Age patterns of severe paediatric malaria and their relationship to Plasmodium falciparum transmission intensity

Abstract

The understanding of the epidemiology of severe malaria in African children remains incomplete across the spectrum of Plasmodium falciparum transmission intensities through which communities might expect to transition, as intervention coverage expands.
Paediatric admission data were assembled from 13 hospitals serving 17 communities between 1990 and 2007. Estimates of Plasmodium falciparum transmission intensity in these communities were assembled to be spatially and temporally congruent to the clinical admission data. The analysis focused on the relationships between community derived parasite prevalence and the age and clinical presentation of paediatric malaria in children aged 0-9 years admitted to hospital.
As transmission intensity declined a greater proportion of malaria admissions were in older children. There was a strong linear relationship between increasing transmission intensity and the proportion of paediatric malaria admissions that were infants (R2 = 0.73, p < 0.001). Cerebral malaria was reported among 4% and severe malaria anaemia among 17% of all malaria admissions. At higher transmission intensity cerebral malaria was a less common presentation compared to lower transmission sites. There was no obvious relationship between the proportions of children with severe malaria anaemia and transmission intensity.
As the intensity of malaria transmission declines in Africa through the scaling up of insecticide-treated nets and other vector control measures a focus of disease prevention among very young children becomes less appropriate. The understanding of the relationship between parasite exposure and patterns of disease risk should be used to adapt malaria control strategies in different epidemiological settings.

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Malaria Journal
Open Access
Review
Age patterns of severe paediatric malaria and their relationship to
Plasmodium falciparum transmission intensity
Emelda A Okiro*1, Abdullah Al-Taiar2, Hugh Reyburn3,4, Richard Idro5,6,
James A Berkley6,7 and Robert W Snow1,7
Address: 1Malaria Public Health and Epidemiology Group, Centre for Geographic Medicine, KEMRI-Wellcome Trust Collaborative Programme,
Kenyatta National Hospital Grounds P.O. Box 43640-00100, Nairobi, Kenya, 2Faculty of Medicine and Health Sciences, Sana'a University, P.O.
Box 13078, Sana'a, Yemen, 3London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK, 4Kilimanjaro Christian
Medical Centre P.O. Box 2228 Moshi, Tanzania, 5Department of Paediatrics, Mulago Hospital/Makerere University Medical School Kampala,
Uganda, 6Kenya Medical Research Institute, Centre for Geographic Medicine Research – Coast, Kilifi, Kenya P.O. Box 230-80108, Kilifi, Kenya and
7Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, CCVTM, Oxford, OX3 9DS, UK
Email: Emelda A Okiro* - eokiro@nairobi.kemri-wellcome.org; Abdullah Al-Taiar - a_m_altaiar@yahoo.com;
Hugh Reyburn - Hugh.Reyburn@lshtm.ac.uk; Richard Idro - ridro@kilifi.kemri-wellcome.org; James A Berkley - jberkley@kilifi.kemri-
wellcome.org; Robert W Snow - rsnow@nairobi.kemri-wellcome.org
* Corresponding author
Abstract
Background: The understanding of the epidemiology of severe malaria in African children remains
incomplete across the spectrum of Plasmodium falciparum transmission intensities through which
communities might expect to transition, as intervention coverage expands.
Methods: Paediatric admission data were assembled from 13 hospitals serving 17 communities
between 1990 and 2007. Estimates of Plasmodium falciparum transmission intensity in these
communities were assembled to be spatially and temporally congruent to the clinical admission
data. The analysis focused on the relationships between community derived parasite prevalence and
the age and clinical presentation of paediatric malaria in children aged 0–9 years admitted to
hospital.
Results: As transmission intensity declined a greater proportion of malaria admissions were in
older children. There was a strong linear relationship between increasing transmission intensity and
the proportion of paediatric malaria admissions that were infants (R2 = 0.73, p < 0.001). Cerebral
malaria was reported among 4% and severe malaria anaemia among 17% of all malaria admissions.
At higher transmission intensity cerebral malaria was a less common presentation compared to
lower transmission sites. There was no obvious relationship between the proportions of children
with severe malaria anaemia and transmission intensity.
