Masters Dissertation: Jadavpur University

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Name: Avipsha Sengupta
Roll number: 1800302071
Class: PG 2
Professor’s name: Dr. Sushil Haldar
Title: DALYs: Disability Adjusted Life Years

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ACKNOWLEDGEMENTS:
I take this opportunity to express my profound gratitude and deep regards to my guide Prof.
Sushil Haldar for showing guidance and being a source of constant encouragement.

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TABLE OF CONTENTS:
Sl. no Page
1. Abstract 4
2. Introduction 5
3. Literature Review 6
4. Measurements 6
5. Uses and Policy applications 10
6. DALYs and Cost-effectiveness 11
7. Disease burden in India 12
8. QALYand DALY 13
9. DALY: A critical review 14
10. Limitations of DALY 17
11. Conclusion 17
List of references

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ABSTRACT:
The Disability Adjusted Life Year or DALY is a summary health measure which has combined
morbidity and mortality into a single measure. It was conceptualized in 1993 to calculate the
burden of disease in human life and has been update several times ever since. This paper tries to
encapsulate the origin and basis for formulation of DALYs. It is an overview of the vast
literature of DALY - its role in resource allocation and cost-effectiveness, its attempt to capture
human disability, its role in providing numerical guidance to health sectors and its flaws as a
metric.
JEL classification: I12, D63, O2
Keywords: DALYs, burden of disease, age-weighting, cost-effectiveness

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INTRODUCTION:
The Disability Adjusted Life Year or DALY is a health measure that quantifies the burden of
disease by taking into account both mortality and morbidity It estimates the gap between what is
the expected ‘ideal’ health and ‘actual’ heath condition of the population.
The basic concept of DALY arises from the very first term ‘disability’ which is defined as any
chronic or acute health condition which reduces mental or physical well being for a short or long
term. ‘Disabilities’ in this framework includes a large number of health conditions, starting from
nutritional deficiencies, maternal and perinatal conditions, non-communicable, infectious and
parasitic diseases, injuries to quadriplegia, total blindness, alcohol dependence, neuropsychiatric
disorders and development disorders. It aims to quantify the years of life lost due to premature
death as well as the years lost due to sub-optimal productivity of mind and body due to ill health.
The basic metric can be represented by a simple equation:
DALY = YLL + YLD
Where YLL= Population’s years of life lost and YLD= Population’s years lived with disability
YLL and YLD are calculated as:
YLL= L × N
N being the number of deaths in the population and L is the average life expectancy of the
population in years.
YLD= (I × L) × W= P × W
I is the number of incident cases of that particular disability in the population, L is the average
length of the disability, P is the prevalence of the condition and W is the disability weight
associated with the condition. Neither YLL nor YLD can be directly measured. YLD depends on
the disability weight (will be explained in the next section) that is assigned to a particular
condition.
Incidence versus prevalence perspectives:

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Since time is chosen unit of measure, the burden of disease could be an incidence or prevalence
based indicator. Since death rates are incidence rates, the obvious choice for mortality is to use
the incidence approach. In contrast disability can have both incidence and prevalent components.
The Global Burden of Disease study used the incidence perspective since the time lost due to
disability is more consistent with premature mortality by this approach and the incidence
approach reflected the health intervention impacts better.
LITERATURE REVIEW:
The Global Burden of Disease Study was started as a single World Bank commission study in
1990. This project quantified the health effects of more than 100 diseases and injuries for eight
regions of the world, giving estimates of morbidity and mortality by age, sex, and region.
Disability Adjusted Life Years also known as DALY was introduced in this study as part of the
World Development Report : Investing in Health (1993) as a metric to study the burden of
injuries, diseases and risk factors. The disability-adjusted life year (DALY) is a measure of
overall disease burden, expressed as the number of years lost due to ill-health, disability or
premature death. C.J.L Murray (1994) tried to quantify the burden of disease by showing the
technical backdrop of a DALY. He argued that any health outcome that caused a loss in welfare
of human life should be included in the indicator of health. Before DALY came into existence,
only mortality rates were considered to determine the burden of disease. However, fatality rates
alone cannot paint a fair picture of the state of health affairs of a nation. An interesting use of
DALY is that it acts an as indicator to quantify health impact of environmental pollution related
to disease burden (Gao.T, Wang.X, Chen.R, Ngo.H, Guo.W, 2014). DALYs take into account
both time lived with a disability and time lost due to premature mortality (Murray, 1994). He
suggests that DALYs can be used in studying cost-effectiveness of health interventions. DALY
can not only be used in quantifying the burden of disease, but also resource allocation on the
basis of DALYs prevented. This point however has been questioned as to how the two
information sets for the two exercises are not the same. (Anand.S, Hanson.K, 1995).
MEASUREMENT:
Reiterating the basic formula developed for calculating DALYs:
DALY = YLL + YLD

