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Cookeet al. Malar J (2015) 14:259
DOI 10.1186/s12936-015-0766-4
RESEARCH
‘A bite beforebed’: exposure tomalaria
vectors outsidethe timesof net use
inthe highlands ofwestern Kenya
Mary K Cooke1, Sam C Kahindi2, Robin M Oriango2, Chrispin Owaga2, Elizabeth Ayoma2,
Danspaid Mabuka2, Dennis Nyangau2, Lucy Abel2, Elizabeth Atieno2, Stephen Awuor2, Chris Drakeley1,
Jonathan Cox1 and Jennifer Stevenson1,3*
Abstract
Background: The human population in the highlands of Nyanza Province, western Kenya, is subject to sporadic
epidemics of Plasmodium falciparum. Indoor residual spraying (IRS) and long-lasting insecticide treated nets (LLINs)
are used widely in this area. These interventions are most effective when Anopheles rest and feed indoors and when
biting occurs at times when individuals use LLINs. It is therefore important to test the current assumption of vector
feeding preferences, and late night feeding times, in order to estimate the extent to which LLINs protect the inhabit-
ants from vector bites.
Methods: Mosquito collections were made for six consecutive nights each month between June 2011 and May
2012. CDC light-traps were set next to occupied LLINs inside and outside randomly selected houses and emptied
hourly. The net usage of residents, their hours of house entry and exit and times of sleeping were recorded and the
individual hourly exposure to vectors indoors and outdoors was calculated. Using these data, the true protective
efficacy of nets (P*), for this population was estimated, and compared between genders, age groups and from month
to month.
Results: Primary vector species (Anopheles funestus s.l. and Anopheles arabiensis) were more likely to feed indoors but
the secondary vector Anopheles coustani demonstrated exophagic behaviour (p < 0.05). A rise in vector biting activity
was recorded at 19:30 outdoors and 18:30 indoors. Individuals using LLINs experienced a moderate reduction in their
overall exposure to malaria vectors from 1.3 to 0.47 bites per night. The P* for the population over the study period
was calculated as 51% and varied significantly with age and season (p < 0.01).
Conclusions: In the present study, LLINs offered the local population partial protection against malaria vector bites.
It is likely that P* would be estimated to be greater if the overall suppression of the local vector population due to
widespread community net use could be taken into account. However, the overlap of early biting habit of vectors and
human activity in this region indicates that additional methods of vector control are required to limit transmission.
Regular surveillance of both vector behaviour and domestic human-behaviour patterns would assist the planning of
future control interventions in this region.
Keywords: Malaria, Exophagic, Endophagic, Anopheles funestus, Anopheles arabiensis, LLIN, IRS, Kenya, Highlands
© 2015 Cooke et al. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License
(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,
provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license,
and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/
publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Open Access
*Correspondence: jennyc.stevenson@macharesearch.org
3 Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg
School of Public Health/Macha Research Trust, Choma, Zambia
Full list of author information is available at the end of the article
Page 2 of 15
Cookeet al. Malar J (2015) 14:259
Background
e feeding locations and the biting times of individual
Anopheles spp. could potentially confound assessments
of their role in local malaria transmission [1, 2]. ere
is evidence that in Kenya and elsewhere in Africa, pri-
mary vectors and other potentially important secondary
malaria vectors do not feed exclusively within houses
[1, 3–14] and that significant levels of vector exophagy,
feeding outdoors, can occur at times when the human
population is still outdoors [5, 7, 11–13, 15, 16]. Malaria
eradication has recently returned to the global health
agenda for the first time since the failure of the Global
Malaria Eradication Programme (GMEP) of the 1950s
and 1960s [17–20]. e development of insecticide
resistance, and the exophily and exophagy of Anopheles
species (resting and feeding outdoors) are thought to be
among the key contributors to the failure of the original
programme [21] which relied heavily on indoor residual
spraying (IRS) with DDT. It has, therefore, been sug-
gested that any future campaign to achieve eradication,
still less elimination, may fail if the lessons learnt from
the collapse of the GMEP are forgotten or ignored [20,
22].
Today, vector malaria elimination plans are heavily
reliant on the use of long-lasting insecticide treated nets
(LLINs) and IRS, both of these being strategies that are
theoretically less effective against the malaria vectors
that are fully or partially exophilic or exophagic [23]. Suc-
cessful malaria control is threatened by the emergence
of physiological, biochemical or behavioural adaptations
within the vector population in response to the use of
insecticide [24, 25]. IRS and LLINs require direct contact
between the mosquito and surfaces carrying sufficient
levels of insecticide to kill or repel the vector. Pre-existing
or adapted feeding and resting behaviour may reduce or
negate this contact [19].
e feeding behaviour and circadian rhythms of
Anopheles are genetically determined [26, 27], with the
former being linked with inversion polymorphisms [26].
ere is an added complication of intraspecies varia-
tion, where mosquitoes of the same species but different
homokaryotypes react to identical environmental condi-
tions in different ways [26]. ere has been some debate
surrounding the importance of pre-existing exophilic and
exophagic Anopheles populations when planning control
efforts [1, 19, 28–30]. Whilst the occurrence and mecha-
nisms of insecticide resistance over the last century have
been well documented in African Anopheles populations
[21, 25, 31], the extent to which the emergence of popula-
tion-wide vector behavioural change in response to con-
trol methods, known as ‘behaviouristic resistance’, affects
the use of nets and IRS remains unclear. is can only
be established by observing vector population behaviour
in the field and there is a lack of basic pre-intervention
baseline studies [12, 25, 31–34].
e time of feeding in both endophagic and exophagic
populations may also be of critical importance if it occurs
in the hours outside of LLIN use [16, 28, 30, 35–38], par-
ticularly in areas where nets are the main control inter-
vention used [1].ere have been reports of net and IRS
use leading to a reduction in indoor biting or resting, and
a shift to exophagic behaviour, earlier feeding times or
feeding on different hosts [10, 39–48]. In Kenya, a pro-
nounced reduction in endophily was observed in the vec-
tors Anopheles gambiae sensu stricto (s.s.) and Anopheles
funestus sensu lato (s.l.) and a shift in host preference
from humans to other mammals after 5years of bed-net
use [44]. Similarly, host choice change in An. funestus s.l.
was observed by Githeko etal. following use of perme-
thrin-impregnated eave-sisal curtains [49]. In Benin, An.
funestus s.l. populations exhibited increased exophagy
and a shift in feeding times after LLIN introduction and
demonstrated a shift to diurnal feeding in a recent study
in Senegal [50, 51]. For these species complexes, this
could be due to a change of the sibling species composi-
tion, rather than a behavioural change of a single species
per se, as some members demonstrate higher zoophagy
and exophagy than others. is was demonstrated in
Kenya where following mass net distribution the An.
gambiae s.s. population decreased and the remaining sib-
ling species Anopheles arabiensis, demonstrated higher
exophagy and zoophagy [52]. In Tanzania, substantial
reduction in the indoor resting and a small increase in
the exophagic behaviour of An. gambiae s.s. was recorded
after the introduction of pyrethroid-impregnated bed
nets in one study village [39]. It should also be noted, that
these changes are not universal, a recent study in Kenya
noted that late night vector feeding behaviour still per-
sisted in areas 10years after bed net distribution [53].
