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A piece of the puzzle: seasonality, distribution and
Leishmania infection rates in sand ies on the
Brazilian side of Foz do Iguaçu
Vanete Thomaz-Soccol
Federal University of Paraná (UFPR)
André Luiz Gonçalves
Federal University of Paraná (UFPR)
Alceu Bisetto-Jr
SESA- Secretary of Health of the State of Paraná and the Ninth Health Region
Rafael Antunes Baggio
Federal University of Paraná (UFPR)
Adão Celestino
SESA- Secretary of Health of the State of Paraná and the Ninth Health Region
Manuel Hospinal Santiani
Federal University of Paraná (UFPR)
André Souza
Foz do Iguaçu City Hall, Zoonosis Control Center, Foz do Iguaçu
Mario Mychalizen
Universidade Positivo
Marcelo Eduardo Borges
Federal University of Paraná (UFPR)
Cláudio Adriano Piechnik ( Claudio.Piechnik@uibk.ac.at )
University of Innsbruck
Research Article
Keywords: Cutaneous leishmaniasis, Dispersion, Environment, Infection, Insect Vectors, Leishmania,
Parasite, Psychodidae, Season, Visceral leishmaniasis
Posted Date: December 5th, 2022
DOI: https://doi.org/10.21203/rs.3.rs-2330805/v1
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Read Full License
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Abstract
Background: The recent geographic expansion of
Leishmania infantum
vectors in the triple border area of
Argentina, Brazil, and Paraguay has highlighted the need to know the seasonality, parasite infection rate,
and the factors that contribute the dispersal and handling of this parasite.
Methods: Entomological, quantitative longitudinal studies were conducted in Foz do Iguaçu, Brazil, where
sand y abundance was higher in cross-sectional studies. Monthly sand y samplings occurred in 2014-
2015.
Leishmania
DNA was detected by PCR and subsequently sequenced, classied, and the infection
rate was estimated. The study also featured an observational and descriptive design. Environmental
variables were analyzed at the micro- and mesoscales, and the data were evaluated along with
entomological and infection inputs.
Results: A total of 3,582 sand ies were caught.
Lutzomyia longipalpis
was the predominant species
(71.5%) among 13 species found in one year of sampling. Four species,
Evandromyia edwardsi,
Expapillata rmatoi, Micropygomyia ferreirana
, and
Pintomyia christenseni
were reported for the rst
time. The NDVI, distance from water, sex, west-to-east wind, and wind speed were signicant variables for
the intra-environment presence and/or abundance of vectors. The presence and/or abundance of vectors
in peri-domicile were inuenced by rain, altitude, maximum temperature, minimum and maximum relative
humidity, west-to-east wind, wind speed, and sex. Considering PCR positivity, females infected with
L.
infantum
were found throughout the year, and especially with
Lu. longipalpis
(prevalence means of 16.4).
Conclusions: Vector colonization concentrates on urban and peri-urban hotspot areas, with some
individuals being present in various parts of the city and few sites showing high vector abundance. This
distribution suggests that the risk of actual contact between humans and parasitic vectors in urban areas
during the epidemic period is associated with patches of peri-urban vegetation and then spreads across
urban areas. We can state that, in the period of this study, the most critical transmission phase for
L.
infantum
in the region is from January to May. Therefore, future management plants to reduce access to
reservoirs might reduce sand y infection and consequently human and animal infections.
Background
Anthropogenic land use changes cause many infectious disease outbreaks and alter the transmission of
endemic infections. These include agricultural encroachment, deforestation, road and dam construction,
irrigation, wetland alteration, mining, concentration or expansion of urban environments, coastal zone
degradation, and, more recently, pipeline construction [1–4]. Urbanization leads to a sharp and signicant
increase in the previously identied risk factors and the development of new and complex scenarios
leading to the transmission of visceral leishmaniasis (VL) in particular. Some risk factors are new, while
others, already known, are becoming more important. Moreover, while some risk factors are related to a
particular eco-epidemiological entity, others affect all cycles of leishmaniasis and its spread.
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In Brazil and many other South American countries, the transmission scenario of VL has changed [4–7].
During the last four decades, the migration of populations from rural to urban areas has led to the rapid
urbanization of VL. Moreover, unplanned urbanization encompassing adjacent rural areas where the
zoonotic cycle of leishmaniasis occurs promotes its rapid spread and infection among humans [8–14]. A
major environmental change in Brazil that caused a VL epidemic was the construction of gas pipelines in
the 1990s [15], which had signicant consequences for the geographic expansion of VL and cutaneous
leishmaniasis (CL) [3, 14, 16].
Similar to VL, CL epidemics have occurred in the South region of Brazil (States of Paraná, Santa Catarina,
and Rio Grande do Sul) over the past four decades. The southern states have accumulated 4,643 cases in
the last ten years. More recently, the annual number of cases has been over 500 (see the Notiable
Diseases Information System - SINAN database) [17]. Approximately 98% of the clinical CL cases in
humans occurred in Paraná. Likewise, VL showed a rapid expansion towards the south-central part of
South America, especially in the Central-West and Southeast regions of Brazil, between 1998 and 2008.