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To simplify, consider a woman with a standard life expectancy of 82.5 years and dying at age 50
would suffer 32.5 YLL. If she additionally turned blind at aged 40, this would add 5 years spent
in a disability state with a weight factor of 0.33, resulting in 0.33 x 10 = 3.3 YLD. In total, this
would amount to 35.8 DALYs.
Disability weights, age weighting and time discounting are some concepts to mention here.
A disability weight is a weight factor that reflects the severity of the disease on a scale from 0
(perfect health) to 1 (equivalent to death). Years Lost due to Disability (YLD) are calculated by
multiplying the incident cases by duration and disability weight for the condition.
Questions like which is worse, a 20 year old suffering from cancer or an 80 year old, or whether
the death of an infant is as bad as the death of a 20 year old are obvious i.e what is the basis for
age-weighting can be asked. Murray, in his paper explaining the technical basis of DALY,
mentioned that the social role a person plays at different ages should be the basis for age-
weighting For reasons of convenience he designed a continuous age-weighting function:
𝐶𝑥𝑒−𝛽𝑥
Where β is a constant taken by Murray in his study as 0.04, 𝐶 is also a constant which ensures
that the global estimated burden of disease is not influenced by unequal age-weights. According
to the WDR of 1993, there are six severity classes according to which weights are assigned; for
example 0.096 for Class 1 disabilities that caused a decrease in things like daily education,
occupation, recreation or /and procreation to 0.920 for Class 6 disabilities which disrupted basic
activities like eating, maintaining hygiene. The 2010 GBD study published weights for 220
unique health conditions with some of them having different weights according to the degree of
severity of disability. Several methods such as Visual Analogue Scale (VAS), standard gamble,
time trade-off (TTO) and person trade-off (PTO) have been used in assigning disability weights
to different health states. The time trade-off method asks people to choose between living in
perfect health for shorter and living with disability for longer time. The person trade-off
compares utility of different groups of respondents to decide what should be the rank given to
disability weights. The GBD, 1990 used two PTO drills to determine the disability weights. The
2010 GBD surveyed households and the focus was on ‘health loss’ as opposed to ‘welfare loss’.

