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Short Communication
Field Efficacy of VectoMax FG and VectoLex CG
Biological Larvicides for Malaria Vector Control in
NorthwesternBrazil
PabloS. Fontoura, 1 AndersonS. daCosta, 1 FrancismarS. Ribeiro, 1
MarcílioS. Ferreira, 1 MarciaC. Castro, 2,† and MarceloU. Ferreira1,3,†,
1Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, Av. Prof. Lineu Prestes 1374, 05508-
900 São Paulo, SP, Brazil2Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA
021153Corresponding author, e-mail: muferrei@usp.br
†These authors contributed equally to this work.
Subject Editor: Ary Faraji
Received 29 August 2019; Editorial decision 29 October 2019
Abstract
Despite historical and contemporary evidence of its effectiveness, larval source management with insecticides re-
mains little used by most malaria control programs worldwide. Here we show that environmentally safe biological
larvicides under field conditions can significantly reduce anopheline larval density in fish farming ponds that have
became major larval habitats across the Amazon Basin. Importantly, the primary local malaria vector, Anopheles
darlingi Root (Diptera: Culicidae), feeds and rests predominantly outdoors, being little affected by interventions
such as long-lasting insecticidal bed net distribution and indoor residual spraying. We found >95% reduction in late-
instar density up to 7 d after the first application of VectoMax FG or VectoLex CG (both from Valent BioSciences), and
up to 21 d after larvicide reapplication in fish ponds (n=20) situated in the main residual malaria pocket of Brazil, ir-
respective of the formulation or dosage (10 or 20kg/ha) used. These results are consistent with a substantial residual
effect upon retreatment and support the use of biological larvicides to reduce the density of anopheline larvae in
this and similar settings across the Amazon where larval habitats are readily identified and accessible.
Key words: Anopheles, Bacillus thuringiensis serovar israelensis, Lysinibacillus sphaericus, larviciding, vector control
Anopheles darlingi Root (Diptera: Culicidae), a widely distributed
Neotropical mosquito, is the most efcient malaria vector in the
Amazon (Sinka etal. 2010). Larval habitats of this species include
natural water bodies with clear water and partially shaded edges
covered with vegetation and articial habitats such as sh farming
ponds used for commercial aquaculture (Maheu-Giroux etal. 2010,
Barros and Honorio 2015, dos Reis etal. 2015).
Adult An. darlingi mosquitoes have gradually changed their
biting and resting behavior over the past decades (Hiwat and Bretas
2011). They now typically feed and rest outdoors (e.g., Gil et al.
2003), with more intense human biting activity at dusk, and some-
times a minor peak at dawn (Conn and Ribolla 2016, Martins etal.
2018). This behavior introduces major challenges for core vector
control strategies that rely on long-lasting insecticidal net distribu-
tion and indoor residual spraying (Ferreira and Castro 2016). First,
early-evening biting is unlikely to be prevented by bednet use, ex-
cept for infants. Second, the efcacy of indoor residual spraying is
limited against mosquitoes that bite and rest mostly outdoors. Even
in areas where indoor transmission still occurs, emerging insecticide
resistance and the poor quality of local houses constitute additional
challenges for indoor residual spraying.
Targeting aquatic immature stages is among the much-needed al-
ternative strategies to control outdoor feeding and outdoor resting
mosquito populations with well delineated, easy to nd, and readily
accessible larval habitats. Indeed, larval source management can be
achieved by permanent or recurrent habitat modication, biological
control with natural predators, and chemical or biological larviciding
(World Health Organization 2013). However, these measures have
not been incorporated in the agenda of most national malaria con-
trol programs (Fillinger and Lindsay 2011), despite historical (Keiser
et al. 2005) and contemporary (Maheu-Giroux and Castro 2013)
evidence of their effectiveness.
