Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages

Arnold S Mmbando; Emmanuel W Kaindoa; Halfan S Ngowo; Johnson K Swai; Nancy S Matowo; Masoud Kilalangongono; Godfrey P Lingamba; Joseph P Mgando; Isaac H Namango; Fredros O Okumu; Luca Nelli

doi:10.1371/journal.pone.0245750

. 2021 Jan 28;16(1):e0245750. doi: 10.1371/journal.pone.0245750

Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages

Arnold S Mmbando ^1,^*, Emmanuel W Kaindoa ^1,², Halfan S Ngowo ^1,³, Johnson K Swai ¹, Nancy S Matowo ^1,^4,⁵, Masoud Kilalangongono ¹, Godfrey P Lingamba ¹, Joseph P Mgando ¹, Isaac H Namango ^1,^4,⁵, Fredros O Okumu ^1,^2,^3,^6,^#, Luca Nelli ^3,^#

Editor: Luzia Helena Carvalho⁷

PMCID: PMC7842886 PMID: 33507908

Abstract

Background

While malaria transmission in Africa still happens primarily inside houses, there is a substantial proportion of Anopheles mosquitoes that bite or rest outdoors. This situation may compromise the performance of indoor insecticidal interventions such as insecticide-treated nets (ITNs). This study investigated the distribution of malaria mosquitoes biting or resting outside dwellings in three low-altitude villages in south-eastern Tanzania. The likelihood of malaria infections outdoors was also assessed.

Methods

Nightly trapping was done outdoors for 12 months to collect resting mosquitoes (using resting bucket traps) and host-seeking mosquitoes (using odour-baited Suna® traps). The mosquitoes were sorted by species and physiological states. Pooled samples of Anopheles were tested to estimate proportions infected with Plasmodium falciparum parasites, estimate proportions carrying human blood as opposed to other vertebrate blood and identify sibling species in the Anopheles gambiae complex and An. funestus group. Environmental and anthropogenic factors were observed and recorded within 100 meters from each trapping positions. Generalised additive models were used to investigate relationships between these variables and vector densities, produce predictive maps of expected abundance and compare outcomes within and between villages.

Results

A high degree of fine-scale heterogeneity in Anopheles densities was observed between and within villages. Water bodies covered with vegetation were associated with 22% higher densities of An. arabiensis and 51% lower densities of An. funestus. Increasing densities of houses and people outdoors were both associated with reduced densities of An. arabiensis and An. funestus. Vector densities were highest around the end of the rainy season and beginning of the dry seasons. More than half (14) 58.3% of blood-fed An. arabiensis had bovine blood, (6) 25% had human blood. None of the Anopheles mosquitoes caught outdoors was found infected with malaria parasites.

Conclusion

Background

Recent advances in malaria control are mostly attributed to scale-up of preventative and treatment measures including, long-lasting insecticidal bed nets (LLINs), indoor residual spraying (IRS), rapid diagnostic tests (RDTs), and artemisinin-based combination therapy (ACT) [1]. In Tanzania, the residual burden varies between districts, but approximately 60% of people are still living in areas having moderate or high burden [2]. As in many other settings, malaria vector control in Tanzania faces several challenges, notably mosquito resistance to commonly used insecticides, and changes in vector behaviours that result in avoidance of indoor control tools [3]. Anopheles mosquitoes that bite or rest outdoors are not readily tackled by LLINs or IRS, and therefore can perpetuate residual disease transmission [4]. Moreover, LLINs and IRS may themselves exacerbate outdoor-biting and resting, thereby worsening outdoor malaria exposure [5,6].

Outdoor biting has been reported in major African malaria vectors, namely Anopheles arabiensis and An. funestus, but also in secondary vector species such as An. rivulorum, An. coustani and An. ziemanni, which can become important vectors in areas where LLINs and IRS effectively controlled An. gambiae and An. funestus [7,8]. Also, human behaviours have been linked with the persistent malaria transmission [9]. Thus, additional mosquito control tools are highly needed to control residual malaria vectors in order to drive transmission to zero [10,11].

While there have been several studies on malaria mosquitoes caught indoors, there is insufficient data on population densities, behaviours and transmission activity of outdoor-biting or outdoor-resting populations. This is partly due to insufficient or lack of appropriate sampling techniques [12,13]. Malaria risk is traditionally mapped using models based on remotely-sensed imagery of climatic and environmental variables to determine spatial and temporal patterns of disease risks at broad-scale [14,15]. However, predictive maps based on such coarse covariates typically lack fine-scale explanatory power for local decision making [16]. Besides, heterogeneities of malaria transmission, especially in low-transmission settings, hinders accurate prediction of residual malaria transmission risks even when risk maps optimized with geo-information techniques [17]. Thus, most malaria risk maps have a poor predictive capacity at a community level and need additional surveillance of malariometric measures from the specific time and place [18].