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Disability weights were adjusted according to the strength of preference for one health state over
the other. Critics have since the introduction of this concept, questioned whether disability
weights can be applied universally. For example, the reduction in quality of life with blindness
maybe different in a rural set-up as compared to an urban set-up or high income country who use
advanced technologies. Adjusting for co-morbidities and co-disabilities is a challenge for
disability weighting. It is important to note that sanitation conditions and diagnostic criteria
widely differ between developed and developing countries, so disability weights should be
adopted accordingly to prevent overestimation of disease.
Instead of explaining age-weighting by some differential intrinsic valuation of life, Murray
attempted to capture different social roles at different ages. Sickness and death among young
productive population group was given more importance since children and elderly people are
dependent on them. (Example: In terms of DALYs, one 20-year-old suffering from AIDS for one
year is approximately as bad as two 80-year-olds suffering from AIDS for one year). In 2006,
this was identified as what makes DALYs unique. Critics have questioned why only age is taken
as indicator of social value and not the occupation. Also, YLLs are biased towards the young,
and so age-weighting in DALYs shifts the focus on young people primarily. A debate over this
continued till in 2000, the GBD results were published both using and not using this component.
It was however dropped in the 2010 GBD study.
Discounting is giving more importance to near term benefits than ones that might accumulate in
the future. Suppose we let DALY estimates guide our health interventions. If this intervention
today prevents say 1000 cases of HIV, it will be removing more DALYs in the total population
count of DALYs than an intervention expected to prevent 1000 such cases of HIV occurring in
the future In the WDR of 1993, a 3 percent discount rate was selected in calculation of DALYs.
Results using a 0 percent discount rate and 6 percent discount rate were also shown. However
some European studies chose to leave this out and it was discontinued in the updated GBD of
2010.
After taking the above components into consideration, in the integral form, DALY can be
expressed as:

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∫ 𝐷
𝑥=𝑎+𝐿
𝑥=𝑎
𝐶𝑥𝑒−𝛽𝑥
𝑒−𝑟(𝑥−𝑎)
𝑑𝑥
Where 𝑎 is age of onset or age of death; 𝐿 is the disability duration or life expectancy; 𝐷 is the
disability weight; 𝐶𝑥𝑒−𝛽𝑥
is the age weight; 𝑒−𝑟(𝑥−𝑎)
is the time weight function.
On solving the definite integral from age a to a+L gives us the DALY formula for an individual:
Where D is the disability weight, r is the rate of discount, C is the age weight correction
constant, 𝛽 is the parameter for age-weighting function, a and L are as mentioned earlier. In the
specific form r= 0.03, 𝛽 = 0.04 and C = 0.16243.
The figure above taken from Murray’s article on Global Burden of Disease shows the DALYs
lost due to death at each age for a male and female. The graph shows the amount of time lost
due to premature mortality, age-weighting and discounting but does not reflect the disability
aspect.

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Now, YLLs and YLDs can also be expressed in integral forms but are very complex and the
subject matter of many debates. The simplified formulae hence used are the ones mentioned
above.
YLL= L × N and
YLD= (I × L) × W= P × W
Life expectancy is used in finding YLL and the WHO guide to Cost Effective Analysis published
in 2003 mentioned four measures to calculate the same for DALYs, the simplest one being
PYLL or Potential Years of Life Lost where the life expectancy of a target population for all age
groups is chosen as standard. For example if the target value is 80 and a person dies at 78, then
he will be contributing 2 YLLs to the population’s count of YLLs. Variations on YLLs are
CEYLLs: cohort expected YLLs, PEYLLs: period expected YLLs and SEYLLs: standard
expected YLLs. These are basically conditional expectancies rather than life expectancies. The
SEYLL approach has been used more widely because of the ease of comparison of model results
across countries and regions.
USES AND POLICY APPLICATIONS:
Since its development, the DALY measure has had applications in both national and global
disease burden and cost-effectiveness studies. The WHO recommends the use of DALYs in cost-
effectiveness studies for the purpose of comparability. DALY losses and costs are estimated for
each intervention under study and then compared using the incremental cost-effectiveness ratio
(ICER) to determine which intervention will offer the best value for money invested.
Infectious diseases can not only be cured but good interventions can prevent the transmission to
other susceptible persons (herd immunity). So, dynamic models are useful for health economic
analysis. Also, since they can have chronic or long term effects, DALY being an incidence based
approach is quite useful.
A case study showed how DALYs are used to compare the disease burden across different
regions. WHO in a research conducted in 2013, calculated DALYs for six major regions in the
world and compared the total DALY per thousand individuals in each region with the world
average. Africa, apparently had the highest disease burden, with DALY values almost double the

