Observed Reductions in Schistosoma mansoni
Transmission from Large-Scale Administration of
Praziquantel in Uganda: A Mathematical Modelling
Study
Michael D. French1,2*, Thomas S. Churcher2, Manoj Gambhir2, Alan Fenwick1, Joanne P. Webster1,2,
Narcis B. Kabatereine3, Maria-Gloria Basáñez2
1 Schistosomiasis Control Initiative, Imperial College London, London, United Kingdom, 2 Department of Infectious Disease Epidemiology, Imperial College London,
London, United Kingdom, 3 Vector Control Division, Ministry of Health, Kampala, Uganda
Abstract
Background: To date schistosomiasis control programmes based on chemotherapy have largely aimed at controlling
morbidity in treated individuals rather than at suppressing transmission. In this study, a mathematical modelling approach
was used to estimate reductions in the rate of Schistosoma mansoni reinfection following annual mass drug administration
(MDA) with praziquantel in Uganda over four years (2003–2006). In doing this we aim to elucidate the benefits of MDA in
reducing community transmission.
Methods: Age-structured models were fitted to a longitudinal cohort followed up across successive rounds of annual
treatment for four years (Baseline: 2003, Treatment: 2004–2006; n = 1,764). Instead of modelling contamination, infection
and immunity processes separately, these functions were combined in order to estimate a composite force of infection
(FOI), i.e., the rate of parasite acquisition by hosts.
Results: MDA achieved substantial and statistically significant reductions in the FOI following one round of treatment in
areas of low baseline infection intensity, and following two rounds in areas with high and medium intensities. In all areas,
the FOI remained suppressed following a third round of treatment.
Conclusions/Significance: This study represents one of the first attempts to monitor reductions in the FOI within a largescale MDA schistosomiasis morbidity control programme in sub-Saharan Africa. The results indicate that the Schistosomiasis
Control Initiative, as a model for other MDA programmes, is likely exerting a significant ancillary impact on reducing
transmission within the community, and may provide health benefits to those who do not receive treatment. The results
obtained will have implications for evaluating the cost-effectiveness of schistosomiasis control programmes and the design
of monitoring and evaluation approaches in general.
Citation: French MD, Churcher TS, Gambhir M, Fenwick A, Webster JP, et al. (2010) Observed Reductions in Schistosoma mansoni Transmission from Large-Scale
Administration of Praziquantel in Uganda: A Mathematical Modelling Study. PLoS Negl Trop Dis 4(11): e897. doi:10.1371/journal.pntd.0000897
Editor: Alison P. Galvani, Yale University, United States of America
Received March 29, 2010; Accepted October 28, 2010; Published November 23, 2010
Copyright: ß 2010 French et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: MDF, AF, and JPW thank the Bill and Melinda Gates Foundation (www.gatesfoundation.org) for SCI support. TSC and MGB thank the Medical Research
Council (www.mrc.ac.uk) and the European commission (http://ec.europa.eu/). MG acknowledges support from the National Institutes of Health, USA (www.nih.
gov). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: michael.french05@imperial.ac.uk
endemic foci of infection around the waterbodies of Lake Albert,
Lake Victoria, Lake Kyoga and along the Albert Nile (Figure 1).
As there is very limited urinary schistosomiasis (due to S.
haematobium) in Uganda, we focus on S. mansoni infections here.
Morbidity is often caused by eggs rupturing the intestinal wall
leading to blood loss and subsequent anaemia, and the immune
response to eggs that become trapped in organs and tissues,
leading to the development of hepatomegaly, splenomegaly, and
eosinophilia [2].
S. mansoni adult worms reproduce sexually in humans, with eggs
released with faeces into fresh water, where they can hatch, with
free-living miracidia subsequently infecting a suitable freshwater
(Biomphalaria) snail intermediate host, within which asexual
Introduction
In terms of its socioeconomic impact upon the afflicted
populations, schistosomiasis constitutes the world’s most important
parasitic disease after malaria, infecting 207 million people
worldwide, of whom 85% live in Africa [1]. The Schistosomiasis
Control Initiative (SCI) was established in 2002 with the aim of
helping establish sustainable schistosomiasis control programmes
based on large-scale praziquantel (PZQ) administration. Uganda
was the first country where SCI implemented control (and hence
the area upon which this study focuses), capitalizing on the
strength of its national expertise. In Uganda, intestinal schistosomiasis (caused by Schistosoma mansoni) is widespread, with highly
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Reductions in Transmission of Schistosoma mansoni
the programme on the prevalence and intensity of infection, and
prevalence of disease. Parasitological data are recorded as the
mean number of eggs per gram of faeces (epg) calculated from two
Kato-Katz preparations from a stool sample to identify and count
schistosome eggs as an indirect measure of worm burden [13,14].
This approach was used throughout the programme in order to
standardise results.
In this paper, we fit an age-structured mathematical model to
longitudinal parasitological data collected over three rounds of
PZQ treatment from locations with different baseline endemicity
levels. The mathematical model is used to estimate changes in the
FOI caused by MDA within the monitored cohort. These results
are then used to predict the impact of MDA on other sections of
the community which do not form part of the SCI monitoring
programme, such as the general treated population (i.e. across all
age ranges) and the untreated school-age population.
Author Summary
Schistosomiasis is a parasitic disease of enormous public
health importance, infecting over 200 million people
worldwide, of which the large majority live in sub-Saharan
Africa. Control programmes based on the mass treatment
of individuals in infected areas with the drug praziquantel
have been shown to be successful in reducing the parasite
burden and likelihood of developing morbidity in those
individuals who receive treatment. Using data from an
ongoing intestinal schistosomiasis control programme in
Uganda and through the application of a mathematical
model, we show that an additional benefit of mass
treatment is a decrease in parasite acquisition, via a
reduction in the number of transmission stages in the
environment. This leads to a lower rate of infection and
reinfection of individuals in those areas. We show that this
result is valid in areas of differing average infection
intensity. The importance of this finding is that this will
benefit untreated as well as treated individuals, and will
allow a fuller estimation of the benefits of schistosomiasis
control programmes.
