Environmental variables associated with anopheline larvae distribution and abundance in Yanomami villages within unaltered areas of the Brazilian Amazon
Sánchez-Ribas et al. Parasites & Vectors
Environmental variables associated with anopheline larvae distribution and abundance in Yanomami villages within unaltered areas of the Brazilian Amazon
Jordi Sánchez-Ribas 1 2
Joseli Oliveira-Ferreira 2
John E. Gimnig 0
Maycon Sebastião Alberto Santos-Neves 1
Teresa Fernandes Silva-do-Nascimento 1
0 Center for Disease
1 Laboratório de Mosquitos Transmissores de Hematozoários, Instituto Oswaldo Cruz-FIOCRUZ , Rio de Janeiro , Brazil
2 Laboratório de Imunoparasitologia, Instituto Oswaldo Cruz-FIOCRUZ , Rio de Janeiro , Brazil
Background: Many indigenous villages in the Amazon basin still suffer from a high malaria burden. Despite this health situation, there are few studies on the bionomics of anopheline larvae in such areas. This publication aims to identify the main larval habitats of the most abundant anopheline species and to assess their associations with some environmental factors. Methods: We conducted a 19-month longitudinal study from January 2013 to July 2014, sampling anopheline larvae in two indigenous Yanomami communities, comprised of four villages each. All natural larval habitats were surveyed every two months with a 350 ml manual dipper, following a standardized larval sampling methodology. In a third study area, we conducted two field expeditions in 2013 followed by four systematic collections during the long dry season of 2014-2015. Results: We identified 177 larval habitats in the three study areas, from which 9122 larvae belonging to 13 species were collected. Although species abundance differed between villages, An. oswaldoi (s.l.) was overall the most abundant species. Anopheles darlingi, An. oswaldoi (s.l.), An. triannulatus (s.s.) and An. mattogrossensis were primarily found in larval habitats that were partially or mostly sun-exposed. In contrast, An. costai-like and An. guarao-like mosquitoes were found in more shaded aquatic habitats. Anopheles darlingi was significantly associated with proximity to human habitations and larval habitats associated with river flood pulses and clear water. Conclusions: This study of anopheline larvae in the Brazilian Yanomami area detected high heterogeneities at micro-scale levels regarding species occurrence and densities. Sun exposure was a major modulator of anopheline occurrence, particularly for An. darlingi. Lakes associated with the rivers, and particularly oxbow lakes, were the main larval habitats for An. darlingi and other secondary malaria vectors. The results of this study will serve as a basis to plan larval source management activities in remote indigenous communities of the Amazon, particularly for those located within low-order river-floodplain systems.
Anopheline larvae; Environmental drivers; Sun exposure; An; darlingi; Yanomami
Malaria is a preventable and treatable parasitic disease
but still poses a high burden in some countries of
Latin America, particularly Brazil which was
responsible for 24% of the total number of cases in 2015
]. Disease distribution is heterogeneous within
endemic regions in the Neotropics, and some
populations are at high risk of acquiring malaria, such as
indigenous communities in the Amazon basin and
Central America [
]. A prime example is the
Yanomami people, considered the largest,
semiisolated indigenous group that inhabits a 192,000 km2
area split between Brazil and Venezuela. Malaria
incidence is unevenly distributed across the Brazilian
Yanomami Indian Reserve with some areas with very
reduced malaria receptivity and other localities that
are hotspots of intense malaria transmission,
including for Plasmodium falciparum . Hotspots in
indigenous areas should be priority target areas for
malaria elimination in Latin America, as in addition
to the severe malaria burden on the indigenous
populations, they may serve as a continuous source of
Plasmodium spp. infections for neighbouring
In line with the current global drive for malaria
elimination, most Latin American countries have
adopted country or sub-regional strategies for the
elimination of Plasmodium spp. transmission [
November 2015, Brazil launched its plan for
countrywide malaria elimination, with a first phase focusing on
sustainably eliminating P. falciparum transmission [
In Brazil, malaria control is mainly based on early
diagnosis and treatment and adult vector control strategies
such as indoor residual spraying (IRS) and long-lasting
insecticidal nets (LLINs) [
]. These strategies, which
target primarily endophagic and endophilic mosquitoes,
may have limited effectiveness against Neotropical
malaria vectors which frequently feed and rest outdoors.
Consequently, classical anti-adult measures may only
partially suppress transmission due to Anopheles
darlingi, the main Amazon malaria vector [
additional vector control tools are required to help to
further reduce malaria in Latin America. Novel vector
control strategies to tackle outdoor transmission include
long-lasting insecticidal hammocks (LLIH) for forest and
mobile populations who may sleep outdoors [
topical repellents for personal protection  and spatial
]. All these strategies aim to reduce the
contact between humans and exophagic host-seeking
malaria vectors and in the case of LLIH, they may also
minimize indoor exposure to mosquito bites in
indigenous dwellings [
Also, there is a renewed interest in strategies targeting
anophelines during their most vulnerable aquatic phase.
This approach has been indicated when larval habitats
are few, fix and findable [
]. However, to apply larval
source management (LSM) activities efficiently, a
comprehensive knowledge of the local ecology of
anopheline larvae and their aquatic habitats is required.
This has been considered a major drawback in
implementing LSM activities in many settings [
Nevertheless, LSM is a potential tool to reduce or
eliminate anopheline populations insufficiently controlled by
IRS and LLINs in some malaria-endemic localities of the
Comprehensive information on malaria
epidemiology and vector bionomics will be necessary to
eliminate malaria, particularly in these remote and
hard-to-work indigenous areas. The variability in
malaria risk in the Neotropics and within Indian Reserves
is due to a complex interaction of many ecological
and social determinants of the disease. Among the
factors influencing transmission, entomological
parameters of a few highly competent malaria vectors
such as An. darlingi and An. albimanus are of major
]. The spatio-temporal distribution of
anopheline larvae and thus, adult host-seeking and
pathogen transmitting anophelines depend on
parameters such as the number, quality and size of potential
larval habitats, their distance from blood meal sources
and a wide range of other environmental factors [
Few entomological investigations have been
conducted in nearby areas of the Brazilian Yanomami
Indian Reserve. Suarez-Mutis et al. [
Hutchings et al. [
] focused on sampling adult mosquitoes
in the Padauari river, Amazon State, and Cabral et al.
] reported both adult and larval collections. Also
in Brazil, a larval study was conducted east of the
Indian Reserve [
] while another report summarized the
adult anopheline occurrence in multiple collecting points
within Roraima State [
]. There have been several
entomological reports focusing on adults [
well as larvae [
] in neighbouring areas of
Venezuela. In this publication, we provide the first
detailed anopheline species inventory, identify the
larval habitat preferences and analyze some
environmental drivers that modulate anopheline occurrence
and densities in remote Yanomami indigenous
communities of the Brazilian Amazon. We report
results concerning larval habitats for seven anopheline
species (six species of the genus Anopheles plus
Chagasia bonneae), including the main malaria vector
of the Amazon rainforest, An. darlingi. This
information will help to devise feasible, sustainable and
costeffective LSM activities, targeting mainly An. darlingi
immature forms in resilient transmission hotspots of
the Yanomami endemic area, primarily within
loworder Amazonian river-floodplain systems.
We performed our study in three remote Yanomami
communities in the northernmost region of the
Brazilian Amazon, namely Parafuri, Toototobi and
Marari (Fig. 1). In Parafuri and Toototobi
communities, bimonthly collections were performed during
19 months, from January 2013 to July 2014, a time
when only sporadic malaria cases were reported. A
detailed description of these areas has been provided
]. Briefly, Parafuri is a hilly Amazonian
sub-montane forested area with altitude 440 m above
sea level (masl), and Toototobi community is located
in a low-land Amazonian rainforest (128 masl). In
each field expedition, we spent 15 days in each
Yanomami community and concentrated our samplings in
the same four villages in each community.