Conclusion: As the intensity of malaria transmission declines in Africa through the scaling up of
insecticide-treated nets and other vector control measures a focus of disease prevention among
very young children becomes less appropriate. The understanding of the relationship between
parasite exposure and patterns of disease risk should be used to adapt malaria control strategies
in different epidemiological settings.
Published: 7 January 2009
Malaria Journal 2009, 8:4 doi:10.1186/1475-2875-8-4
Received: 5 November 2008
Accepted: 7 January 2009
This article is available from: http://www.malariajournal.com/content/8/1/4
© 2009 Okiro et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Background
During the 1980's and 1990's a series of epidemiological
observations were reported on the age and clinical pat-
terns of severe malaria in African children across a range
of Plasmodium falciparum transmission intensities [1-4]. It
appeared from these early observations that the intensity
of transmission affected the mean age and clinical features
of severe disease and rates of disease showed a nonlinear
relationship with transmission intensity, stimulating
much heated debate and commentary [5-9].
Subsequent to these earlier studies there has been a renais-
sance in the clinical epidemiology of severe paediatric
malaria across a wide range of different transmission set-
tings, leading to descriptions of severe paediatric malaria
from Sudan [10], Mozambique [11], Tanzania [12,13],
Mali [14], Niger [15], Kenya [16], Uganda [17,18], Yemen
[19], Ghana [20,21] and Zambia [22]. In addition, there
have been several further attempts to compare the epide-
miological patterns of severe malaria between sites of dif-
ferent transmission intensity in Gabon [23], Burkina Faso
[24], Uganda [17], Sudan [25], Tanzania versus Mozam-
bique [26], and one study that compared severe malaria
risks at different altitudinal transmission limits in Tanza-
nia [13]. The consensus view of all studies is that as the
intensity of P. falciparum transmission increases, the mean
age of severe malaria decreases. Less consistent is the
reported relationship between clinical syndromes of
severe paediatric malaria and transmission intensity.
There are three limitations of many of the reported eco-
logical comparisons. First, they often compare data from
very few sites, reducing the contextual ranges of the obser-
vations and thus their wider validity. Second, the meas-
ures of transmission intensity used in most studies are
often imperfect or assumed rather than measured
[13,17,23,25]; or not matched to the period of clinical
surveillance under review [11,26]. Finally, despite an
increased number of observational studies of severe
malaria, they often do not cover the same age range, nor
do they use similar diagnosis and surveillance methods.
To circumvent some of these limitations of cross-site com-
parisons and increase the power to generalize from obser-
vations, data from 17 sites across seven countries are
presented. The standardization of metrics used to define
transmission intensity in each site have significantly
improved, have been temporally matched to the clinical
surveillance period and attempts have been made to
ensure standardization in surveillance and diagnostic
methods between survey observations, to examine the
relationship between age patterns of hospitalized paediat-
ric malaria and P. falciparum transmission intensity.
Methods
Clinical surveillance
In this review we have assembled clinical admission data
from 17 communities served by 13 hospitals. The surveil-
lance sites were selected on the basis of having established
clinical and parasitological surveillance, often to specifi-
cally study the pathophysiology, management and epide-
miology of severe paediatric malaria.
Study sites
The 17 communities represent a wide range of malaria
ecology typical of the P. falciparum endemic world (Figure
1, Table 1). These include six sites where the clinical pat-
tern of severe malaria and its relationship to transmission
intensity were described by Snow and colleagues in the
early 1990s [2,3]; three communities in Kenya (Kilifi
North, Kilifi South and Siaya), two in The Gambia (Bakau
and Sukuta) and one community in Tanzania (Ifakara).
The data collected in Ifakara [2] were re-assembled to
ensure that only clinical admissions from Namawala and
Michenga villages were included to spatially correspond
directly to measures of malaria transmission. Three addi-
tional temporally discrete surveillance periods have been
included among approximately similar communities
studied during the 1990's around Kilifi District Hospital,
on the Kenyan Coast including Kilifi North, Chonyi and
Junju investigated approximately ten years after clinical
descriptions in these approximately matched areas. Data
from a further six sites in Africa, where identical surveil-
lance methods were reported, were also included:
Humera, Ethiopia [27], Foni Kansala, The Gambia
(reported in [28]), Mponda, Malawi (reported in [28]),
Magunga and Kilimanjaro, Tanzania [13] and Kabale,
Uganda [17]. Two additional sites in the Arab peninsular
make up the last study sites and are regarded here as shar-
ing a similar malaria and dominant vector species ecology
to the horn of Africa; these include clinical admission data
from the Yemeni-Swedish Hospital, in Taiz, and Althowra
Hospital in Hodeidah City [19].