The eld efcacy of biological larvicides against An. darlingi
remains little studied, despite promising preliminary results with
Lysinibacillus sphaericus application in Brazil (Galardo etal. 2013,
Ferreira etal. 2015), Peru, and Venezuela (reviewed by Conn and
Ribolla 2016). To address this gap, we evaluated the efcacy of
biological larvicides in reducing anopheline larval density in sh
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Journal of Medical Entomology, 57(3), 2020, 942–946
doi: 10.1093/jme/tjz220
Advance Access Publication Date: 21 November 2019
Short Communication
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943Journal of Medical Entomology, 2020, Vol. 57, No. 3
farming ponds in Juruá Valley, the main residual malaria pocket in
Brazil, accounting for 18.5% of the country’s malaria burden. Here,
we report the results of a eld trial of two biological larvicide formu-
lations as a measure to reduce the proliferation of anopheline larvae
in sh farmingponds.
Materials and Methods
The study area is located in the rural community of Nova Cintra
(07°49′17ʺS, 72°39′54ʺW), situated along Juruá River, that experi-
ences year-round malaria transmission. Nova Cintra (population,
371)is part of the municipality of Rodrigues Alves, Acre State, close
to the Brazil–Peru border. Average monthly rainfall estimates during
the study period were obtained from the Climate Hazards group
Infrared Precipitation with Stations (CHIRPS) dataset, which uses
modeled satellite-based infrared data (http://chg.geog.ucsb.edu/data/
chirps). The annual parasite incidence in Rodrigues Alves, estimated
at 343.4 cases per 1,000 inhabitants in 2016, is the second highest for
a municipality in Brazil (Ministry of Health of Brazil, unpublished
data). Nova Cintra has been targeted for free insecticide-treated
bednet replacement within the past 3 yr; indoor residual spaying
with pyrethroids is irregularly carried out and reported to meet with
frequent refusals, mostly due to allergic reactions. The main malaria
vector is An. darlingi, although larvae of An. albitarsis s.l. (Galvão
and Damasceno) are also abundant in water bodies across the region
(dos Reis etal. 2015, Martins etal. 2018).
Two granular formulations of biological larvicides donated
by Valent BioSciences LLC (Libertyville, IL) were evaluated: a)
VectoMax FG (lot number, 277444N830), which combines toxins
from Bacillus thuringiensis serovar israelensis (Bti; strain AM65-52)
and Lysinibacillus (formerly Bacillus) sphaericus 2362 (Ls; strain
ABTS-1743) in a single microparticle, with a potency of 50 interna-
tional toxin units; and b) VectoLex CG (lot number, 276440N830),
which has Ls 2362 (strain ABTS-1743) toxins attached to the bac-
terial spores in corncob granules, with a potency of 50 international
toxin units. These products were applied using an 18-liter capacity
knapsack power mistblower (Guarany, Itu, Brazil) operating at a
walking speed of 0.5 m/s, with a reach of 10 m, covering a surface
area of 5 m2/s.
The trial aimed to examine the eld efcacy and residual activity
of VectoMax FG and VectoLex CG, and to determine their optimum
application dosage in sh farming ponds. We georeferenced all 24
sh ponds, most of them articial, situated in the community of
Nova Cintra. Their surface areas ranged from 200 to 12,000 m2, or
0.02 to 1.2 hectares (ha). Field activities were carried out between
27 September and 4 December 2017. On September 27, we assessed
the baseline larval density using a standard dipping technique for
sampling water bodies (World Health Organization 1992); 2–3 dips
were taken, using a 500-ml ladle, every 3 m along the edges of the
sh pond. Larvae were classied as rst (L1), second (L2), third (L3),
or fourth (L4) instar, and then as early (L1 and L2) or late (L3 and
L4) instars. The presence and number of pupae were recorded but
not used in the analysis due to the impracticability of morphological
differentiation under eld conditions. Larval density in each water
body was calculated as the average count per dip. At baseline all
ponds were positive for immature anopheline stages and supported
active sh farming.
