which further reinforces the solidity of such a proxy for WTP value. For

morbidity outcomes involving the provision of medical services we used a WTP/COI ratio 2,26.

Chronic Bronchitis (CB) is an example of severe decrease of welfare beyond medical costs, which

could justify an even larger WTP proxy. While we agree on placing a comparatively large cost in a

burdensome illness like CB, we would rather apply consistent WTP values for air pollution-related

outcomes in the absence of specific information for CB. The estimated cost per case of premature

mortality or specific health endpoint is presented in table 5.2. The cost per case (comprising Cost

of illness plus the proxy for WTP) is the basis for the estimation of the annual costs in table 5.1. by

multiplying each unit case cost by the cases in table 4.3.

Table 5.2. Estimated Unit Cost by Health End-Point

Health categories Total cost Per case

(000 Colon)

Cost-of-illness

Per case (000

Colon)

WTP proxy

(000 Colon)

Mortality 199,000 – 248,000 N/A N/A

Chronic bronchitis 8,888 2,718 6,170

Hospital admissions 7,917 2,421 5,496

Emergency room /Outpatient hospital visits 523 160 363

Restricted activity days (adults) 5 5 N/A

Lower respiratory illness in children 164 50 114

Respiratory symptoms (adults) 0.3 0.3 N/A

Source: estimates by authors

Table 5.3. details the baseline data that were used for the estimation of the cost of illness and the

costs of time lost to illness. For consistency with other World Bank evaluations in the context of

Latin America, we kept the same assumptions regarding duration of illness, rate and length of

hospitalization, average time lost per health endpoint, frequency of doctor visits and discount rate

used by Larsen (2004). We valued time lost to illness at 75% of average urban wage, and applied

such cost both to working and non-working individuals, based on the assumption of an equivalent

opportunity cost for both categories.

There is still little evidence of healthcare usage and costs of patients regarding the cost of a new

case of Chronic Bronchitis. In the case of Costa Rica, we could not find local data either on

incidence or on the usage and cost of healthcare by patients. Therefore, we relied on the

information used by Schulman et al (2001) and Niederman et al (1999) from the United States and

Europe and applied them to Costa Rica. The estimate of lost work days per year is based on

frequency of estimated medical treatment plus 7 additional days for each hospitalization and one

extra day for each doctor and emergency visit. These days are added to reflect time needed for

recovery from illness. The estimated cost of a new case of CB assumes a 20-years duration of

illness over which medical costs and value of time experience an annual real increase of 2 percent,

and costs are discounted at a 3% rate per year, a value commonly applied by WHO for health

effects.

Table 5.3. Baseline Data for Cost Estimation

Baseline Source:

Cost Data for All Health End-Points:

Cost of hospitalization (Colones per day) 370,000 Per consultations with medical

service providers and health

authorities Cost of emergency visit (Colones) – urban 120,000

Cost of doctor visit (Colones) – urban 30,000

Value of time lost to illness (Colones per day) 20,000 Based on urban wages in

Costa Rica

Chronic Bronchitis (CB):

Average duration of Illness (years) 20 Based on Shibuya et al (2001)

Percent of CB patients being hospitalized per year 1.5 % From Schulman et al (2001)

and Niederman et al (1999) Average length of hospitalization (days) 10

Average number of doctor visits per CB patient per

year

1

Percent of CB patients with an emergency

doctor/hospital outpatient visit per year

15 %

Estimated lost work days (including household work

days) per year per CB patient

2.6 Estimated based on frequency

of doctor visits, emergency

visits, and hospitalization

Annual real increases in economic cost of health

services and value of time (real wages)

2 % Estimate

Annual discount rate 3 % Applied by WHO for health

effects

Hospital Admissions:

Average length of hospitalization (days) 6 Estimates

Average number of days lost to illness (after

hospitalization)

4

Emergency Room Visits:

Average number of days lost to illness 2

Restricted Activity Days:

Average number of days of illness (per 10 cases) 2.5

Lower Respiratory Illness in Children:

Number of doctor visits 1

Total time of care giving by adult (days) 1 Estimated at 1-2 hours per day

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Annex 1. Economic basis for choice of VSL (Source: text and calculations adapted from an

original contribution by Elena Golub)

Our choice of a Value of a Statistical Life (VSL) for Costa Rica is based on a recent study by Ortiz et

al. (2009). This study aims to estimate the population’s willingness to pay (WTP) to reduce risks of

death associated with “typical” air pollution policies and, consequently, the value of a statistical

life (VSL) in São Paulo, Brazil. Uniquely for that country, the study uses a methodology that has

previously been tested in several industrialized countries (USA, Japan, Canada, South Korea,

England, France and Italy) and involves a computer-based contingent valuation survey. This survey

instrument was adapted to the Brazilian context and used to elicit willingness-to-pay measures of

reductions in risk of death in Brazil.