However, the South region of the country also experienced the emergence of
Leishmania infantum
(Kinetoplastida: Trypanosomatidae), causing VL. The rst case was recorded in São Borja, Rio Grande do
Sul, followed by epidemics in Argentina and Paraguay [2, 8, 18–20].
In the State of Paraná, health decision-makers were alerted in 2011 to the presence of the main vector of
L. infantum
in Puerto Iguazú, Argentina [21]. In 2012, the presence of the vectors was conrmed on the
Brazilian side [22]. In that regard, a transversal study on sand y dispersal in the far west of Paraná
showed that vectors and reservoirs of CL and VL were present in that region [13, 23]. Identifying variables
such as transmission risk periods and abiotic factors can lead to more specic prevention and control
strategies. From this perspective, the present study aimed to evaluate the sand y fauna in the city of Foz
do Iguaçu, including its temporal dynamics and the ecological factors involved, as well as the rates of
Leishmania
infection in these vectors and the periods that represent the greatest risk for humans and
animals to acquire the parasite. Based on this reasoning, the following hypotheses were raised: 1) The
periods of risk for
Leishmania
infection can be identied by monitoring the longitudinal uctuation of the
sand y fauna; 2) The rate of
Leishmania
infection in the sand ies follows the uctuation of the
population of these vectors; 3) The epidemiology of VL can be inuenced by the behavior of
Lu.
longipalpis
, present in the peridomicile and intradomicile areas. This longitudinal study is part of the
International Development Research Centre (IDRC) research project #107577-2, which aims to study the
leishmaniasis epidemics at the triple border of Brazil, Argentina, and Paraguay.
Methods
Study area: Sand y collection and identication
This study has an observational, descriptive design based on a quantitative longitudinal survey carried
out in Foz do Iguaçu (25º32'52"S, 54º35'17"W), the city with the largest international border population in
Brazil, with an estimated population (2021) of 257,971 inhabitants according to recent data from the
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Brazilian Institute of Geography and Statistics [24]. Together with the municipalities of Ciudad del Este
(Paraguay) and Puerto Iguazú (Argentina), Foz do Iguaçu forms a large urban settlement in South
America. In a previous transversal study, we showed that different sand y species are present in many
areas of Foz do Iguaçu. However, in certain patches, they are found in higher density, forming hotspots
[13]. From that point on, such hotspots were grouped into four landscape units (strata) for the conduction
of the present longitudinal study: A, B, C, and D (Fig.1). In each stratum, three or four hotspots were used
for sand y collection.
Unit A corresponds to the ‘commercial/administrative’ area of the city and concentrates the highest
density of buildings along the Paraná River. This area contains two forest remnants that occupy a large
portion of this stratum. In unit A, the four hotspots surveyed were 415 (-25°30.430/-54°35.177), 421
(-54°35.177/-54°35.241), 448 (-25°31.240/-54°32.563), and 470 (-25°31.057/-54°31.547). In the last one,
the survey was conducted in both intra- and peridomiciles. Unit B corresponds to one of the eastern
residential areas, bordering rural areas to the east. It has an intermediate housing density and a relatively
even distribution. Three hotspots were surveyed in this unit: 458 (-25°31.091/-54°32.563), 463
(-25°31.057/-54°31.547), and 551 (-25°32.233/-54°33.119). In the latter, the survey was conducted in both
intra- and peridomiciles. Unit C lies in the northern part of the city, bordered to the south by units A and B,
to the west and north by the Paraná River, and to the east by rural areas. It is characterized by a
discontinuous massif interrupted by large green areas (sports elds, small cultivated areas, among
others). Spots 27 (-25°26.433/-54°34.389), 264 (-25°28.511/-54°30.292), and 329 were sampled in both
intra- and peridomiciles (-25°29.175/-54°32.174), and spot 321 (-25°29.321/-54°34.117) only in the
peridomicile. Unit D is located south of the city and of units A and B, in the corner produced by the Iguazú
River when it ows into the Paraná River. It has an intermediate/high density of buildings with vegetation
patches that surround the unit in the beds of both rivers. The sites surveyed were 597 (-25°33.178/
-54°34.374) and 613 (-25°33.598/ -54°35.055), where the sand ies were collected in peridomiciles, and
616, both intra- and peridomiciles (-25°34.139/-54°34.538). The geographic coordinates of all sampled
sites were recorded with a Global Positioning System device (Garmin eTrex10). Thus, 20 sites in total
were sampled, 14 in the peridomicile and six (06) in the intradomicile.
The study was carried out from November 2014 to October 2015. At each site, HP traps (CDC-type) [25,
26] were set up 1.5 m above the ground for three consecutive nights in each month, from 05:30 p.m. to
07:30 a.m. The total sampling effort amounted to 10,122 hours. After collection and screening, all sand
ies were separated by sex and identied morphologically according to the Galati identication keys [27].
Female identication was carried out by dissection of the abdominal segments and morphological
analysis of the spermathecae, whereas males were identied by their genitalia and internal organs.
Moreover, the female sand ies were placed in 2-mL tubes containing 70% ethanol and maintained at −
20 oC for later genetic analyses [13].