We used stratied block randomization to allocate sh ponds to
different treatments. Briey, we ranked sh ponds according to base-
line larval density and excluded from randomization the four ponds
with the lowest densities. The remaining ponds were stratied into
larval density quartiles; within each quartile, habitats were randomly
allocated to one of the following four treatments: a) VectoLex CG,
10 kg/ha; b) VectoLex CG, 20 kg/ha; c) VectoMax FG, 10kg/ha;
d) VectoMax FG, 20kg/ha. Five additional sh ponds, with similar
surface areas and larval densities, were selected as controls and re-
mained untreated throughout the trial period. To avoid contamina-
tion, controls were chosen in a rural community named Vila Assis
Brasil (07°35′30ʺS, 72°48′29ʺW), situated 27 km from the main
studysite.
Larval density was monitored within 48h and 72h after the rst
larvicide application, and then weekly until the prevalence of L4 was
similar in treated and untreated habitats. Fish ponds were retreated
21 d after the rst application, following their original allocation
to products and dosages, and further monitored for larval density
within 48h, 72h, 7 d, 14 d, 21 d, 35 d, and 42 d after retreatment.
Main outcome variables were: a) anopheline larval density, total
and by instar stage, in treated and control sh ponds, and b) percent
reduction in larval density (%RLD) relative to untreated controls,
total and by instar stage, calculated using Mulla’s formula (Mulla
etal. 1971):
%
RLD =100
ïÅC
1
T1ã×ÅT
2
C2ãò×
100,
where C1 and C2 are the baseline and posttreatment average number
of larvae per dip in the control habitats, respectively, while T1 and
T2 are the baseline and posttreatment average number of larvae per
dip in the treated habitats. When %LDR was negative (i.e., larval
density was higher in treated compared with untreated sh ponds),
the value was taken as zero. The mean numbers of anopheline larvae
per dip in treatment and control habitats were compared using the
nonparametric Kruskal–Wallis test. When individual Kruskal–Wallis
tests indicated a signicant difference (P<0.05) among treatment
groups, posthoc Dunn’s tests for multiple comparisons were carried
out with each pair of habitats to determine whether differences in
habitats were observed. Comparisons were separately made for each
sampling day using Stata 14.1 (StataCorp, College Station,TX).
The study was approved by the Institutional Review Board of
the Institute of Biomedical Sciences, University of São Paulo, Brazil
(CAAE number 6467416.6.0000.5467).
Results and Discussion
At baseline, water pH in the treated sh ponds ranged between 4.96
and 6.59, with water temperatures between 30.3 and 32.1°C. The
study period partially overlapped with the rainy season, and average
monthly rainfall estimates were 179mm in September, 151mm in
October, 288mm in November, and 282mm in December2017.
All treated ponds remained free of L2, L3, and L4 larvae until
day 7, although L1 larvae were already present in 16 (80%) ponds
on day 7.We note that newly hatched L1 larvae have a much lower
feeding rate and thus ingest lower amounts of larvicides, potentially
leading to an underestimation of larvicide efcacy. By days 14 and
21 after treatment, L4 larvae were found in 11 of 20 (55%) and 17
of 20 (85%) treated ponds, respectively. Table 1 shows the average
number of anopheline larvae per dip in treated and untreated sh
ponds, at baseline and following the rst application of biological
larvicides. Until day 7 after treatment, average late instar densities
were signicantly lower in all treated ponds, compared with control
ponds, with %LDR >95% irrespective of the larvicide formulation
and dosage. Indeed, the different products and dosages were simi-
larly effective in reducing larval density between 48h and 7 d after
treatment (Dunn’s tests, P=0.500 for all comparisons).
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944 Journal of Medical Entomology, 2020, Vol. 57, No. 3
Ponds were retreated on day 21, following the original allocation
to formulations and dosages as in the rst application. Time points
shown in Table 2 were dened considering day 21 of the primary
treatment as day 0 (baseline) of retreatment. Until day 14 after lar-
vicide reapplication, early and late instars were not found in any sh
pond, regardless of the product and dosage used. Interestingly, all
ponds remained free of L4 larvae until day 21 after reapplication,
and most of them remained negative for L4 until days 28 (16 of
20, 80%) and 35 (12 of 19, 58%), consistent with some prolonged
residual effect of the larvicides upon reapplication. One of the ve
ponds treated with 20kg/ha of VectoMax was empty after day 28
after reapplication, hence a total of 19 ponds were monitored at
days 35 and42.