The third Yanomami community, Marari, is in a
lowland Amazonian rainforest area (139 masl), which is
drained by first to third order rivers and surrounded by
nearby high mountains. The sampling efforts in the
Marari community consisted of two pilot studies in 2013
and four field collections that covered the long dry
season, from September 2014 to March 2015. In Marari,
there is perennial and periodically intense malaria
transmission, and the community is characterized by
villages with high population density and a high risk of
year-round immigration of parasite carriers from highly
endemic areas outside the Yanomami Indian Reserve.
Larval habitat definition and sampling strategy
We used a defined set of criteria to classify the
natural larval habitats that we encountered in these
Amazonian low-order river-floodplain systems. In
short, association with river flood pulses, seasonality
and degree of sun exposure were the main
characteristics for larval habitat classification. Lakes associated
with the river (LAR), which were subdivided into
oxbow lakes (OX) and non-oxbow lakes (NOX), were
permanent and always associated with river flood
pulses. These larval habitats had a high degree of sun
exposure. Flooded areas associated with the river
(FAAR), which are also associated with river water
levels fluctuations, were always seasonal. These larval
habitats varied in their degree of sun exposure. We
also identified inland water bodies which were out of
the reach of river flood pulses and formed mostly due
to increased rainfall, such as flooded areas not
associated with the river (FANAR), rainfall pools (RP) and
small (SFS) and medium forest streams (MFS). These
aquatic habitats not associated with river flood pulses
were predominantly shaded.
We identified all larval habitats within a 1 km
radius of each village with the help of a local guide.
Larval habitats were sampled following a standardized
methodology. We used a fine-scale laser rangefinder
(Scout DX 1000 ARC, Bushnell®, Overland Park,
USA) to accurately quantify the perimeter of all larval
habitats and after adjusting for the presence of
additional niches adequate for larval proliferation, we
estimated the total effective breeding area (tEBA) for
each larval habitat. We defined the tEBA as the sum
of all those portions of the water body surface that
were suitable for anopheline proliferation. Based on
the tEBA, we conducted some dips for each larval
habitat. Dips were taken from the different EBA
subtypes of all larval habitats. For larger larval
habitats, a small portable inflatable boat was used to
collect larvae that could not be reached from the
edge of the habitat. Each larval habitat constituted a
single record comprised of the larval collections of
different subtypes of EBA. We recorded the total
number of anophelines per dip, and then transferred
larvae from standard 350 ml dippers (BioQuip,
Rancho Dominguez, CA, USA) to plastic tubes with
80% ethanol. We reared a subset of field-collected L4
larvae in individual vials to obtain larval and pupal
skins and their associated adult forms. A more
detailed description of the classification of natural
breeding habitats within low-order river-floodplain
systems, procedures for the location of larval habitats
and the larval sampling methodology used in our
study area have been provided elsewhere [
employed MosqTent traps [
] to collect host-seeking
adult female anophelines during three or four
consecutive nights in each village, alternating during each
field trip between 4 h (18:00–22:00 h) collections at
the same time in the intra, peri and extradomicilliary
environments and 12 h collections in the peridomicily
or extradomicily. These adult collections occurred
concomitantly with the larval samplings. Larvae
(third and fourth-instar) and adults were identified
using the keys of Consoli and Lourenço-de-Oliveira
and Forattini [
Assessment of environmental variables
Larval habitats were geo-referenced with a hand-held
global positioning system (GPS) device. We recorded
environmental variables for each aquatic habitat
during each field survey, including its association with
river flood pulses, seasonality (seasonal or
permanent), sun exposure (shaded, partially sun-exposed or
mostly sun-exposed), presence of submersed
macrophytes, distance to the nearest human habitation,
water turbidity (clear, semi-turbid or turbid) and
water movement (stagnant waters or with some water
movement). Permanent aquatic habitats were those
that had water in all our field visits, while temporary
ones were those that were completely dry on at least
one visit. Sun exposure for each habitat was
categorized as (i) mostly sun-exposed sites if between 75
and 100% of the tEBA of the larval habitat was
exposed to the sun for a reasonable amount of time; (ii)
partially exposed to the sun if between 25 and 75% of
the tEBA was exposed to sunlight; and (iii) shaded if
less than 25% of the tEBA was exposed to direct
sunlight. Typically, water bodies of this last category
were under dense forest cover, and little or no
sunlight reached their tEBA. The distance from each
larval habitat to the nearest dwelling was calculated
using the BaseCamp software (Garmin, Olathe, KS,
USA). Turbidity was determined by collecting a small
sample from the water surface layer with a crystal pot
and determining the visibility of two differential
density black lines drawn on a white paper and
placed on the far side of the pot. If both lines were
visible, only the thickest or none of them, we
classified water turbidity as clear, semi-turbid or turbid,
respectively. Lastly, larval habitats classified with
water movement presented some degree of current
(longitudinal water movement) and some degree of
constant water levels fluctuations due to its
connection with a pulsing-system, such as riverbed pools or
LAR directly connected to the river.
We combined data for each species from the three
communities to obtain a wider picture of anopheline
ecological parameters within the Brazilian Yanomami
Indian Reserve. All three areas are drained by
loworder and clear water rivers, presented the same type
of larval habitats and many species were common in
the three areas. Separate analyses were done for each
species that could be identified. We did not conduct
any analyses on anopheline mosquitoes which we
were unable to identify to species. All descriptive
statistics were adjusted to estimate the number of larvae
per 100 dips.
We analyzed data using a negative binomial
regression, which uses counts as the outcome variable and
is appropriate for overdispersed data where many
counts are zeros. We considered as a dependent
variable the number of larvae adjusted for the
number of dips, which worked as the model offset,
correcting for the differences in the number of dips
per larval habitat, which depended on the tEBA
calculation per larval habitat in each survey [
An. darlingi, the outcome included the total number
of all instars as L1-, and L2-instars of these species
could easily be identified. For all other species, only
the total number of L3- and L4-instars were included
in analyses. We included in our final dataset a total
of 711 data entries for analysis. Visits during which
larval habitats were dry were excluded from the
analysis, but the information was used for determining
the seasonality of the habitat. We conducted
univariate analyses for seven anopheline species from which
An. oswaldoi (s.l.)
An. triannulatus (s.s.)
An. nuneztovari (s.l.)
we retrieved sufficient specimens and explored the
effect of each environmental variable on mosquito
densities independently. We then considered in
multivariate regression models a continuous variable
(distance from larval habitats to nearest Yanomami
dwelling) and up to 6 categorical variables
(association with flood pulses, seasonality, the degree of sun
exposure, turbidity, water movement and presence of
submersed macrophytes). As we detected strong effect
modification between variables in the adjusted model
for An. triannulatus (s.s.), an interaction term
between seasonality and sun exposure was included in
the analysis to obtain reliable outcomes. For An.
triannulatus (s.s.) and Chagasia bonneae, only five
variables were considered in the multivariate model as
two variables had categories with no mosquitoes
collected. Those comparisons with P < 0.05 were
considered statistically significant.
We entered the data into a database created using the
Epi Info software (Epi Info™, Atlanta, GA, USA). For
processing geo-data and LANDSAT images, we used
ArcGIS software (ESRI, Redlands, CA, USA). Data
management and statistical analyses were done using SAS
software (SAS Institute Inc., Cary, NC, USA).