Key features of the survey instrument involve eliciting the health status of the respondents and

their family; explaining basic concepts of probability, and proposing simple practice questions to

familiarize the respondents with the probabilities concepts introduced; presenting the leading

causes of death for a Brazilian individual of the respondent’s age and gender, and setting these in

the context of common risk-mitigating behaviors; and finally, asking individual’s willingness to pay

for risk reductions of a given magnitude that occur at a specified time.

The mean and median willingness-to pay values were estimated using the interval data model that

can be generated from the dichotomous choice with follow-up question format. The responses to

willingness-to-pay and follow-up questions were combined to generate intervals in which the

unobservable respondents’ willingness to pay are to be found. Weibull probability distribution was

selected for the random variable willingness to pay. The statistical willingness-to-pay model using

the Weibull distribution is estimated using the maximum likelihood method.

The corresponding values of a statistical life were estimated using both median willingness-to-pay

estimates (conservative estimates) and mean willingness-to-pay values. They were obtained by

dividing the willingness-to-pay figures by the corresponding annual risk reduction being valued. It

was assumed that respondents implicitly considered the risk reduction evenly over the ten-year

period, which makes it possible to avoid discounting the respondents’ annual payments.

The values of a statistical life estimated from 1-in-1000 risk reductions are much higher than those

estimated using the 5-in-1000 risk reduction. This is purely due to the lack of proportionality

between the willingness-to-pay estimates regarding the differences in the size of risk reductions. It

is suggested that the VSL estimates derived from mean and median willingness-to-pay estimates

for a 5-in-1000-risk reduction are of greater policy relevance since they represent more

conservative estimates than those estimated using willingness-to-pay estimates for 1-in-1000-risk

reduction. Thus, for policy assessments in São Paulo it is suggested conservative values of a

statistical life ranging between US$ 0.77 – 1.31 million.

When compared with European and North American estimates these values seem to be higher

than expected. Given the close link between willingness-to-pay estimates and the population

income, lower willingness-to-pay values for developing countries might be expected. A possible

reason for the high WTP and VSL estimates found in the current study might have been the

’cooperative’ behavior observed in many of the respondents. It is possible that, those respondents

tried to be “cooperative” or helpful by saying “yes” to every question. We believe that the

relatively high figures in this valuation exercise may be partly due to this bias. Value of a statistical

life excluding possible ‘yeah-say’ responses using parametric estimation of mean and median

annual willingness to pay in US$ 2003 (Weibull distribution, 95% CI ) is US$ 0.4-0.5 million and in

US$2009 0.45-0.56 million2.

WDI (2009) Countries Brazil Costa Rica GDP per capita (current US$) 8,251 6,373 GDP (current US$) 1,594,489,675,024 29,255,751,296 Population, total 193,246,610 4,590,790 GDP (current LCU) 3.19E+12 16.76E+12 Exchange rate 2 573 Value of Statistical Life (VSL): VSL estimates from Brazil (Ortiz et al, 2009) 0.45 0.56 Costa Rica GDP (US$ billion) in 2009 29 29 Costa Rica Population (million) in 2009 4.59 4.59 Costa Rica GDP per capita (US $) in 2009 6,373 6,373 Average GDP/capita differential to Costa Rica in 2009 77.24% 77.24% Exchange rate (year average 2003) 573 573 Income elasticity of VSL 1 1 VSL in Costa Rica for adult individuals dying from pollution, mln US$. 0.35 0.43 VSL in Costa Rica for adult individuals dying from pollution, mln LCU. 199 248

2 Adjusted using CPI presented by U.S. Department Of Labor, Bureau of Labor Statistics (2012)

ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.txt.

Annex 2. List of Acronyms

Acronym Meaning

CB Chronic bronchitis

CCSS Caja costarricense del seguro social (Costa Rican Social Security Administration)

COI Cost of illness

DALY Disability-adjusted life year

GDP Gross domestic product

GMA Greater metropolitan area

HCA Human capital approach

IDW Inverse distance weighting

LAC Latin America and the Caribbean

LCU Local currency unit

LRI Lower respiratory illness

OECD Organization for the economic cooperation and development

PM2.5 Particulate matter with a diameter smaller than 2.5 microns

PM10 Particulate matter with a diameter smaller than 10 microns

UNA Universidad Nacional de Costa Rica (Costa Rican National University)

USNIH United States National Institutes of Health

VSL Value of a statistical life

WHO World Health Organization

WTP Willingness to pay