On day 21 after reapplication, overall differences in mean L3+L4
density across groups were of borderline signicance (Kruskal–
Wallis test, P=0.056), but %LDR for late instars remained >95%
for all products and dosages. Pairwise comparisons with Dunn’s tests
still revealed signicant differences between control and treatment
groups on day 21 for L3+L4 density, with P values ranging between
0.0001 and 0.0009. Average %LDR for late instars ranged between
85 and 100% on day 28, but differences in L3+L4 density across
groups were no longer signicant beyond day 21 after reapplication
(Kruskal–Wallis tests, P values between 0.090 and 0.481).
Commercial aquaculture represents a major challenge for ma-
laria control in the Amazon Basin (Maheu-Giroux et al. 2010,
Barros and Honorio 2015, dos Reis etal. 2015). Indeed, sh farming
Table 2. Larval density (LD), estimated as the mean number of larvae per dip, and percent larval density reduction (%LDR)
after retreatment of fish ponds in Juruá Valley, northwestern Brazil, with either 10 or 20kg/ha of VectoLex CG and VectoMax
FG biolarvicides
Treatment Group
None (control) VectoLex CG 10kg/ha Vectolex CG 20kg/ha VectoMax FG 10kg/ha Vectomax FG 20kg/ha
Time L1+L2 L3+L4 Total L1+L2 L3+L4 Total L1+L2 L3+L4 Total L1+L2 L3+L4 Total L1+L2 L3+L4 Total
48 h LD 0.44 0.46 0.90 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
72 h LD 0.39 0.49 0.88 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
7 d LD 0.36 0.40 0.76 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
14 d LD 0.29 0.59 0.88 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
21 d LD 0.81 1.01 1.82 0.01 0.01 0.02 0.06 0.01 0.07 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 95.6 96.5 96.1 83.2 96.5 89.1 100.0 100.0 100.0 100.0 100.0 100.0
28 d LD 0.70 0.97 1.67 0.00 0.00 0.00 0.07 0.04 0.11 0.01 0.01 0.02 0.01 0.03 0.04
%LDR — — — 100.0 100.0 100.0 77.3 85.4 81.3 90.4 95.9 94.2 92.1 88.9 89.9
35 d LD 0.19 0.27 0.46 0.04 0.01 0.05 0.04 0.03 0.07 0.03 0.03 0.06 0.1 0.05 0.15
%LDR — — — 24.7 86.9 61.4 52.3 60.7 56.7 0.0 55.6 36.8 0.0 33.5 0.0
42 d LD 0.22 0.25 0.47 0.18 0.07 0.25 0.08 0.07 0.15 0.09 0.09 0.18 0.08 0.06 0.14
%LDR — — — 0.0 1.1 0.0 17.5 1.1 9.1 0.0 0.0 0.0 0.0 13.8 0.0
Average densities in bold are signicantly different from those in the control group (P<0.05) for the same larval stages (L1+L2, L3+L4, or all), and
on the same day of monitoring (Kruskal–Wallis test followed by posthoc Dunn′s tests).
