Vaccine 24S3 (2006) S3/164–S3/170

Chapter 19: Cost-effectiveness of cervical cancer screening

Sue J. Goldie

a

,

∗

, Jane J. Kim

a

, Evan Myers

b

a

Department of Health Policy and Management, Harvard School of Public Health, 718 Huntington Avenue, 2nd Floor, Boston, MA 02115, USA

b

Department of Obstetrics and Gynecology, Duke University, Durham, NC, USA

Received 26 April 2006; accepted 15 May 2006

Abstract

In the last two decades, computer-based models of cervical cancer screening have been used to evaluate the cost-effectiveness of different

secondary prevention policies. Analyses in countries with existing screening programs have focused on identifying the optimal screening
interval, ages for starting and stopping screening, and consideration of enhancements to conventional cytology, such as human papillomavirus
(HPV)-DNA testing as a triage for equivocal results or as a primary screening test for women over the age of 30. Analyses in resource-poor
settings with infrequent or no screening have focused on strategies that enhance the linkage between screening and treatment, consider
noncytologic alternatives such as HPV-DNA testing, and target women between the ages of 35 and 45 for screening one, two, or three times
per lifetime. Despite differences in methods and assumptions, this paper identifies the qualitative themes that are consistent among studies,
and highlights important methodological challenges and high-priority areas for further work.
© 2006 Elsevier Ltd. All rights reserved.

Keywords: Cervical cancer screening; HPV vaccines; Cost-effectiveness

1. Introduction

While randomized controlled trials provide the most valid

estimate of cancer screening efficacy, as they adjust for both
known and unknown confounding variables, they pose sev-
eral economic and practical difficulties. First, because only a
small proportion of the population will develop the disease
and realize a screening benefit, trials would require screen-
ing of very large populations to generate a measurable effect.
Additionally, several decades of observation might be neces-
sary from the time of initiating a program to when an effect
on cancer incidence would be measurable. Furthermore, a
randomized controlled trial of different screening strategies
may not be considered an acceptable alternative if screening
is already widely accepted as a standard of care. In the case
of cervical cancer screening, it is unlikely that clinical trials
will be performed that could adequately compare all the pos-
sible variations of screening and treatment and the follow-up
cohorts of patients for the decades required to assess long-

∗

Corresponding author. Tel.: [phone]; fax: [phone].

E-mail address:

sue [e-mail]

(S.J. Goldie).

term mortality and quality of life outcomes. Thus, disease
simulation modeling is undoubtedly necessary.

In the last two decades, several computer-based cervical

cancer models have been developed to inform specific policy
questions related to cervical cancer prevention. We and others
have assessed the comparative cost-effectiveness of different
screening strategies while explicitly considering such factors
as the relative performance and costs of different screen-
ing tests, the tradeoffs between screening test sensitivity and
specificity, the attributes of tests that might facilitate uptake,
options to manage abnormal results, and the effectiveness
of different treatments

[1]

. Quantitative cost-effectiveness

results of model-based screening analyses can be challeng-
ing to compare directly. In part, this is due to (1) the choice
of model and parameter assumptions, which vary depend-
ing on the nature of the study objective, (2) the uncertainty
around estimates of costs and outcomes, as well as variabil-
ity in the value of these parameters in different settings, and
(3) the different perspectives taken by analysts (e.g., societal
versus healthcare payer). However, once these variables are
accounted for, results are far more comparable and several
general themes can be identified consistently among studies.

0264-410X/$ – see front matter © 2006 Elsevier Ltd. All rights reserved.
doi:

10.1016/j.vaccine.2006.05.114

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This chapter will synthesize the findings from cost-

effectiveness analyses (CEAs) that have focused on cytology-
based cervical cancer screening and identify several qualita-
tive themes

[2–5]

. Second, consistent findings from analy-

ses that have considered HPV-DNA testing as a triage for
equivocal cytologic abnormalities

[6–11]

and HPV-DNA

testing as a primary screening test with or without cytol-
ogy

[7–9,11–13]

will be described for countries with exist-

ing screening programs. Key themes from studies that have
assessed noncytology-based strategies that enhance the link-
age between screening and treatment and may be more feasi-
ble in developing countries

[14–17]

will be identified. Finally,

a summary of the most important methodological challenges
and high-priority areas deserving of analytic attention will be
provided.