Human behaviour may also influence the extent of
human-vector contact. Entomological studies carried out
in Zambia and Tanzania incorporated the proportion of
the human population indoors but not asleep and those
indoors and asleep under an LLIN, in order to calculate
the protective efficacy of bed nets [37, 38, 45]. e meth-
odology of these studies provides a useful insight into the
true protective efficacy of bed nets when both human
and vector behaviours are combined but are partially lim-
ited, as they do not estimate the area-wide effects on the
vector population that universal coverage of LLIN can
offer [54].
e World Health Organization recommends that
adequate baseline information is collected in an area
before residual insecticide is used [55]. Without a good
understanding of the baseline entomological situation,
the emergence of true behavioural adaptations will be
Page 3 of 15
Cookeet al. Malar J (2015) 14:259
difficult to detect. is concern has led to a call for reg-
ular monitoring of vector feeding behaviour as control
programmes are expanded [37]. Regrettably, as noted by
Smits etal., vector control is susceptible to a reduction in
supervision and evaluation when activities have been in
place for some time [4]. Success is more likely if control
efforts are designed to adapt to changing local conditions
[4]. Without a baseline vector dataset it is difficult to
identify the emergence of behaviouristic resistance, and
the accuracy of malaria transmission models used to plan
future control efforts will be compromised [56–58].
is study aimed to assess the behaviour of exophagic
or partially exophagic malaria vectors in Rachuonyo
South, western Kenyan highlands, over different seasons,
and to assess the level of exposure to Anopheles bites that
individuals experience when not protected by an LLIN.
Using vector exposure calculations, the protective effi-
cacy of nets was calculated for this population.
Methods
Study site
e current Kenyan national malaria strategic plan aims
to reduce morbidity and mortality caused by malaria,
using current control tools, including regular national
mass distributions of LLINs and IRS in selected regions
[59]. e western Kenyan highlands are considered an
area of unstable Plasmodium falciparum transmission
and prone to epidemics, and as such are included in those
areas selected for intensive malaria control by universal
LLIN distribution and either annual or intermittent IRS
[60–62]. Malaria transmission in this region is charac-
terized by marked temporal and spatial heterogeneity
[49, 63, 64]. e identification of malaria vectors, their
behaviour and the contribution of each vector to local
transmission are key to evaluating the success of con-
trol measures, and to planning future campaigns [2, 37,
56, 57]. is is particularly important in areas of unstable
transmission which constitute key targets for eliminat-
ing the disease as vector dynamics can vary dramatically
by season [65–67]. In Nyanza Province, western Kenya,
a number of descriptive studies have been carried out in
Kisii district of vector distribution and behaviours in the
context of control interventions [68, 69]. However in the
highland fringe area of neighbouring Rachuonyo South,
a district of approximately 200,000 population bordering
the highly endemic lake area, no recent data exist on vec-
tor bionomics.
is study was carried out under the highland Malaria
Transmission Consortium in southern Nyanza Province,
Kenya in the adjacent villages of Lwanda and Siany, in
Rachuonyo South District (0°25′59.53″ S, 34°55′40.36″
E; altitude 1,420–1,570m ASL). is location was previ-
ously identified as an area of relatively high P. falciparum
transmission during cross-sectional and cohort parasi-
tological surveys carried out in 2009 and 2010 and with
indoor-resting anopheline populations [70]. IRS had been
carried out by the local health services in this region in
2010 using Fendona (alphacypermethrin), a year before
the study began, and was repeated in July 2011 using
Icon (Lambda-cyhalothrin). is area was also included
in the mass distribution of LLINs during the rainy sea-
son (April–June) in 2011, as part of the Kenyan National
Malaria Strategy [71]. However, prior to the distribution
in 2011, 100% of the 48 houses recruited into the present
study already owned a minimum of one net (and more
than half of the households owned two or more nets).
In western Kenya the primary vectors of P. falciparum
are considered to be, An. arabiensis, An. funestus and An.
gambiae s.s., three of the six malaria vector species iden-
tified in Kenya [72, 73]. ere is some evidence that the
once widely distributed An. gambiae s.s. has declined in
recent years and that An. arabiensis has encroached upon
its previous distribution [52, 73, 74]. is shift has been
attributed to the wide-scale use of insecticide-treated
nets (ITNs) [44, 52].
Sample size
e study was designed to compare the catch of light-
traps set outdoors with those placed indoors over 1,800
trap nights, 900 trap nights for each study arm over
a 1-year period. To test the null hypothesis that there
was no difference between the mean density of primary
malaria vector species feeding inside and outside houses,
data from a previous field study in the region were used
to estimate minimum sample sizes. As there was the
potential for intracluster correlation caused by repeated
sampling at trap locations, formulae for community stud-
ies from Hayes and Bennett were used [75]. e mini-
mum sample size required to compare An. gambiae s.l.
feeding inside and outside, with 80% power, 95% preci-
sion and a coefficient of variation of 0.8 was 7.9 traps in
each study arm per night, giving a total of 16 traps in use
per study night. Using the same power, precision and
coefficient estimates, a total of 8.4 traps per study arm
would be required to compare the mean catches of An.
funestus s.l. As previous studies had been disrupted by
unexpected weather conditions (outdoor catches, in par-
ticular, can be interrupted by heavy rain), a conservative
total of 24 traps, 12 indoors and 12 outdoors, running
each night was selected for the study.