Improved ecological models for transmission risk can improve outcomes [16], especially if local disease data is incorporated in simple interactive models [19]. Through mosquito surveillance systems, we can identify places with a high risk of residual malaria transmission (hot spot) and places with low transmission (cold spot). Variations of resistant malaria vector population densities could be predicted in terms of space (spatial) and time (temporal), which will help to identify the correct seasons and locations to apply the complementary tools.

To accelerate malaria control towards eventual elimination at local level, there is need for a careful integration of both large-scale and fine-scale surveillance systems to account for variations of risk, associated with mosquitoes resistant to insecticides, or those biting outdoors [16]. This current study investigated the distribution of malaria mosquitoes biting or resting outside dwellings in three low-altitude Tanzanian villages where LLINs are highly used and malaria transmission persists. The study villages are characterized by high pyrethroid-resistant Anopheles mosquitoes. The study focused on outdoor mosquito populations as opposed to indoor populations, and also assessed the likelihood of malaria infections in these villages.

Methods

Study area

This study was conducted in three low-altitude wards (Kivukoni; 8.2135^oS & 36.6879^oE, Minepa; 8.2710^oS & 36.6771^oE, and Mavimba: 8.3124^oS & 36.6771^oE) in the malaria-endemic Kilombero valley in South-Eastern Tanzania (Fig 1). Data collection was done between February 2015 and February 2016. The main economic activity in the area is rice cultivation, but other land use activities included fishing, forestry and livestock-keeping [20]. Annual rainfall is 1200–1800 mm, with intermittent rainfall from November to January, followed by more consistent rainfall starting from March to May. Mean daily temperatures are 20°C - 33°C, and altitude ranges between 120 to 350 m above sea level [21,22]. Primary malaria vectors are Anopheles funestus and Anopheles arabiensis, both of which are resistant to pyrethroids [5,23,24]. Other Anopheles spp. e.g. An. coustani, An. pharoensis, An. wellcomei and An. ziemmani, are also present together with non-malaria mosquitoes such as Mansonia, Culex and Aedes species.

Selection of outdoor mosquito sampling units

Square grids (200m × 200m) were overlaid on the village maps, and the centroids (grid points) of each cell was geo-referenced as described by Mwangungulu et al [21]. A total of 270 grid points with human settlements were randomly selected for mosquito sampling across the three villages: 118 in Kivukoni, 86 in Mavimba and 66 in Minepa. Two sentinel grid points were assigned in each village. Mosquitoes were sampled from each of these sentinel grid points for ten nights in each round (totalling 30 trap-nights/month), repeated ten times from February 2015 to February 2016).

In addition to the sentinel grid points, four others were randomly selected to sample mosquitoes each night. The randomly sampled grids remained were used for nightly repeat sampling for a month, before another set of four random grid points was selected. Following this sampling design, each grid point in each village was visited once per experimental round for the 10 rounds. Therefore, each village had six grids being sampled in each night (four that were randomly selected every month and two which remained fixed). The fixed grids enabled assessment of both spatial and temporal patterns, while the randomly-selected grids enabled assessment of only spatial distribution of malaria vectors.

Mosquito traps and attractant

Mosquitoes host-seeking outdoors were trapped using odour-baited Suna® Traps, while those resting outdoors were trapped using resting Bucket Traps (RBu) (Fig 2). The Suna® traps were suspended 30 cm above ground like in the previous studies (Fig 2A) [25]. The Suna® traps proved to catch significantly higher number of Anopheles species in the field conditions as well as it significantly reduce entry of malaria mosquitoes inside the experimental huts [25,26]. The traps were baited with synthetic attractants dispensed in pellets and supplemented with carbon dioxide gas from yeast-molasses fermentation [27–29]. Yeast-molasses mixtures (35gm yeast,500ml molasses, and 2L water) were prepared one hour before starting mosquito collections each night [30].

Fig 2 — Mosquito Traps: Odour-baited Suna® trap, for sampling host-seeking mosquitoes (A) and Resting bucket trap (RBu) for resting mosquitoes (B).