We collected a total of 9122 anopheline larvae
(including all Anopheles spp. and Chagasia bonneae) from a
total of 177 larval habitats, from where we performed
71,288 dips over the entire study period. We identified a
total of 13 species, four species of the subgenus
Nyssorhynchus [An. darlingi, An. oswaldoi (s.l.), An.
triannulatus (s.s.) and An. nuneztovari (s.l.)], four species
of the subgenus Anopheles (An. mattogrossensis, An.
intermedius, An. guarao-like and An. costai-like), three
species of subgenus Stethomyia (An. kompi, An. thomasi
and An. nimbus), one member belonging to the
Lophopodomyia subgenus (An. squamifemur) and one
species of the genus Chagasia (Chagasia bonneae).
Hereafter, we focus on the seven most abundant species
We identified a total of 1966 (21.6%) late-instar
larvae (third and fourth stage) to species level. We
were unable to identify at species level 5979 (65.5%)
larvae (1970, 1949 and 2060 unidentified larvae in
Toototobi, Parafuri and Marari, respectively), mainly
because they were early instar (first and second
stages) larvae and they were not An. darlingi. We
also identified 1177 (12.9%) early instar An. darlingi
larvae. The results of larvae collections stratified per
Yanomami community are shown in Table 1. The
results stratified by village are provided in
Additional file 1: Table S1.
Table 1 Diversity and number (percentage) of Anopheles
species collected per Yanommami community. We have not
included the 1177 early instar An. darlingi larvae identified in the
table. The number of early instar An. darlingi for each
community was as follows; Toototobi (2), Parafuri (993) and
We identified to species level 671 mosquitoes in
Toototobi community. Anopheles oswaldoi (s.l.) (47.8%)
was the most widely disseminated species and was the
most abundant in three out of four villages, followed in
overall counts by An. mattogrossensis (15.5%) and An.
guarao-like (15.5%). In contrast, An. darlingi was the
predominant species (53.3%) among the 763 anophelines
identified in the hilly submontane rainforest area of
Parafuri community, followed by An. triannulatus (s.s.)
(21.4%) and An. oswaldoi (s.l.) (10.6%). Anopheles
darlingi abundance was markedly heterogeneous
amongst Parafuri community. One village accounted for
97.1% of all An. darlingi collections within Parafuri
community, while this species was absent in two villages and
collected in low densities in another (4.9%) and the
vicinities of the Health Post (3.5%). In the third
Yanomami community of Marari, we identified to
species level 532 anophelines. Anopheles oswaldoi (s.l.) was
again the predominant species (41.0%), followed by An.
darling (18.0%). However, the An. darlingi/An. oswaldoi
(s.l.) the ratio was heterogenous between villages.
Anopheles triannulatus (s.s.) and An. nuneztovari (s.l.)
were only collected in one village, the latter being found
in very high densities.
The total of anophelines collected in each type of
larval habitat per community is shown in Table 2. We
found substantial variability in the productivity of An.
darlingi within OX and NOX between communities and
villages. For example, only two L2 larvae of An. darlingi
were collected during 19 months of sampling efforts in
) ) ) ) ) ) )
.8 .5 .5 ) .3 ) .4 ) .0 .8
7 5 5 .0 ) ) 3 .6 ) ) 1 ) ) .0 1 ) ) ) ) 8
lta (41 (14 (14 (31 .(75 .)01 .(41 1 (57 (01 .(84 .(66 (23 .(81 .(41 3 (81 (48 .(46 .(35 .(35 .)51 .(83 (1 6 ts
o 2 0 0 7 8 ( 0 7 0 1 7 0 6 4 1 6 6 1 4 8 8 ( 0 00 32 96 re
T 0 3 1 1 8 3 7 1 6 4 8 0 3 5 1 1 1 7 9 2 3 2 2 8 2 1 5 1 fo
ity IRV =n 0 0 0 0 0 0 0 0 0 n 0 0 0 0 0 0 0 0 0 n 4 7 0 1 0 0 4 0 1 1 re
6 6 a
e ) ) o
rc ) ) ) ) .5 ) .4 ) ) ) xb
(reep X 8= .(3910 .(2749 .(2016 .)(60 .(1283 97 10= (5881 .(1142 .)(70 (2096 44 16= .(2205 .(3256 .()886 .()618 .)(70 .)(72 .(2710 59 810 -oonn
b O n 0 7 4 3 1 2 0 0 1 n 3 6 0 0 4 1 0 0 5 n 6 9 2 1 2 8 0 8 2 1 X
lea2biirtsyveD iit/ssyceeunopmm ittoooob .iilrgadnn .()..illssodaonw .irttsssseogoannm like.r-oaaugn like.i-tscaon .()..lirttsssuauannn iseeobaagaannh lirtsaeeehonhnp lttauob ifrraau .iilrgadnn .()..illssodaonw .irttsssseogoannm ilke.r-oaaugn ilke.i-tscaon .()..lirttsssuauannn iseeobaagaannh lirtsaeeehonhnp lttauob irraa .iilrgadnn .()..illssodaonw .irttsssseogoannm like.r-oaaugn ilke.i-tscaon .()..lirttsssuauannn iseeobaagaannh lirtsaeeehonhnp lttauob ltao :xoobiitrsveoabXbnO ,irrtrssvaeemIRV
T C T A A A A A A C O S P A A A A A A C O S M A A A A A A C O S T A s
= = t
d P 2 3 o
e R n 0 0 0 0 1 0 0 0 1 n 8 0 0 4 0 0 0 0 1 n 0 0 0 0 0 0 0 0 0 1 n
one shaded OX of Toototobi community. In contrast, a
single mostly sun-exposed OX in Parafuri community
accounted for 78.8% of An. darlingi (all instars)
collections of this community. In Marari, An. darlingi was the
second most abundant species collected in OX after An.
oswaldoi (s.l.). Overall, An. darlingi was primarily found
in the OX hydrological type with 67.7% of this species
collected in OX.
Anopheles oswaldoi (s.l.) was collected from all types
of larval habitats, except rainfall pools. Anopheles
triannulatus (s.s.) was almost exclusively collected in
OX and NOX larval habitats. Anopheles
mattogrossensis was more abundant in larval types associated with
the river flood pulses, such as OX, NOX and FAAR.
Anopheles guarao-like was found a wide variety of
hydrological types in the three Yanomami areas and
An. costai-like was also collected from different larval
habitats, although in this case, larvae were more
abundant in water bodies that were not associated
with river flood pulses, such as FANAR, SFS and
MFS. Chagasia bonneae were collected almost
exclusively from water bodies with some degree of
water movement, such as SFS, MFS and margins of
low-order rivers. The other anophelines section of
Table 2 included less frequent species such as An.
nimbus, An. thomasi, An. kompi and An.
squamifemur, which were collected from shaded SFS and
FANAR larval habitats, An. intermedius which we
found in OX and FAAR hydrological type and An.
nuneztovari (s.l.) which was only collected from
sun-exposed OX and co-occurring with other Nyssorhynchus
species such as An. darlingi, An. oswaldoi (s.l.) and An.
Association of anopheline species with environmental factors
The data for mean number of each anopheline species
adjusted for 100 dips and their associations with the
seven environmental factors considered in our
analysis are presented in Table 3. Figure 2 provides a
schematic distribution displaying the associations of
the seven species considered for analysis with
different combinations of larval habitat hydrological types
and degree of sun exposure. For example, 76.3% of all
An. darlingi were collected from OX that were
classified as sun-exposed.