Surveillance and diagnosis
At each hospital all paediatric admissions routinely
undergo a screening procedure where symptom histories
are recorded. the definition of paediatric is restricted to
children aged less than ten years. Each child was examined
on admission and a blood sample taken for malaria para-
sitology and haematology. Diagnosis was supported by
detailed clinical examination; all clinical and laboratory
data are reviewed by investigating physicians who estab-
lished a primary diagnosis (defined as the principal rea-
son for the child's admission). A primary diagnosis of
malaria was made when a child had a positive blood
smear and no other detectable cause for the clinical pres-
entation, after a review of all available clinical and haema-
tological data and where indicated, X-ray and

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microbiological data. Two clinically important complica-
tions of severe malaria in African children are cerebral
malaria and severe malarial anaemia [29,30]. Conscious-
ness on admission is recorded at most sites according to
the Blantyre Coma Score (BCS) based on verbal, motor,
and gaze responses to stimulation [29,31]. To allow com-
parison across studies a BCS of 0, 1, or 2 (4 or 5 consid-
ered normal depending on age [29]) was used to define
coma and cerebral malaria in the presence of malaria
infection and absence of other causes for the clinical pres-
entation. In Kabale, a BCS of ≤ 2 was used to describe cer-
ebral malaria in children aged less than 5 years old and a
Glasgow Coma score [32] of ≤ 8 for children 5–9 years
Severe malaria anaemia was defined as a diagnosis of
malaria with an admission haemoglobin level of less than
5.0 g/dl or PCV of less than 15%.
Plasmodium falciparum transmission intensity
Cross-sectional estimates of P. falciparum infection preva-
lence from the communities served by the study hospital
sites were assembled from information available as part of
The Malaria Atlas Project [33] database [34,35]. Infection
prevalence estimates were identified where they were spa-
tially congruent, within 20 km of the hospital (Authors,
unpublished data), and temporally congruent, during the
years of the hospital surveillance. This restriction increases
the accuracy of assigning transmission intensity to each of
the clinical admission series. For each series of parasite
prevalence survey data, the age-ranges reported varied
between surveys and these were standardized to a single
age range 2–10 years (PfPR2–10) using algorithms
described elsewhere [36].
Results
The study series included a total of 11,446 children admit-
ted to the 13 hospitals with a primary diagnosis of malaria
confirmed by microscopy from the 17 communities cov-
ering a total of 17 survey years between 1990 and 2007
(Table 1, Figure 1). The communities served by the hospi-
tals represented the entire range of transmission intensity
from PfPR2–10 values of 1% in Kilifi North between 2004–
07 to as high as 87% in Namawala/Michenga villages in
Tanzania in the early 1990s (Table 1).
To examine the corresponding age-patterns of malaria
admission against transmission intensity we computed
Hospital sites included in the study of the age and clinical epidemiology of hospitalized paediatric malariaFigure 1
Hospital sites included in the study of the age and clinical epidemiology of hospitalized paediatric malaria: Kilifi
District Hospital (A), Althowra Hospital (B), Royal Victoria Hospital & the Medical Research Council hospital (C), Yemeni
Swedish Hospital (D), Kilimanjaro CMC (E), Humera district Hospital (F), Kabale regional refferal Hospital (G), Mangochi dis-
trict Hospital (H), Sibanor Clinic (I), Korogwe District Hospital (J), Siaya District Hospital (K), St Francis Hospital (L).

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the proportion of all malaria admissions by single years of
age 0 to 9 years at each site, arranged in descending order
of PfPR2–10 in Figure 2. Across the 17 communities the ten-
dency was toward a greater proportion of older children
presenting as PfPR2–10 estimates decreased and a greater
proportion of younger children admitted where PfPR2–10
was higher. It was nevertheless notable, that even at very
low estimates of PfPR2–10, the proportion of cases after the
fourth birthday was lower than in early childhood (last
five panels in Figure 2).
For a number of reasons, that are expanded on in the dis-
cussion, the public health and intervention significance of
clinical risks in infancy is of programmatic importance.