Mosquito collection
Fieldwork was carried out between February 2011 and
May 2012. Community sensitization, recruitment, map-
ping and a pilot study took place between February and
May 2011. Sampling began in June 2011 and continued
Page 4 of 15
Cookeet al. Malar J (2015) 14:259
for six nights every lunar month (with the exception of
December 2011) until the end of May 2012, a total of 75
collection nights. Sampling was scheduled on nights near
a new moon to minimize the effect of moonlight on the
outdoor light-trap collection and to reduce bias when
comparing species distribution and flight activity across
seasons [76–78]. An estimate of the presence and period
of moonlight was calculated using a lunar calendar and
the method described by Bowden [77, 79].
A stratified random sampling method was adopted to
minimize sampling bias when selecting sampling loca-
tions and to reduce variance in the dataset [80]. e
study site was identified with the aid of satellite imagery
(Quickbird Inc, Longmont, CO, USA), with a spatial res-
olution of <1m, which could therefore be used to identify
structures on the ground. Using GIS software (ArcGIS
9.2, Redmond CA, USA), a sampling grid was defined to
divide the area into 36 quadrants (300m×300m) cover-
ing an area of 1.8sq km running across the valley floor
and a portion of the adjoining hillsides.
A survey of the selected quadrants was conducted on
the ground. Quadrants with permanent breeding sites
(n = 13) were selected for recruitment, as these have
been associated with higher adult vector productivity in
highland areas than temporary breeding sites, and are
more likely to be present throughout the sampling year
[81] (Figure1). Quadrants with fewer than four occupied
houses were omitted from the recruitment. Remain-
ing eligible quadrants were randomized and processed
sequentially until 12 quadrants had been recruited into
the study. Within each quadrant the mapped houses
were randomized and four households with associated
light-trap workers were recruited into the study. During
recruitment, data on house construction, occupant num-
bers, bed nets, local IRS activity, and domestic animal
ownership were collected.
To reduce selection bias six quadrants (i.e., 24 houses)
were randomly selected for trapping each night. Within
quadrants, two houses were randomly selected for out-
door sampling with the remaining two allocated for
indoor trapping. As the effective range of light-traps
has been estimated at 5m [82], outdoor sampling took
place at least 10m from the house to reduce the chance
of the inhabitants acting as unshielded bait. A miniature
CDC light-trap with a standard 6.3V incandescent bulb
(Model 512, John W Hock, Florida, USA), with an LLIN
occupied by a light-trap worker, was used to trap mosqui-
toes. Traps set indoors were hung in the sleeping quarters
and traps set outside were hung adjacent to an occupied
temporary, open-sided rain shelter constructed from a
domed one-man tent (Kenya Canvas, Nairobi, Kenya).
Traps were checked and connected by 17:30 and the
light-trap worker replaced the collection cups every
hour until 22:30. e traps inside the houses continued
to run until 05:30 the next morning when the collection
cup was changed for the final hour. For traps set outside,
no collections were made between 22:30 and 05:29 as it
was assumed that all residents would be indoors between
these times. ese times were based on a survey of sleep-
ing times carried out by Battle, recording sleeping times
in rural Nyanza province, and are consistent with previ-
ous assumptions on sleeping times in rural areas and the
scope of Anopheles activity [1, 83]. Between 05:29 and
06:30, a final hour of trapping was carried out both inside
and outside. Supervisors made random checks through-
out the night, every night, to ensure traps were running
and set up correctly.
Mosquitoes were killed by freezing, and morphologi-
cally identified to genus and species level using morpho-
logical keys [84, 85]. A subsample of female Anopheles
that were neither blood fed, gravid nor semigravid were
dissected for determination of parity status as a proxy
for age [86]. Samples were stored in 0.5-ml micro centri-
fuge tubes packed with silica gel crystals and transported
to the Centre for Global Health Research, Kenya Medi-
cal Research Institute/Centers for Disease Control and
Prevention in Kisian, Kisumu (CGHR, KEMRI/CDC),
for further analysis. Sibling species of the An. gambiae
complex were identified using an An. gambiae spe-
cific diagnostic PCR [87]. e presence of P. falciparum
or Plasmodium vivax CSP in specimens was tested by
ELISA using an established methodology used by CGHR,
KEMRI/CDC, adapted from techniques described by
Beier etal. and Wirtz etal. [88, 89].
Population sleeping andbehaviour survey
Questionnaires were used to gather information on the
time people entered and exited their houses in the even-
ing and morning, the time they slept and their use of bed
nets. e head of each household used a digital watch to
complete the questionnaire on behalf of all adults and
children that slept in that house. Questionnaires were
distributed and completed twice during each six-night
sampling period, on a week night and a Saturday night,
and collected the next day. Questionnaires were not dis-
tributed during the sampling week in December 2011
due to the short study period.
Statistical analysis
e location and times of Anopheles feeding behaviour
were analysed using a random-effects negative binomial
model accounting for repeated measurements using
Stata (Version 11, StataCorp LP, Texas, USA). Bivariate
analysis was carried out to assess the role of potential
confounders, not on the causal pathway, against the out-
come of interest. ose variables deemed not significant
Page 5 of 15
Cookeet al. Malar J (2015) 14:259
(p > 0.05) were discarded. Independent variables were
then tested for correlation using a Pearson’s product-
moment correlation test. ose demonstrating multi-
collinearity (correlation>0.90) were identified and one
variable, from the two tested, chosen for the model. In all
analyses, a predetermined significance level of p< 0.05
for the incident rate ratio (IRR) was sufficient evidence
that the null hypothesis could be rejected. A model was
Figure1 Maps of the study site showing the sampling quadrants, and phases of recruitment. a Construction of sampling grid and identification of
building structures using aerial maps; b Survey of sampling grid to identify and exclude quadrants without breeding sites or with fewer than four
houses; c Randomization of houses within the remaining quadrants and sequential recruitment of four houses per quadrant; d An example of a
typical night of sampling, with six quadrants active and six quadrants deactivated.
Page 6 of 15
Cookeet al. Malar J (2015) 14:259
deemed a poor fit if the Wald Chi squared test statistic
(χ2) had a p>0.05.
To determine whether there were groups within the
local human population that were at greater risk of expo-
sure to malaria vectors than others, the mean catch of An.
funestus s.l., An. arabiensis and An. gambiae s.s. trapped
by hour and location were extracted for each sampling
week and the man biting rate (MBR) for each hour that
the traps were running was calculated for both locations.
e potential exposure of individuals to these vectors
was then estimated using each individual’s responses to
the sleeping questionnaire for the sampling week that the
questionnaire was completed, thus creating a dataset that
reflected any change to the vector-human interaction
throughout the sampling year.