2. Prior CEAs in developed countries

The vast majority of published CEAs of population-based

cervical cancer screening performed in the last two decades
have focused on high-income countries. Consequently, they
have addressed issues such as the choice of screening inter-
val, ages for starting and stopping screening, enhancements
to conventional cytology, and integrating HPV-DNA testing
into cytology-based screening programs as a triage for equiv-
ocal cytology results or as a primary screening test for women
over the age of 30. Several general themes emerge from mul-
tiple studies despite differences in modeling structure and
assumptions. These can be summarized as follows:

• The cost-effectiveness of screening in the general popu-

lation becomes increasingly less favorable as programs
are intensified by screening more frequently than every
2–3 years and/or aggressively following equivocal or low-
grade cytological abnormalities that are likely to regress.
This occurs because for any given level of test sensitivity
and specificity, costs increase almost linearly with shorter
intervals while the incremental gains in benefits rapidly
diminish. In most analyses in developed countries, screen-
ing intervals of 3–5 years usually fall within acceptable
limits of cost-effectiveness ratios. Biennial and annual
screening strategies have very high cost-effectiveness
ratios, and are generally considered not cost-effective from
a policy perspective. The high costs of frequent screen-
ing are due not only to the increased number of tests, but
also the detection and treatment of more low-grade lesions
which, in the absence of screening, would regress on their
own without intervention.

The majority of European countries recommend screen-

ing beginning between the ages of 20 and 25 years, and
continuing every 3–5 years until age 60–65

[18]

. These

general policies have cost-effectiveness ratios that would
be considered very cost-effective according to multiple
suggested criteria for cost-effectiveness ratio thresholds
(see Chapter 18;

[4]

). For these countries, priorities should

be expanding coverage in the population by using new
technology such as HPV-DNA testing in a cost-effective
manner and deciding how a vaccine could be utilized given
existing screening practices. In the US, screening strategies
implemented in clinical practice are often incongruent with
those recommended by clinical guidelines, which in turn,
at least until recently, are not always the most cost-effective
strategies. However, in recent years, consistent with find-
ings from cost-effectiveness analyses, recommendations
have shifted to screening less frequently, delaying the ini-
tiation of screening until 3 years after sexual debut, and
considering cessation of screening for women over age 65
who have been regularly screened and are negative.

• There appears to be little benefit from beginning screening

at a very young age, and there could be harmful conse-
quences due to unnecessary colposcopy and other proce-
dures. In most countries with existing screening programs,
the recommended age of beginning cytology screening
ranges from 21 to 25

[4]

. In the US prior to 1992, most

national guidelines recommended initiating cervical can-
cer screening with the onset of sexual activity or at age 18

[19]

. An analysis that compared this recommendation to

policies that delayed screening until 3 years after sexual
debut showed delayed screening to be more cost-effective.

• For women who have undergone cervical cancer screen-

ing at regular intervals throughout their lifetime and have
consecutive negative results, a policy that discontinues
screening around age 65 is reasonable

[20]

. Benefits of

screening (in terms of life-expectancy gains) in a well-
screened cohort decline rapidly after age 65 because the
risk of dying from cervical cancer is substantially reduced
because of the natural history of the disease, a reduc-
tion in prevalence resulting from screening and treatment
at younger ages, and increasing risk of death from other
causes. The relative cost-effectiveness of continued regular
screening in low-risk older woman will somewhat depend
on the screening frequency. For example, when screening
intervals are three to five years, termination of screening
at age 65 does not save many resources

[21]

. It should

be noted, however, that where women have not previously
been screened, screening at older ages is very cost-effective
because there is a large risk of disease in older unscreened
women.

• Strategies that employ screening tests with higher sen-

sitivity than conventional Pap smears (e.g., liquid-based
cytology with HPV-DNA testing to triage equivocal cytol-
ogy results, enhanced cytology with computer-assisted
imaging, primary screening with HPV-DNA testing in
older women) without modifying the routine screening
interval offer little incremental benefit but increase costs,
and thus are associated with very high incremental cost-
effectiveness ratios. For example, in an analysis of screen-
ing in the US, the magnitude of the life-expectancy gains
for annual screening with HPV-DNA testing and cytol-
ogy compared with biennial screening with those same
tests was 4 hours. Accordingly, the incremental cost-

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effectiveness ratio exceeded $2 million per year of life
saved (YLS)

[12]

. Regardless of the criterion used for a

cost-effectiveness threshold (see Chapter 18), this strategy
would not be cost-effective.