Among the six communities where the PfPR2–10 estimate
was ≥ 40%; approximately 40% of all malaria admissions
were in children aged < 1 year. This compared with an
average of 20% of all malaria admissions in infancy
among the eight sites with a PfPR2–10 between 5 and 39%,
and 10% of all admissions at the three sites where PfPR2–
10 was recorded as < 5%. There is a direct and strong linear
relationship between increasing PfPR2–10 and the propor-
tion of paediatric malaria admissions that are infants (R2
= 0.73, p < 0.001; Figure 3a) and the converse relationship
with the proportion of admissions that are aged between
5–9 years (R2 = 0.47, p = 0.002; Figure 3b). A few outliers
Table 1: Description of clinical surveillance sites and the characteristics of the catchment populations in relation to transmission
intensity (PfPR2–10-Plasmodium falciparum parasite prevalence in children 2 to 10 years).
Study Site
[Map Reference]
Dates
(years)
Malaria admissions BCS1 ≤ 2 recorded
(Y/N)
SMA2 recorded
(Y/N)
PfPR 2–10
(years recorded) [number
examined]
Kilifi North, Kenya [A] 2004–07
(4)
712 Y Y 1.3
(2005–07) [828]
Hodeidah, Yemen [B] 2002–04
(1.75)
283 Y Y 1.7
(2005–06) [5886]
Bakau, The Gambia [C] 1992–94
(3)
99 Y N 2.1
(1988) [386]3
Taiz, Yemen [D] 2002–04
(1.75)
1049 Y Y 5.7
(2005–06) [4908]
Kilimanjaro, Tanzania [E] 2002–03
(1)
162 Y Y 6.2
(2001–02) [382]
Humera, Ethiopia [F] 1994–95
(1)
458 N Y 12.6
(1995) [616]
Kabale, Uganda [G] 2002–03
(1.5)
160 Y5Y18.0
(2006) [64]4
Kilifi South Junju, Kenya [A] 2005–07
(3)
92 Y Y 25.9
(2005–07) [1601]
Mponda, Malawi [H] 1994–95
(1)
356 Y Y 33.0
(1996)
Foni Kansala, The Gambia [I] 1994–95
(2)
193 Y Y 34.1
(1991–92) [117]
Korogwe, Tanzania [J] 2002–03
(1)
3948 Y Y 34.9
(2000–02) [927]
Sukuta, The Gambia [C] 1992–95
(4)
605 Y N 42.4
(1996) [125]
Kilifi South Chonyi, Kenya [A] 1999–01
(3)
346 N Y 43.0
(1999–01) [1918]
Kilifi North, Kenya [A] 1990–95
(5)
1358 Y Y 51.9
(1995) [540]
Siaya, Kenya [K] 1992–96
(3)
715 Y Y 75.1
(1995) [570]
Kilifi South, Kenya [A] 1992–96
(4)
766 Y Y 76.9
(1996) [212]
Namawala/Michenga, Tanzania
[L]
1991–92
(1)
144 Y Y 87.5
(1989–91) [3947]
1BCS – Blantyre Coma Score
2 SMA Severe Malaria Anaemia defined as Hb <5 gm/dl or PCV<15%
3 The estimate of PfPR was not temporally matched however it was regarded as a legitimate estimate for this peri-urban community four years later
when the clinical surveillance data began.
4 Kabale is a high altitude area and while there were 3 years difference in the estimation of PfPR and the clinical surveillance period the estimate of
infection prevalence is regarded as a good approximation.
5 The investigators used a BCS ≤ 2 to describe cerebral malaria in children aged less than 5 years old and a Glasgow Coma score [32] of ≤ 8 for
children 5–9 years.

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are worth identifying: first Junju, Kilifi South, Kenya with
a PfPR2–10 estimate of 26% had no admissions above 5
years of age during the observation period; second, at Kil-
ifi North between 2004–07 PfPR2–10 was recorded as 1%
and Kilimanjaro with a PfPR2–10 estimate of 6%, however,
both had considerably more children admitted aged 0–4
years compared to those 5–9 years of age. Finally, the Kil-
ifi South (Chonyi) admission series documented between
1999 and 2001 shows a high proportion of infants while
transmission intensity is intermediary between two sites
where the infant admissions are much lower.
