SUPPLEMENT ARTICLE
The Theory of Measles Elimination: Implications
for the Design of Elimination Strategies
Nigel J. Gay
Health Protection Agency, Modelling and Economics Unit, Communicable Disease Surveillance Centre, London, United Kingdom
The theory of disease transmission provides a consistent framework within which to design, evaluate, and
monitor measles elimination programs. Elimination of measles requires maintaining the effective reproduction
number R at !1, by achieving and maintaining low levels of susceptibility. The essential features of different
vaccination strategies (e.g., routine versus campaigns, number of doses) can be compared within this framework. Designing an elimination program for a particular population involves setting target levels of susceptibility, establishing the current susceptibility profile, selecting an approach to reduce susceptibility below the
target, and selecting an approach to maintain susceptibility below the target. A key indicator of the sustainability
of an elimination program is the residual level of susceptibility of a cohort after it has completed its scheduled
vaccination opportunities. This can be estimated from vaccination coverage data. The high transmissibility of
measles poses a significant challenge to any attempt to eliminate it.
Measles elimination goals have been adopted in a range
of countries, subregions, and regions adopting a variety
of vaccination strategies. Here I present the theoretical
concepts relevant to measles elimination, such as the
reproduction number and susceptibility threshold; investigate and compare the essential features of routine
and campaign vaccination strategies within this framework; present the stages of designing a measles elimination strategy; and discuss implications for surveillance of measles elimination programs.
BASIC CONCEPTS
Measles is transmitted from person to person. The crucial factor determining the spread of infection is therefore the number of secondary cases caused by each
infectious person.
Basic reproduction number, R0. The basic reproduction number, R0, is a summary measure of the transmissibility of an infection within a population, defined
as the average number of secondary infections pro-
Reprints or correspondence: Nigel J. Gay, Health Protection Agency, Modelling
and Economics Unit, Communicable Disease Surveillance Centre, 61 Colindale
Ave., London NW9 5EQ, United Kingdom ([email protected]).
The Journal of Infectious Diseases 2004; 189(Suppl 1):S27–35
2004 by the Infectious Diseases Society of America. All rights reserved.
0022-1899/2004/18909S1-0005$15.00
duced by a typical infective person in a totally susceptible population. It depends on the characteristics of
the infectious agent (e.g., infectivity and duration of
infectiousness) and of the population (e.g., population
density and social mixing patterns). R0 therefore differs
between infections in the same population but also for
the same infection in different populations. For example, within any given population, the R0 for measles
is greater than the R0 for rubella, and, all else being
equal, the R0 for measles is greater in a dense, urban
population than a sparse, rural population.
Because R0 is defined on the basis of the potential
for transmission in a totally susceptible population, it
does not depend on the level of susceptibility in the
population and is unaffected by vaccination. It represents the maximum transmission potential of the infection—the average number of persons with whom an
infected person makes effective contact during the infectious period.
Effective reproduction number, R. The effective
reproduction number, R, is a summary measure of the
potential for transmission of an infection within a population, defined as the average number of secondary
infections produced by a typical infective person. The
value of R depends on the levels of susceptibility in the
population and on the basic reproduction number R0.
In a completely susceptible population R p R 0.
Theory of Measles Elimination • JID 2004:189 (Suppl 1) • S27
When R is 11, each case produces on average 11 secondary
case, so the number of cases increases from one generation of
cases to the next; when R is !1, the number of cases decreases.
Thus, the value R p 1 is an important threshold [1].
Elimination criterion. If R is maintained constantly at !1,
the number of cases will decrease (on average) with each generation, and all endemic chains of transmission will eventually
die out. Imported cases introduced into the population will
not be able reestablish endemic transmission. Elimination of
indigenous transmission will therefore be achieved.
Susceptibility threshold. To be relevant to vaccination policy decisions, the theoretical concepts of R0 and R must be
applicable to practical questions regarding available data. Perhaps the most important question regards the susceptibility
threshold: What level of susceptibility corresponds to the R p
1 threshold? The simplest case to consider is that of a homogeneously mixing population. Although such simple models ignore the complexities of real populations, they are worthy of
discussion to establish the basic principles, many of which carry
over into more complicated models.
In a homogeneously mixing population, the basic and effective reproduction numbers are related simply by R p R 0 x,
where x is the proportion of the population susceptible to
infection. The threshold at R p 1 defines the critical proportion
susceptible, x ∗ p 1/R 0.