Detection of Leishmania DNA in trapped sand y females
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For the molecular assessment of the presence and species identication of
Leishmania
, we worked with
a female pool with a maximum of three individuals of the same species and from the same sample. DNA
was extracted according to Thomaz-Soccol et al.[13]. DNA purity and the concentration of the extracted
genetic material was measured using a spectrophotometer (Nanodrop GE). DNA detection of
Leishmania
was performed by end-point PCR reactions for amplication of the ribosomal internal transcribed spacer
1 (ITS1) using the LITSR and L5.8S primers, previously designed by Schönian et al. [28], in a Veriti
thermocycler. The PCR mix (25 µL) contained 2.5 µL of DNA, 1 X buffer, 50 mM MgCl2, 0.2 mM dNTP, 0.1
pmol of each primer, and 2 U of
Taq
DNA-polymerase. As an internal control, primers were used to
amplify the IVS6 region of the cacophony gene [29] in order to verify the quality of DNA extraction.
Positive and negative controls were added in each PCR reaction. The amplication products were
separated in 1.5% agarose gel and visualized after staining with ethidium bromide. The positive PCR
products in electrophoresis were puried and sent to Macrogen (Korea) for sequencing. The
electropherograms were manually checked on the BioEdit Sequence Alignment Editor software and
compared with sequences deposed in GenBank [30].
Statistical analysis of infection rate
Females were grouped by species and trap, with an average of two or three individuals. A minimum
infection rate (MIR) for the insects was calculated as follows: MIR = number of positive groups ×
100/total number of insects [31, 32]. The samples were considered positive for parasite loads with at
least one parasite per group. Statistical analysis was performed using the GraphPad software. Fisher’s
exact test with a signicance level of 5% was used to compare the proportion of sand ies infected with
the parasite between species. The infection prevalence in the population was determined using the pool
screening test developed by Katholi et al. [33], with a signicance level of ρ < 0.05.
Abiotic variables studied
The climate was classied according to Köppen [34], corresponding to a temperate oceanic or subtropical
highland climate (Cfb),
i.e.
, long and warm summers and short and mild winters. Throughout the year, the
weather is rainy and partly overcast (1,848 mm). March is the month with the highest rainfall rates,
whereas the lowest rainfall rates occur in August [35]. The annual temperature generally varies from 12 to
32°C, rarely reaching values lower than 4 or higher than 36°C. Micro- and mesoscale factors were
evaluated to assess the environmental variables that affect the presence and abundance of sand y
species. Furthermore, during the sand y collection period, interviews were conducted, during which
several questions were recorded and the environmental variables were measured.
The abiotic variables selected for this study are shown in Fig.2, including the mean of the minimum and
maximum temperatures and the relative humidity of each night. The maximum (max) and minimum
(min) temperatures (T) and the relative humidity (RH) were recorded during the sampling period with
digital thermo-hygrometers (TFA, Germany) in each domestic unit. Rainfall and wind velocity data were
obtained from a weather station in the city of Foz do Iguaçu.
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The Normalized Difference Vegetation Index (NDVI) was used to highlight the presence of vegetation and
plant biomass in each studied area [36]. Three LandSat 8 satellite images from February, August, and
October 2014 were used to generate the NDVI. The NDVI values ranged from − 1.0 to + 1.0, with values
closer to + 1.0 indicating a high presence of vegetation and values closer to − 1.0 representing the
absence of vegetation. Maps were made based on bands 6 (B6 – near infrared band) and 5 (B5 – near
red band) of the LandSat 8 satellite and processed using the open software QGIS, version 2.18 [37]. The
normalized difference water index (NDWI) was used to characterize the moisture in the sampled
environments, which also allowed us to estimate the imperviousness of the areas by assessing the
degree of anthropization. The NDWI was generated based on the mid-infrared (6 TM and 5 OLI) and near-
infrared bands (5 – OLI and 4 - TM)). This index was generated according to Gao [38].
In order to test which environmental variables predicted the presence and abundance of sand y species
found in the traps, we applied a Zero Inated Negative Binomial regression (ZINB) with the pscl package
[39] in the R environment [40]. The ZINB model considers the excessive number of zeros and the
overdispersion found in the data by combining a logistic component for the presence and absence of
individuals and a count component that assumes that the predicted abundance values are drawn from a
negative binomial distribution [41, 42]. The analyses were made separately for three species (
Lu.
Longipalpis
,
Nyssomyia whitmani
, and
Ny. Neivai
) and in the intradomicile and peridomicile traps. Since
there was a high degree of multicollinearity between variables (Fig.2), we applied a bidirectional stepwise
regression to select which predictors were included in the model [43]. Firstly, we created a correlation
matrix between all pairs of environmental factors to test their collinearity. Then, each variable was tested
individually with ZINB to predict its inuence on the presence and abundance of individuals in the traps.