The outcomes of the multivariate analyses for the 6
Anopheles spp. and Chagasia bonneae are summarized
in Table 4. For species in the subgenus Nyssorhynchus,
we found that An. darlingi occurrence was positively
associated with proximity to Yanomami dwellings (Z =
4.10, P < 0.0001), larval habitats associated with river
flood pulses (Z = -2.29, P = 0.022), aquatic habitats that
were partially or mostly exposed to the sun (Z = -6.37,
P < 0.0001) and clear or semi-turbid waters over turbid
ones (Z = 3.20, P = 0.001 and Z = 2.00, P < 0.046,
respectively). However, the univariate analysis also
detected positive associations of An. darlingi with
permanent water bodies (Z = 2.47, P = 0.014), with
stagnant waters (Z = -8.83, P < 0.0001) and with the
presence of submerged macrophytes (Z = -4.43, P < 0.0001).
Anopheles oswaldoi (s.l.) showed preference only for
larval habitats which were partially and mostly
sun-exposed (Z = -2.20, P = 0.028) and for semi-turbid and
turbid larval habitats (Z = -3.55, P = 0.0004). The
univariate analysis also detected significantly more An.
oswaldoi (s.l.) in larval habitats without water movement
(Z = -2.22, P = 0.026) and the absence of submersed
macrophytes (Z = 2.34, P = 0.02). Larvae of An.
triannulatus (s.s.) were significantly associated with permanent
larval habitats (Z = 2.23, P = 0.026) and with the
presence of submersed macrophytes (Z = -5.82, P < 0.0001).
The univariate model for this species indicated that
larvae was negatively associated with proximity to
human habitations (Z = 2.10, P = 0.036) and preferred
water bodies that were mostly exposed to the sun
compared to partially exposed ones (Z = -5.04, P < 0.0001).
No larvae of An. triannulatus (s.s.) were collected from
shaded water bodies, larval habitats not associated with
river flood pulses and with water movement.
Within the members of the Anopheles subgenus,
significantly more larvae of An. mattogrossensis were found
in larval habitats further from the human habitations
(Z = 3.54, P = 0.0004), associated with flood pulses
(Z = -2.96, P = 0.003), seasonal water bodies (Z = -3.85,
P = 0.0001), mostly and partially sun-exposed (Z = -5.97,
P < 0.0001), clear waters over turbid ones (Z = 2.20,
P = 0.028) and without submersed macrophytes
(Z = 1.97, P = 0.048). In univariate analyses, An.
mattogrossensis was also positively associated with larval
habitats without water movement (Z = -2.07, P = 0.038), and
positive associations concerning the adjusted analysis
were only retained for the preference of larval habitats
associated with flood pulses and sun exposure. In the
adjusted model for An. costai-like, only a significant
association with larval habitats out of the reach of river
flood pulses was detected (Z = 5.34, P < 0.0001).
However, when considering the univariate analysis, An.
costai-like was also significantly more abundant in
seasonal larval habitats (Z = -2.75, P = 0.006), shaded larval
habitats (Z = 2.84, P = 0.005) and water bodies without
the presence of submerged macrophytes (Z = 2.64,
P = 0.008). For An. guarao-like, the only variable
explaining the occurrence of this species was its
preference for shaded over mostly sun-exposed larval habitats
(Z = 2.01, P = 0.045). In the univariate analysis, only
stagnant larval habitats were positively associated with
more larvae (Z = -2.34, P = 0.019). This species was
never found in larval habitats with the presence of
Finally, Chagasia bonneae was positively associated
with larval habitats closer to the Yanomami dwellings
(Z = -2.18, P = 0.029), with river flood pulses (Z = -4.19,
P < 0.0001) and with water movement (Z = 8.12,
P < 0.0001). Nonetheless, contrarily to the adjusted
model, the univariate analysis indicated positive
associations with larval habitats not associated with river flood
pulses (Z = 3.04, P = 0.002), permanent (Z = 2.14,
P = 0.032) and shaded (Z = 2.48, P = 0.013). These
results indicate a very strong modulating effect between
variables for this species.
During a two-year larval collection in the Brazilian
Amazon, within low-order river-floodplain systems (first
to fifth river order), An. darlingi was the second most
abundant species only exceeded in numbers by An.
oswaldoi (s.l.). In contrast, larvae of An. darlingi have
been regarded as difficult to find. In Belize for example,
no An. darlingi larvae were found over a two-year study
]. In the Zo’é Indian Reserve of Brazil, a total of 6392
adults of An. darlingi were collected while only 26 larvae
were recorded during three field expeditions [
Anopheles darlingi has been found in many different
larval habitats, natural [
] and man-made [
] as well as from large and permanent to small and
temporary water bodies [
]. This species has been
characterized by its adaptability to different and
changing ecological environments [
]. Microdams, which
are sections of streams and rivers where water surface
flow is obstructed by overhanging twigs or fallen stumps
coupled with the accumulation of floating debris have
been reported as important larval habitats for An.
30, 32, 34
]. In the Suriname Rainforest, An.
darlingi was associated with seasonally flooded forest
areas from the river and rain waters [
]. On the interior
forested malaria-endemic area of Guyana, An. darlingi
preferred waters found in forest streams, seepage
swamps and larval rainwater habitats, while in the
savannahs of the interior, lakes were reported as
preferred larval habitats [
]. On the other hand, in the
coastal areas of Guyana, An. darlingi larval habitats
included man-made water bodies such as irrigation
canals, rice fields and flooded drains and ditches [
Our results contrast with some of the previous
observations of An. darlingi preference for certain larval
habitats. For example, our immature anopheline
collections were negative in the low-order rivers in
the Toototobi and Parafuri areas. We believe this was
because these river canals had no microenvironments
suitable as anopheline larval habitats. These
microenvironments would be represented by micro-dams
.ce lve eoann .)*026 .)719 .)7112 .)802 –.2070
n le b – – – – .7
rrcceuo frceeeen iifccaen isgaaahC .*9790 ..(080020 .feR ..(039125 .feR ..(008191 ..(055040 .feR llA enoN enoN .(030255 .feR llA enoN
e r n
il n ig
e o s
h n e
op o th
% re s ro
5 a r a g
re9pp sceom ltttee .)*81 .)71 –.)*003 b.)*37 a.)*488 a.)*45 .)59 .)81 ttcaaeh
,L95uC% .)t500uo iiffrteenhd .iliragdnnA .*276990 –..(6000220 .feR –..(2809382 .feR ..(00016000 –..(6000510 .feR –..(2911435 –..(2015532 .feR –..(8001630 .feR –..(4106690 .feR illttcceeond
r < w s s
e e n
lea4blii(rtsskaRoow illiiiif(ttttsscycaaanngP iiirrttscaaeeeeongdd .)005< liraeb irttttsscaaeeeuonnh iillfttssscaeuooohpddw oN seY litsyaaeno rtaeePnnm lsaaSeno rsxeeuuonp aSehdd llirtsxyaaeePopd ltssxyeeoopdM iirtyudb lraeC ii-rtSeubdm irTubd rttvaeeeonmm seY oN rrtsscyaeeeuhodbpmm tsenbA rtseePn :lliscaeepmiilltrsveaobbnA
T S ca (P aV D A S S T W S A
within the 1 km upstream and downstream perimeter
from each village. In the low-order rivers of Marari
on the other hand, only a small number of
anopheline larvae (including An. darlingi) were collected
during the dry season, mainly in micro-dams exposed
to sunlight created by fallen trees with floating debris,
sunlight pools in the riverbed, and the edges of the
river with emergent vegetation or filamentous algae.
Nonetheless, although anopheline larvae were
collected, low-order rivers were not considered
primary anopheline larval habitats since these
habitats, and the larvae collected, were present in low
numbers. In Marari villages, LAR (and specially OX)
within 1 km radius of each village constituted the
main larval habitats for An. darlingi, An. triannulatus
(s.s.), An. oswaldoi (s.l.) and An. nuneztovari (s.l.). OX
were more frequently positive and had the highest
densities of An. darlingi larvae compared to other
hydrological types. Larval habitats similar to
sunexposed LAR were previously reported as primary
larval habitats [
23, 24, 38
]. In the state of Bolivar in
Venezuela, natural lagoons and artificial water bodies
generated due to mining activities were considered
the primary larval habitats for An. darlingi and An.