Table 1. Larval density (LD), estimated as the mean number of larvae per dip, and percent larval density reduction
(%LDR) after the first treatment of fish ponds in Juruá Valley, northwestern Brazil, with either 10 or 20kg/ha of VectoLex
CG and VectoMax FG biolarvicides
Treatment Group
None (control) VectoLex CG 10kg/ha Vectolex CG 20kg/ha VectoMax FG 10kg/ha Vectomax FG 20kg/ha
Time L1+L2 L3+L4 Total L1+L2 L3+L4 Total L1+L2 L3+L4 Total L1+L2 L3+L4 Total L1+L2 L3+L4 Total
0 h LD 0.85 0.97 1.82 0.65 1.11 1.76 0.48 1.22 1.70 0.54 1.21 1.75 0.55 1.29 1.84
48 h LD 0.29 0.78 1.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
72 h LD 0.17 0.81 0.98 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
7 d LD 0.44 1.33 1.77 0.07 0.00 0.07 0.08 0.00 0.08 0.02 0.00 0.02 0.09 0.00 0.09
%LDR — — — 78.5 100.0 95.9 66.0 100.0 95.1 92.6 100.0 98.8 67.3 100.0 94.9
14 d LD 0.63 1.05 1.68 0.12 0.09 0.21 0.25 0.16 0.41 0.19 0.13 0.32 0.14 0.16 0.30
%LDR — — — 74.8 93.3 87.6 27.4 88.0 73.7 49.4 90.8 80.1 65.3 88.5 82.2
21 d LD 0.81 1.06 1.87 0.23 0.30 0.53 0.36 0.30 0.66 0.12 0.27 0.39 0.14 0.30 0.44
%LDR — — — 62.4 75.3 70.5 18.7 77.7 62.0 76.4 79.6 78.2 71.0 79.4 76.6
Average densities in bold are signicantly different from those in the control group (P<0.05) for the same larval stages (L1+L2, L3+L4, or all) and on
the same day of monitoring (Kruskal–Wallis test followed by posthoc Dunn′s tests).
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945Journal of Medical Entomology, 2020, Vol. 57, No. 3
Table 2. Larval density (LD), estimated as the mean number of larvae per dip, and percent larval density reduction (%LDR)
after retreatment of fish ponds in Juruá Valley, northwestern Brazil, with either 10 or 20kg/ha of VectoLex CG and VectoMax
FG biolarvicides
Treatment Group
None (control) VectoLex CG 10kg/ha Vectolex CG 20kg/ha VectoMax FG 10kg/ha Vectomax FG 20kg/ha
Time L1+L2 L3+L4 Total L1+L2 L3+L4 Total L1+L2 L3+L4 Total L1+L2 L3+L4 Total L1+L2 L3+L4 Total
48 h LD 0.44 0.46 0.90 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
72 h LD 0.39 0.49 0.88 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
7 d LD 0.36 0.40 0.76 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
14 d LD 0.29 0.59 0.88 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
21 d LD 0.81 1.01 1.82 0.01 0.01 0.02 0.06 0.01 0.07 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 95.6 96.5 96.1 83.2 96.5 89.1 100.0 100.0 100.0 100.0 100.0 100.0
28 d LD 0.70 0.97 1.67 0.00 0.00 0.00 0.07 0.04 0.11 0.01 0.01 0.02 0.01 0.03 0.04
%LDR — — — 100.0 100.0 100.0 77.3 85.4 81.3 90.4 95.9 94.2 92.1 88.9 89.9
35 d LD 0.19 0.27 0.46 0.04 0.01 0.05 0.04 0.03 0.07 0.03 0.03 0.06 0.1 0.05 0.15
%LDR — — — 24.7 86.9 61.4 52.3 60.7 56.7 0.0 55.6 36.8 0.0 33.5 0.0
42 d LD 0.22 0.25 0.47 0.18 0.07 0.25 0.08 0.07 0.15 0.09 0.09 0.18 0.08 0.06 0.14
%LDR — — — 0.0 1.1 0.0 17.5 1.1 9.1 0.0 0.0 0.0 0.0 13.8 0.0
Average densities in bold are signicantly different from those in the control group (P<0.05) for the same larval stages (L1+L2, L3+L4, or all), and
on the same day of monitoring (Kruskal–Wallis test followed by posthoc Dunn′s tests).
ponds are among the main larval habitats in Juruá Valley, currently
the area with the highest malaria transmission levels in Brazil (dos
Reis etal. 2015, Martins etal. 2018). These are relatively small, easy
to nd, and readily accessible water bodies that constitute ideal tar-
gets for larviciding (World Health Organization 2013).