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world average. The results were consistent with those of low income and low welfare continents
such as Africa. On the opposite end of the spectrum was the Western Pacific region with the
lowest DALYs followed by American and European regions all of which had DALYs lower than
the world average.
A new field has been developed (WHO, 2002) known as ‘environmental burden of disease
study’ which researches on how DALYs can be linked to amount of air pollutants and burden of
disease caused by them. As many pollutants cause diseases, their impact on health can be
interpreted as disease burden too. DALY can provide powerful tools for risk quantification of
environmental pollutants. The pollutants can be classified into organic substances, inorganic
substances and microorganisms. Another way of grouping is by putting them under the headings:
carcinogenic toxins, mutagenic toxins and teratogenic toxins. Ingestion or contact with pollutants
can cause several health hazards and disabilities. There are four steps before one can apply the
DALY methodology to quantify the environmental burden of disease: identification of harmful
pollutants, exposure assessment, dose response analysis and morbidity/mortality analysis.
DALYs AND COST-EFFECTIVENESS:
DALYs have been used in cost-effective analysis since 1993 both at micro levels and sector
wise. The impact of interventions on DALYs (DALYs averted by interventions) is calculated
taking two cases, one with interventions and one without interventions. In order to calculate
DALYs averted in cost-effectiveness analysis, local life expectancy can be used in place of life
expectancy assuming stable mortality. However, if it is changing over time, then each new birth
cohort will experience a different life expectancy becomes less accurate representation of future
life for interventions that impact on particular age groups. Murray suggested the use of cohort
life expectancy instead in order to estimate the change with or without intervention. However, a
tricky situation is one where the study involves an intervention applied over many years that
changes the age specific mortality rates.
Christopher Murray in his paper, Quantifying the burden of disease, had mentioned earlier that
DALYs not only measure the disease burden but also help define the resource allocation. There
are some general limitations of cost effectiveness analysis. If the resource allocation problem is
restricted to the health interventions only, then the non health sector interventions having health

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sector returns are ignored. For example, provision of clean drinking water in homes not only
reduces diarrhoeal infections but also increase social economic benefits by saving the time which
would be required to fetch clean water. Evaluating from the health sector perspective tends to
overlook non health sector benefits. Another shortcoming of this analysis is that in the DALY
minimization framework, the appropriate budget constraint cannot be guessed correctly.
DISEASE BURDEN IN INDIA:
Many countries including India wish to calculate the burden of disease estimates which consists
of mortality and disability to help them in prevention and control of diseases. National Burden
Estimates (NBE) was created in 2017 to procure the required data at national as well as sub
national levels.
In order to calculate this for India, a combination of UN 2017 death totals, national and sub-
nationals mortality rates for 2010-17 and causes of death from 211166 verbal autopsy interviews
for the years 2010-14 were used. YLLs and YLDs were calculated using data from WHO Global
Estimates. The causes of death were grouped into 45 categories and the YLLs and YLDs were
summed up to calculate the DALYs for these causes. This study covered rural and urban zones
of 21 major Indian states.
As per the findings, in 2017, there were approximately 9.7 million deaths and 486 million
DALYs in India. 75 percent of these were in rural areas. More than a third of national DALYs
were attributed to communicable, maternal, perinatal and nutritional disorders. Most of the
DALYs in the rural areas were for chronic respiratory diseases, fevers, diarrhea, perinatal
conditions and nutritional disorders. Ishcaemic heart disease showed high DALYs in urban areas
(9.6 percent of all DALYs). 11.4 percent of national DALYs were due to injuries. The top 15
conditions responsible for maximum number of DALYs were mostly the ones causing mortality
too (chronic respiratory diseases (5.7 percent), fevers, diarrhea (4.7 percent), perinatal conditions
and nutritional disorders, cancer (4 percent), liver and alcohol (3 percent) related diseases to
name some) and disability due to some conditions like neuropsychiatric conditions, sensory loss,
musculoskeletal disorders. DALYs for five conditions were mostly due to YLDs as opposed to
YLLs: neuropsychiatric conditions, musculoskeletal disorders, renal failure. More than 70
percent DALYs at all ages resulted from YLLs mainly for communicable, perinatal and maternal