The RBu traps on the other hand, consisted of 20 litre plastic buckets lined with black cotton lining on the inside to provide dark environments for mosquitoes to hide and rest (Fig 2B). The traps were set at dusk and a small wet cloth placed inside to provide humid condition which favoured mosquito resting [31]. The mosquitoes found resting inside the RBu traps were aspirated out early each morning [32].

Each sampling night, the Suna® traps were placed at the centroid of the selected grids, while the RBu traps were situated 50m away from the Suna® traps. Mosquitoes sampling was done nightly between 6pm and 7am each night.

Assessment of environmental and anthropogenic conditions in the sampling areas

For each grid point, environmental and anthropogenic features potentially affecting outdoor mosquito densities were assessed and recorded within 100m radius from each trap location. First, land use activities like mining, crop-cultivation and house construction events were observed and recorded. Second, land cover characteristics were identified, namely open land, grassland, wetland, seasonal swamp, river stream, shrub and forest. Third, distances to the nearest household, road, cowshed, toilet and water-bodies were also recorded, by using the hand-held GPS. Lastly, anthropogenic activities such as time when people went indoors each night, presence and densities of domestic animals and poultry in peri-domestic areas, and occurrence of leisure activities were observed and recorded. If a certain factor was present in a certain map grid was recorded by ‘‘yes” otherwise ‘‘no”.

Mosquito identification

All mosquitoes collected were retrieved each morning and sorted by sex, physiological state and taxa. An. gambiae s.l and An. funestus s.l mosquitoes were separated in labelled tubes and analysed to identify sibling species, based on DNA from hind limbs of individual mosquitoes, processed by PCR amplification [33,34].

Detection Plasmodium sporozoite infection in malaria vectors

Female Anopheles mosquitoes caught in Suna and RBu traps were segregated by taxa and examined in pools of ten, using ELISA assays to detect Plasmodium circumsporozoite antigens in the mosquito salivary glands [35].

Identification of mosquito blood-meal hosts

The blood-fed Anopheles, which were mainly caught by the RBu-traps, were screened for presence of immunoglobulins indicative of human, dog, chicken, bovine and goat in the mosquito abdomen [36].

Ethics statement

Volunteers participating in this study were adequately informed of the study objectives, potential benefits and potential risks, after which written informed consents were obtained. Since we used the odour-baited mosquito and Resting bucket traps, the volunteers were not at risks of being infected with malaria parasites during the experiments. Ethical approval was obtained from the institutional review board of Ifakara Health Institute (IHI/IRB/No: 34–2014) and the Medical Research Coordinating Council at Tanzanian National Institute of Medical Research Certificate No. NIMR/HQ/R.8a/Vol.IX1903). This manuscript has also granted a permission to publish by NIMR, reference number; NIMR/HQ/P.12 VOL XXX/.

Data analysis

Mosquito count data was analysed using R-statistical software [37]. Factors affecting distribution of malaria vectors were investigated using generalised additive mixed-effect models (gamm) with a Poisson distribution, separately for each mosquito species. Only host-seeking mosquito count data were used to assess the association of residual malaria vectors and factors affecting their distributions. However, resting mosquito data were subjected to descriptive statistics which provided their composition in proportions. Hot-seeking mosquito counts were modelled as a function of land use, environmental, anthropogenic and distance-related factors. To account for the effect of time, a smoothing function of the month (1 to 12) was included as a cyclic cubic spline. To assess consistent patterns in the spatial autocorrelation of the host-seeking mosquitoes counts, a bivariate tensor-product P-spline of X and Y coordinates of the centroid of each cell was used [38]. A random effect was included on cell label, because some of the cells were sampled more than once.

The first models included all measured variables, but Akaike’s Information Criterion (AIC) was performed to select the best subset of variables for each host-seeking mosquito species. Model fitness was assessed by graphically inspecting residuals versus fitted plot to verify homogeneity [39]. Then, the Relative risk ratio (RR) together with 95% confidence intervals (CI) was calculated from the model estimates.

Using the best model for each host-seeking mosquito species, each sampled cell was reclassified according to observed mosquito counts, and maps showing the expected abundance for each species were generated. To visualize maps of such predictions according to a continuous surface, and to highlight “hotspots” of mosquito abundance, ordinary Kriging estimation was done [40], using the cell centroids and predicted mosquito counts. All of the malaria vectors count data caught by both Suna® traps and RBu-traps were combined to assess the species composition, blood feeding and sporozoite rates and the results were presented in percentages.