• Similar strategies with more sensitive screening tests do,

however, appear cost-effective in the context of screen-
ing every 3–5 years. For example, studies in European
countries have shown that strategies that utilize HPV-DNA
testing to triage equivocal results in the context of conven-
tional or liquid-based cytology every 3 or 5 years have
cost-effectiveness ratios that fall below each country’s
GDP per capita

[7,8,22]

. In the US, using HPV-DNA test-

ing as a triage test for equivocal results or in combination
with cytology every 2–3 years among women over the age
of 30 was also found to be attractive compared to using
cytology alone annually

[9]

.

Most studies report that primary HPV-DNA testing, and

combined cytology and HPV-DNA testing are associated
with a greater risk of unnecessary colposcopy throughout
a woman’s lifetime. The potential negative quality-of-life
effects of screening with such a sensitive test are not easily
measured, but these will be approximately proportional to
the number of screening rounds, and thus will be greater in
scenarios of frequent screening. The rate of unnecessary
colposcopies is another reason to carefully weigh the rel-
ative harms and benefits associated with all screening fre-
quencies using more sensitive tests. Similarly, using HPV-
DNA testing as a primary screening test in young women in
their 20s will undoubtedly lead to very high rates of screen-
positives. The impact of even a small and transient disutil-
ity experienced from a false-positive result could be enor-
mously influential at the population level. Better data on
the impact of HPV-DNA status on quality of life, individ-
ual screening behavior, and sexual behavior are a priority.

• Small changes in specificity are very influential on

cost-effectiveness in settings with frequent screening
and aggressive follow-up strategies

[23]

. This trend is

important since HPV-DNA testing has on average 20–30%
greater sensitivity but about 5–10% lower specificity than
Pap cytology for detecting high-grade lesions or cancer
in studies based on combined testing of all women with
both cytology and HPV-DNA test (see Chapter 20). This
is shown in

Fig. 1

, which displays the impact of test speci-

ficity on total per-woman lifetime costs for different levels
of population screening coverage for twice-in-a-lifetime
screening (Panel A) and annual screening (Panel B),
compared to no screening, using a previously-published
model

[15]

. Across all levels of screening coverage,

decreases in test specificity result in higher lifetime costs.
As expected, specificity has a greater impact in settings
with high coverage rates. When screening is infrequent
(Panel A), the impact of specificity is quite small; however,
with frequent screening, which is typical of developed
countries (Panel B), the impact on costs is much greater.

• Strategies that capitalize on the information provided by

HPV-DNA testing (e.g., consecutive years of negative

Fig. 1. Impact of test specificity on total lifetime costs per-woman for differ-
ent levels of population screening coverage for twice-in-a-lifetime screening
(Panel A) and annual screening (Panel B) with HPV-DNA testing, compared
to no screening. When screening is infrequent (Panel A) at 100% coverage,
increasing specificity from 60 to 100% results in a decrease in cost of $7.
With very frequent screening (Panel B) at 100% coverage, lifetime costs
decrease by nearly $50 as specificity increases from 60 to 100%. Analyses
were conducted using a previously-published model

[15]

.

cytology and HPV-DNA results) and consequently modify
a woman’s future screening interval and strategy have
the potential to be very cost-effective. The combination
of cytology and HPV-DNA testing attains sensitivity and
negative predictive values that approach 100%. Therefore,
using a combination of cytology and HPV-DNA testing
in a screening program could safely allow an increase of
testing intervals, for example from 1–3 years to 3–5 years,
or even longer, as has become the target of demonstration
trials in different countries in Europe and North America
(see Chapter 20).

3. Prior CEAs in developing countries

There are fewer published studies that assess screening in

developing countries

[14–17,24]

. In one of the earliest mod-

S.J. Goldie et al. / Vaccine 24S3 (2006) S3/164–S3/170

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eling evaluations of cervical cancer screening programs in
developing regions, Sherlaw-Johnson et al.

[14]

reported that

the most efficient use of resources would be to concentrate
screening efforts using cytology and HPV-DNA testing on
women age 30–59 at least once per lifetime as such blanket
screening would reduce the lifetime risk of cervical cancer
by up to 30%. Results published since then, using data from
Thailand and South Africa, were qualitatively similar

[15,16]

.