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diseases as opposed to YLDs constituting 86.8 percent of DALYs for nutritional deficiencies.
One important observation was that the disease common to one area was not common to another
one. This suggested the importance of state specific management of disease. India tops the
ranking when it comes to highest deaths and DALYs due to the condition asthma.
QALYs AND DALYs:
The term ‘quality-adjusted life year’ (QALY) was first used in 1976 by Zeckhauser and Shepard
to indicate a health outcome measurement unit that combines duration and quality of life. But the
underlying concept had been formally shaped in the early 1970s in the development of a ‘health
status index’. QALY measures the burden of disease on a life by including both quality and
quantity of lived life. It gives us an estimate of the number of years that can be added to a life if
an intervention is given. So, like DALY, QALY can also be used in cost-effective analysis of
any treatment.
The basic idea of QALY is straightforward: it assumes that a year of life lived in perfect health is
equivalent to 1 QALY (1 Year of Life × 1 Utility = 1 QALY) and that a year of life lived in a
state of less than perfect health is worth less than 1. In order to find the exact QALY value, one
can simply multiply the utility value associated with a given state of health by the years lived in
that state. QALYs are hence expressed in terms of "years lived in perfect health" which translates
to, half a year lived in perfect health is equivalent to 0.5 QALYs (0.5 years × 1 Utility), the same
as 1 year of life lived in a situation with utility 0.5 (e.g. bedridden) (1 year × 0.5 Utility). Let’s
take a simple example of cost-utility analysis using QALY:
Say Treatment A has a cost of $1200 and QALYs = 4.6
Treatment B has a cost of $700 and QALYs = 2
Increment of A over B (cost) = $500 and Increment of A over B (QALYs) = 2.6
Incremental cost/ Incremental Outcome (QALY) = $500/2.6 QALYs = $192.31 per QALY
gained
*(3.6 QALYs = 4 years × 0.9 Units of Utility); (1 QALY = 2 years × 0.5 Units of Utility)

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If an intervention provided perfect health for one additional year, it would produce one QALY.
Likewise, an intervention providing an extra two years of life at a health status of 0.5 would
equal one QALY.
QALYs are a measure of the number of years a person lives in a perfect state of health, whereas
DALYs measure the number of years that an individual loses due to imperfect health state. Since
QALYs and DALYs are both used in cost effective analyses (CEA), comparison can be made on
this basis. Both these measures can be viewed on a scale between 0 and 1. For QALY, 0
corresponds to dead and 1 corresponds to ‘perfect health’. For DALY it is the exact opposite- 0
for perfect health and 1 for dead. A study has pointed out key differences between cost per
DALY and cost per QALY. The latter is focused more high income countries while the former
focuses on lower income countries. So cost per QALY tends to address diseases like cancer
which are seen in wealthier nations as opposed to cost for DALYs which addresses diseases like
tuberculosis and HIV which are common in poorer countries. As a result of this cost per QALY
studies look into pharmaceuticals and cost per DALY studies look into immunization schemes.
Researchers conducting CEAs in countries with limited data capacity may find it easier and less
expensive to use the cost-per-DALY metric. Also, DALYs seem more suitable to the developing
world, because the majority of global burden of disease is accounted for by developing regions.
Even though a recommended value for a DALY has been suggested, a fair value for a QALY is
unknown in many societies.
DALY- A CRITICAL REVIEW:
Like any other measure, DALY also faces certain criticisms and has some shortcomings. Anand
and Hanson critically reviewed the DALY framework as explained by Murray in his paper which
shall be discussed hereafter. The very definition of DALY is that it is a measure of ‘burden’ of
disease. This however does not include the burden that falls on people around the disabled, nor
does it talk about how the individual deals with the disability. Also, DALYs use the standardized
life expectancies for measuring disease burden or in cost effectiveness study, implying that
health interventions alone can increase these life expectancies. However many non-health
circumstances need to change in order for these values to rise, which have been ignored. The
standard age gap (with 82.5 life expectancy for a female and 80 for a male) considered in DALY
calculation is seen to be different from the ones in low mortality populations, for example for