Methods
Age-Profiles of Infection
Schistosome infections tend to display a distinctive age-infection
profile, with prevalence and intensity rising sharply in young
children, peaking in adolescents and young adults (15–20 years),
and declining in older age groups [15]. This relationship is thought
to be caused by behavioural practices (age-specific changes in
water contact and hygiene), and/or in combination with the
gradual development of acquired protective immunity ([16] for
urinary schistosomiasis; [17] for intestinal schistosomiasis). For this
reason, and because of logistic advantages and the demography of
populations, school-age children are often targeted for MDA in
control programmes. Fitting models to this characteristic ageintensity profile at baseline is important to ensure that the model
captures the relevant epidemiological characteristics at endemic
equilibrium, prior to implementation of treatment.
The majority of mathematical models of schistosomiasis
epidemiology and control have been fitted to baseline (pretreatment) data only, with projections then being made of the
likely impact of control interventions [18,19,20,21]. These
projections should be treated with caution as models fitted to
baseline data may accurately reproduce pre-treatment patterns but
can fail to fully capture post-treatment population dynamics of the
parasite [22], (though see [23]). Part of the reason for this is the
lack of data available to parameterise such longitudinal models.
Due to the extensive size and longitudinal nature of the SCI
cohorts, we have been able to fit the model simultaneously to pre(baseline) and post- (three subsequent years) treatment data on
infection and reinfection collected in areas differing in baseline
infection intensity. Fitting to multiple years concurrently is
expected to provide a more robust picture of the effects of
treatment on parasite populations and help to measure any
reductions in environmental transmission with multiple treatment
rounds.
reproduction occurs. Cercariae are then released by the snail back
into water, which complete the life-cycle by infecting humans who
come into contact with infested water. The infection in the
(human) definitive host can be treated effectively with PZQ, a safe,
affordable, and efficacious drug which kills the adult worms and
therefore reduces egg counts. Although effective at clearing worm
infections (with a cure rate efficacy of 50–80% and an egg
reduction rate of 95% [3,4], reinfection will occur following
treatment (unless this is provided regularly for prolonged periods),
and so, schistosomiasis control programmes based on chemotherapy have been aimed primarily at controlling morbidity rather
than at suppressing transmission.
Given this reinfection and the absence of direct multiplication
within the human host, the severity of infection (and hence of
morbidity) is likely to reflect the cumulative exposure of an
individual to infection over a period of years [5], in addition to the
operation of individual host immune responses and concomitant
immunity via already-established worms. The rationale of control
programmes is that by reducing worm burdens in humans, and
particularly children (who are the most likely to be heavily
infected), the more serious sequelae of infection (organomegaly
and fibrosis) are less likely to develop, and are more easily reversed
if they do develop [6].
There are many examples of significant success in controlling
infection intensity and morbidity in schistosomiasis control
programmes using a mass drug administration (MDA) approach
[7,8,9,10]. What has not yet been quantified is the benefit of largescale MDA to the wider community, including to those who are
untreated, via reductions in environmental transmission. Such
reductions would manifest as a decreased force of infection (FOI),
the rate at which new incoming worms establish in the human host
population. By estimating any change in the FOI under the
chemotherapeutic pressure of such large-scale MDA we aim to
assess the collateral impact of the programme on the untreated, as
well as treated, sections of the population. Any reductions in the
FOI observed would likely lead to lower infection intensities and a
lower likelihood of developing subsequent morbidity.
The SCI’s extensive monitoring and evaluation (M&E)
framework is detailed elsewhere [7,11,12]. Briefly, in East Africa,
school-age and community cohorts are monitored prior to each
annual round of chemotherapy in order to quantify the impact of
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Datasets
The cohorts were assembled from the SCI’s M&E component
of the Ugandan national schistosomiasis control programme,
which commenced large-scale treatment with PZQ in 2003, and
re-treated host populations at yearly intervals for 3 years (follow-up
year 1 (F1), 2004; follow-up year 2 (F2), 2005; and follow-up year 3
(F3), 2006). A longitudinal cohort of school-age children who were
positively identified and presented at each of the 4 treatment
occasions (using unique identification codes) was constructed. This
cohort consisted of 1,764 individuals (49.6% female), aged
between 6 and 15 years. Additionally, a cross-sectional cohort of
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Figure 1. Baseline schistosomiasis prevalence in Uganda. Map of Uganda showing results from baseline prevalence mapping of intestinal
schistosomiasis in the country. The three main areas of schistosomiasis transmission are situated along the shores of Lake Victoria, Lake Albert, and
Albert Nile. Monitoring and evaluation (M&E) areas were chosen using a statistical sampling framework to provide a representative sample of the whole
treated area described in [31]. The three levels of Schistosoma mansoni endemicity at baseline are represented by closed circles: high ($400 epg, violet);
medium (100–399 epg, purple), and low (1–99 epg, pale pink) transmission. Figure reproduced with permission from Zhang et al. (2007) [31].
doi:10.1371/journal.pntd.0000897.g001
In order to explore the influence of the level of initial endemicity
on model outputs, reductions in the FOI, and possible future
treatment strategies, the model described below (see Current
Mathematical Model) was fitted separately for areas where the
average intensity of infection recorded at baseline (as the
arithmetic mean epg across all hosts in the population) fell within
the high, medium, or low categories proposed by the World
Health Organization, i.e., heavy infection: $400 epg; moderate
infection: 100–399 epg; light infection: 1–99 epg [24]. These
categories were chosen as they are thought to relate to the
children and adults (3,387 individuals) treated at baseline
(composed of 2,538 children #15 years of age (45.5% female)
and 849 adults (46.8% female)) was constructed in order to provide
age-specific infection profiles. The SCI treatment approach is to
target (enrolled and non-enrolled) school-age children in all areas
where schistosomiasis is endemic. In addition, where infection
levels are high (as indicated by a prevalence of over 50% in schoolage children), treatment of adults in the community is also carried
out [11,24]). Thus the overall treatment coverage in an area will
vary depending on that area’s underlying level of endemicity.