The observations summarized in Figure 2 include overlap-
ping communities seen at different times with very differ-
ent estimates of PfPR2–10 during each observation period:
Kilifi North in the 1990s and 2000s and two closely
located communities surveyed between 1999 and 2007
south of Kilifi District Hospital and corresponding to Kil-
ifi South surveyed in 1990's. In the same communities
over the two time periods transmission had dropped dra-
matically. In Kilifi North over ten years PfPR2–10 dropped
from 52% to 1% and at Kilifi South (1992–1995) and the
nested area of Chonyi (1999–2001) corresponding PfPR2–
10 estimates were 77% and 43% respectively. In both areas
the age patterns of malaria admissions had shifted toward
older children as PfPR2–10 declined but the most dramatic
age-shift was observed at Kilifi North with the largest
decline in PfPR2–10 over a longer time frame.
The hospitals that routinely recorded unconsciousness
using a BCS or anaemia on admission are shown in Table
1. Across this admission series of 10,642 and 10,742 cases
of paediatric malaria respectively, cerebral malaria was
reported among 4% and severe malaria anaemia among
17% of admissions. The relationship between the propor-
tion of admissions presenting with cerebral malaria (BCS
≤ 2) and PfPR2–10 is shown in Figure 4a. This suggests that
at higher transmission intensity cerebral malaria is a less
common presentation compared to lower estimates of
PfPR2–10, however, without the very high proportion of
cerebral malaria cases reported at Kilimanjaro this rela-
tionship is less convincing. Similarly excluding the com-
munity of Nyamawala/Michenga in Tanzania where 50%
of all admissions had a PCV <15% there appears to be no
direct relationship between increasing transmission inten-
sity and increase in proportion of severe malaria anaemia
cases (Figure 4b).
Discussion
There is mounting evidence that the epidemiology of
malaria infection and disease risks are in transition is
some parts of Africa, in part as a result of scaling of the
provision of insecticide treated nets (ITN) and adoption
of new effective therapeutics [37-41]. How changing the
natural risks of parasite exposure by vector control will
alter the clinical epidemiology of severe, complicated dis-
ease in young African children was the subject of concern
Age distribution of hospitalized malaria from 17 communities arranged by decreasing PfPR2–10 (Plasmodium falciparum parasite prevalence in children 2 to 10 years)Figure 2
Age distribution of hospitalized malaria from 17 communities arranged by decreasing PfPR2–10 (Plasmodium
falciparum parasite prevalence in children 2 to 10 years). The bars denote the percentage of children in each single age
group of all malaria admissions 0–9 years at each site.
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Malaria Journal 2009, 8:4 http://www.malariajournal.com/content/8/1/4
Page 6 of 11
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Age specific proportion of total hospitalized paediatic malaria cases under different transmission intensities (x-axis; PfPR2–10-Plasmodium falciparum parasite prevalence in children 2 to 10 years)Figure 3
Age specific proportion of total hospitalized paediatic malaria cases under different transmission intensities (x-
axis; PfPR2–10-Plasmodium falciparum parasite prevalence in children 2 to 10 years). The graphs show for each study
sites the proportion of total malaria cases in children < 1 year (Figure 3a) and the proportion of total malaria cases in children
5–9 years (Figure 3b).
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Malaria Journal 2009, 8:4 http://www.malariajournal.com/content/8/1/4
Page 7 of 11
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Proportion of total malarial cases diagnosed with clinical syndrome of cerebral malaria (Figure 4a) and severe malarial anaemia (Figure 4b) under different transmission intensities (PfPR2–10 – Plasmodium falciparum parasite prevalence in children 2 to 10 years)Figure 4
Proportion of total malarial cases diagnosed with clinical syndrome of cerebral malaria (Figure 4a) and severe
malarial anaemia (Figure 4b) under different transmission intensities (PfPR2–10 – Plasmodium falciparum para-
site prevalence in children 2 to 10 years).
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over 50 years ago [42,43] and interest in this area re-
emerged ten years ago following early comparisons of the
clinical outcomes of infection in different transmission
settings [3,4,8,44].