Human exposure to malaria vectors and the true pro-
tective efficacy of bed nets was calculated using methods
adapted from the work described by Geissbuhler et al.,
based on the formulae published by Killeen etal. [37, 45]
(see Additional file 1). ese earlier studies calculated
the protective efficacy of bed nets as a result of reduced
exposure to An. gambiae bites, incorporating the propor-
tion of the population indoors but not asleep and those
indoors and asleep under an ITN. In the present study,
calculations were made for exposure to the three primary
vectors An. funestus s.l., An. arabiensis and An. gambiae
s.s.
In this region it is rare for individuals to sleep outdoors
at night, and this was excluded from the analysis. A limi-
tation of this method is the necessary assumption that the
protective efficacy of the bed nets (P) is uniform between
houses, and that each individual used an identical model
and age of bed net, and used it correctly. ere was a
mass distribution of LLINs during this study, but there
was evidence of older LLINs in use within the recruited
households. In this calculation the functional protective
efficacy of LLINs is assumed to be 80% (P=0.8), which
had been adopted by previous studies informed by exist-
ing evidence from experimental hut trails [37, 45]. We
have also reported estimates that assume functional pro-
tective efficacy to be 100% for comparison purposes with
other studies. Pairwise Kruskal–Wallis (K–W) analysis
was used to compare P* between participant age groups
and month of data collection.
Ethics
Informed consent was obtained from those participating
in the study. is work was reviewed and approved by the
KEMRI/National Ethics Review Committee, Kenya (SSC
No. 2007) and by the Ethics Committee of the London
School of Hygiene and Tropical Medicine, UK. Informed
consent was obtained from the head of each household
recruited into the study and from every light-trap worker.
Results
Anopheles species identication andfeeding behaviour
A total of 3,330 Anopheles were trapped between June
2011 and May 2012. Based on morphological identifica-
tions, the greatest proportion of female Anopheles were
the vector species An. funestus s.l. (n=1,475, 44%) and
An. gambiae s.l. (n = 263 8%). Anopheles funestus s.l.
was the species most frequently trapped both inside and
outside houses (inside: n=1,099, 69% of females caught,
and outside: n=376, 33%). A total of 2,750 (99%) of all
Anopheles trapped were examined using An. gambiae-
specific diagnostic PCR to identify sibling species. e
remaining 1% of samples examined did not contain suf-
ficient material to analyse. Using PCR, 145 were iden-
tified as An. arabiensis (inside: n = 110, and outside:
n=35) and five samples were confirmed as An. gam-
biae s.s. (inside: n=5, and outside: n=0). e remain-
der did not amplify when tested, the majority of which
had been morphologically identified as An. funestus s.l.
Due to logistical constraints, PCR was not carried out
to identify members of the An. funestus complex. is
is a recognized limitation of this study which should be
addressed by ongoing studies to genetically sequence
these specimens.
When comparing indoor and outdoor catches directly
at times when traps were running concurrently, there
was evidence that An. funestus s.l. were more likely
to feed indoors than outdoors (IRR=1.5, 95% CI: 1.1-
2.010, p = 0.006) (Table 1). is species complex was
also more likely to be trapped indoors when carry-
ing eggs, when either semigravid or gravid (IRR = 4.5,
95% CI 2.5–8.2, p< 0.005). Combined, a total of 18.9%
(n=174) An. funestus s.l. were identified as either semi-
gravid or gravid. For collections carried out between the
hours of 17:30 and 22:29 and 05:30 and 06:30 when peo-
ple are likely to be outside of a net, An. funestus s.l. bit-
ing increased indoors between 18:30 and 19:29 (
x
=0.18,
95% CI 0.14–0.22) and 19:30 and 20:29 (
x
=0.13, 95%
CI 0.10–0.15) with a third rise between 21:30 and 22:29
(
x
=0.16, 95% CI 0.12–0.20) (Figure2). However, there
was no evidence to indicate that the numbers recorded
for these hours differed significantly (p > 0.1). When
compared directly to the numbers caught between
21:30 and 22:29, fewer An. funestus s.l. were likely to be
trapped indoors very early in the evening (17:30–18:29:
p<0.001), between 20:30 and 21:39 (p=0.020) and in
the early morning, 05:30–06:29 (p<0.001). Outdoors An.
funestus s.l. females fed later between 19:30 and 20:29
(x=0.21, 95% CI 0.13–0.22) carrying through to 21:30–
22:29 (x=0.076, 95% CI 0.06–0.096, p<0.001).
Anopheles arabiensis was also caught in both indoor
(n=67) and outdoor traps (n=35) and, was also more
likely to feed indoors (IRR = 1.9, 95% CI 1.03–3.4,
Page 7 of 15
Cookeet al. Malar J (2015) 14:259
p=0.038) (Table1). A total of 12.7% (n=13) An. ara-
biensis were identified as either semi-gravid or gravid.
Indoor An. arabiensis biting activity started in the early
evening between 18:30 and 19:29 (
x
= 0.012, 95% CI
0.0042–0.020) and 19:30 and 20:29 (
x
=0.011, 95% CI
0.0033–0.018) with a second rise in MBR between 21:30
and 22:29 (
x
= 0.026, 95% CI 0.015–0.040) (Figure2).
However, there was no evidence to indicate that the two
periods of increased activity differed in intensity (p>0.1).
Outdoor biting started later in the evening with activity
increasing between 19:30 and 20:29 (
x
=0.019, 95% CI
0.01–0028) and continuing until 22:29 (p<0.001). ere
was significantly less activity in the early hours of the
evening (18:30–19:29: p<0.05) when compared to the
numbers recorded between 21:30 and 22:29.
A total of four An. gambiae s.s. females were trapped
between the hours of 17:30 and 22:29 and 05:30 and
06:29, all indoors. e increase in the indoor mean hourly
MBR occurred between 20:30 and 21:29 (
x
= 0.0027,
95% CI −0.0010 to 0.0064). ere were insufficient data
to make a comparison between the hour of biting or the
numbers of An. gambiae s.s. found inside and outside.