The non-signicant variables (ρ > 0.05) for any model were excluded from the analysis. Among the
signicant factors, the variables with the highest p value of each collinear pair (ρ > 0.7 or ρ < − 0.7) were
also excluded (Table1). Next, we regressed with the ZINB model all the remaining candidate variables
against the presence and abundance of specimens. To avoid overparameterization, the variables that did
not increase the predictability of the model were removed. Therefore, we tested for the elimination of
variables those with the highest ρ-value, which were not signicant in each component of the model. This
approach resulted in three different possibilities: 1) removal of the variable from the logistic component
of the model, 2) removal from the count component of the model, and 3) simultaneous removal of
variables from both components of the model. The models were compared by the Akaike Information
Criterion (AIC), after which the model with lowest AIC value was chosen. The elimination process was
repeated until the elimination of candidate variables did not decrease the AIC value for the tested models.
Maps throughout this paper were created using the ArcGIS® PRO software developed by Esri. ArcGIS®
and ArcMap™ are the intellectual property of Esri and are used herein under license. Copyright © Esri. All
rights reserved.
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Table 1
Candidate variables excluded from the model when showing high correlation with other environmental
variables (ρ > 0.7 or ρ < − 0.7).
Species Site Excluded colinear environmental variables
Lutzomyia longipalpis
Intradomicile NDWI, NS Wind
Peridomicile NDWI
Nyssomyia neivai
Intradomicile -
Peridomicile Max temperature
Nyssomyia whitmani
Intradomicile -
Peridomicile Max temperature
(NDVI: Normalized Difference Vegetation Index; NDWI: Normalized Difference Water Index; NS Wind:
North-to-South Wind)
Results
Sand y fauna
During the 12-month period, a total of 3,582 sand ies were collected and classied into 13 different
species. The present study reports, for the rst time, the species
Evandromyia edwardsi
,
Expapillata
rmatoi
,
Micropygomyia ferreirana
, and
Pintomyia christenseni
in Foz do Iguaçu. The most abundant
species was
Lu. longipalpis
(71.5%), followed by
Nyssomyia whitmani
(19.9%) and
Ny. neivai
(1.9%). The
average male to female ratio was 3.31:1.00. Unidentiable specimens were named Phlebotominae sp.
(Table2).
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Table 2
Sand y species collected with HP traps in Foz do Iguaçu, Paraná, Brazil from
November 2014 to October 2015, their percentage and sex ratio (male:female).
Species Male Female Total % Sex ratio
Lutzomyia longipalpis
2,237 339 2,576 71.5 6.60
Nyssomyia whitmani
409 342 751 19.9 1.19
Nyssomyia neivai
43 26 69 1.9 1.65
Evandromyia cortelezzii s.l.
28 32 60 1.7 0.88
Brumptomyia brumpti
13 16 29 0.8 0.81
Micropygomyia quinquefer
3 22 25 0.7 0.14
Expapillata rmatoi
8 0 8 0.2 -
Evandromyia edwardsi
0 5 5 0.1 0.00
Migonemyia migonei
4 1 5 0.1 4.00
Pintomyia christenseni
0 4 4 0.1 0.00
Pintomyia pessoai
0 4 4 0.1 0.00
Micropygomyia ferreirana
2 1 3 0.1 2.00
Nyssomyia intermedia
0 2 2 0.1 0.00
Phlebotominae sp. 4 89 93 2.6 0.04
Total 2,751 883 3,634 100.0 3.11
Seasonality
Figure3 shows the numbers of sand ies collected in both peri- and intradomiciles per month. The
highest density was recorded in March and April, and the lowest occurred in July. For the three most
abundant species (
Lu. longipalpis
,
Ny. Whitmani
, and
Ny. neivai
), the peridomicile and intradomicile
populations were analyzed for the behavior of males and females. The results revealed that males and
females of
Lu. longipalpis
enter the houses from February to June. In the peridomicile, both sexes are
more prevalent between January and May. However, the largest population in both ecotypes occurs in
April. With regard to
Ny. whitmani
, there was an increase in the male population in August, December, and
January in the peridomicile. In contrast, inside the houses, the population increased in August, April and
May. Males and females entered the houses and were prevalent in the peridomicile between April and
October, decreasing signicantly in July. With regard to
Ny. neivai
, the adult population was larger in the
peridomicile than inside the houses.
Spatial dispersion by area and season
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The highest abundance in the peridomiciliary environment was observed in unit C, followed by units A
and D. When we analyzed the abundance in the 20 sites, we observed that ve of them (329, 264, 448,
470, and 616) had the highest number of sand ies. In the house environment, sites 329 and 470 showed
the highest numbers of sand ies captured, especially in the autumn and winter. Spatial distribution
maps were constructed for the two species with the greatest abundance in the four units of Foz do
Iguaçu. The females of
Lu. longipalpis
predominated in the summer and autumn (Fig.4), whereas the
females of
Ny. whitmani
predominated in the winter and spring (Fig.5).
Abiotic variables
Based on the data of the 14 environmental variables studied, those that were signicant in at least one of
the ZINB models (count or logistic) were summarized in Table3. The statistically signicant variables for
sand y abundance in the intradomicile were the distance from water (+, positively), NDVI (-, negatively),
west-to-east wind (+), wind speed (-), and sex (+) for
Lu. longipalpis
; maximum (+) and minimum moist (-)
for
Ny. whimani
; and rain (-) for
Ny. neivai
. No variables inuenced the intradomicile presence of these
species. For the peridomicile, the altitude (-), maximum temperature (-), and minimum (+) and maximum
(+) moist inuenced the presence, whereas the altitude (+),west-to-east wind (+), and sex (+) affected the
abundance of
Lu. longipalpis
. The rain (-) and wind speed (-) inuenced the abundance, and the wind
speed (-) inuenced the peridomiciliary presence of
Ny. whitmani
. The wind speed (+) affected the
peridomiciliary abundance of
Ny. neivai
.