Critical vaccination coverage. Eliminating infection requires maintaining R ! 1 , by keeping the proportion susceptible below the critical value x ∗ p 1/R 0 . Equivalently, the proportion immune must be greater than the critical proportion
immune pc p 1 ⫺ x ∗ p 1 ⫺ 1/R 0. Achieving this level of immunity through a vaccination program administered at birth
will be sufficient to attain elimination. Two important points
are often overlooked. First, the formula assumes that vaccination is given at birth, or as soon as infants become susceptible—if vaccination is delayed until the second or third year
of life, a higher proportion immune will be required [2]. Second, this formula refers to the level of immunity that must be
achieved, not the vaccination coverage—the efficacy of the vaccine must be taken into account when calculating the coverage
required. The duration of protection afforded by successful
vaccination is also important—waning of immunity that enabled persons experiencing secondary vaccine failure to become
significant transmitters of infection would thwart attempts at
elimination.
Epidemic cycle. If measles is endemic in a population, it
occurs in epidemic cycles (figure 1). During the course of an
epidemic cycle, R oscillates around threshold at R p 1, changing constantly as the level of susceptibility fluctuates. An epidemic can begin if R 1 1. After the onset of an epidemic, those
infected acquire immunity, so the number of susceptible persons falls and R begins to decline. When infection has depleted
the pool of susceptible persons sufficiently, R is reduced to !1
and the number of cases in the outbreak declines. At the end
of the outbreak, R begins to increase again because of the
addition of new susceptible persons through birth. When R
exceeds 1, a new epidemic can begin. If a population is sufficiently large, chains of transmission can be sustained throughout the period when R ! 1; otherwise, an epidemic will not
occur until the infection is reintroduced to the population.
Critical community size. The concept of a critical community size for sustaining endemic measles transmission arose
through work in the prevaccination era, studying the persis-
Figure 1. Simple model of measles transmission in a population with 80% routine vaccination coverage (90% efficacy) from year 5. (Two-week
time step: number of cases indicated by bars; number of susceptibles by dots.)
S28 • JID 2004:189 (Suppl 1) • Gay
tence of measles in island and city populations [3, 4]. The issue
is whether chains of transmission could persist through the
post-epidemic period, when R ! 1 , until the susceptible persons
build up to the critical level at which R 1 1, when the next
epidemic can begin. At such low levels of transmission, stochastic (chance) effects become paramount. Consider cases as
occurring in discrete generations. At each generation there is
a finite probability that no secondary infections will be produced and therefore that transmission will die out. This probability depends on the expected number of cases in the next
generation (i.e., on the number of cases in the current generation and the current value of R). In small communities, the
number of cases in each generation becomes so low in the
trough of transmission that the chain almost always breaks at
some point, and transmission fades out before the susceptible
persons have built up again. In contrast, the probability of fadeout is very low in sufficiently large communities, because the
number of cases never becomes critically small. The critical
community size is the size of population needed to sustain
endemic transmission (i.e., to prevent fade-out). For measles
in an unvaccinated population, this is observed to be ∼250,000–
500,000 [3, 4], possibly lower for sparse populations and higher
for dense populations [4]. The critical community size may be
better expressed in terms of the average number of cases per
generation, or equivalently the average input of susceptible persons into the population per generation interval. Routine vaccination (at a level insufficient to achieve elimination) would
increase the community size needed to sustain measles transmission, because it reduces the input of new susceptible persons
into the population.
The concepts of elimination and critical community size
should not be confused. In sufficiently small populations, fadeout can occur after only a short period in which R ! 1. However, if susceptible persons are allowed to reaccumulate and R
is not maintained at !1, widespread transmission may recommence when the infection is reintroduced. This is not elimination. Elimination requires the (indefinite) maintenance of
R ! 1 throughout a population. If this is achieved, by achieving
a sufficiently low proportion of susceptible persons in each
population subgroup, chains of transmission will eventually die
out regardless of the total number of susceptible persons within
the population, because each case will, on average, produce !1
secondary case. Moreover, elimination achieves a stable situation—reintroduction of infection will not lead to widespread
transmission.
Estimating R0. During the course of an epidemic cycle, R oscillates around 1 as the proportion susceptible oscillates around
the threshold. If disease remains endemic, the average proportion susceptible to infection remains at the threshold level,
even after vaccination is introduced (figure 1). Thus, in any
population that is assumed to mix homogeneously in which
measles is endemic, R0 can be estimated directly as the reciprocal of the average proportion susceptible. This provides a
straightforward method for estimating R0 from seroprevalence
data, which can be used after the introduction of vaccination,
even for growing populations.