A smaller number of samples were morphologically
identified as those that have been previously documented
in Kenya and may represent infrequent or second-
ary malaria vectors [14, 73, 90]. Of these, An. coustani,
Anopheles demeilloni, An. maculipalpis, Anopheles pre-
toriensis, Anopheles squamosus, and Anopheles rufipes
females were predominantly trapped outdoors (p<0.05).
Samples of other species were too few in number to fit
the model (Table1).
ere was evidence that older Anopheles females
that had previously laid eggs (parous mosquitoes)
Table 1 Female Anopheles morphologically identied vector
species between the hours of 17:30 and 22:29 and 05:30
and06:30
NC negative binomial statistical model could not converge.
Outcome
measure Total number
Anopheles
caught bytrap
location
Comparison betweenindoors
andoutdoors withoutdoor
IRR=1
Indoor Outdoor Indoor IRR
(95% CI) P Wald χ2 (p)
Primary African malaria vector species
An. funestus
s.l. 544 376 1.5 (1.1–
2.010) 0.006 18 (<0.001)
An. arabi-
ensis
67 35 1.9 (1.03–3.4) 0.038 17 (0.0023)
An. gambiae
s.s. 4 0 NC NC NC
An. nili 1 1 NC NC NC
Other documented Kenyan Anopheles species
An. coustani 19 151 0.15 (0.090–
0.25) <0.001 64 (<0.001)
An. demeil-
loni
63 148 0.42 (0.26–
0.68) <0.001 37 (< 0.001)
An. dthali 2 4 0.52 (0.080–
3.3) 0.49 2.3 (0.32)
An. gibbinsi 1 11 0.13 (0.015–
1.08) 0.059 3.6 (0.059)
An. longipal-
pis
2 5 NC NC NC
An. maculi-
palpis
17 55 0.31 (0.16–
0.58) <0.001 25 (<0.001)
An. natal-
ensis
1 3 NC NC NC
An. parensis 1 2 NC NC NC
An. preto-
riensis
9 29 0.41(0.18–
0.94) 0.035 9.02 (0.011)
An. rufipes 5 26 0.204 (0.078–
0.54) 0.001 13 (0.0012)
An. salbaii 2 7 NC NC NC
An. squamo-
sus
3 21 0.22 (0.056–
0.86) 0.029 9.6 (0.0081)
An. symesi 4 4 1.03
(0.22–4.7) 0.97 0.00 (0.97)
An. ziemanni 1 1 NC NC NC
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
ruohrepdeppartselamefnaeM
An. arabiensis
Outdoors
Indoors
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
ruohrepdeppartselamefnaeM
An. funestus
a
b
Hourly catch data
unavailable between
22:30-05:29
Hourly catch data
unavailable between
22:30-05:29
Figure2 Mean hourly catch of a Anopheles arabiensis and b Anoph-
eles funestus s.l. caught by CDC light-traps. Traps were emptied hourly
between 17:30 and 22:29 each evening and between 05:30 and 06:29
the next morning.
Page 8 of 15
Cookeet al. Malar J (2015) 14:259
were more likely to bite outdoors (p<0.05) and, con-
versely, that younger nulliparous females were more
likely to feed indoors (p< 0.05). However, when ana-
lysing the catch of malaria vector species: An. funestus
s.l. (55% parous indoor, 78% outdoor), An. arabiensis
(78% indoor, 80% outdoor) and An. gambiae s.s. (100%
indoor, 0% outdoor) there was either insufficient data
to fit a model, or the model did not fit well (Wald χ2
p > 0.05). ere was a similar difficulty when fitting
models to the other Anopheles species that had been
dissected (Wald χ2 p > 0.05), with the exception of
An. coustani. A total of 44 An. coustani were success-
fully dissected, with 77% (n=34) identified as parous
(indoor n= 4, 12% and outdoor n=30, 88%). ere
was some evidence that parous An. coustani females
were more likely to forage outdoors (IRR=0.26, 95%
CI 0.091–0.77, p=0.05).
Entomological inoculation rate (EIR)
A subset (n = 2,706, 98%) of female Anopheles were
tested for the presence of P. falciparum and P. vivax CSP,
these samples included those from indoor traps left run-
ning between 22:30 and 05:30. Five samples were not
tested due to sample damage. Of the samples tested,
P. falciparum CSP was detected in 44 samples (1.6%)
(Table2). e majority of infected Anopheles were mor-
phologically identified as An. funestus s.l. (n=30, 69%,
2.0% CSP positive). Other morphologically identified
species included An. demeilloni (2.7% CSP positive) An.
gibbinsi (7.7% CSP positive) and An. longipalpis (12.5%
CSP positive). One sample of An. arabiensis (contained P.
falciparum CSP (0.7%). Plasmodium vivax CSP was not
detected from any of the samples tested.
e estimated annual EIR was calculated using the
indoor collections, as indoor data spanned the complete
sampling night from 17:30 to 05:30 the next morning. e
EIR for this region, was 20 (95% CI 17–22) P. falciparum-
infected bites per person per year. Estimates of the mean
indoor EIR per person per night were calculated for the
study period and these ranged between no infected bites
per person per night and a maximum of 0.27 (95% CI
0.22–0.32) recorded in March 2012.
Protective ecacy ofbed nets
e true mean bed net protective efficacy (P*), calculated
as efficacy against the combined bites of primary malaria
vectors (see Additional file1) was estimated at 51% (95%
CI 50–53%) if nets were assumed to offer protection
against 80% of vector bites and 64% (95% CI 62–66%) if
they were 100% effective. is equates to a drop in effi-
cacy of 29% (95% CI 27–30%) if bed nets are assumed to
offer protection against 80% of vector bites when used cor-
rectly. e P* calculated for each sampling month ranged
from 45 to 56% (Figure3). Protective efficacy varied sig-
nificantly across the sampling year when taking into con-
sideration the protection offered against the bites of all
primary malaria vectors (K–W χ2=37, 11 df, p=0.0001),
An. funestus s.l. alone (K–W χ2=37, 11 df, p=0.0001),
An. arabiensis (K–W χ2=230, 11 df, p=0.0001) and An.
gambiae s.s. (K–W χ2=170, 11 df, p=0.0001).