There are very few serial, long-term clinical observations
of severe paediatric malaria in areas where transmission
intensity is in transition [41]. Thus to understand the rela-
tionships between transmission intensity and disease out-
come we must default to cross-sectional estimations of
risk and exposure from different settings to infer what
might happen if single communities transitioned between
exposure states. Ecological comparative observational epi-
demiology is not without its limitations. An attempt has
been made to standardize observations across 17 commu-
nities to minimize methodological measurement differ-
ences in the study of the clinical epidemiology of
hospitalized paediatric malaria and transmission. Here
PfPR2–10 estimates of transmission contemporary with the
clinical observations were used to ensure congruence
between exposure and outcome.
One of the most striking observations was the relation-
ship between increasing transmission intensity and the
predominant age of paediatric malaria admissions (Fig-
ures 2, 3a and 3b). Among communities where PfPR2–10 is
≥ 40% more than 40% of malaria admissions to paediatric
wards were infants, compared to only 10% in areas where
PfPR2–10 is < 5%. These observations are consistent with
the view that the speed of acquired clinical immunity
scales with the frequency of parasite exposure since birth
[3,4,45]. Interestingly from the sites where the intensity of
transmission was very low (Figure 2), there remains evi-
dence of some acquired functional immunity as expressed
by the continued decline after the fourth birthday in the
proportion of overall malaria admissions. This was most
notable at Taiz (PfPR2–10 6%) and Bakau (PfPR2–10 2%).
These declining risks with age under very low parasite
exposure from birth suggest that only a few parasite expo-
sures might confer a degree of clinical immunity [46] or
age itself modifies risks of hospitalized malaria [47].
Despite the overall linear pattern of proportions of admis-
sions aged less than one year (Figure 3a) or greater than
five years (Figure 3b) with increasing transmission inten-
sity there were some interesting exceptions to this general
pattern. At two coincidentally matched sites investigated
between ten years apart (Kilifi North) and five years apart
(Kilifi South versus Chonyi) on the Kenyan coast the age-
patterns were not as one might have anticipated based on
the age patterns of disease seen in areas with very similar
PfPR2–10 (Figure 2). Both sites did show a changing age
pattern of disease presentation with decreasing transmis-
sion intensity but had not resulted in an age pattern simi-
lar to those of historically similar transmission intensity
in their second observation period. What these data might
suggest is that the cross-sectional investigation of the clin-
ical epidemiology of hospitalized malaria during a period
of transmission transition, inevitably results in the study
of older children exposed to different transmission inten-
sity risks at different times in their young lives with a
cohort effect of accumulated acquired immunity. Thus the
"true" age pattern in a community would take some time
to stabilize. This phenomenon might also explain the
slightly divergent patterns seen at the two South Eastern
sites in Tanzania (Magunga and Kilimanjaro) where
scaled ITN coverage may also have resulted in a difference
between "historical" estimations of PfPR2–10 and the cur-
rent values used to match the clinical surveillance period
[48].
More importantly the differences in peak age of hospital-
ized malaria disease presentation and transmission inten-
sity have implications for the design of suites of
prevention strategies planned for the control of malaria in
Africa. The benefit of targeted intervention in the use of
bed nets for malaria control as currently recommended by
the WHO is based on the reasoning that targeting bed nets
to the highest risk groups; infants and pregnant women,
achieves the highest public health impact. Following the
same reasoning it is clear that the likely public health
impact of intermittent presumptive treatment of infants
(IPTi) coincidental with vaccine schedules [49], is likely to
be greatest in areas of the transmission axis where the dis-
ease burden in concentrated in infancy (Figure 3a). As the
estimate of PfPR2–10 declines IPTi must adapt to include
increasingly older age risk groups [50] until one considers
adoption of IPT in school-aged children [51] (Figure 3b).
It seems entirely plausible that with adequate scaling of
ITN coverage in most areas of Africa where PfPR2–10 starts
at values <40% a dramatic reduction in transmission
intensity is likely within 3–5 years [52], as this happens
the age-patterns of severe malaria presenting to hospital
will change and increasingly become less dominated by
infants, making the adaptation of the IPTi rationale an
immediate priority. Following the same reasoning, outpa-
tient screening tools such as the WHO recommended
IMCI guidelines currently in use across many African
countries will need to be modified to accommodate
expected changes in disease presentation. The current
dogma is that across Africa hospitalized malaria is a young
paediatric problem, however recent assemblies of PfPR2–
10 information from across the continent [34], suggest that
the predominant transmission pattern is one approximat-
ing to areas closer to the left hand side of the X-axis of Fig-
ures 3a and 3b. Areas of exceptionally high transmission
are likely to be less common than previously thought and
yet are often the choices of location for most clinical stud-
ies of hospitalized malaria in childhood.