Most early analyses did not include programmatic costs and
focused on a single country, thus, limiting the generalizability
of key findings.

Recently, Goldie et al. conducted a comprehensive assess-

ment of the cost-effectiveness of novel cervical cancer screen-
ing strategies in five regions of the world with differing epi-
demiological profiles where conventional cytology screening
programs have thus far not been sustainable

[17]

. Costs were

assessed using primary and secondary data, and included
direct medical, direct nonmedical, patient time, and pro-
grammatic costs. To facilitate a broad policy comparison
between studies, assumptions were standardized by experts
with experience in each country. Strategies differed by initial
screening test, targeted age of screening, number of visits
required (one, two, or three), and protocols for follow-up.
Initial screening tests included visual inspection with acetic
acid, cervical cytology, and HPV-DNA testing. Three-visit
strategies included an initial screening test, a diagnostic
work-up incorporating colposcopy and biopsy in women
with positive results, and treatment of cervical intraepithe-
lial neoplasia (CIN). Two-visit strategies incorporated ini-
tial screening followed by treatment of all screen-positive
women, without evaluation by colposcopy. One-visit strate-
gies (i.e., “screen and treat”) incorporated immediate treat-
ment in screen-positive women. Outcomes included the life-
time risk of invasive cancer, years of life saved, and lifetime
costs (international dollars).

In all five regions, lifetime cancer risk was reduced by

approximately 25% with a single lifetime screen using either
one-visit VIA or two-visit HPV-DNA testing targeted at
women 35–40 years of age. This reduction was nearly dou-
bled with strategies performed two or three times per lifetime.
Although the average per-woman lifetime costs varied con-
siderably, strategies were identified in all five countries that
had incremental cost-effectiveness ratios less than each coun-
try’s per capita GDP (see Chapter 18). To place the results
into the context of other public health interventions in devel-
oping countries, single-lifetime screening strategies were as
cost-effective as hepatitis B immunization, second-line treat-
ment for tuberculosis, and malaria prevention with bed nets

[17]

.

In the analysis above, the cost-effectiveness results were

most sensitive to loss to follow-up, targeted screening age,
coverage rates, and the cost of care (surgical or palliative)
for invasive cervical cancer. In addition, they found that the
population-level impact of screening (i.e., reduction in the
incidence and mortality of cervical cancer) was most influ-
enced by the level of coverage.

Fig. 2. Impact of test sensitivity on reduction in lifetime risk of cervical
cancer for different levels of population screening coverage for twice-in-a-
lifetime screening (Panel A) and annual screening (Panel B), compared to
no screening. See text for further details. Analyses were conducted using a
previously-published model

[15]

.

Fig. 2

shows the impact of test sensitivity on reduction

in lifetime risk of cervical cancer for different levels of pop-
ulation screening coverage for twice-in-a-lifetime screening
(Panel A). Across all levels of screening coverage, increases
in test sensitivity provide greater reductions in the lifetime
risk of cancer, but the magnitude of cancer risk reduction
depends on the level of coverage. At coverage rates of 25%
or below, increasing sensitivity from 60 to 100% provides an
incremental reduction in the lifetime risk of cancer of less
than 5%. In contrast, when coverage exceeds 50%, increas-
ing test sensitivity from 60 to 100% provides an incremental
reduction in the lifetime risk of cancer of nearly 15%. The
same graph is reproduced for an extreme case of annual
screening (Panel B) to illustrate how important background
screening intensity is when assessing the influence of test
sensitivity

[25]

. In contrast to the typical developing coun-

try situation of once- or twice-in-a-lifetime screening, where
increasing sensitivity has a greater impact when coverage is
higher, in the context of intense frequent screening, increas-

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ing sensitivity has a greater impact when coverage is lower.
For example, at 25% coverage, reduction in lifetime risk of
cancer is 13% when increasing sensitivity from 60 to 100%,
whereas at 100% coverage, reduction in cancer risk is only
4%.

Several general themes have been identified by studies

focusing on resource-poor settings that have been unable to
implement and support ongoing screening programs. These
can be summarized as follows:

• For countries with limited resources, screening efforts

should target women age 35 or older, and strategies should
focus on screening all women at least once in their life-
time before increasing the frequency of screening. If high
coverage can be achieved, screening two to three times
per lifetime could reduce lifetime cancer risk by 25–40%.
Targeting the appropriate age groups is crucial, generally
around age 35 and then at 40 in the case of two lifetime
screening tests; screening three times in a lifetime should
occur between 30 and 50 years of age with spacing between
tests of about 5 years.