e estimated proportion of indoor and outdoor expo-
sure to malaria vectors fluctuated significantly across the
sampling year (K–W χ2=147, 11 df, p=0.0001) (Fig-
ure3), with a peak in the proportion of outdoor expo-
sure to the primary vectors in early October 2011 (with
bed net: 27%, 95% CI 19–34% and without bed net:
9.7%, 95% CI 7–12%). When tested using the two-sam-
ple Mann–Whitney test, there was no significant differ-
ence in the outdoor exposure to malaria vectors between
men and women (M–W, z=0.35, p=0.72), or between
Table 2 Percentage ofP. falciparum CSP positive, blood fed and parous primary vector species trapped betweenthe
hours of17:30 and22:29 and05:30 and06:30
Primary vector species % CSP positive % blood fed % parous
An. funestus s.l. 2.0% (n = 30) 14.1% (n = 130) 66% (n = 126)
An. arabiensis 0.7% (n = 1) 13.7% (n = 14) 79% (n = 11)
An. gambiae s.s. 0.0% (n = 0) 0.0% (n = 0) 100% (n = 1)
An. nili 0.0% (n = 0) 50% (n = 1) 0.0% (n = 0)
30%
40%
50%
60%
70%
80%
90%
)
*P(ycaciffeevitcetorpeurT
80% True protecve efficacy (P*)
Figure3 Monthly mean true protective efficacy of nets (P*) against
the combined bites of primary malaria vectors. For the purpose of
this study, primary malaria vectors are defined as An. nili, An. funestus
s.l. and An. gambiae s.l.
Page 9 of 15
Cookeet al. Malar J (2015) 14:259
participants’ exposure on a week night as opposed to a
night at the weekend (M–W, z=1.1, p=0.26).
e P* of LLINs also varied with the age group of par-
ticipants (K–W χ2=147, 18 df, p = 0.0001), for An.
funestus s.l. alone (K–W χ2=144, 18 df, p =0.0001),
An. arabiensis (K–W χ2=119, 17 df, p=0.0001) but it
was not significant for the small number of An. gambiae
s.s. trapped (K–W χ2=14, 13 df, p> 0.1). When indi-
vidual age groups were compared against the reference
age group of under 9years, those aged 10–59 had signifi-
cantly different levels of P* than those aged under 9years
(p<0.001), and examination of the medians and means
indicate that the levels of P* are lower in these age groups
(Figure4).
Indoor versusoutdoor exposure
Based on the times recorded during the survey, it was
estimated that individuals not using bed nets would
experience a mean of 95% of their total vector exposure
inside their houses (95% CI 95–96%), and 5% outdoors
(95% CI 4–5%). It was estimated that a mean 31% (95% CI
29–33%) of their daily exposure occurred indoors before
they went to bed. A mean of 64% (62–66%) of daily expo-
sure occurred while they were asleep. When individuals
used bed nets their estimated mean exposure reduced
from 1.3 vector bites per night (95% CI 1.2–1.3%) to 0.47
(95% CI 0.44–0.51) (Figure5).
Discussion
In common with the previous work carried out in Zam-
bia and Tanzania to determine the protective bed net effi-
cacy, this study highlights the importance of integrating
human behaviour into the assessment of human-vector
contact in relation to malaria transmission [16, 37, 38,
45]. Despite predominantly endophagic primary vec-
tors in this region, the overall P* was low at 51% (95% CI
50–53%) and this may be explained by exposure occur-
ring indoors at times of the evening before nets are used
which equates to 31% of total mean daily exposure. is
is substantially lower than the bed net efficacy using
similar methods reported from rural Tanzania [37], but
higher than that reported from urban Tanzania where
An. arabiensis is predominantly exophagic [45]. In the
present study, 90–95% of vector exposure was calculated
to occur within the house if LLINs were not used, which
is similar to levels reported for An. funestus s.l. in Zam-
bia [38] and the results of a study of matched surveys of
human and mosquito behaviour from Burkina Faso, Tan-
zania, Zambia, and Kenya [91]. e use of LLINs in the
present study reduced an individual’s exposure from 1.3
bites per night to 0.47 bites per night. In agreement with
a recent study carried out in Western Kenya the major-
ity of exposure occurred indoors [53], an estimated 65%
of mean daily exposure occurred during sleeping hours,
indicating that nets still may offer personal protection in
an area of low transmission.
e two primary vector species An. funestus s.l. and
An. arabiensis were both active inside and outside
from 18:30 onwards, two-and-a-half hours before the
mean time local residents reported going to bed. When
studying mosquito activity outside times when indi-
viduals are likely to be asleep, the peak hours of biting
varied between species, but universally very little activ-
ity occurred during the early evening (17:30–18:29) and
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
ycaciffetendebevitcetorpeurtnaeM
(P=0.8)
Age group (years)
Figure4 Variation in mean true protective efficacy of nets (P*) by age group of participants. Calculations based on a bed net efficacy where nets
are estimated to prevent 80% of bites when used correctly.
Page 10 of 15
Cookeet al. Malar J (2015) 14:259
morning (05:30–06:29). e latter may be due to the low
dawn temperatures in this area, but the former may have
been influenced by the heat and light intensity in the
hours before dusk. During the times studied, An. funes-
tus s.l. demonstrated a distinct bimodal pattern of indoor
feeding activity, with the first increase in biting activity
between 18:30 and 20:30 followed by a second at 21:30
and 22:29. Although there was no evidence that these
periods differed in intensity (p <0.05), they were both
significantly higher than the preceding or interim hours
(p<0.05).
e residents of this area reported that 90% used nets,
greater than that previously recorded in Kakamega in the
western Kenyan highlands (56%) [92], or by the Malaria
Indicator Survey in 2010, 61% [62]. However, the former
survey was conducted in a different area with a different
ethnic populations. Furthermore, the area of the current
study was a research site where active health teams had
been working for the past 2years and data were collected
during a year of mass LLIN distribution with prolonged
marketing campaigns to increase awareness and adher-
ence. Net use recorded in the present study may not
reflect wider patterns of bed net use.
It is important to note that this study, in common
with previous work [16, 37, 38, 45], did not estimate
the area-wide effects on the vector population that may
result from universal coverage of LLIN [54]. It has been
shown that mass distribution will reduce transmission of
principally endophagic vectors by reducing the reservoir
of disease [16]. e P* estimated here may be an underes-
timation as it does not include any potential community-
wide effects.
Anopheles funestus s.l. was the most abundant primary
vector species trapped in the area throughout the year
with an indoor MBR of 0.15–1.2 and an outdoor MBR of
0.13-1.2 bites per person per night. Similar findings were
reported from lowland areas in Nyanza Province [93].