]. Lagoons (which could correspond to
OX, NOX or FAAR in our classification) were major
larval habitats for An. triannulatus and An. darlingi
in the Venezuelan Yanomami area [
In our study sun exposure was a major determinant
of anopheline occurrence. We encountered
significantly more An. darlingi in larval habitats mostly
(1365 larvae) or partially sun-exposed (305 larvae)
compared with shaded ones (10 larvae). Our findings
corroborate other reports on Neotropical anophelines.
Galvão et al. [
] emphasized that exposure to the
sun was a major factor that governed An. darlingi
occurrence and reported that in shaded forest larval
habitats, specimens of this vector were absent.
However, if the same area suffered deforestation and
exposed some parts of the previously fully shaded
larval habitats to the sun, these new exposed spots
became productive larval habitats for An. darlingi
while adjacent shaded areas continued to be
unsuitable for this species. Deane et al. [
] also reported
few larvae of An. darlingi collected from shaded
areas, and that vector preferred areas intensively
exposed to the sun. Vittor et al. [
] conducted a
larvae ecology study in the Amazon region of Peru.
They found that larval habitats with < 70% of their
water surface covered in the shade were nearly twice
as likely to have An. darling than water bodies with
> 70% of their surface covered in the shade. However,
An. darlingi preference for shaded larval habitats
were also observed [
]. In the Brazilian Amazon,
shade seemed to be a major driver for An. darlingi
proliferation in micro dam larval habitats [
] close to houses.
Remote indigenous communities in the Amazon are
typically located in ecologically conserved areas where
most of the anthropogenic impacts are in the form of
subsistence agriculture near their huts where the
forest is cut down and previously shaded larval habitats
may be exposed to sunlight and potentially become
larval habitats for An. darlingi. This was observed in
small, ephemeral and sun-exposed RP in Parafuri and
a sun-exposed SFS segment in Marari. In Marari
besides micro deforestation for agriculture purposes,
an airstrip construction created suitable habitats for
An. darlingi, demonstrating the importance of
small-scale landscape modifications. Forested fully
shaded SFS and RP had no An. darlingi larvae during
In addition to sunlight, the presence of certain
subtypes of supportive EBA, such as submersed
macrophytes, emergent vegetation, filamentous algae, water
body margins with leafs or debris or clusters of
floating debris inside LAR (further away from LAR’s
shoreline) are necessary to support An. darlingi
breeding. In the univariate analysis, both sunlight and
submersed macrophytes were positively associated
with An. darlingi. However, sunlight was the
predominant factor in the multivariate analysis. The lack of
significance for vegetation and An. darlingi presence
in the multivariate analysis was likely due to
collinearity between sun exposure and these other
Anopheles darlingi larvae have been collected in
areas with current water such as the edges of small
rivers and canals [
]. Although water movement
was not a predictive factor in our multivariate model
for An. darlingi, our unadjusted analysis indicated an
association of this species with stagnant waters
(conditions found in OX and NOX that disconnect
seasonally from rivers). However, we also found a few
An. darlingi larvae within streams and low-order
rivers with low water movement. Anopheles darlingi
is believed not to thrive in turbid or polluted waters
. Although we found significantly more An.
darlingi larvae in clear waters, a few larvae were also
collected in turbid LAR waters during its low-waters
phase. Anopheles darlingi was previously reported in
large, bare, and muddy road-pools [
Our data further indicated that An. darlingi was the
only species in which densities were significantly
higher in larval habitats closer to the Yanomami huts,
suggesting a dependency on human blood. In a recent
study in the Western Amazon, the same was observed
with higher densities of An. darlingi in fishponds
within 100 m of houses and an absence of malaria
cases in places > 900 m from fishponds [
However, An. darlingi in the Lacandon forest of South
México was found to be significantly more abundant
in larval habitats away from human habitations [
Differences reported in the characteristics of An.
darlingi larval habitats in the various studies might
be due to An. darlingi genetic variability [
local adaptation . However, marked differences
have also been reported in populations without clear
biogeographical barriers such as our findings of an
association of An. darlingi larvae with sun-exposed
larval habitats and the shaded larval habitat
preference reported in Southern Roraima state [
Different observations could also be due to how sun
exposure is defined by different investigators as open
pools surrounded by vegetation may experience some
shading for certain parts of the day. Differences
reported in the larval ecology of An. darlingi could
also be due to differences in sampling methodology.
Primary An. darlingi habitats such as OX which are
relatively large and intrinsically complex pose serious
sampling challenges, including accessibility for all
EBA subtypes. Some authors have emphasized that in
their studies, only accessible margins of water bodies
were sampled for An. darlingi occurrence [
35, 45, 49
We found An. darlingi larvae mainly in OX and
NOX hydrological types, which required the use of a
small inflatable boat to access most EBA subtypes
within the larval habitat. In fact, we found most An.
darlingi larvae in EBA subtypes that were not
accessible from the LAR perimeter (Sánchez-Ribas J,
unpublished data). Different conclusions regarding the
association between environmental factors and An.
darlingi would have been obtained if we had not used
the inflatable boat in our study. We and other
26, 48, 49
] warn against the strategy of
focusing the sampling on the margins of aquatic
habitats and advocate for extending the collections to
other EBA subtypes within larval habitats. To
circumvent this problem, we have recently proposed a
standardized sampling methodology, which may be
applicable in size variable and intrinsically complex
Neotropical larval sites [
Anopheles oswaldoi (s.l.) showed marked ecological
plasticity being found in almost all hydrological types
and all villages of the three Yanomami communities.
Anopheles oswaldoi (s.l.) is a complex composed of at
least three different species, i.e. An. oswaldoi (s.s.), An.
oswaldoi A and An. oswaldoi B [
] that are widely
distributed in South America and have been found in a
wide range of larval habitats, with a marked tolerance of
different degrees of sun exposure, turbidity and larval
habitat sizes [
]. Anopheles oswaldoi (s.l.) was also the
most common species collected as larvae, followed by
An. triannulatus and An. darlingi during the dry season
in partially shaded and shallow lagoons in the Yanomami
area of Ocamo, Venezuela [
] and the nearby Ye’kuana
and Sanema indigenous areas of southeastern Venezuela
]. In a littoral area of the northeastern Sucre State of
Venezuela, An. oswaldoi (s.l.) was primarily found in
permanent and vegetated ponds of freshwater and
non-vegetated canals [
]. Anopheles oswaldoi (s.l.) was
associated with heavily shaded swamps in Panama [
Molecular analysis (cytochrome c oxidase subunit 1
gene, cox1) on adult mosquitoes detected the
cooccurrence of An. oswaldoi B, An. oswaldoi sp. nr. A
and a single specimen which did not match with any of
this other two groups (Sánchez-Ribas J, unpublished
data). High ecological plasticity detected for An.
oswaldoi (s.l.) larvae could be partially explained by potential
bionomic differences between members of this species
complex that co-occur in the Brazilian Yanomami Indian
Preferred larval habitats of An. triannulatus have
been described as partial sun-exposed water bodies
associated with emergent, submerged or floating
macrophytes such as freshwater swamps, permanent
ponds, lakes, ditches and river margins [
] but also
in seasonal water bodies such as rock holes, small
ground pools and animal tracks [
triannulatus was classified as a habitat generalist in a
study conducted in the Roraima and Pará States of
Brazil, with a widespread local distribution without
clear environmental associations [
]. In the Pantanal
region of Brazil, the three sibling species of the An.
triannulatus complex, An. triannulatus (s.s.), An.
halophylus and An. triannulatus species C, were
associated with large floodplain water bodies, most of
them permanent [
]. Although An. triannulatus (s.s.)
and An. halophylus exploited similar water bodies,
they differed in their salinity tolerance, with the
former species found in fresh waters and the latter in
brackish water bodies [
]. Anopheles triannulatus
(s.s.) is present in Central and South America while
An. halophylus and An. triannulatus C has only been
found in a geographically restricted area of
centralwestern Brazil [
]. All specimens collected by us
were identified as An. triannulatus (s.s.) and found
almost exclusively in partially or mostly sun-exposed
permanent larval habitats, without water movement
and strongly associated with submerged macrophytes.