Leishmania infection rate in females
Among the 831 females collected, 327 pools with one, two, or three females of the same specie were
assessed for the DNA presence of
Leishmania
spp. Among these, 113 pools belonged to the species
Lu
longipalpis
, 114 pools to
Ny whitmani
, 61 pools to Phlebotominae sp., 15 pools to
Ny neivai
, two pools to
Pintomyia pessoai
, one pool to
Ny intermedia
, and one pool to
Migonemyia migonei
. The positivity for
Leishmania
was 14.1% throughout the year, and most of the infected females were identied as
Lu
longipalpis
(47 pools). Fifteen and three female pools were found for
Ny whitmani
and
Ny neivai
,
respectively. Among the unidentied females, seven pools had DNA of
Leishmania
spp. The highest
number of infected females was found in trap 329 in both the peri- and intradomicile. Table4 shows the
number of infected females per sand y species and the prevalence per area and season.
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Table 4
Number of females assessed for the presence of
Leishmania sp.
DNA, and its prevalence for each sand
y species and unit surveyed in Foz do Iguaçu, Paraná.
Sand y species Examined
pools Female
pool size Total
examined
females
Negative
pools Prevalence a
Min b Avg c Max d
Lutzomyia
longipalpis
113 3 339 66 12.6 16.4 20.8
Nyssomyia
whitmani
114 3 342 99 2.8 4.6 7.1
Nyssomyia
neivai
13 2 26 10 4.7 12.3 26.1
Phlebotominae
spp. 61 2 122 52 4.2 7.7 12.9
Nyssomyia
intermedia
1 1 1 1 0.0 2.5
Pintomyia
pessoai
1 1 1 0 97.5 100.0
Migonemyia
migonei
2 1 2 2 0.0 1.3
Total / Mean a305 1.86 a833 230 11.4 14.1 17.1
a
Unit Season
Unit
ATotal 68 3 204 47 7.8 11.6 16.5
Spring 15 3 45 12 2.7 7.2 15.9
Summer 33 3 99 23 6.4 11.3 18.3
Autumn 10 3 30 6 6.7 15.7 29.7
Winter 10 3 30 6 6.7 15.7 29.7
Unit
BTotal 11 3 33 9 2.0 6.5 16.3
Spring 3 3 9 2 3.2 12.6 33.6
Summer 5 3 15 5 0.0 0.2
Autumn 1 3 3 1 0.0 0.8
a The prevalence of
Leishmania
sp. in the different sand y species was calculated using the average
number of individuals in the pool. Minimum b, average, c and maximum d infection rate.
Page 11/29
Sand y species Examined
pools Female
pool size Total
examined
females
Negative
pools Prevalence a
Min b Avg c Max d
Winter 2 3 6 1 5.6 20.6 45.9
Unit
CTotal 111 3 333 75 9.0 12.3 16.1
Spring 16 3 48 15 0.5 2.1 7.4
Summer 53 3 159 37 7.1 11.3 16.8
Autumn 27 3 81 13 13.5 21.6 31.6
Winter 15 3 45 10 5.8 12.5 23.4
Unit
DTotal 47 3 141 44 0.8 2.2 5.1
Spring 9 3 27 9 0.0 0.1
Summer 5 3 15 4 1.8 7.2 21.8
Autumn 10 3 30 10 0.0 0.1
Winter 23 3 69 21 0.9 3.0 7.9
a The prevalence of
Leishmania
sp. in the different sand y species was calculated using the average
number of individuals in the pool. Minimum b, average, c and maximum d infection rate.
Fifty-six of the 75 pools with positive PCRs were sequenced, allowing species identication of the
parasite in 34 of them. The remaining 22 pools showed a mixed of
Leishmania
spp. sequences in the
electropherogram, which prevented species identication.
Leishmania infantum
accounted for 94% of
infections among the different phlebotomine species. Only one female group of
Ny. neivai
was infected
with
L. braziliensis
. Moreover, microlariae larvae and bacteria were also found in several specimens.
Perhaps the microbiome technique might solve this problem in future research.
Discussion
This longitudinal survey revealed, for the rst time, 13 different sand y species in Foz do Iguaçu.
Previously, eight sand y species [44] had been signaled in 1990 in the west region of the State of Paraná,
with
Lutzomyia longipalpis
being observed for the rst time in 2012 [22] and 11 species in 2014 in a
cross-sectional study conducted in Foz do Iguaçu [13].
Lutzomyia longipalpis
was present for 11 months
(except July) in the present study, representing 71.5% of the populations and prevailing in the 20
peridomicile and intradomicile traps. In the cross-sectional survey mentioned before, the abundance of
this species on the Brazilian side was 55.7%, representing 74.2 and 47.9% in Argentina and Paraguay,
respectively [45, 46]. These results indicate that the vectors do not respect borders, and control measures
Page 12/29
must embrace all three countries. In Brazil, the abundance of
Lu. longipalpis
can vary from 25 to 97%,
depending on the region [47–50], and males generally predominate over females [48, 49, 51, 52]. For
example, in an area of active VL transmission in the Southeast region of the country, the ratio of males to
females was 2.9:1 [48, 51]. In the Northeast region, the same ratio was 2:1 [48].