• Results of published analyses show that the choice between

cytology, HPV-DNA testing (most-effective), and visual
methods (least costly), is most sensitive to the ability to
link screening and treatment in fewer visits, the resources
required with each test, and test sensitivity.

• When screening is only one to three times per lifetime, and

if coverage rates are below 25%, enhancements to screen-
ing test sensitivity have minimal impact at the population
level (e.g., increasing sensitivity from 60 to 100% provides
an incremental reduction in the lifetime risk of cancer of
less than 5%). However, provided widespread coverage
can be achieved, small changes in sensitivity are more

influential on population impact and cost-effectiveness in
settings with infrequent screening, while changes in speci-
ficity are much less influential.

• In developing countries, within-country and between-

country differences affect screening cost components to a
greater degree than in resource-rich settings (see Chapter
18). The absolute level of cervical cancer mortality reduc-
tion is most sensitive (by far) to coverage rates, minimizing
loss to follow-up of women with positive results, and long-
term effectiveness of cryosurgery in screen/treat strategies,
whereas the cost-effectiveness ratios are most sensitive to
nonmedical costs (time and transportation) and the avail-
ability and cost of cancer treatment (see Chapter 18).

4. Overview of CEA results in all world regions

The need for a global perspective in a discussion of poli-

cies for cervical cancer prevention is made apparent by a
comparison of the strategies used in very different settings.

Fig. 3

shows the discounted lifetime costs and clinical bene-

fits (expressed as reduction in the lifetime risk of cancer) of
different screening strategies performed at different screen-
ing intervals. The cost-effectiveness of moving from one
screening strategy to a more costly alternative is represented
by the difference in cost divided by the difference in can-
cer incidence reduction associated with the two strategies.
Strategies lying on the efficiency curve dominate those lying
to the right of the curve (not shown) because they are more
effective, and either cost less or have a more attractive cost-
effectiveness ratio, than the next best strategy. For each strat-
egy on the curve, a range of cost-effectiveness ratios and
examples of countries in which cost-effectiveness analyses

Fig. 3. Efficiency frontier depicting costs and benefits of screening strategies in different regions of the world

[6–10,12,17,26]

. Strategies differ by screening

test (i.e., visual inspection using acetic acid (VIA), HPV-DNA testing, conventional cytology, and

*

liquid-based cytology with HPV-DNA testing to triage

equivocal results) and screening frequency.

S.J. Goldie et al. / Vaccine 24S3 (2006) S3/164–S3/170

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were conducted are shown based on a review of the pub-
lished literature. The slope between two strategies is steepest
when the net gain in cancer incidence reduction is greatest
(see Chapter 18). In this figure, strategies differ by screening
test and screening frequency, ranging from once per lifetime
to annual screening.

Strategies at the lower left of the curve are those which

involve less technically intensive tests (VIA and HPV-DNA
testing) and infrequent screening intervals (e.g., one to
three times per lifetime). Such strategies, which have cost-
effectiveness ratios ranging from $110 to $2500 per YLS,
are considered to be attractive strategies for countries in poor
regions of the world, such as India and Thailand

[17]

.

Screening at 3- and 5-year intervals using conventional

cytology produces cost-effectiveness ratios that range from
$6800 to $25,600 per YLS based on analyses in European
countries such as the UK, The Netherlands, France, and Italy

[7,8,10]

, and 2-year screening with cytology ranges from

$34,500 to $56,400 per YLS based on analyses in Australia
and the US

[6,9,12,26]

. More aggressive strategies, such as

screening every 2 years or annually using liquid-based cytol-
ogy (with HPV-DNA testing for triage of equivocal cytology
results), fall on the “flat of the curve” because they have
much higher costs yet add very little benefit; these strategies,
assessed mainly in analyses conducted to address clinical
guideline questions in the US, range from $174,200 to over
$1 million per YLS

[6,9]

.