Here we show that commercially available biological larvicides
can signicantly reduce anopheline larval density in sh farming
ponds under eld conditions, with substantial residual effect. We
found >95% reduction in late instar density up to 7 d after the rst
application and up to 21 d after reapplication of the same products.
Importantly, the study period overlapped the rainy season in the
Amazon, when heavy rainfall may potentially raise the water level
of larval habitats, diluting the products and washing away oating
toxins. Percent larval density reduction was similar across treatment
groups, irrespective of the formulation (VectoMax FG or VectoLex
CG) or dosage (10 or 20kg/ha) used.
Taken together, these results support the use of biological larvi-
cide formulations to reduce anopheline larval density in areas where
larval habitats can be easily identied and treated. However, whether
decreased larval density will translate into reduced local malaria
transmission remains to be determined. To address this gap, we re-
cently started a 1-yr eld trial of monthly treatment with 20kg/ha
of VectoMax FG of 170 sh farming ponds in Juruá Valley, which
is expected to help dene the role of larvicide-based larval source
management in malaria control in this and similar settings across
the Amazon Basin.
Table 1. Larval density (LD), estimated as the mean number of larvae per dip, and percent larval density reduction
(%LDR) after the first treatment of fish ponds in Juruá Valley, northwestern Brazil, with either 10 or 20kg/ha of VectoLex
CG and VectoMax FG biolarvicides
Treatment Group
None (control) VectoLex CG 10kg/ha Vectolex CG 20kg/ha VectoMax FG 10kg/ha Vectomax FG 20kg/ha
Time L1+L2 L3+L4 Total L1+L2 L3+L4 Total L1+L2 L3+L4 Total L1+L2 L3+L4 Total L1+L2 L3+L4 Total
0 h LD 0.85 0.97 1.82 0.65 1.11 1.76 0.48 1.22 1.70 0.54 1.21 1.75 0.55 1.29 1.84
48 h LD 0.29 0.78 1.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
72 h LD 0.17 0.81 0.98 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
%LDR — — — 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
7 d LD 0.44 1.33 1.77 0.07 0.00 0.07 0.08 0.00 0.08 0.02 0.00 0.02 0.09 0.00 0.09
%LDR — — — 78.5 100.0 95.9 66.0 100.0 95.1 92.6 100.0 98.8 67.3 100.0 94.9
14 d LD 0.63 1.05 1.68 0.12 0.09 0.21 0.25 0.16 0.41 0.19 0.13 0.32 0.14 0.16 0.30
%LDR — — — 74.8 93.3 87.6 27.4 88.0 73.7 49.4 90.8 80.1 65.3 88.5 82.2
21 d LD 0.81 1.06 1.87 0.23 0.30 0.53 0.36 0.30 0.66 0.12 0.27 0.39 0.14 0.30 0.44
%LDR — — — 62.4 75.3 70.5 18.7 77.7 62.0 76.4 79.6 78.2 71.0 79.4 76.6
Average densities in bold are signicantly different from those in the control group (P<0.05) for the same larval stages (L1+L2, L3+L4, or all) and on
the same day of monitoring (Kruskal–Wallis test followed by posthoc Dunn′s tests).
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946 Journal of Medical Entomology, 2020, Vol. 57, No. 3
Acknowledgments
We thank Maria José Menezes for excellent administrative support; Dr.
José Bento P. Lima and Prof. Maria Anice Sallum for helpful suggestions;
and Hélio Cameli, Muana Araújo, Francisco Menezes, and José Wilson for
their invaluable logistical support. Financial support was provided by the
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Brazil
(grant 2016/18740–9). P.S.F. receives a FAPESP post-doctoral fellowship
(grant 2016/25617–9), and M.U.F. receives a senior research scholarship
from the Conselho Nacional de Desenvolvimento Cientíco e Tecnológico
(CNPq), Brazil. Valent BioSciences LLC supplied the biological larvicides
and one mistblower. Dr. Peter DeChant (Global Technical Manager at Valent
BioSciences) provided technical expertise in eld trial implementation. The
funders had no role in data collection and analysis, decision to publish, or
preparation of the manuscript.
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