At the studied location,
Ny. whitmani
accounted for 19.9% of the sand y fauna, whereas
Ny. neivai
accounted for only 1.9%, with the females of these species predominating in colder months. In the cross-
sectional study, the abundance values were 16.4 and 9.4 for
Ny. whitmani
and
Ny. neivai
, respectively. In
Argentina and Paraguay, the abundance of
Ny. whitmani
was 25% (Puerto Iguazú) and 38.8% (Alto
Paraná Department), respectively. In Brazil, in the northern region of Paraná, research conducted in rural
areas where CL is endemic has shown an alternate prevalence of
Ny. whitmani/Nyssomyia intermedia
s.l.
In these areas, transmission of
L. braziliensis
is linked to forest remnants [53–56]. The predominance of
Ny. whitmani
could be reach rates up to 68% [57, 58]. In the northwest of the state (City of Japurá),
Ny.
intermedia
s.l. is the dominant species, followed by
Ny. whitmani
[59, 60]. In south-eastern Brazil, these
species have been found with a high density in endemic areas in the States of São Paulo, Minas Gerais,
and Espírito Santo [61]. Their presence has been recorded in animal shelters and in the peridomicile and
intradomicile.
In Foz do Iguaçu,
Lu. longipalpis
occurred mostly in the summer and autumn, especially in urbanized
areas, and had a lower presence from June to August. Still, when we observe our puzzle image, the period
of highest abundance of
Lu. longipalpis
on the Argentinian side (the other piece of the puzzle) was early
autumn, and the species was mainly distributed in the most urbanized areas [11]. In Latin America,
several studies have reported that a higher prevalence of
Lu. longipalpis
is related to the rainy season,
particularly in northeastern Brazil [47, 62–66]. In a VL focus in the city of Belo Horizonte, Minas Gerais
(Central Brazil), this vector showed higher abundance from October to March, increasing progressively
until February. Then, the population started to decrease in April until reaching the lowest levels from June
to August [47, 49]. In the state of Mato Grosso do Sul, Central Brazil, a survey carried out by Oliveira et al.
[67] for two consecutive years revealed the occurrence of several peaks of
Lu. longipalpis
: the rst in
February, and the second in April, with a higher frequency (72%) in the rainy season compared to the dry
season (28%). In our survey,
Ny. whitmani
females in the intradomicile were mainly observed in May and
June. In the State of Rio de Janeiro,
Ny. whitmani
was abundant in the coolest months (June, July, and
August), although both occurred throughout the year [61]. In Argentina,
Ny. whitmani
mainly occupied
less urbanized areas, showing abundance peaks in early spring and summer [12].
The aim here was to know which variables had signicance for the presence of
Lu. longipalpis
in the
intradomicile and peridomicile. The signicant variables for the intradomicile were NDVI, NDWI, altitude,
minimum temperature, and EW wind, as shown by Salomon [7]. In the peridomicile habitat, in addition to
the previous variables, the minimum and maximum relative humidity were also signicant. Other studies
have supported that the distribution of
Lu. longipalpis
was associated with climatic conditions such as
temperature, humidity, and wind [7, 67]. In addition, peridomicile characteristics such as the presence of
Page 13/29
chickens or dogs [68, 69] and the type and amount of vegetation cover, type of street paving, distance to
water bodies, and landscape features were also related to the distribution of this species [10, 11, 13, 66].
In the present study, the intradomicile presence of
Ny. whitmani
was signicantly related to the altitude,
water distance, NDWI, EW wind, and maximum temperature. In the peridomicile, only the rainfall, EW wind,
and wind speed were signicant. The abundance of
Nyssomyia whitmani
was also correlated with
weather conditions [61, 70], and this species was captured in large numbers in pig and chicken sheds [8].
The distribution of
Ny. whitmani
has also been associated with several landscape features [8, 11, 61, 71–
73]
The infection rate by
Leishmania
was determined using the PCR approach followed by sequencing of the
ITS1 target. Out of 792 traps (22 traps x 12 months x 3 nights), 36 (4.5%) contained infected females.
Two sand y species (
Lu. longipalpis
with 71.5% and
Ny. whitmani
with 19.9%) were found with
L.
infantum
, with a mean infection rate of 14.1% (11.4 minimum – 17.1% maximum). In Argentina, Moya et
al. [45] reported a 3.9% infection rate across the triple border. On the other hand, in the Alto Paraná
Department (on the other side of the puzzle– Paraguay), the infection rate of
Lu. longipalpis
was 23.4%
[46]. In the Americas, the studies conducted thus far showed that the infection rates can change
according to the country/region, season, or vector species. For example, during two years of sampling in
Colombia, the natural infection by
L. infantum
was 1.9% [74]. In Brazil, the estimated infection range was
between 0.2 and 36.5%. Considering the different states that constitute the Brazilian territory, a 0.2%
prevalence of infected females was observed in Bahia [75], 2.6% in Mato Grosso do Sul [76], 2.7 to 3.9%
in Minas Gerais [49, 77], 3.7% in Maranhão [78], 36.5% in Ceará [32], and 4.8 to 7.2% in São Paulo [79].