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likelihood of individuals developing morbidity [25]. Also, as the
relationship between overdispersion in the distribution of egg
counts per host and mean infection intensity differed sufficiently
between areas, it was deemed that the model warranted separate
fits (see Supplementary Information Protocol S1 and Figure S1).
The sizes and characteristics of the datasets for the longitudinally followed and cross-sectional cohorts in each of the three
epidemiological settings are given in Table 1.
Arithmetic means of infection intensity were used as measures of
central tendency [26,27] in order to compare the means of agegroups and to provide agreement with the model output. Ninety
five percent confidence intervals (95%CI) around the observed
means were calculated via the normal approximation for large
sample sizes [28]. Point estimates of prevalence of infection and
categories of infection (as described above) were also calculated
and the normal approximation to the binomial distribution was
used to estimate their 95% CI given the large sample sizes
available [28]. When preparing age-intensity profiles, age ranges
were chosen to ensure a minimum of 20 individuals in each agegroup. Given these relatively small sample sizes, instead of
assuming a certain distribution of data, 95%CI were derived
from 100,000 bootstrap re-sampling of the data with replacement
[29].
Statistical comparison of means was performed via normal
distribution z-tests for large samples (see Table 1). Prevalence
values were compared by z-tests on the difference between two
proportions [28]. The proportional reduction over treatments of
infection prevalence and intensity was estimated as the absolute
value of the ratio of the difference between the final and initial
values to the initial value, expressed as a percent.
from the rate at which the host population is infected by other
parasitic stages, such as by cercariae from the environment.
In order to measure any reductions in parasite establishment
caused by the control intervention, we estimated the underlying
FOI prior to treatment and following successive rounds of PZQ.
One approach to measuring this reduction in infection would be to
use parasitological information from previously untreated individuals entering the cohort each year (aged 6 yr in our case) as a
proxy for the wider untreated population. Annual cross-sectional
studies would then provide information on secular changes in
infection markers, as done in previous studies [31]. This method
estimates the reduction in the FOI over the lifetime of the 6-year
old child. Though useful, this approach cannot be used to estimate
the changes in the FOI after each round of treatment (a potentially
more useful measurement due to its immediacy) since the results
would be heavily influenced by assumptions regarding the amount
of exposure to infective stages by infants and very young children.
We have very little information about these children prior to their
entry into the cohort. Previously, it has been assumed that very
young children are not exposed and contribute little to
contamination [32,33]. However more recent work has reported
higher infection prevalence levels than previously thought in very
young children [34,35]. Instead, we use a method of estimating the
mean change in the FOI caused by each round of treatment by
fitting the mathematical model to the rate of parasite reinfection
observed in the longitudinal cohort. Parasite intensity estimates
were made prior to treatment each year, so the change in the FOI
(expressed as a ratio of the FOI at baseline) is calculated as an
average of the rising value across the previous year. The
reductions in the FOI seen after each round were assumed to be
equal across ages, as studies have shown that the infection profile
generally returns to the same pattern following reinfection [36].
Force of Infection (FOI)
EpiSchisto
The FOI for macroparasitic infections is defined as the per capita
rate at which a host acquires new infections [30]. This can be
interpreted in a number of different ways according to which stage
of the parasites’ life-cycle is of interest. The number of adult
schistosomes within a host can rarely be measured directly, so
parasitological surveys typically rely on faecal egg counts as a
proxy for parasite intensity. Therefore routinely used diagnostic
tools cannot identify newly established parasites until they reach
patency and reproduce successfully. For the purposes of this paper
the FOI is defined as the rate at which new incoming worms
establish into adult parasites and reach patency (initiate detectable
egg production) in the human host population. This may differ
EpiSchisto [18,37] is a deterministic model of schistosomiasis
transmission based on partial differential equations which describe
the rate of change in mean (adult) worm burden and immunity of
the human hosts with respect to human host age and time.
EpiSchisto has previously been fitted to baseline data and used to
project the future course of control programmes in Tanzania and
Ghana with mixed success [18,19,20]. A number of processes
within EpiSchisto are very difficult to quantify separately and
accurately. These include the contamination of the environment
by the host population and the actions of host immunity, each of
which we discuss in more detail in the next two sections. In past
modelling studies, a range of plausible parameters have been used,
Descriptive Statistics
Table 1. Cohort sample sizes.
Intensity area (categorised by mean epg at baseline)
Baseline Total (Longitudinal; Cross-Sectional)
F1
F2
F3
(2003)
(2004)
(2005)
(2006)
High ($400)
1,210 (428; 782)
404
435
262
Medium (100–399)
1,613 (404; 1,209)
403
413
235
Low (1–99)
2,305 (909; 1,396)
851
916
600
Sample sizes for the baseline longitudinal and cross-sectional cohorts followed up across all four years in each of three endemic areas for Schistosoma mansoni in
Uganda.
NOTE: Areas are classified according to their baseline intensity of infection (measured as the mean number of eggs per gram of faeces, epg, from all individuals sampled
in that area). Numbers vary between years in the longitudinal cohort because some individuals presented on the day of treatment but did not provide faecal samples;
individuals were included in the study from follow-up years as long as they were administered all 4 rounds of treatment. F1 = follow-up year 1, F2 = follow-up year 2,
F3 = follow-up year 3.