Anopheles funestus s.s. is considered the anthropophagic
exception in a complex of zoophagic species [94], so
it is likely that the An. funestus s.l. in this study contain
other morphologically identical members of the complex.
Work continues to genetically sequence the full set of
anophelines caught to confirm species identities. Alter-
natively, it is possible that the LLIN and IRS use in this
area has induced this species to seek alternative hosts.
Such phenotypic, plastic feeding behaviour has been
observed in An. gambiae s.s., which can demonstrate
zoophilic behaviour in field conditions if their preferred
human hosts are not readily available [95]. is shift
from anthropophagy to zoophagy was noted in Kenyan
0
0.05
0.1
0.15
0.2
0.25
0-4
5-9
10-14
15-19
20-24
25+
Mean biting rate (per person per night)
Age (years)
Outdoors
Indoors
Indoors in bed
MBR indoors
MBR outdoors
Outdoor hourly catch data is
unavailable between 22:30-05:29
Figure5 Combined hourly man biting rate (MBR) for Anopheles arabiensis and Anopheles funestus s.l. Biting activity overlaid on the reported move-
ments of the local human population indoors and outdoors before, during and after sleep (mean hours). Data for outdoor hourly MBRs were not
collected between the hours of 22:30–05:29. For diagrammatic proposes, data for indoor MBR estimates between the hours of 22:30–05:29 were
divided equally across the 7 h of collection. Data collected between June 2011 and May 2012.
Page 11 of 15
Cookeet al. Malar J (2015) 14:259
An. funestus s.l. populations in response to permethrin-
impregnated eaves-sisal curtains [42] but again no data
were given as to the sibling species of the complex.
Anopheles arabiensis was also present in the study site,
with a peak MBR of 0.12 bites per person per night. is
is not consistent with either the historical distribution of
this species or recent work carried out in the Nandi hills,
where An. gambiae s.s. females were more prolific than
An. arabiensis [72, 96]. However, these findings do align
with the observations of Ndenga etal. who surveyed lar-
val breeding sites above 1,500m in neighbouring West-
ern province, where An. arabiensis represented a third of
the An. gambiae s.l. larvae collected [74]. Anopheles ara-
biensis is found at high densities in lowland Nyanza and it
is therefore conceivable that this species has encroached
upon the neighbouring highland fringe areas, filling the
niche left by An. gambiae s.s., which was selectively tar-
geted by local control efforts [41, 44, 52, 68]. It is possible
that the distribution of An. arabiensis may have always
included highland areas, with this species being over-
looked by those studies that predominantly used indoor
traps that do not target outdoor-resting and feeding spe-
cies [74].
EIR estimates were higher than those previously
reported for similar areas of western Kenya [49, 63].
Ndenga et al. reported an EIR of 0.2–1.1 in highland
areas of the neighbouring district Kisii Central and in
Kakamega (neighbouring province) and Githeko et al.
recorded a peak EIR of 12.8 from comparable elevations
in Kakamega [49, 63]. ose studies may have underes-
timated the EIR as they used pyrethrum spray catches,
which will not trap endophagic and exophilic Anopheles
that are infected but exit the house early. Furthermore,
in the current study, the site was specifically selected
due to high P. falciparum prevalence and incidence and
high indoor-resting densities of anopheline mosquitoes.
Within this area of higher transmission, only houses
within quadrants that contained breeding sites were
selected, and thus the EIR from the present study could
be interpreted as that of a transmission ‘hotspot’ [97].
In common with studies that used methods other than
human landing catches (HLC) to estimate EIR [98], the
present study did not include an estimation of outdoor
transmission and thus potentially overestimated the total
exposure an individual will experience throughout the
year. In addition to these limitations, it is also possible
that the EIR may be overestimated. is study did not
include steps to limit false-positive CSP-ELISA results by
reanalysing the homogenate therefore it is possible that
false-positives were included in the EIR estimate [99].
Across all Anopheles species trapped, there was evi-
dence (p < 0.05) that females carrying eggs were 4.5
times more likely to feed indoors, potentially presenting a
higher transmission risk indoors as these mosquitoes are
older than nulliparous females. However, unfed parous
females without eggs are used as a proxy for older females
and were more likely to bite outdoors (p<0.05) and, con-
versely, younger nulliparous females were more likely to
feed indoors (p<0.05). erefore, the number of gravid
females caught in traps indoors may reflect the recruit-
ment of the female indoor-resting population that are
attracted to the CDC-light trap during egg development.
e findings of this study support the hypothesis that
the levels of both LLIN and IRS coverage are currently
not sufficient to interrupt transmission in this setting. IRS
should be an effective control tool in a region where the
majority of exposure occurs inside the house and should
complement the use of LLINs if biting occurs before
times of net use and/or the observed exophagy is also
accompanied by indoor-resting behaviour. IRS was and is
still implemented in Rachuonyo district but coverage at
the time was not universal, with 38% of houses sprayed
in the previous 12months [62]. Improving the coverage
of the current IRS campaign may be more effective, but
if conducted poorly it may also encourage the develop-
ment of insecticide resistance. erefore, as the majority
of exposure is currently occurring indoors, measures to
bar entry to Anopheles may be a cost-effective option to
complement existing interventions. ese could include
the use of ceilings, window and door screens, measures
that have successfully reduced the number of Anopheles
indoors both historically and in experimental hut trials
[100, 101].
An important limitation of the present study is the
use of light-traps outdoors. Light-traps have been in use
since the early part of the 20th century, and have been
used widely in a variety of transmission settings, includ-
ing Africa [56, 82, 102]. ese traps work on the principle
that the mosquito is drawn into the ‘dazzle zone’, at which
point the fan mechanism sucks them into the trap [78,
102]. e exact mechanics of this process and the extent
to which it is species-specific are not well understood
[102, 103]. e type and size of catch may be influenced
by a number of factors, including the species of mosquito
[78], the model of trap and the wavelength of the light
used [102] and whether the strength of illumination can
be kept constant. Indeed, it is reasonable to assume that
the traps used during the present study could not achieve
a uniform level of illumination throughout the night.