The Old World is no different in that regard: Branco et al. [80] showed a 4% prevalence of infected
females in Portugal, whereas Goméz-Saladín et al. [81] showed a 2.9% rate in italy. In Morocco, Mhaid et
al. [82] used PCR with ITS as a target and obtained a prevalence rate of 7.3%. In Madrid, 58.5% of the
Phlebotomus perniciosus
specimens were positive for
L
.
infantum
infection using kDNA-PCR methods
[83], whereas in Northern and Central Tunisia the prevalence of infection by
L
.
infantum
within
P
.
perniciosus
was 0.2% using nested ITS-PCR [84]. It would be certainly interesting to apply the same
methodology in order to compare infection rates. In addition, reverse transcription should be used to
differentiate infection only by the presence of DNA, using a robust methodology to obtain more reliable
results. Control measures must be appropriate in order to reduce the risk of
L. infantum
infection in sand
ies. Therefore, it is important to know the infection rates and the periods in which it occurs.
Nyssomyia
whitmani
and
Ny. neivai
have been implicated in the transmission of
L. braziliensis
[85, 86] under
sympatric conditions [13]. Thus, we show that the pathogenic complex (
Leishmania
/hosts) can be
composed of several vectors and genotypes of the parasite and a main reservoir: the dog. Another aspect
that has drawn attention is that these two elements (vector, and reservoir) are closely linked to humans. In
this context, the theoretical (genesis of the focus) and practical (ght strategy) interests are fundamental
to propose control measures.
At this stage, we have gone beyond the critical inventory of collected data, also revealing that: 1) The
population of
Lu. longipalpis
increases in the peridomicile and intradomicile from the summer to autumn;
Page 14/29
2) Population increases in the intradomicile could be a response to reductions in temperature and
environmental humidity, leading females to enter the houses to seek shelter.
The ‘microfocus’ of
L. infantum
can be maintained and rapidly propagated below the 54S parallel in
areas where conditions are now favorable and climate change has already been observed through
temperature increases of about 2°C, as shown by De La Rocque et al. [87]. Therefore, innovative
measures are necessary to control infections, especially in humans. As a result, it is imperative that the
medical service be trained to recognize this disease in new areas where it was not endemic, thus
preventing treatment delays. The increase in the canine population of all continents will help maintain the
macrofocus of VL. The dog population tends to grow due to their proximity to humans, who are
increasingly attached to pets as emotional support. There are many dogs (reservoirs) abandoned in city
streets, which, due to cultural and social factors, are raised for guarding purposes. In many cities, these
animals sleep outside residences, increasing their contact with the vectors in the peridomicile. Infected
dogs have spread across cities and countries (especially in border areas) without being assessed for VL
infection.
In this study, the periods with the highest rates of sand y infection with
L. infantum
were the autumn
and spring. However, there were infected females in ten out of the 12 months surveyed. Chemical control
could be a way to control vector populations when the rst population (August, September) appears. In
the winter period, it could be possible to reduce the population by using chemical control inside human
houses and animal shelters. These measures would be easily performed with knowledge about vector
density peaks outside and inside residences. Moreover, continued surveillance can provide new insights
on a global scale and particularly when it comes to this complex biological ecosystem of vector-parasite-
host-environment-climate, especially in countries and regions that have recently become endemic [88, 89].
Vulnerable populations need assistance and education to understand the life cycle of
Leishmania
and
sand ies and prevent the transmission and worsening of leishmaniasis.
Finally, it has been shown that the methodology employed here should be used by responsible
administrators to implement vector population control and reduction policies; moreover, identifying
hotspots will allow targeted control measures. New vector colonization is concentrated in urban and peri-
urban hotspots, with some individuals being present in various parts of the city. However, few sites show
a high abundance of vectors. This distribution suggests that the risk of actual contact between humans
and parasitic vectors in urban areas during epidemic periods is associated with patches of peri-urban
vegetation, with subsequent dispersion into urban areas; the period of higher transmission of
L. infantum
is from January to May. Therefore, if measures are taken to reduce access to infection sources, there will
be fewer female sand y infections, and, consequently, reduced human infection. If intervention measures
are implemented for vector control from September to December, the population of sand ies will be
smaller, and the risk of protozoan transmission to humans will be reduced.
Conclusions
Page 15/29
Thirteen sand y species were observed in our puzzle piece, of which
Lu longipalpis
prevailed.
Lutzomyia
longipalpis
is present in all sampled sites of Foz do Iguaçu, and hotspot colonization is corelated with the
presence of water bodies and vegetation remnants. The distribution of
Lu longipalpis
was associated
with climatic conditions such as temperature, humidity, and wind speed. The main transmission seasons
of
Leishmania
were the summer and autumn.