Various formulas have been derived to relate the average
proportion susceptible before introduction of vaccination to
easily observed parameters such as the average age at infection
in the absence of vaccination, A; the life expectancy, L; and the
average duration of maternal antibody protection, m [5, 6].
The simplest case is for a population with no growth in which
no individuals die before acquiring measles. In this scenario,
the average time for which an individual is susceptible to measles is A–m (being susceptible between ages m and A), out of
a life expectancy L. With no population growth, the average
proportion of the population susceptible is given simply by
x ∗ p (A–m)/L. Note that the relationship R 0 p 1/x ∗ can be
used to express R0 in terms of these parameters; R0 p L/
(A–m) in the above example. This simple formula has been
used to estimate R0 for measles at 14–18 in England and Wales
and at 12.5 in North America [2].
Thus, assuming homogeneous mixing, the critical level of
immunity in England and Wales was calculated as 94% (using
the upper estimate of R 0 p 18 ) or 96% if vaccination was delayed until the second birthday [2]. Such high levels of immunity cannot be achieved with a single dose of a vaccine that
has 90%–95% efficacy.
Heterogeneity. Although homogeneous mixing models illustrate qualitatively the impact of vaccination, many practical
applications demand that some of the heterogeneity of the population is accounted for. In the design of vaccination programs,
most attention has focused on modeling heterogeneity arising
from age-related contact patterns [7–12], but spatial and temporal heterogeneity can also have implications [6, 11]. Such
models divide the population into subgroups and specify the
degree of mixing within and between these subgroups [6]. Difficulties in estimating the contact patterns arise from the absence of information on “who acquired infection from whom”
[6, 9], but further progress has been made by combining information from several infections with similar transmission
routes [13].
Given the different contact rates between the various groups
in a heterogeneously mixing population, the difficulty in calculating R0 and R lies in defining a “typical” infective person
as some suitable average across all subgroups within the population. A mathematically rigorous method for calculating R0
and R from the average number of secondary cases in each
group caused by an infective person in each of the groups (the
“next-generation matrix”) does not yield any simple formulas [14]. In particular, R0 cannot be estimated as the reciprocal
of the average proportion susceptible. However, the rigorous
Theory of Measles Elimination • JID 2004:189 (Suppl 1) • S29
definition does preserve the most important results from homogeneous mixing populations for heterogeneously mixing
populations. Most notably, R ! 1 remains the criterion for elimination. Also, if a proportion x of every population subgroup
is susceptible, then R p R 0 x . Thus, elimination can be achieved
by reducing the proportion susceptible in each population subgroup below 1/R0 (pc p 1 ⫺ 1/R 0 ). However, this is not the most
efficient way of eliminating the disease. There are many different combinations of susceptibility levels in the various subgroups that produce the threshold R p 1. Achieving levels of
susceptibility below 1/R0 in the core groups that contribute
most to transmission allows higher levels of susceptibility elsewhere and consequently more susceptible persons overall [15].
The importance of schools in the transmission of measles in
developed countries was confirmed by a model that incorporated variable contact rates among school-aged children (higher
during school terms than during school holidays) [8], which
reproduced the seasonal pattern of measles within the biannual
epidemic cycle. Incorporating age-dependent contact rates reduced estimates of pc for measles to 84%–92% [7] (from 94%,
using a homogeneous model). However, these early models
focused on primary school children and underestimated the
potential for measles transmission among older children. Refining the contact rates used for these age groups on the basis
of more recent data precludes values of pc !90% [9].
Epidemiology after elimination. After the elimination of
endemic measles transmission from a population, all cases of
measles must be linked to infections imported from outside
the population [16]. As long as R is maintained at !1, importations will not reestablish endemic transmission but may cause
limited secondary spread. The expected distribution of the size
Figure 2.
and duration of such outbreaks depends on R; the larger the
value of R, the larger and longer the outbreaks [16].
IMPLICATIONS FOR DESIGN OF MEASLES
ELIMINATION PROGRAMS
The implications of this theory for elimination strategies are
clear. The first step is to reduce the levels of susceptibility in
the population so that R ! 1; the task thereafter is to ensure
that these low levels of susceptibility are maintained. To design
an elimination program for a particular population following
this general approach requires setting target levels of susceptibility, establishing the current susceptibility profile, selecting
an approach to reduce susceptibility below the target, and selecting an approach to maintain susceptibility below the target.