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Japan, the same is 6 years. So according to critics, this choice may have been arbitrary. One
aspect of DALY assessment by Murray which has raised many eyebrows was the idea of ‘age-
weighting’ or valuing time lived in different ages differently. As this paper has mentioned earlier
in the age-weighting section, this primarily means that a different value is assigned to different
ages of a man’s lifetime. The age-weighting function is assumed maximum at age 25 but of a 2
year old’s value by this logic is just 20 percent of the maximum and someone aged 70 has only
46 percent of maximum value. Murray developed this keeping in mind the productivity of a man
at different ages and the dependency of infants or older individuals on younger, more productive
people. He followed the money value to life and disability approach and tried to capture the
social roles played by humans at different ages in their life. He claimed that assigning higher
weights at a particular age did not mean that the other ages weren’t as important to the
individual, but that the ‘social value of that time maybe greater’. Here comes the story of
intrinsic versus instrumental valuation. Anand and Hanson argue that age-weighting does not
constitute intrinsic valuation and instead focuses on instrumental valuation since the middle aged
individuals are valued higher than younger or elderly. Another argument says that if we are
taking productive people as high valued then professionally, nurses and doctors should be valued
higher. The time of people who can contribute through taxation to the health care budget, should
be given most value according to Anand. To conclude on the age-weighting aspect, a principle of
universalism of life (Anand and Sen) emphasizes on common intrinsic valuation of human life
irrespective of the age. Murray formulated DALYs suffered as a function of both Life
Expectancy Li and disability weight Di (maybe referred as ‘uncompensated’ disability weight).
However, a better measure will take into account the way in which social resources can
compensate for the disability that one experiences. ‘Compensated’ disability weights would
depend on the income of the disabled along with whatever local services he has to assist with his
disability. These weights would be a closer reflection of the actual ‘burden’ of disability felt by
an individual. Critics have also questioned about the possibility of removing the health status
from a ‘social context’ because the fall in quality of life due to a disability (for example
paraplegia) maybe different in countries with higher income versus those having lower income
or say rural communities. One more problem pointed out with regard to disability weight is that
Class six of disability weights (mentioned earlier in this paper) mentions those illnesses which
require assistance in feeding or cleaning. Infants however have the same functional limitations,

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but they obviously do not contribute to disease burden. So for disability weights should be more
consistently defined to avoid the age-illness issue. Reidpath critiqued the ethical implications of
the disability weights in the DALY, but emphasized on the way later iterations of the DALY was
unsuccessful in making the measure more equitable. The 3 percent discount rate applied to the
DALY formula implies that a life saved today will be more than five lives saved in 55 years.
Critics have asked whether there is any justification that an illness will affect more today than it
will after one year. If we apply discounting, then that the same illness will affect less in the latter
case. Murray’s framework has not been able to differentiate between discounting DALYs (or
utility) and discounting money (or consumption). Murray explains discounting in the aspect of
cost-effectiveness analysis where he claims that undiscounted health benefits will mean that all
resources are spent on eradication of disease and this will outweigh other schemes which do not
result in eradication.
Anand and Hanson in their paper have claimed that the technical basis for DALY is not justified
and in many areas, quite unclear. It is very important that the two frameworks of measuring
disease burden and allocation of resources are properly distinguished according to their
information sets. Murray’s principle of ‘treating health outcomes as like’ seems a bit strange in
the context of DALYs. It implies that two people having the same age, sex, disability and time
period are treated the similarly. Maybe this principle works for measuring burden but in from the
resource allocation perspective, two such people should technically not be compared because
they may differ in wealth or access to services. This principle does not say much about treatment
of people who are unlike along the above mentioned dimensions. Finally the allocation of
resources based on the minimization of aggregate DALY leads to contrary results according to
Hanson. Michael Reich, another economist, says that a primary flaw of the DALY is its target to
be a “double metric,” which means that it seeks to increase efficiency as well as equity. He
disapproves of the DALY’s use as a means to achieve two of Hammer’s three goals (improving
aggregate health status and improving equity), instead of only the one that Hammer argues that it
is appropriate for (improving health status). The issue here is that these two goals are not always
aligned; Reich attacks the 1993 World Development Report (WDR), for which the DALY was
designed, for not mentioning clearly what to do “when cost-effectiveness and equity are in
conflict.”