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the relative to baseline ratio of the average FOI after each round of
treatment, with subscript P indicating the number of rounds of
PZQ treatments the population has received, and the function t(a)
describes the (dimensionless) age-specific contact function normalized over the total host population which depends on two shape
parameters (which together determine its convexity) (see Supplementary Protocol S2, equations S1 and S2). Thus, f0 = 1 at
baseline, and f1 , f2 , and f3 indicate the ratio of the FOI at followup years (F1), (F2), and (F3) relative to that at baseline,
respectively. (A value of fP lower than 1 indicates a reduction in
the FOI from baseline, and we consider a statistically significant
reduction to be indicated where the entire range of the confidence
interval lies below 1.) L(a) denotes the yearly average number of
(egg-producing) worms acquired per person of age a. As such, this
expression will comprise the product of the contact rate with
infective stages, the probability of infection upon contact, and the
average population of cercariae in the environment. It is assumed
that treatment instantaneously reduces adult worm burden by
95% in all hosts given PZQ (the egg reduction rate [3,4], see next
section). In the longitudinal cohorts, therapeutic coverage is, by
default, 100% as only those known to have received all four
treatment rounds were included. A full list of model parameters is
given in Supplementary Table S1.
and although they may not influence the fitting of equilibrium
scenarios they will have a strong impact on post-control dynamics.
Contamination of the Environment
EpiSchisto assumes that the relative contribution of each age
group to the contamination of the environment is equal to its
relative exposure to infective stages. There is very little evidence
supporting this assumption due to the difficulty in measuring an
individual host’s contribution to transmission, which is likely to
vary substantially according to local sanitation practices and
environmental conditions. Overestimating the contribution to
transmission of highly infected age groups will substantially
overestimate the community benefits of chemotherapy, particularly of those programmes which target heavily infected age
groups. Therefore the contamination function is not modelled
explicitly here and we use the approach outlined below.
Modelling Parasite Establishment
In EpiSchisto [37] and in previous modelling work [21,38], the
rates of infection and immunity have been modelled explicitly and
separately with the rate of infection declining exponentially with
acquired immunity according to the strength of such immunity.
However, although it is widely accepted that there is some form of
human acquired immunity to schistosome infections [15,16,17,39],
its mode of action, against which parasite stages it operates, how it is
elicited, its strength, efficacy and duration in vivo, and whether
acquired immunity is the chief explanation for the relative
insusceptibility of adults, are all still incompletely understood
[39,40,41]. Thus, there seems to be little justification for including
an explicit immunity function in the model, given the likely
correlation between parameters. For instance, there will be
significant correlation between the length of immunological
memory (i.e. the rate at which immunity is lost over time) and
any changes in the FOI following chemotherapy.
Fitting Approach and Sensitivity Analysis
The number of eggs per gram of faeces (epg) is thought in S.
mansoni to be a reliable, indirect measure of the intensity of
infection, particularly at the commencement of an intervention
(though see [42] which suggests that egg production may be
density dependent). Assuming that each worm produces on
average 5.26 eggs per gram of faeces [18] allows the adult worm
burden generated by the mathematical model in equation (1) to be
converted to the epg count and fitted to the longitudinal data
collected by the SCI.
The cross-sectional cohort at baseline consisted of both children
and adults in order to provide the profile of age-related exposure.
The age-stratified mean-based model was fitted simultaneously to
the longitudinal cohort and cross-sectional baseline data using
maximum likelihood estimation [43]. The method allows the
model to be fitted to individual host data taking into account the
high degree of parasite overdispersion observed (empirically
described by the negative binomial distribution, see Protocol S1).
This provides more robust estimates than those that can be
achieved by fitting to aggregate measurements of infection
intensity. The model was used to estimate concurrently the
baseline FOI, lB , the two shape parameters of the contact function
(b and c), and the change in the annual FOI after each round of
chemotherapy (f1 , f2 and f3 ) relative to that at baseline. In
addition to these six parameters being fitted, a concurrent
sensitivity analysis was carried out on fixed values of two further
biologically important parameters with uncertainty around their
values, namely, the per capita worm death rate (mM ), and the
efficacy of PZQ (e) in terms of egg reduction rate expressed as a
percentage). The fixed values used for the sensitivity analysis were
taken from the literature and are presented in Supplementary
Table S1.
The 6-dimensional parameter space was explored using the
Latin Hypercube sampling method [44,45]. As part of this fitting
approach, the infection intensity observations of individuals were
compared to the model-derived, age-specific mean intensity of
infection. Ninety five percent confidence intervals around each of
the model parameters were calculated using the Fisher Information Matrix [46] for a range of plausible adult worm mortality
rates (from 2 to 10 years) and PZQ egg reduction efficacies (from
Current Mathematical Model
The approach taken in this paper is to model phenomenologically a composite FOI that incorporates together the rates of
contamination, of parasite acquisition and the effects of any
immunologically-mediated and/or host age-dependent processes
that may modulate such a rate. This allows the number of new
infections to be decoupled from the number of adult parasites,
allowing the FOI to be estimated directly from data as opposed to
being generated through the underlying assumptions of EpiSchisto
(such as the highly uncertain contamination function). Given that
our aim is to provide policy-orientated outputs rather than a
detailed description of the underlying mechanisms of schistosomiasis transmission and infection, this should provide a more robust
approach.
The rate of change in adult worm burden (M) with respect to
host age (a) and time (t) can be written as the following
immigration-death model,
LM(a,t) LM(a,t)
z
~L(a){mM M(a,t),
Lt
La
ð1Þ
where L(a) is the net FOI at age a, and mM is the per worm death
rate of established adult worms.
In turn, L(a) is given by Equation 2,
L(a)~lB fP t(a)
ð2Þ
where lB is the average underlying baseline FOI per person, fP is
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90% to 99%). Ninety five percent confidence intervals around
model outputs were estimated by re-running the model and
randomly selecting parameters from within their 95%CI bounds.
Runs which generated likelihood values not statistically significantly different from the best fit run (tested using a x2 distribution
with the appropriate degrees of freedom) were used to construct
95%CI around model outputs [47]. The maxima and minima
mean egg output at each timepoint from these included runs
constituted the upper and lower confidence intervals respectively
for the model output.
The longitudinal cohort consisted of individuals who were
observed to have received all treatment rounds. As there was no
replenishment of the youngest age classes it would be expected that
without treatment there would be an increase in the intensity of
infection in the cohort over the length of the study as the cohort
ages. This is due purely to the increase in exposure typically
experienced by children between the ages of approximately 5–15
years [23]. The fitted mathematical model takes this into account
by allowing the age of the cohort to increase over time; not
controlling for this would have led to underestimating the
reductions in the FOI.