Setting Susceptibility Targets
Setting target levels of susceptibility first requires Rmax, the maximum permissible value of R, to be selected. Clearly, for elimination, R max ! 1, but the choice of a particular value is a policy
decision that takes into account the safety margin desired, the
degree of secondary spread from imported cases that can be
tolerated, and the resources available—lower values of Rmax provide more security but require a greater vaccination effort. At
the simplest level, all that is then required is an estimate of R0.
For example, if R 0 p 16 and Rmax is chosen to be 0.8, the target
level below which the proportion susceptible in all age groups
and other subgroups must be reduced is 0.8/16 p 5%.
More flexibility can be introduced into susceptibility targets
by balancing higher levels in some age groups against lower
World Health Organization target levels of susceptibility for measles elimination in Europe
S30 • JID 2004:189 (Suppl 1) • Gay
levels in others, to give the same overall R. The effects of agespecific transmission rates can be accounted for in these calculations. For example, the target levels of susceptibility in the
World Health Organization (WHO) strategy for the elimination
of measles from the European region were designed for
R max p 0.7 by use of a heterogeneous mixing model for which
R 0 p 11 (figure 2). A crude calculation suggests a 6.4% susceptibility target for all age groups, but achieving a lower level
(5%) in age groups with the highest transmission rates, namely
secondary school children and young adults, allows higher levels of susceptibility in preschool (15%) and primary school
(10%) children.
Establishing Susceptibility Profile
The susceptibility profile describes the distribution of susceptibility to measles within a population. Most important is the
variation in the proportion susceptible to measles by age, but
other relevant variables include vaccination status and, in some
cases, population subgroup. Three sources of data are useful
in assessing the susceptibility profile: measles case notifications,
vaccination coverage reports, and seroprevalence surveys.
The most direct way to estimate the susceptibility profile is
via a suitably stratified serological survey, interpreting samples
negative for measles antibody as indicating susceptibility to
measles. It is essential to ensure that the assay used is adequately
sensitive and specific, especially in highly vaccinated populations in which many persons protected by vaccination may
have low antibody levels. Use of quantitative assays allows standardization of results between different surveys through panels
of reference serum samples [17] and against international
standards.
The proportion of each birth cohort not protected by vaccination can be calculated from vaccination status—the proportions that have received no dose, 1 dose only, or 2 doses—
and the efficacy of 1 and 2 doses: proportion not protected by
vaccination p proportion unvaccinated + [proportion receiving 1 dose only ⫻ (1 ⫺ efficacy of 1 dose)] + [proportion receiving 2 doses ⫻ (1 ⫺ efficacy of 2 doses)]. Vaccination status
may be measured directly (e.g., in surveys) or inferred from
coverage data. Because this calculation does not attempt to
account for naturally acquired immunity, it is most useful in
cohorts with high vaccine coverage. It will significantly overestimate the proportion susceptible in cohorts with low vaccine
coverage and a high exposure to natural infection.
Case notifications are best used by calculating the age-specific
incidence during the most recent epidemic by means of the
finest possible age stratification. This provides only a qualitative
indication of the relative susceptibility at different ages, because
the attack rate among susceptible persons may be age-dependent—it is often higher in school-aged children than in preschool children. It should also be noted that cases may provide
a better reflection of the susceptibility before the epidemic than
after it.
More complex methods that combine information from several types of data are also available, including susceptible reconstruction methods [18] and dynamic transmission models [19].
Reducing Susceptibility below Targets
Campaigns. Mass vaccination campaigns aim to immunize
a high proportion of the susceptible persons in the population
by achieving a high level of coverage across a wide age range,
often over a short period of time. The age range for a campaign
Figure 3. Simple model of measles transmission in a population with an vaccination campaign in year 5 that immunizes 80% of all susceptible
persons and 80% routine vaccination coverage from year 5.
Theory of Measles Elimination • JID 2004:189 (Suppl 1) • S31
Figure 4. A, Vaccination status in the year 2000 of children in England born during 1990–1998. These cohorts were too young to be vaccinated
in the 1994 national measles vaccination campaign (which targeted 5- to 16-year-olds) and have been vaccinated with measles-mumps-rubella vaccine
according to the routine schedule (at 12–15 months and 4 years). B, Estimated susceptibility in 2000 of children in England born during 1990–1998.