Abbreviations
AIC
Akaike Information Criterion
Cfb
temperate oceanic climate
CL
cutaneous leishmaniasis
EW
east-to-west
IDRC
International Development Research Center
max
maximum
min
minimum
NDVI
Normalized Difference Vegetation Index
NDWI
Normalized Difference Water Index
RH
relative humidity
SINAN
Notiable Diseases Information System
T
temperature
VL
visceral leishmaniasis
ZINB
Zero Inated Negative Binomial regression
Declarations
Acknowledgements
Page 16/29
Special thanks to Dr. Oscar Daniel Salomón, Director of the Instituto Nacional de Medicina Tropical,
Puerto Iguazú, Misiones, ARGENTINA; coordinator of the project: "Controlling the emergence and spread
of leishmaniasis at the borders of Argentina, Brazil and Paraguay", supported by IDRC-Canada with the
collaboration of PAHO from 2014 to 2017 and to Dra Zaida Yadon of PAHO - Department of
Communicable Diseases and Health Analysis, Pan American Health Organization, for her collaboration
during the project. We are grateful to the inhabitants of the phlebotomine collection areas in the city of
Foz do Iguaçu to providing access to their households during the survey. Thanks to the Brazilian
government, Paraná State Health Secretariat (SESA- PR) and governments of Foz do Iguaçu for the
logistics and support during eld work. We also thank the Parana Meteorological System (SIMEPAR) for
the data from the meteorological station from Foz do Iguaçu city. We would like to express our special
thanks to the entomological teams of SESA from Paraná State: Alvir Swisderski (
in memorian
), Rimar
Pires, Adelino Fidelis Pereira, Israel Silva Santos and all those who worked so intensively in the eld
sampling, without your help the work would have been unfeasible.
Funding
The International Development Research Centre (IDRC) (grant number 107577-002.VTS), the Brazilian
National Council for Scientic and Technological Development (CNPq), the Fundação Araucária (FA), and
PAHO/WHO supported this work. FA provided reagents. CNPq provided consumables goods. The funders
had no role in study design, data collection and analysis, decision to publish, or preparation of the
manuscript.
Availability of data and materials
The data that support the ndings of this study are available from the corresponding author upon
reasonable request.
Authors’ contributions
VTS, ABJr and AS contributed to the research design and supervised the eldwork; VTS, ALG, RAB, AC and
MHS have been responsible to the eldwork, data acquisition and analysis; ALG identied the sand y
collected; CAP performed the molecular analysis; MM carried out eld survey; VTS, ALG and CAP have
been responsible for data curation, formal analysis, investigation, writing the original draft; MEB was
responsible for performing statistical analysis. VTS and CAP writing, review & editing; VTS was
responsible by funding acquisition. All authors have read and approved the manuscript.
Ethics approvaland consent to participate
Not applicable.
Consent for publication
Not applicable.
Page 17/29
Competing interests
The authors declare that they have no known competing nancial interests or personal relationships that
could have appeared to inuence the work reported in this paper.
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Tables
Table 3 is available in the Supplementary Files section.
Figures
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Figure 1
Hotspots surveyed for sandies and infection by
Leishmania
from November 2014 to October 2015 in
Foz do Iguaçu (one side of the puzzle). The city has been divided into four units. Unit A covers the city
center and borders Paraguay (415, 421, 448, and 470). Unit B centralized and without international
borders has an intermediate housing density with a relatively even distribution (458, 463, and 551). The
northernmost region of Unit C has a greener region (27, 264, 321, and 329). Unit D corresponds to the
Page 25/29
southernmost anks of the Paraná River along the border with Argentina (597, 616, and 625). The maps
were made using the ArcGIS® PRO software developed by Esri. Map data ©OpenStreetMap, scale
1:90,000.
Figure 2
Correlation matrix for the environmental variables measured in the intradomicile (A) and peridomicile (B)
traps used in this study. Colors represents positive (blue) and negative (red) correlations, and white
represents the absence of correlation.
Page 26/29
Figure 3
Environmental parameters and seasonal density of sand ies captured for one year from November 2014
to October 2015 in Foz do Iguaçu, Paraná, Brazil. The left side shows the comparison of climatic and
surface cover parameters (A) Temperature, (B) Humidity, (C) Cumulative rainfall, and (D) Surface cover –
Normalized Difference Vegetation Index (NDVI) and
Normalized Difference Water Index
(NDWI). The right
side shows the total number of sand ies collected per species, sex, and capture site – peridomicile and
Page 27/29
intradomicile, (E) Total specimens, (F)
Lutzomyia longipalpis
, (G)
Nyssomyia whitmani,
(H)
Nyssomyia
neivai
.
Figure 4
Distribution of
Lutzomyia longipalpis
in the hotspots of the four studied units in Foz do Iguaçu, Paraná,
Brazil, shown per season: 2014-2015. (A) Spring, (B) Summer, (C) Autumn, and (D) Winter. The maps were
Page 28/29
made using the ArcGIS® PRO software developed by Esri. Map data ©OpenStreetMap, scale 1:100,000.
Figure 5
Distribution of
Nyssomyia whitmani
in the hotspots of the four studied units in Foz do Iguaçu, Paraná,
Brazil, shown per season: 2014-2015. (A) Spring, (B) Summer, (C) Autumn, and (D) Winter. The maps