Results
Reductions in Intensity and Prevalence of Infection
Three rounds of treatment significantly reduced average
infection intensity in all areas. In areas that were classified as of
high endemicity at baseline, mean epg values fell by 84% (from
766 (95%CI: 704–828) epg at baseline to 121 (95%CI: 69–172)
epg at follow-up year 3, P,0.001). In moderate endemicity areas,
infection intensity fell by 75% (from 231 (95%CI: 209–257) to 58
(95%CI: 29–87) epg, P,0.001). In low endemicity areas there was
an 87% decrease (from 33 (95%CI: 27–39) to 4.4 (95%CI: 1.6–
7.1) epg, P,0.001). Significant reductions in infection prevalence
were also observed, with decreases of 48% (from 84% (95%CI:
82–86) at baseline to 44% (95%CI: 38–50) at follow-up year 3,
P,0.001); 55% (from 57% (95%CI: 55–59) to 25% (95%CI: 20–
31), P,0.001), and 79% (from 21% (95%CI: 19–23) to 4.5%
(95%CI: 2.8–6.2) P,0.001) in, respectively, high, moderate and
low intensity areas.
Age-Intensity Profiles of Infection at Baseline
The model successfully describes the baseline age-intensity
profiles observed in the data from the three different endemicity
levels, and replicates the classic convex relationship often seen in
schistosome infections (Figure 2).
Treatment Effects in the Broader Population
The model was used to investigate how temporal changes in
the FOI caused by MDA may influence different sections of the
population which are not part of the longitudinal cohort. It is
assumed that any reduction in the FOI over successive rounds of
chemotherapy is due to a reduction in the number of infective
stages within the environment and not through secular changes
in host immunity (which would mainly affect the treated
population). The population age structure was estimated from
Ugandan census data [48], assuming a constant human death
rate with age (Figure S2). Estimates of the number of hosts in
each of the different WHO intensity categories were generated
using the relationship between infection prevalence and
intensity that permitted estimation of the aggregation parameter of the negative binomial distribution as described in
Protocol S1.
Treatment Effects in the Treated Longitudinal Cohort
The dynamics of infection intensity after the introduction of
successive rounds of chemotherapy in the longitudinal cohort are
shown in Figure 3.
Table 2 presents the estimated parameter values for the baseline
FOI and for the relative to baseline reductions in the FOI that best
fitted the data. In low intensity areas, where treatment is aimed
only at school-age children, a substantial and statistically
significant reduction (of about 76% from baseline) in the FOI
was effected by a single round of MDA (f1 = 0.24). In moderate
intensity areas (where there is a mixture of only school-age
children treatment, and school-based and community treatment
depending on an area’s prevalence of infection), one treatment
Figure 2. Age-profiles of Schistosoma mansoni infection intensity at baseline. Intensity is measured in eggs per gram of faeces (epg) at
baseline as observed in the cross-sectional cohorts (blue markers) and fitted by the model (red line): A) high intensity areas; B) medium intensity
areas; C) low intensity areas, as defined in Figure 1. Error bars are the 95% confidence intervals of the data calculated by 100,000 bootstrapping
repetitions with replacement. Dotted lines are the 95% confidence intervals around model outputs. Age-groupings were chosen to ensure a
minimum of 20 observations per category. Note the differences in the y-axis scales between the three endemicity levels.
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Figure 3. Impact of treatment on average infection intensity. The temporal dynamics of S. mansoni infection intensity (epg) in the
longitudinal cohort in three areas of varying endemicity in Uganda after introduction of yearly treatment with praziquantel: A) high intensity areas; B)
medium intensity areas; C) low intensity areas, as defined in Figure 1. The model was fitted to the baseline (BL) longitudinal and cross-sectional cohort
data collected in 2003, and to the longitudinal cohorts for follow up years 1 (F1, 2004), 2 (F2, 2005), and 3 (F3, 2006) as described in the main text,
Protocol S2, and Tables 1 and S1. Dotted lines indicate the 95% confidence intervals around the model outputs. Note the differences in the y-axis
scales between the three endemicity levels.
doi:10.1371/journal.pntd.0000897.g003
the percentage of individuals harbouring heavy intensity infections
fell from 17% (95%CI: 13–22%) to 3% (95%CI: 0–15%) (a
reduction of 83%, P,0.001). In areas of low intensity at baseline
(,100 epg), the prevalence of those harbouring heavy infection fell
from 1.91% (95%CI: 0–6.0%) to 0.33% (95%CI: 0–8.3%); a fall of
82.5% (P = 0.01). Figure 4 shows the reductions in the frequency of
infection category in the different areas. The left-hand column
demonstrates the fit of the model to observed frequencies of
infection category in the longitudinal cohort. Parameter values
obtained from fitting the model were then used to make predictions
regarding the effect of MDA on the untreated human population.
Using Uganda-specific demography, the impact of treatment on
those school-age children (aged 6–15 yr) who did not receive
treatment is shown in the right-hand column. Any changes here are
caused purely by reductions in FOI.
round resulted in no change in FOI (f1 = 1.04), two treatment
rounds achieved approximately a 66% reduction in FOI
(f2 = 0.34), with a 54% reduction achieved after three rounds
(f3 = 0.46), although the latter did not reach statistical significance
(95% CI included 1). In high intensity areas (where both schoolage children and the whole community receive MDA), the first
treatment round only reduced the FOI by 22% from baseline
(f1 = 0.78) and this did not reach statistical significance. Subsequent reductions were of the order of 63% for the second
(f2 = 0.37) and third rounds of treatment (f3 = 0.37), both of which
were statistically significant.