Incidence of measles virus infection in England was very low during 1990–2000, so all immunity is assumed to be vaccine-derived (10% of children
assumed to remain susceptible after 1 dose of vaccine and 1% after 2 doses of vaccine). The second dose (at age 4 years) reduces the susceptibility
of the cohort from 20% to 10% within the WHO European region target for the 5- to 9-year age group. However, the 10% residual susceptibility at
age 5 years is above the 5% target for older age groups, suggesting that this limit will be exceeded as these cohorts age. Targeting of 0-dose children
is needed to reduce susceptibility in these cohorts. Susceptibility in older cohorts targeted by the 1994 campaign, and in adults, is low (!5%).
Figure 5. Estimated proportion of children susceptible to measles in
England in 2000 by district health authority (DHA). Each point represents
1 DHA and shows the proportion susceptible among children born during 1990–1994 and 1995–1997. Contour lines indicate the values of R
associated with the susceptibility levels. There is considerable variation
in vaccination coverage between districts: The 20 districts in which
R 1 0.85 were provided with some extra resources to conduct additional
vaccinations.
can be selected by comparing the susceptibility profile of the
population against the susceptibility targets—including in the
campaign all cohorts in which susceptibility exceeds the targets.
By immunizing a high proportion of the susceptible persons
in the population, successful campaigns reduce R well below
1. This has a dramatic impact on the incidence of measles,
causing chains of transmission to die out rapidly (figure 3).
For example, if R is reduced to 0.5, the number of cases will,
on average, halve with each new generation of cases (every ∼2
weeks). The potential for endemic transmission will not reemerge until the input of new susceptible persons into the
population has restored susceptibility to the R p 1 threshold.
The time taken to do this will depend principally on the number
of susceptible persons immunized by the campaign and the rate
at which new susceptible persons are added [20]. The duration
of impact of campaigns in heterogeneously mixing populations
can be estimated in a similar fashion as the time taken for R
to exceed 1 [19].
Routine programs. Introduction of a routine vaccination
program does not have the same rapid impact on the proportion of the population susceptible to infection as does a vaccination campaign. Rather, programs that vaccinate early in life
reduce the rate at which susceptible persons are added into the
population (figure 1). Protecting some individuals from infection reduces the number of infectious cases, lessening the risk
that a susceptible person will contact an infectious person and
thereby become infected. Both the direct protection of new
cohorts and the reduction in the risk of infection cause the age
distribution of susceptible persons to shift toward older age
groups [18]. However, unless sufficiently high levels of immunity are achieved in the vaccinated cohorts, the infection
will remain endemic and establish a new epidemic cycle oscillating around R p 1 (figure 1). These direct and indirect effects
can be investigated by use of dynamic models of the transmission of infection.
Use of a single dose of measles vaccine cannot achieve a high
enough level of immunity to achieve elimination. A routine 2dose schedule can achieve high levels of immunity (198% efficacy), but it takes many years to feed through all age groups.
Outbreaks often occur in the cohorts just too old to have received 2 doses. Most countries that have achieved elimination through high coverage with a routine 2-dose schedule have
also conducted specially targeted supplementary vaccination of
older age groups who were born before or missed by the 2dose schedule.
Maintaining Susceptibility below Targets
To maintain R at !1 requires a strategy for preventing the reaccumulation of susceptible persons in the population. This entails
achieving high levels of immunity in children too young to be
vaccinated during the campaign and those born after it. Two
alternative approaches are available: a routine 2-dose schedule
or 1 routine dose plus regular follow-up campaigns [21].
Whatever vaccination strategy is adopted, a crucial factor
determining success or failure in the long run is the residual
level of susceptibility of a cohort after it has completed its
scheduled vaccination opportunities. The choice of strategy
should largely be determined by the need to minimize this
residual proportion susceptible. If the residual susceptibility of
each cohort is not reduced below the critical level, the accumulation of susceptible persons will eventually increase R to
11. Vaccination status of each cohort should be assessed once
it has completed its scheduled vaccination opportunities to
enable the proportion susceptible to be calculated directly (cohorts born after a catch-up campaign will have had little exposure to natural infection). As above, the proportion susceptible is most sensitive to the proportion remaining completely
unvaccinated, and it is crucial that the second opportunity
minimizes the number of “0-dose” children.