It is compelling to examine this figure in the context of

the most pressing policy issues in developing versus devel-
oped countries. From a broad public health perspective we are
reminded of the differences in the potential “value” of a sin-
gle dollar invested where it is needed most (i.e., in developing
countries) versus the “value” of a dollar invested in wealthy
countries with existing screening. It is interesting to invert the
incremental cost-effectiveness ratio to gain an insight into the
differences between the most aggressive screening strategy
shown on the graph (far upper right) and the least aggressive
(far lower left). Expressing the incremental benefits relative
to the incremental costs using a “benefit-cost ratio” would
translate to 2.2 weeks of average life expectancy gain per
$50,000 in the US. In contrast, in India, this would translate
to a gain of 5000 years of life expectancy per $50,000.

5. Ongoing challenges

There will always be parameter and model uncertainty in

each of the model-based analyses summarized here. Param-
eter uncertainty concerns the true values of the input param-
eters, whereas model uncertainty involves the way these
parameters are modeled (or synthesized or manipulated to
be appropriate for the model structure). Typically, models
are calibrated to match data on age-specific cancer incidence
and mortality, and, if available, prevalence of HPV and CIN.
A limitation of this approach is that modelers are matching a
cohort simulation to cross-sectional data. There may be sub-

stantial cohort effects that will affect cancer incidence and
mortality, including exposure to HPV (age at sexual debut,
average number of partners), exposure to factors which may
contribute to increased cancer risk once infected with HPV
(pregnancy, smoking, HIV), changes in competing risks (age-
specific mortality from other causes, rates of hysterectomy for
benign disease), changes in factors which affect diagnosis of
cervical cancer (access to medical care, changes in endemic
conditions, which lead to symptoms that mimic early cer-
vical cancer), and changes in stage-specific survival from
cervical cancer (improvements in treatments, reductions in
morbidity and mortality associated with treatment). Ideally,
age–period–cohort models could help address some of these
issues, but the data necessary for construction of these mod-
els are not commonly available, especially in the developing
countries where some of these secular trends may be most
dramatic.

The choice of model structure will continue to be challeng-

ing. Cervical cancer natural history and screening models
have evolved considerably in parallel with a better under-
standing of the role of HPV in cervical carcinogenesis, and
as the policy questions become more complex, this pro-
cess will need to continue. For example, analyses focusing
on HPV-DNA testing as a primary screening test require
additional sophistication in model structure to represent the
detailed age-specific patterns of HPV positivity in women
without cytologic abnormalities, with equivocal and low-
grade abnormalities, and with high-grade disease. To assess
newer screening strategies that diverge based on an indi-
vidual woman’s history, we require first order Monte Carlo
methods (see Chapter 18), which more easily allow the ana-
lyst to incorporate many dimensions of heterogeneity (e.g.,
type-specific HPV, individual-based risk factors such as HIV,
parity, smoking, etc.), to reflect both variability and uncer-
tainty in a more sophisticated manner and to permit the
risk of a single event to depend on a series of past events.
Models used for evaluating cervical cancer control strate-
gies in developing countries must be able to accommodate
more details regarding the operational delivery of screen-
ing and treatment services. Models that include vaccination
strategies will need to either link with, or utilize parame-
ters from, dynamic transmission models (see Chapter 21).
Finally, for analyses that address the critical questions about
how screening test performance might change in the presence
of a type-specific vaccination (see Chapter 20), the mod-
els need to fully represent HPV type-specific heterogeneity.
The price of representing increasing complexity and hetero-
geneity of HPV types in a model of cervical carcinogenesis
is that the number of “unobserved” natural history param-
eters quickly multiplies. Fortunately, epidemiologic data on
age-related prevalence of type-specific HPV, age-related inci-
dence of CIN and invasive cancer, and the distribution of HPV
types within CIN and cancer are increasingly available. These
data, together with formal calibration methods, can theoret-
ically permit the development of a model that both respects
our uncertainty regarding natural history but forces the model

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to be consistent with multiple sources of epidemiologic data

[27]

.

Disclosed potential conflicts of interest

ERM: Consultant (Merck and Co., Inc., Medical Trans-

portation Management, Inc.); Research Grants (Merck and
Co., Inc.)

Acknowledgments

SJG and JJK gratefully acknowledge grant support from

the US National Cancer Institute (grant #R01 CA093435)
and The Bill and Melinda Gates Foundation (grant #30505),
and the valuable contributions of Steven Sweet and Meredith
Holtan of the Harvard School of Public Health, Boston, MA,
for their outstanding technical assistance.

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