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LIMITATIONS OF DALY:
The paper has tried to furnish a critical evaluation of DALYs by experts in the previous sections.
This section will just touch upon the disadvantages or limitations of the DALY approach. A
study is Africa on ascariasis in children showed that DALY focuses primarily on health and fails
to capture the societal impact of diseases. A study on maternal health interventions listed a few
problems regarding evaluation of the burden of maternal health using DALYs. It was noted that
DALY does not take into account everyday burden of gynaecological problems of females. The
calculation of DALYs does not estimate healthy years of life lost for stillbirths because counting
can only start at birth, as per the definition. Hence, the burden of disease due to perinatal causes
does not include late foetal or intra-partum deaths. Another limitation of DALY is that the
method is complicated and requires man inputs about population specific age structures, life
expectancies, incidence, prevalence and more making it tedious for local groups to calculate
DALY. Over the years this metric has not become simpler even after age-weighting and
discounting has been dropped from some models. The other problem is that though the metric
was developed to be able to compare across time and place, this is not being possible because
there have been so many changes in the studies since early 1990s and 2000s. The components of
DALY like life expectancies, updated disability weights, using discounting or dropping it, these
have changed over the years making the resultant calculations cumbersome. The changes have
not been well explained making the process difficult to interpret.
CONCLUSION:
A summary metric to calculate disease burden globally and locally, DALY has evolved over the
years, ever since its origin in early 1990s. It is a composite indicator, combining premature
mortality and non-fatal outcomes. When conceptualized, the value choices that were made, like
the ‘social value’ of life at different ages, time lost due to early mortality were different from the
past indicators. They were selected for ease of comparison across a range of situations. The main
advantage of DALY was that included the time lived with disability which other indicators like
potential years of life lost (PEYLL) did not consider. This paper has also shown the use of
DALYs in cost-effectiveness assessment, which in turn helps the government decide between
where to allocate its resources, which health programs to fund, how to subsidize different
interventions. The government also tries to assist private purchasers to improve their choices

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regarding resource allocation. A small section has mentioned some statistics in the context of
India and DALYs lost, which is like a representation of the health scenario in developing
countries. However, this, like any other metric has its shortcomings and has been revised and
updated several times. The earlier considered highest observed life expectancy has been
substituted by lowest life expectancy, specific to different age groups. Disability weights have
also been replaced. Discounting and age-weighting which have been questioned and critiqued by
many because of the missing intrinsic valuation were removed from recent DALY studies. Many
of the initial concerns regarding the metric have been taken care of. It is important to note that
DALYs were formulated over two decades ago and was a unique metric then, and made
contributions in burden of disease calculations (especially chronic diseases) worldwide and at
more granular levels. However, refined DALY studies may be slightly unclear for researchers
now to use this metric in GBD studies. If the improvements on the DALY methods are properly
explained and documented, it may give researchers more freedom to use DALYs in current
health studies at global and local levels.

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Health Policy Unit, London School of Hygiene and Tropical Medicine, London, UK; Health
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