Previous reports also showed An. triannulatus (s.s.)
significantly associated with less shaded with
submerged macrophytes lagoons in the Yanomami
Venezuelan area of Ocamo [
] and also in
Venezuela, An. triannulatus was found in dry season
river bed pools and clusters of floating vegetation
during the rainy season [
]. However, no An.
triannulatus (s.s.) larvae were collected by us in SFS or
MFS and river canal-related larval habitats.
Although An. mattogrossensis has been incriminated
as a secondary malaria vector in Brazil [
], few data
have been published regarding its bionomics,
particularly on the ecology of its immature forms.
Anopheles mattogrossensis is a species of the subgenus
Anopheles, and its larval habitats were more similar
to species of the subgenus Nyssorynchus such as An.
triannulatus (s.s.) and An. darlingi rather than with
the other species of its subgenus (e.g. An. guarao-like
and An. costai-like). Anopheles mattogrossensis was
more likely to be found in partially or mostly
sunexposed larval habitats. Specimens morphologically
identified as An.costai-like were found in shaded
larval habitats not associated with river flood pulses.
Larval habitats exploited by An. guarao-like were
similar to those of An. oswadoi (s.l.), being collected in all
types of water bodies but with a preference for shaded
water bodies. Even for the most generalist species found
in our study area, An. oswaldoi (s.s.) and An. guarao-like,
a significant predictor of larvae occurrence was sun
exposure. The taxonomic status of An. costai-like and
An.guarao-like remain unresolved, and therefore we
were unable to compare our data with previously
published studies. Work is underway to elucidate the
formal identities of species classified as An. costai-like
and An. guarao-like in the present publication.
Finally, Chagasia bonneae was associated with larval
habitats that were predominantly shaded (univariate
analysis), without submersed macrophytes and with
some degree of water movement. These characteristics
were found mainly in shaded SFS and MFS and also
in shaded or partially exposed margins of low-order
rivers. Filamentous algae were usually absent from
SFS and MFS. In Venezuela, this species has been
collected from stream edges with algae and partially
exposed to the sun [
]. In the Zo’é Indian Reserve
of Brazil, a dense Amazonian forested area traversed
by the low-order Cuminipanema river, Chagasia
bonneae was the most common species collected as
immatures, although the preferred hydrological type
of this species was not specified [
member of the genus, Chagasia bathana, was found in
shaded running streams, mainly in areas of slowed
current due to projected roots into the streams as
well as within debris and dead leaves of side pools of
Our study had a number of limitations that should
be considered when interpreting the results. A major
challenge for any quantitative study of the larval
ecology of mosquitoes is the difficulty in reliably
sampling larvae. For this study, a rigorous sampling
methodology was followed in all larval habitat types
and attempted to sample all EBA subtypes within
the habitat, including those EBA distant from the
shoreline of large larval habitats that are normally
out of reach. Data such as physicochemical measures
of temperature, pH, total dissolved salts (TDS),
conductivity and dissolved oxygen were not included in
the uni- and multivariate regression models since we
were unable to measure them reliably during the
whole study period. Additionally, our sun exposure
classification did not take into account the amount of time
that each segment of EBA subtype was exposed to direct
sunlight. Also, we were unable to identify and consider for
statistical analysis first and second instars for all species,
except An. darlingi. Molecular taxonomic analyses were
not conducted on larvae and several mosquitoes identified
in this study are known to be complexes of species.
Molecular studies to identify these mosquitoes are
ongoing. Small samples sizes for Chagasia bonneae (only 41
specimens) may have led to spurious results, such as the
observation that Chagasia bonneae densities were higher
in larval habitats located closer to the Yanomami
huts while only three adult specimens of Chagasia
bonneae were sampled in all collections highlighting
a low anthropophilic biting profile.
We identified high heterogeneity in species
composition and larval densities between Yanomami
communities and villages. This variability was explained by
the different availability of larval habitats with
different intrinsic characteristics at a micro-scale level. We
confirmed that LAR, and especially sun-exposed OX,
were key for the maintenance of local malaria vector
populations of An. darlingi, An. triannulatus (s.s.),
An. oswaldoi (s.l.) and An. mattogrossensis. Sun
exposure was a major modulator for the occurrence of
the majority of anophelines. Anopheles darlingi
thrived in those few spots which were exposed to
sunlight within an overwhelmingly predominant
shaded forest environment. In this study, natural
larval habitats of An. darlingi in remote indigenous
areas located within low-order river-floodplain
systems represent an excellent opportunity to
incorporate feasible and sustainable LSM approaches.
Targeting immature anophelines may be a
costeffective intervention in some specific resilient malaria
hotspots of remote indigenous areas of the Amazon
basin and Central America. Finally, more information
on the ecology of Neotropical anopheline immature
forms is needed in other settings, particularly for An.
darlingi, to better understand the key environmental
drivers that may modulate the occurrence of the main
malaria vector of the Amazon basin.
Additional file 1: Table S1. Total and percentage of late instar
anopheline larvae collected per village. (XLSX 12 kb)
Additional file 2: Table S2. Dataset used for univariate and multivariate
statistical analysis. (XLSX 263 kb)
FAAR: Flooded areas associated with the river; FANAR: Flooded areas not
associated with the river; GPS: Global positioning system; IRS: Indoor residual
spraying; LAR: Lakes associated with the river; LLINs: Long-lasting insecticidal
nets; LSM: Larval source management; MFS: Medium forest streams;
NOX: Non-oxbow lakes; OX: Oxbow lakes; RP: Rainfall pools; SFS: Small forest
streams; tEBA: Total effective breeding area
We are especially grateful to the Yanomami people for their great
welcoming and for allowing us to perform larvae collections around their
villages, their invaluable assistance in locating larval habitats and general
logistical support. We also thank the health personnel of the Distrito
Sanitário Especial Indígena Yanomami for overall support during field work,
Dr Ricardo Lourenço de Oliveira for his valuable comments on the
manuscript and Ryan Wiegand for providing statistical advice.
This study was supported by grants from CNPq (grant number 479559/
2013–9) and FAPERJ (grant number E-26/110.803). These funding bodies did
not participate in the design of the study and collection, analysis,
interpretation of data and in writing the manuscript.
Availability of data and materials
The datasets analyzed during this study are included in this published article
and its additional files.
Conceived and designed the project: JSR, TFSN and JOF. Performed
anopheline field collections: JSR, TFSN and CPR. Analyzed and interpreted
the data: JEG, JSR, TFSN and JOF. Contributed with reagents/laboratory
support/analysis tools: JEG and MN. Drafted the first version of the
manuscript: JSR. Contributed to the final draft: JSR, JEG, TFSM, JOF and MN.
All authors read and approved the final manuscript.
The present study was approved by the CONEP Central Ethics Committee in
Brasilia (CONEP n° 16,907). Also, an initial meeting was held in each
Yanomami village, including their representatives, to fully explain the
objectives, methods and risks of the study. We sought for approval in each
Consent for publication
The authors declare that they have no competing interests.