Malaria Journal 2009, 8:4 http://www.malariajournal.com/content/8/1/4
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In this study series, cerebral malaria appeared to be a more
common presentation among children hospitalized with
malaria from lower intensity transmission settings com-
pared to areas of high transmission (Figure 4a). This
observation has been made in other between site compar-
ative studies [2,3,13,17,24,53]. The proportion of malaria
admissions regarded as having a BCS ≤ 2 varied consider-
ably under a wide range of transmission conditions from
PfPR2–10 1% to 33%, however, and may also reflect the dif-
ficulties in measuring cerebral malaria in very young chil-
dren [54]. The proportion of children presenting with
severe malaria anaemia showed little variation across the
range of transmission conditions from 1–80% PfPR2–10
(Figure 4b) with the exception of the highest recorded
proportion of anemic children (50%) from Nyamawala/
Michenga villages where PfPR2–10 was 87%. The epidemi-
ology of severe malaria anaemia may be more complex
than previously thought [12,55] and while is a common
feature in young hospitalized infants remains a clinical
predictor in older children [30]. A recent study looking at
severe anaemia in children indicates that the occurrence
of SMA is more likely to be multi-factorial than is CM and
importantly is also more likely to be context specific relat-
ing to nutrition, prevalence of HIV and prevalence of
other diseases which are associated with severe anaemia
[56], thus complicating direct comparisons between sites.
The incidence of hospitalization has not been examined,
largely because the precise calculation of the paediatric
populations at risk was not possible across most of the
sites studied after the 1990's. Therefore, no specific com-
ments on the overall changing risks of hospitalization as
PfPR2–10 declines can be made. Nevertheless, it is interest-
ing to note that the one long-term serial study of severe
clinical malaria in Africa has investigated the rate of hos-
pitalization during a time of major transmission reduc-
tion at Kilifi North [41]. O'Meara et al. (2008) showed
that in this community, that began with a PfPR2–10 of
approximately 50% and declined to 1% over ten years,
resulted in a ten-fold decline in the risks of hospitalization
with malaria in childhood. The focus here has been on
better descriptions, across more sites of the age and clini-
cal presentation of hospitalized malaria in childhood
likely to be observed with reductions in transmission
intensity across Africa as prevention strategies go to scale
over the next ten years. Perhaps not surprisingly these
results confirm many other observations, using less rigor-
ous inclusion criteria [11,23,25], that declining transmis-
sion intensity will result in fewer infants and
proportionately more children of older age groups as rep-
resenting the clinical burdens facing hospitals in Africa. It
is less certain whether the case-mix of cerebral malaria and
severe malaria anaemia will change coincidental with
declining transmission intensity.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
EA assembled all the hospital data, restructured the data
and wrote the manuscript; AAT, HR, RI and JAB were
responsible for the assembly of hospital data from Yemen,
Tanzania, Uganda and Kilifi, Kenya respectively and con-
tributed to the final manuscript. RWS was responsible for
the project and its overall scientific management, interpre-
tation and preparation of the final manuscript.
Acknowledgements
The following people generously helped with the provision of clinical and
parasitological data presented in this paper and their interpretation: James
Nokes, Geisler Snieder, Terrie Taylor and Edna Ogada. We thank Quique
Bassat and Robert Opoka who provided comparative data which for vari-
ous inclusion criteria reasons we were unable to include in this paper. We
thank Simon Hay and Wendy O' Meara for helpful comments on earlier
versions of the manuscript. RWS is supported by the Wellcome Trust as
Principal Research Fellow (#079081). AAT was funded by UNICEF-UNDP-
World Bank-WHO Special Programme for Research and Training in Trop-
ical Diseases (TDR) (project ID: A30333 linked to project ID: A10491). HR
was funded by Medical Research Council, UK (grant no. 9901439). JAB is
supported by the Wellcome Trust as a Research Fellow (#083579). There
are no competing interests. This work also forms an output of the Malaria
Atlas Project (MAP, http://www.map.ox.ac.uk) and is published with the
permission of the director of KEMRI.
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