Reductions in Heavy Infection in the Cohort and Wider
Population
A reduction in the numbers of people harbouring heavy infection
(and who will thus be most likely to suffer from current and future
morbidity) is clearly paramount from a morbidity control
programme perspective. In high intensity areas the prevalence of
heavy infection (proportion of individuals excreting $400 epg) fell
from 47% (95%CI: 43–51) at baseline to 8% (95%CI: 0–19) after 3
rounds of treatment (a reduction of 83%, P,0.001). Similarly in
areas with an average moderate intensity at baseline (100–399 epg),
Reduction in Worm Acquisition
In areas of high intensity, the worm acquisition rate in schoolaged children fell from 53.8 worms per person per year at baseline,
to 19.8 following 3 rounds of treatment. Similarly in moderate
intensity areas, the per capita worm acquisition rate falls from 15.9
to 7.3 per year, and from 2.7 to 0.5 per year in low intensity areas.
Table 2. Best fitting parameter values.
Parameter
Description
High
Medium
Low
lB
Baseline FOI
30.0 (10.2, 57.7)
10.0 (3.8, 20.6)
1.7 (0.3, 6.5)
f1
The proportion of FOI relative to baseline after 1 PZQ round
0.78 (0.46, 1.50)
1.04 (0.49, 2.00)
0.24 (0, 0.61)
f2
The proportion of FOI relative to baseline after 2 PZQ rounds
0.37 (0.22, 0.63)
0.34 (0.13, 0.74)
0.32 (0.06,
0.64)
f3
The proportion of FOI relative to baseline after 3 PZQ rounds
0.37 (0.19, 0.86)
0.46 (0.17, 1.06)
0.20 (0.04,
0.43)
These values are estimated separately for areas of High, Medium, and Low average infection intensity at baseline. Parameter lB is the force of infection at baseline
(average number of incoming worms establishing and egg-shedding per person per year); f1 is the FOI relative to baseline following 1 round of PZQ treatment; f2 is the
FOI relative to baseline following 2 rounds of treatment; f3 is the FOI relative to baseline following 3 rounds of treatment. Thus any figures below 1 indicate a reduction
in the FOI. Figures in brackets are 95% CI calculated using the Fisher Information Matrix.
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Figure 4. Impact of treatment on categories of infection intensity in treated and untreated populations. This shows the change in the
proportion of people within each infection intensity category following praziquantel treatment. The left-hand column shows the observed figures
from the baseline longitudinal and cross-sectional cohorts (data points and error bars representing 95% confidence intervals derived from 100,000
bootstrap repetitions with replacement) compared to the model-derived values (shaded areas). The right-hand column shows the predicted
reduction in categories of infection intensity in those school-age children who do not receive treatment, using Uganda-specific demographic
structure. Thus, any reduction in the prevalence of heavy infection in the latter will be due to changes in the FOI. Red = heavy infection ($400 epg);
dark orange = moderate infection (100–399 epg); light orange = light infection (1–99 epg), pale yellow = uninfected (0 epg). The upper, middle, and
bottom rows refer, respectively, to areas of high, medium, and low intensity at baseline, as defined in Figure 1. The years correspond to: 2002–2003:
baseline; 2004: follow up year 1; 2005: follow up year 2; 2006: follow up year 3.
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Figure 5. Model outputs for 6yr olds versus observed data. The comparison between the model temporal dynamics for 6-yr olds (solid lines)
and the observed infection intensities of untreated 6-yr olds as they enter the cohort each year (data points): A) high intensity areas; B) medium
intensity areas; C) low intensity areas, as defined in Figure 1. Dotted lines are 95% confidence intervals around the model outputs. Error bars are 95%
confidence intervals on the data, derived from 100,000 bootstrap repetitions with replacement. Note the differences in the y-axis scales between the
three endemicity levels. Years are as in Figure 4.
doi:10.1371/journal.pntd.0000897.g005
change in frequency of heavy and moderate infection categories
(light and non-infected are omitted for clarity).
Use of 6-Year-Olds to Measure Reductions in the FOI
Figures 5 and 6 compare with model predictions and for
untreated 6-year olds, the observed parasite load and the
percentage of children within each intensity category, respectively.
There is a statistically significant reduction in infection intensity
(P,0.001) in the 6-year olds between baseline and follow-up year
2 (F2) in areas which were classified as of high intensity at baseline,
and non-significant declines for moderate (P = 0.324) and low
intensity areas (P = 0.142). Conversely, the intensity of infection in
6-year old children is higher at F3 than at F2 in both the high
(P = 0.051) and low (P = 0.093) intensity schools. Such a result may
be interpreted as a reduction in population MDA coverage in the
last round of treatment. However, our analysis indicates that this
was not reflected in the rate of parasite reinfection in older age
groups (Table 2). In high intensity areas the observed data and
predicted outcomes match relatively well though in medium and
low intensity areas the model over- and underestimates parasite
intensity respectively. We derive a reasonable fit to the data for the
Discussion
The impact of many helminth control programmes is often
underestimated if reductions in FOI are not calculated. This issue
has been raised by Miguel and Kremer [49] who noted that
following a schistosomiasis control programme in Kenya, the
intensity of infection decreased in the treated populations and also,
crucially, in a nearby untreated population. The study presented
here demonstrates that, as well as reducing the intensity of
infection, MDA has a substantial impact on reducing the rate of
parasite establishment in the human host population in some
areas, even after one treatment round (and without reaching
universal coverage). Although the magnitude of the reduction in
the FOI varied in the three endemicity levels investigated, there
were significant reductions in all areas. Quantifying these
Figure 6. Categories of infection intensity in untreated 6yr olds. The comparison between model outputs (dashed lines) and observed values
(solid lines) with respect to the frequency of infection intensity categories in previously untreated 6-yr olds entering the cohort each year: A) high
intensity areas; B) medium intensity areas; C) low intensity areas, as defined in Figure 1. BL, F1, F2 and F3 as in Figure 3. Red lines indicate heavy
intensity of infection ($400 epg), and blue lines indicate moderate intensity of infection (100–399 epg). Note the differences in the y-axis scales
between the three endemicity levels.