Disclaimer: The opinions or assertions contained in this manuscript are the
private ones of the authors and are not to be construed as official or
reflecting the views of the U.S. Public Health Service or Department of
Health and Human Services. Use of trade names is for identification only and
does not imply endorsement by U.S. Public Health Service or Department of
Health and Human Services.
Springer Nature remains neutral with regard to jurisdictional claims in published
maps and institutional affiliations.
Control and Prevention, CDC, Atlanta, USA. 4Distrito Sanitário Especial
Indígena Yanomami, DSEI-Y, Boa Vista, Brazil.
1. WHO. World malaria report 2016 . Geneva: World Health Organization; 2016 .
2. Lapouble OM , Santelli AC , Muniz-Junqueira MI . Epidemiological situation of malaria in the Brazilian amazon region, 2003 to 2012 . Rev Panam Salud Publica . 2015 ; 38 : 300 - 6 .
3. Lainhart W , Dutari LC , Rovira JR , Sucupira IM , Povoa MM , Conn JE , et al. Epidemic and non-epidemic hot spots of malaria transmission occur in indigenous comarcas of Panama . PLoS Negl Trop Dis . 2016 ; 10 ( 5 ): e0004718 .
4. MS/FNS. Situação da Saúde e Assistência - Relatório epidemiológico annual . Boa Vista: Ministerio da Saúde - Fundação Nacional da Saúde ; 2010 .
5. Conde M , Pareja PX , Orjuela LI , Ahumada ML , Duran S , Jara JA , et al. Larval habitat characteristics of the main malaria vectors in the most endemic regions of Colombia: potential implications for larval control . Malar J . 2015 ; 14 : 476 - 85 .
6. Santelli AC , Damasceno CP , Peterka CL , Marchesini PB . Plano de eliminação de malária no Brasil. Fase 1 - Malária falciparum . Brasília: Coordenação Geral dos Programas Nacionais de Controle e Prevenção da Malária e das Doenças transmitidas pelo Aedes; 2016 .
7. Magris M , Rubio-Palis Y , Alexander N , Ruiz B , Galvan N , Frias D , et al. Community-randomized trial of lambdacyhalothrin-treated hammock nets for malaria control in Yanomami communities in the Amazon region of Venezuela . Tropical Med Int Health . 2007 ; 12 : 392 - 403 .
8. Grietens KP , Xuan XN , Ribera J , Duc TN , Bortel W , Ba NT , et al. Social determinants of long lasting insecticidal hammock use among the Ra-glai ethnic minority in Vietnam: implications for forest malaria control . PLoS One . 2012 ; 7 : e29991 .
9. Hill N , Lenglet A , Arnez AM , Carneiro I . Plant-based insect repellent and insecticide-treated bed nets to protect against malaria in areas of early evening biting vectors: double blind randomised placebo-controlled clinical trial in the Bolivian Amazon . BMJ . 2007 ; 335 : 1023 .
10. Charlwood JD , Nenhep S , Protopopoff N , Sovannaroth S , Morgan JC , Hemingway J. Effects of the spatial repellent metofluthrin on landing rates of outdoor biting anophelines in Cambodia, Southeast Asia . Med Vet Entomol. 2016 ; 30 : 229 - 34 .
11. WHO. Larval source management. A supplementary measure for malaria vector control. An operation manual . Geneva: World Health Organization; 2013 .
12. WHO. Interim position statement: The role of larviciding for malaria control in sub-Saharan Africa . Geneva: World Health Organization; 2012 .
13. Sinka ME , Rubio-Palis Y , Manguin S , Patil AP , Temperley WH , Gething PW , et al. The dominant Anopheles vectors of human malaria in the Americas: occurrence data, distribution maps and bionomic precis . Parasit Vectors . 2010 ; 3 : 117 - 50 .
14. Tusting LS , Thwing J , Sinclair D , Fillinger U , Gimnig J , Bonner KE , et al. Mosquito larval source management for controlling malaria . Cochrane Database Syst Rev . 2013 ; 8 : CD008923 .
15. Suarez-Mutis MC , Fe NF , Alecrim W , Coura JR . Night and crepuscular mosquitoes and risk of vector-borne diseases in areas of piassaba extraction in the middle Negro River basin, state of Amazonas, Brazil . Mem Inst Oswaldo Cruz . 2009 ; 104 : 11 - 7 .
16. Hutchings RS , Hutchings RW , Menezes IS , Motta MA , Sallum MA . Mosquitoes (Diptera: Culicidae) from the northwestern Brazilian Amazon: Padauari River . J Med Entomol . 2016 ; 53 : 1330 - 47 .
17. Cabral AC , Fe NF , Suarez-Mutis MC , Boia MN , Carvalho-Costa FA . Increasing incidence of malaria in the Negro River basin , Brazilian Amazon. Trans R Soc Trop Med Hyg . 2010 ; 104 : 556 - 62 .
18. Nagm L , Luitgards-Moura JF , Neucamp Cde S , Monteiro-de-Barros FS , Honorio NA , Tsouris P , et al. Affinity and diversity indices for anopheline immature forms . Rev Inst Med Trop Sao Paulo . 2007 ; 49 : 309 - 16 .
19. de Barros FS , de Aguiar DB , Rosa-Freitas MG , Luitgards-Moura JF , Gurgel Hda C , Honorio NA , et al. Distribution summaries of malaria vectors in the northern Brazilian Amazon . J Vector Ecol . 2007 ; 32 : 161 - 7 .
20. Magris M , Rubio-Palis Y , Menares C , Villegas L. Vector bionomics and malaria transmission in the upper Orinoco River, southern Venezuela . Mem Inst Oswaldo Cruz . 2007 ; 102 : 303 - 11 .
21. Moreno JE , Rubio-Palis Y , Paez E , Perez E , Sanchez V , Vaccari E. Malaria entomological inoculation rates in gold mining areas of southern Venezuela . Mem Inst Oswaldo Cruz . 2009 ; 104 : 764 - 8 .
22. Rubio-Palis Y , Bevilacqua M , Medina DA , Moreno JE , Cardenas L , Sanchez V , et al. Malaria entomological risk factors in relation to land cover in the lower Caura River basin , Venezuela. Mem Inst Oswaldo Cruz . 2013 ; 108 : 220 - 8 .
23. Rejmankova E , Rubio-Palis Y , Villegas L . Larval habitats of anopheline mosquitoes in the upper Orinoco, Venezuela . J Vector Ecol . 1999 ; 24 : 130 - 7 .
24. Rubio-Palis Y , Menare C , Quinto A , Magris M , Amarista M . Caracterización de criaderos de anofelinos (Diptera: Culicidae) vectores de malaria del Alto Orinoco , Amazonas, Venezuela. Entomotropica. 2005 ; 20 : 29 - 38 .
25. Rubio-Palis Y , Moreno JE , Bevilacqua M , Medina D , Martínez A , Cardenas L , et al. Caracterización ecológica de los anofelinos y otros culícidos en territorio indígena del Bajo Caura , Estado Bolívar, Venezuela. Bol Malariol Salud Ambiental . 2010 ; 50 : 95 - 107 .
26. Sánchez-Ribas J , Oliveira-Ferreira J , Rosa-Freitas MG , Trilla L , Silva-doNascimento TF . New classification of natural breeding habitats for Neotropical anophelines in the Yanomami Indian reserve, Amazon region, Brazil and a new larval sampling methodology . Mem Inst Oswaldo Cruz . 2015 ; 110 : 760 - 70 .
27. Lima JB , Galardo AK , Bastos LS , Lima AW , Rosa-Freitas MG . MosqTent: an individual portable protective double-chamber mosquito trap for anthropophilic mosquitoes . PLoS Negl Trop Dis . 2017 ; 11 ( 3 ): e0005245 .