The other consideration is the age at which this low level of
susceptibility is achieved: the later the age, the more susceptible
persons in the population, the greater the value of R, and the
greater the risk that R will exceed 1. In this respect, it would
be ideal to give the second dose of a 2-dose schedule as soon
as possible after the first, for example, at 15–18 months of age.
However, the age at vaccination may also affect the coverage
Theory of Measles Elimination • JID 2004:189 (Suppl 1) • S33
Figure 6. R for measles in England, 1995–2002, estimated from distribution of outbreak size. R has increased with the reaccumulation of susceptible
children after the 1994 campaign, because of the failure to maintain sufficiently high vaccination coverage. Elimination of measles, achieved between
1995 and 2001 [23], appears unlikely to be sustained.
achieved; many developed countries find that school entry (at
age 4–6 years) provides a good opportunity to achieve high
coverage, particularly among previously unvaccinated children.
In such settings, the advantage of achieving lower residual susceptibility in a cohort must be balanced against the disadvantage of allowing those with failure of first-dose vaccination to
remain susceptible until school entry. Heterogeneity plays a key
role in this decision: Contact rates among school-aged children
are considerably higher than among preschool children. Provided that first-dose coverage is high, a lower value of R may
be achieved by ensuring minimal levels of susceptibility in the
age groups with highest contact rates than by providing an
early opportunity to protect those with failure of first-dose
vaccination. Delaying the second dose further, for example until
secondary school entry at 11–12 years, has no such justification,
as it is unlikely to result in further improvement in coverage
but allows those experiencing vaccination failure to remain
susceptible throughout primary school.
Surveillance
Having selected a strategy for maintaining R at !1, monitoring
its implementation is largely a question of ensuring accurate
and timely vaccination data. To calculate susceptibility of a birth
cohort once it has completed its vaccination opportunities requires that the vaccination status of the cohort is known (particularly the proportion of “0-dose” children) (figure 4), and
not just the coverage at each vaccination opportunity independently. This calculation may be best performed at the local
(e.g., district) level as a key performance indicator for the vacS34 • JID 2004:189 (Suppl 1) • Gay
cination program. When necessary, districts can then implement supplementary measures (e.g., identifying and vaccinating
“0-dose” children) to bring susceptibility below the target level
(figure 5).
Surveillance of measles cases can also be used to monitor
the value of R. After the elimination of endemic measles transmission from a population, all cases of measles must be linked
to infections imported from outside the population [16]. The
expected distribution of the size of outbreaks depends on R;
the larger the value of R, the larger and longer the outbreaks
[16]. Monitoring the proportion of imported cases and the size
and duration of outbreaks enables R to be estimated [16, 22]
(figure 6). A successful elimination program should maintain
R below the target (Rmax).
Obstacles to Elimination
Clearly, the success of measles elimination strategies depends
on the ability to implement them fully in practice. Potential
problems range from the initial difficulty of identifying sufficient resources to the challenge of sustaining high vaccination
coverage after the disappearance of endemic disease.
Measles transmission in groups who refuse vaccination is
emerging as a problem in many developed countries with elimination programs and merits discussion here. Such groups do
not present the potential for sustaining endemic transmission
unless they reach the critical community size. However, little
can be done to prevent large outbreaks when measles is introduced into them. Strictly then, measles is not eliminated from
such groups because R is not maintained at !1. However, they
cannot sustain endemic transmission if they do not reach the
critical community size. What does this mean for the population as a whole? Again, strictly, measles is not eliminated from
the population, but it cannot sustain endemic transmission.
“Elimination of endemic transmission” may be the most appropriate phrase to describe this situation.
What are the implications for a potential global eradication
program [24]? Clearly, if every country achieved true elimination and sustained R at !1 everywhere, then global eradication would be achieved. But what if every population (e.g.,
country, WHO region) reached the state at which it had “eliminated endemic transmission,” but pockets of unvaccinated individuals remained? Could global measles transmission be sustained by transmission between populations? Clearly yes, in
theory, if the unvaccinated groups within different populations
were sufficiently connected and their combined size was sufficiently large. Investigation of the potential for sustained transmission between groups who refuse vaccination is needed.
SUMMARY
The theory of disease transmission provides a consistent framework within which to design, evaluate, and monitor measles
elimination programs. The key is to identify the susceptibility
profile of the population and to plan a vaccination strategy to
reduce and maintain susceptibility below the threshold. Nevertheless, the high transmissibility of measles poses a significant
challenge to any attempt to eliminate it.
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