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Reductions in Transmission of Schistosoma mansoni
of high intensity and no reduction in medium intensity areas
following the first round of treatment. Whether this is due to low
coverage of the wider MDA programme in the region in the first
year is difficult to ascertain given the well documented difficulties
of accurately measuring actual population coverage in these
programmes [53]. Multiple rounds of treatment could be required
to reduce environmental contamination of the parasite in medium
and high intensity areas. Transmission may be more resilient in
these areas, and this may be caused by a relaxation in densitydependent processes acting on the parasite infra-populations
(within-definitive host populations) following a treatment that kills
adult worms and hence reduces parasite density. Such processes
have been documented affecting the rate of parasite establishment
in helminths (for onchocerciasis see [54]; for schistosomes [55,56],
with the latter exploring the relationship between transmission and
virulence, which may be related to density dependence). The
differences observed in the relative FOI reductions between areas
of different endemicities may also be related to secular changes in
environmental transmission in these areas, such as the extent of
suitable water-contact sites, and/or the distribution of the snail
intermediate host. It should be remembered that in all areas,
without further sustained intervention, the reductions in the FOI
will only be transitory and will return towards pre-treatment levels.
The results presented here indicate that the SCI programme is
achieving significant reductions in S. mansoni infection intensity in
treated individuals in all areas, and also in untreated individuals in
high intensity areas in Uganda. The consecutive reductions in the
proportion of those heavily infected in the population, principally
in areas of high baseline endemicity are particularly striking,
especially as this subset of individuals is thought to be the most
likely to develop schistosomiasis-associated morbidity later in life
[4]. Whether this constitutes an ‘important’ reduction in infection
intensity is an interesting question. Clearly, much still remains to
be ascertained as to the precise relationship between infection
intensity and host morbidity. However it is clear that high
infection intensities, particularly in childhood, are associated with
increased subsequent chronic morbidity [2,57,58]. Therefore it is
logical to predict that reducing infection intensities from ‘heavy’ to
‘medium’ as classified by the WHO represents a meaningful
reduction (see Figure 4).
By extension, the importance of reducing the FOI is also
demonstrated in Figure 4 (right hand column particularly). Here
we can observe a reduction in the proportion of untreated
individuals harbouring heavy intensities of infection. It may be
expected that this would also result in a reduction of the morbidity
in those individuals in future years.
Traditionally, MDA is viewed as a short- to medium-term
solution to controlling schistosomiasis morbidity, whilst aiming for
longer-term interventions such as improved sanitation and
increased access to clean water to reduce transmission. Given
the need to optimize interventions in resource-constrained settings,
designing the most efficient and cost-effective control programmes
is crucial. Programmatic costs can be lowered by reducing MDA
frequency or through a shift towards targeted treatment. In low
intensity areas treatment targeted at school-age children appears
to have reduced the FOI substantially, justifying this approach.
However, further studies are required to determine whether
targeted treatment can reduce the FOI in medium to high
transmission intensity areas (since a combination of school and
community treatment were used in these regions). One possible
approach could be to switch to targeted treatment after a number
of rounds of population-wide MDA have reduced the infectivity of
the environment. However, any decision to reduce the populationwide coverage or to introduce intermittent ‘‘treatment holidays’’
reductions is important from a programmatic point of view, and
because these results can be used to project the dynamics of
infection in the general population.
For the purposes of this paper the FOI was defined as the rate of
establishment of patent infections. Other interpretations of the FOI
are possible, such as the rate of cercarial acquisition by humans
(leading or not to successful parasite establishment). However the
current definition can be regarded as the most closely linked to the
likelihood of developing morbidity as disease sequelae are related
to the production of schistosome eggs and the host’s corresponding
immune response, with the production of eggs proportionally
related (linearly or otherwise) to the adult worm burden
[18,30,42].
Our current lack of understanding as to how host immunity
influences the rate of host reinfection suggests that the changes in
the FOI over time need to be interpreted carefully. The reduction
in the rate of parasite reinfection following chemotherapy could be
explained either through a decrease in environmental transmission
or a decrease in the treated host population’s susceptibility to
reinfection. PZQ treatment releases somatic parasite antigens (not
otherwise exposed to the host’s immune system) which may elicit
protective responses that facilitate resistance to reinfection
[50,51,52]. However, it is far from clear how much this
immunological response may influence the rate of S. mansoni
establishment, development, or fecundity. The significant reduction in the intensity of infection in the untreated 6-year olds
between Baseline and Follow-up Year 2 in high intensity areas
provides evidence that there is possibly a true decrease in the
number of infective stages within the environment following
chemotherapy. These children had never received treatment so
would not have had their immune system boosted by schistosome
antigens revealed after PZQ treatment. Indeed, if PZQ treatment
reduced significantly the rate of reinfection, the model would be
expected to underestimate parasite intensity in untreated 6-year
olds. The most extreme manifestation of this would be in the high
intensity areas, where higher parasite burdens would lead to
greater release of immunogenic antigens with possibly an elevated
degree of immunological resistance. This would in turn cause the
reduction in the FOI to be overestimated and the observed
intensity in 6-year olds to be higher than model predictions.
Figures 5 and 6 indicate this is generally not the case, especially
not in high intensity regions.
However, the increase in intensity levels in 6yr olds between F2
and F3, a change which is not reflected in the wider population,
highlights the dangers of relying too heavily on a single age group
(with potentially low sample size) to detect secular changes in
parasite exposure. There is likely to be considerable uncertainty
about the exposure and infection patterns of pre-school age
children, and potentially significant variance between different
settings (i.e. related to proximity to water source). Currently there
are very little data available on the profiles of exposure and
intensity for infants and young children (,6yrs particularly) which
would help highlight this issue. In addition, as these data begin to
become available the contact function in the model (r(a) See
Equation S1) could be updated as this would have a significant
impact on estimating changes in the FOI.