28. Consoli RAGB , Lourenço-de-Oliveira R . Principais mosquitos de importância sanitária no Brasil. Rio de Janeiro: Fiocruz; 1994 .
29. Forattini OP . Culicidologia Médica , Vol. 2 : Identificação, Biologia, Epidemiologia. São Paulo: Edusp; 2002 .
30. Manguin S , Roberts DR , Andre RG , Rejmankova E , Hakre S. Characterization of Anopheles darlingi (Diptera: Culicidae) larval habitats in Belize, central America. J Med Entomol . 1996 ; 33 : 205 - 11 .
31. dos Santos RC , Padilha A , Costa MDP , Costa EM , Dantas-Filho HC , Povoa MM . Vetores de malária em duas reservas indígenas da Amazônia Brasileira . Rev Saúde Pública . 2009 ; 43 : 859 - 68 .
32. Barros FS , Arruda ME , Gurgel HC , Honorio NA . Spatial clustering and longitudinal variation of Anopheles darlingi (Diptera: Culicidae) larvae in a river of the Amazon: the importance of the forest fringe and of obstructions to flow in frontier malaria . Bull Entomol Res . 2011 ; 101 : 643 - 58 .
33. Hiwat H , Bretas G . Ecology of Anopheles darlingi root with respect to vector importance: a review . Parasit Vectors . 2011 ; 4 : 177 - 89 .
34. Charlwood JD . Biological variation in Anopheles darlingi root . Mem Inst Oswaldo Cruz . 1996 ; 91 : 391 - 8 .
35. Barros FS , Honorio NA . Deforestation and malaria on the Amazon frontier: larval clustering of Anopheles darlingi (Diptera: Culicidae) determines focal distribution of malaria . Am J Trop Med Hyg . 2015 ; 93 : 939 - 53 .
36. Hiwat H , Issaly J , Gaborit P , Somai A , Samjhawan A , Sardjoe P , et al. Behavioral heterogeneity of Anopheles darlingi (Diptera: Culicidae) and malaria transmission dynamics along the Maroni River, Suriname, French Guiana . Trans R Soc Trop Med Hyg . 2010 ; 104 : 207 - 13 .
37. Giglioli G. An investigation of the house-frequenting habits of mosquitoes of the British Guiana coastland in relation to the use of DDT . Am J Trop Med Hyg . 1948 ; 28 ( 1 ): 43 - 70 .
38. Moreno J , Rubio-Palis Y , Acevedo P. Identificación de criaderos de anofelinos en un área endémica del estado Bolívar , Venezuela. Bol Malariol Salud Ambiental . 2000 ; 60 : 21 - 30 .
39. Galvão ALA , Damasceno RG , Marques AP . Algumas observações sobre a biologia dos anofelinos de importância epidemiológica de Belem, Pará . Arquiv Higiene . 1942 ; 12 : 51 - 11 .
40. Deane LM , Causey OR , Deane MP . Notas sôbre a distribuição e a biologia dos anofelinos das regiões nordestina e amazônica do Brasil . Rev Serv Esp Saud Pública . 1948 ; 1 : 827 - 965 .
41. Vittor AY , Pan W , Gilman RH , Tielsch J , Glass G , Shields T , et al. Linking deforestation to malaria in the Amazon: characterization of the breeding habitat of the principal malaria vector, Anopheles darlingi . Am J Trop Med Hyg . 2009 ; 81 : 5 - 12 .
42. Root FM . Studies on Brazilian mosquitoes. I. The anophelines of the Nyssorhynchus group . Am J Hyg . 1926 ; 6 : 684 - 717 .
43. Kumm HW , Ram LM . Observations on the Anopheles of British Honduras . Rockefeller Foundation; 1940 .
44. Faran ME , Linthicum KJA . Handbook of the Amazonian species of Anopheles (Nyssorhyncus) (Diptera: Culicidae) . Mosq Syst . 1981 ; 13 : 1 - 81 .
45. dos Reis IC , Codeco CT , Degener CM , Keppeler EC , Muniz MM , de Oliveira FG , et al. Contribution of fish farming ponds to the production of immature Anopheles spp. in a malaria-endemic Amazonian town . Malar J . 2015 ; 14 : 452 .
46. Villarreal-Treviño C , Penilla-Navarro RP , Vazquez-Martinez MG , Moo-Llanes DA , Ríos-Delgado JC , Fernández-Salas I , et al. Larval habitat characterization of Anopheles darlingi from its northernmost geographical distribution in Chiapas, Mexico . Malar J. 2015 ; 14 : 517 .
47. Emerson KJ , Conn JE , Bergo ES , Randel MA , Sallum MA . Brazilian Anopheles darlingi root (Diptera: Culicidae) clusters by major biogeographical region . PLoS One . 2015 ; 10 : e0130773 .
48. Conn JE , Ribolla PE . Ecology of Anopheles darlingi, the primary malaria vector in the Americas and current nongenetic methods of vector control . In: Adelman ZN, editor. Genetic control of malaria and dengue . London: Elsevier Science; 2015 . p. 81 - 102 .
49. Rufalco-Moutinho P , Schweigmann N , Bergamaschi DP , Mureb Sallum MA. Larval habitats of Anopheles species in a rural settlement on the malaria frontier of southwest Amazon, Brazil . Acta Trop . 2016 ; 164 : 243 - 58 .
50. Ruiz-Lopez F , Wilkerson RC , Ponsonby DJ , Herrera M , Sallum MA , Velez ID , et al. Systematics of the oswaldoi complex (Anopheles, Nyssorhynchus) in South America . Parasit Vectors . 2013 ; 6 : 324 .
51. Grillet ME . Factors associated with distribution of Anopheles aquasalis and Anopheles oswaldoi (Diptera: Culicidae) in a malarious area, northeastern Venezuela. J Med Entomol . 2000 ; 37 : 231 - 8 .
52. Komp WHW . The anopheline mosquitoes of the Caribbean region . In: National Institute of Health Bulletin , vol. 179 . Washington; 1942 .
53. Silva-do-Nascimento TF , Lourenco-de-Oliveira R . Diverse population dynamics of three Anopheles species belonging to the Triannulatus complex (Diptera: Culicidae) . Mem Inst Oswaldo Cruz . 2007 ; 102 : 975 - 82 .
54. McKeon SN , Schlichting CD , Povoa MM , Conn JE . Ecological suitability and spatial distribution of five Anopheles species in Amazonian Brazil . Am J Trop Med Hyg . 2013 ; 88 : 1079 - 86 .
55. Silva do Nascimento TF , Lourenco-de-Oliveira R . Anopheles halophylus, a new species of the subgenus Nyssorhynchus (Diptera: Culicidae) from Brazil . Mem Inst Oswaldo Cruz . 2002 ; 97 : 801 - 11 .
56. Moreno JE , Rubio-Palis Y , Sánchez V , Martínez A . Fluctuación poblacional y hábitat larval de anofelinos en el municipio Sifontes, estado Bolívar, Venezuela . Bol Malariol Salud Ambiental . 2015 ; 55 : 52 - 68 .
57. Tadei WP , Dutary Thatcher B. Malaria vectors in the Brazilian Amazon: Anopheles of the subgenus Nyssorhynchus . Rev Inst Med Trop Sao Paulo . 2000 ; 42 : 87 - 94 .
58. Berti J , Guzman H , Estrada Y , Ramirez R . New records of mosquitoes (Diptera: Culicidae) from Bolivar state in south eastern Venezuela, with 27 new species for the state and 5 of them new in the country . Front Public Health . 2014 ; 2 : 268 .