Light-traps have several practical advantages: they are
commercially available which aids standardisation [104],
they are easily accepted by communities within study
sites [105] and they have low running costs. A number of
experiments have been carried out to establish whether
light-trap catches correlate well with those from HLC
and some studies have indicated that light-trap catches
Page 12 of 15
Cookeet al. Malar J (2015) 14:259
of Anopheles have relatively high sporozoite rates [103–
105]. Other studies have reported no significant differ-
ence between sporozoite rates from light-traps and HLC,
with a corresponding similarity in parity rates between
these trapping methods [106–108]. With a lack of stand-
ardisation between studies, there appears to be no defini-
tive evidence to indicate whether light-traps, with or
without human bait, can catch the anthropophagic vec-
tor population.
It has been claimed that CDC light-traps cannot be
used outdoors [109], yet this appears to be based on lim-
ited evidence. e small number of studies that assessed
HLC with light-traps hung outside tended to place the
light-traps directly under the eaves of houses [110, 111],
either with an accompanying light-trap inside the same
house [110, 112] or with no accompanying human bait
[110, 113]. Costantini etal. (1998) did hang CDC light-
traps away from houses, under a thatched rain shelter
with human bait, but found no correlation between its
catch and that of HLC when comparing An. gambiae s.l.
However, when An. funestus numbers were compared
there was a density-dependent correlation between the
catch of the outdoor HLC and the CDC light-trap [114].
e authors concluded that outdoor traps were not
effective but acknowledged that this was based on a lim-
ited data set [114]. Overgaard etal. (2012) used a CDC
light-trap with a UV bulb outdoors but with no human
bait and reported a correlation between the numbers of
An. gambiae s.l. and An. melas trapped by the two light-
traps. e authors did, however, express some doubts
about the practicality of using light-traps outdoors with
such low numbers and such high levels of variability
between catches [110]. Currently, there is insufficient
evidence to definitively dismiss the use of light-traps
outdoors as a means of collecting anthropophagic
Anopheles. Where HLC is not available, light-traps
remain one of the few viable trapping methodologies not
designed solely to catch the resting Anopheles popula-
tion, and may represent a useful tool to catch the vector
population.
e present study contributes to the knowledge of both
primary and secondary vector species dynamics in the
fringe area of the western Kenyan highlands. e exist-
ence of predominantly exophagic potential secondary
vector species such as An. coustani and An. demeilloni
should be an important consideration when planning
future control efforts, as they are likely to be overlooked
during campaigns targeted at the primary vector species
that feed indoors during sleeping hours. ese species
have the potential to maintain low levels of transmis-
sion in this area. It is therefore vital that entomologi-
cal surveillance should be carried out on a regular basis
in this area and in other regions of unstable malaria
transmission targeted for malaria control or future
malaria elimination.
Conclusions
e present study indicates that primary vectors are more
likely to feed indoors in the fringe of the western Kenyan
highlands. Exophagic behaviour does occur, but when
considered in conjunction with the human behaviour
recorded in this study, the majority of exposure occurs
indoors. However, surveillance must be maintained to
detect any shift in behaviour and to monitor exophagic
populations of potential secondary vectors. Greater expo-
sure to primary vector bites occurs indoors in the early
evening when LLINs are not used. e early biting habit
of these vectors was shown to reduce the protective effi-
cacy of LLINs, although the actual estimate of protec-
tive efficacy calculated here does not take into account
the mass effect on mosquito populations when an entire
community uses nets. ere are indications that expo-
sure and therefore protective efficacy of nets varies with
both an individual’s age and across seasons. A key aspect
of man-vector contact is the behaviour of the human
local population, and this is not static across the seasons.
ese results indicate that LLINs may theoretically reduce
malaria vector exposure if used correctly, but that other
measures are required to protect against early indoor bit-
ing. Regular surveillance of both vector behaviour and
domestic human-behaviour patterns are needed for the
planning of future control interventions in this region.
Abbreviations
CSP: circumsporozoite protein; ELISA: enzyme-linked immunosorbent
assay; EIR: entomologial inoculation rate; GMEP: Global Malaria Eradication
Programme; HLC: human landing catches; IRR: incident rate ratio; IRS: indoor
residual spraying; ITN: insecticide-treated nets; KEMRI/CDC: Kenya Medi-
cal Research Institute/Centers for Disease Control and Prevention in Kisian,
Kisumu; LLIN: long lasting insecticidal net; MBR: man biting-rate; P*: true
protective efficacy; PCR: polymerase chain reaction.
Authors’ contributions
MC, JS, JC and CD conceived and designed the study. MC, SK, RO, CO, EA, DM,
DN, LA, EA, and JS performed the experiment, contributed to study design
and entered and cleaned the data. MC performed the data analysis. MC, JS
and JC wrote the paper. All authors read and approved the final manuscript.
Author details
1 Faculty of Infectious and Tropical Diseases, London School of Hygiene
and Tropical Medicine, London, UK. 2 Kenya Medical Research Institute Centre
for Global Health Research/Centers for Disease Control and Prevention,
Kisumu, Kenya. 3 Johns Hopkins Malaria Research Institute, Johns Hopkins
Bloomberg School of Public Health/Macha Research Trust, Choma, Zambia.
Additional le
Additional le1: Calculation of true bed net protective efficacy. The
document details the method used to calculate true bednet protective
efficacy.
Page 13 of 15
Cookeet al. Malar J (2015) 14:259
Acknowledgements
We are grateful to the staff of the Highland MTC team for their hard work and
we would particularly like to thank, Silas Otieno, Diana Okello-Mburu and
Wycliffe Odongo. We would also like to thank the staff at the Centre for Global
Health Research, Kenya Medical Research Institute/Centres for Disease Control
and Prevention, (CGHR, KEMRI/CDC) Kisumu and the Ifakara Health Institute
(Tanzania) for their support of this project. We thank Brandy St Laurent and Neil
Lobo at the Eck Institute for Global Health, University of Notre Dame, Indiana,
USA for arranging and carrying out the sequencing of samples. We are grateful
to the residents of Lwanda and Siany (Rachuonyo South) for their hospitality,
tolerance and their contribution to this work. We would particularly like to
thank our guides George Onyango and Hezron Adika for their invaluable help.
This work was funded by the MTC by the Bill & Melinda Gates Foundation
(USA) Grant Number 45114 and a DTA studentship Grant from the Medical
Research Council (UK). This article has been approved by the Director of the
Kenya Medical Research Institute.
Compliance with ethical guidelines
Competing interests
The authors declare that they have no competing interests.
Received: 23 December 2014 Accepted: 6 June 2015
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