The greatest relative reductions in the FOI after one round of
treatment were observed in low intensity areas. This is perhaps not
surprising given that the underlying intensity of transmission in
this area is probably lower, resulting in a weaker resilience to
control perturbations. However, significant reductions in the FOI
were also observed in medium and high intensity areas after two
rounds of treatment, and the FOI remained suppressed with a
third round. There was only a modest decrease in the FOI in areas
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should take into consideration how this would influence the
community FOI and thus morbidity within the untreated section of
the population. Ultimately, those making decisions on MDA
frequency and breadth should consider how compliance varies
over time across the population, to assess whether the extra cost of
frequent population-wide MDA can be justified through reductions in environmental contamination.
This study explores the changes in the FOI with yearly
treatment for S. mansoni in an East African setting. Further work
could compare this with a biennial treatment approach such as
those taking place in the SCI programmes in West Africa, and in
the future to any programmes that operate a twice-yearly
treatment approach, where data are available. Given that in this
study the FOI is calculated across the year and is therefore actually
an average of a rising value, it may be predicted that increasing
treatment frequency to every 6 months will have a greater than
additive effect in reducing the FOI.
This study has implications for the design of M&E programmes,
the purpose of which are to record, measure, and interpret the
impact of control interventions appropriately. Firstly, longitudinal
studies following the same children annually should control for the
ageing of the cohort, given the highly convex age-intensity and
age-exposure profiles seen in schistosomiasis. Secondly, treatment
is often aimed primarily at school-age children; however, it is
important to understand the patterns of exposure and infection
that are occurring in pre-school children [59], as these patterns are
still open to some debate [32,34]. Involving these younger age
groups who do not receive treatment in the monitoring
programme will improve our understanding of the secular changes
in transmission caused by a morbidity control programme, helping
differentiate between the impact of PZQ on the individual and the
community.
The aim of the SCI is morbidity control and thus the SCI’s
M&E is designed to reflect changes in the human parasite
component, rather than the snail intermediate host, and therefore
a method for estimating changes in the FOI from the human
parasite burden (as measured by epg) [22] is presented here. As
such, to our knowledge this is the first study attempting to quantify
changes in the FOI caused by a large-scale schistosomiasis control
programme using routinely collected data. Other methods, such as
monitoring infections in the vector, have been used to assess the
impact of MDA on the transmission potential of the parasite. For
example Sturrock and colleagues [60,61] used long-term snail
sampling and cercariometry, whilst Butterworth and colleagues [4]
examined changes in incidence of new infections among young
children. (See also Yaméogo and colleagues [62] for an example of
the use of black fly infectivity to estimate changes in the
transmission of human onchocerciasis caused by control programmes). These approaches, incorporating longitudinal snail
sampling to capture seasonal variations in transmission [63], will
likely provide ultimate confirmation of reductions in FOI, and will
provide useful validation of the results obtained in the present
study. Combining these different approaches and incorporating
the impact of non-random patters of compliance in relation to
parasite burden as has been suggested [64,65,66,67], would
provide valuable information on the true effectiveness of MDA
control programmes. This work will also help identify areas that
are potentially open to local elimination of the disease and of the
infection reservoir, and we advocate that the use of mathematical
models could guide this process.
to the entire human population. This study provides one of the
first attempts to quantify the impact of large-scale MDA on
transmission and the FOI. The ancillary benefit of MDA on
transmission can be used as a powerful advocacy tool aimed at
those funding and implementing programmes. There is a need for
similar studies to investigate the effect of MDA in other ecoepidemiological settings, and for other parasitic diseases where
MDA is a key component of infection and morbidity control.
Supporting Information
Appendix S1 References to supporting information.
Found at: doi:10.1371/journal.pntd.0000897.s001 (0.02 MB
DOC)
Figure S1 Relationship between school-level prevalence of
infection and average infection intensity (epg) fitted as described
in Protocol S1. A) Areas that recorded high infection intensity
(epg$400) at baseline, B) areas that recorded medium infection
intensity (100#epg,400) at baseline, and C) areas that recorded
low infection intensity (1,epg,100) at baseline. The schools were
sampled at baseline (turquoise squares) and re-sampled at follow
up year 1 [F1] (green diamonds), [F2] (pale pink circles), and [F3]
(light blue triangles). Note changes in scale of axes.
Found at: doi:10.1371/journal.pntd.0000897.s002 (0.22 MB
TIF)
Figure S2 Comparison of observed population age-structure of
Uganda (source: U.S. Census Bureau [3]) and the model-derived
age-structure fit assuming a constant death rate.
Found at: doi:10.1371/journal.pntd.0000897.s003 (0.19 MB
TIF)
Protocol S1
Found at: doi:10.1371/journal.pntd.0000897.s004 (0.05 MB
DOC)
Protocol S2
Found at: doi:10.1371/journal.pntd.0000897.s005 (0.29 MB
DOC)
Table S1 Parameter definitions and values used in the model.
The table differentiates between parameters that were fixed
throughout and those that were fitted using baseline cross-sectional
and longitudinal cohort data. H = Areas of high average intensity
at baseline ($400epg), M = Areas of medium average intensity at
baseline (100–399 epg), L = Areas of low average intensity at
baseline (1–99epg).
Found at: doi:10.1371/journal.pntd.0000897.s006 (0.07 MB
DOC)
Acknowledgments
We extend our sincere thanks to the schoolchildren, teachers and drug
distributors who participated in this investigation. We thank Ugandan and
UK-based members of the SCI and partner organizations for the
professional and successful management of the control programme. We
also acknowledge the helpful discussion of ideas with the EU-funded
CONTRAST consortium.
Author Contributions
Conceived and designed the experiments: AF JPW NBK. Analyzed the
data: MDF TSC MG M-GB. Contributed reagents/materials/analysis
tools: M-GB. Wrote the paper: MDF TSC M-GB. Reviewed the
manuscript: TSC MG AF JPW NBK M-GB. Organised and implemented
longitudinal fieldwork: AF JPW.
Significance and Conclusions
Quantifying the reduction in transmission of a schistosomiasis
control programme helps to understand fully the benefits of MDA
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