Results

Host-seeking and resting mosquitoes caught

A total of 8,992 Anopheles mosquitoes were caught, of which 90% (8,089) were unfed suggesting there were host-seeking (caught using Suna® traps) and 10% (903) were resting mosquitoes (caught using RBu traps). Of the host-seeking mosquitoes, 19.2% (1556) were An. arabiensis, 1.9% (155) An. funestus and 90% (7281) were other Anopheles spp (Table 1A). These RBu-traps caught a total of 405 female mosquitoes, whereby about 52.3% (210) were female Culex spp. followed by Anopheles spp. 28.5% (117) and Mansonia spp 19.3% (78). Of the resting mosquitoes, 44.5% (402) were female and 55.5% (501) male mosquitoes. Only 17 female An. arabiensis were caught by RBu-traps, of which 13 were blood-fed and 4 unfed.

Table 1. a: Sibling species identification of primary malaria vectors. 1b: Blood-meal and sporozoite detection in Anopheles species caught.

Laboratory assay	Species tested	No. specimen	PCR-amplification rate	Species confirmed
Species identification- PCR	Anopheles gambiae s.l.	1556	1291/1556 (82.9%)	1291/1291 (100.0%) An. arabiensis
	Anopheles funestus s.l.	155	133/155 (85.8%)	71/133 (53.4%) An. funestus Giles
				55/133 (41.4%) An. rivulorum
				7/133 (5.3%) An. leesoni
Laboratory assay	Species tested	No. specimen	ELISA-detection rate	Host confirmed	Sporozoite confirmed
Blood-meal ELISA	Anopheles arabiensis	28	24/28 (85.7%)	14/24 (58.3%) Bovine	N/A
				6/24 (25.0%) Human
				4/24 (16.7%) Dog
Sporozoite ELISA	Anopheles arabiensis	1556	N/A	N/A	Plasmodium falciparum negative
	Anopheles funestus	155
	Anopheles coustani	955
	Anopheles pharoensis	431
	Anopheles squamosus	239
	Anopheles wellcomei	49
	Anopheles ziemanni	5607
	Total malaria vectors	8992

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Blood-meal preferences and Plasmodium infection status of Anopheles mosquitoes

A total of 24 blood-fed female An. arabiensis mosquitoes were caught by both Suna and RBu traps, of which 58.3% (14) had fed on bovines, 25% (6) on humans and 16.7% (4) on dogs. All of the 8,992 female malaria vectors tested for Plasmodium infection turned out to be negative (Table 1B).

Environmental and anthropogenic factors influencing malaria vector densities

Presence of water bodies covered with vegetation was associated with 22% higher densities of An. arabiensis, 51% lower densities of An. funestus and 59% lower densities of other Anopheles spp. Seasonal swamps also significantly increased An. arabiensis densities by 35%, but had no effect on the other vectors. Presence of natural water bodies such as rivers and springs were associated with increased the densities of the An. arabiensis (91% increase), but had no effect on other malaria vectors. Presence of grassland and shrubs around the sampling points significantly affected An. arabiensis and An. funestus densities, but slightly reduced densities of the other Anopheles spp. by 16%, (Table 2). Lastly, rice cultivation within 100m radius was associated with 19% lower densities of other Anopheles spp, but no effect was observed on densities of An. arabiensis or An. funestus.

Table 2. Factors affecting outdoor malaria vector abundance in the three study villages in the Kilombero Valley, south-Eastern Tanzania.

Category	Variable	Anopheles arabiensis		Anopheles funestus		Other Anopheles species #
		RR [95% C.I]	P-value	RR [95% C.I]	P-value	RR [95% C.I]	P-value
Environmental factors	Grassland	0.94 [0.82–1.08]	0.382	1.14 [0.68–1.90]	0.611	0.84 [0.76–0.94]	0.001
	Shrubs	1.02 [0.89–1.17]	0.771	0.67 [0.29–1.57]	0.353	N/A	N/A
	Natural water bodies	1.91 [1.67–2.18]	<0.001	N/A	N/A	1.05 [0.96–1.15]	0.023
	Artificial water bodies	1.00 [0.90–1.11]	0.944	1.75 [1.20–2.56]	0.043	N/A	N/A
	Covered water bodies	1.22 [1.13–1.34]	<0.001	0.49 [0.33–0.73]	0.021	0.41 [0.39–0.44]	<0.001
	Sunlight water bodies	0.93 [0.85–1.00]	0.007	0.52 [0.37–0.76]	0.025	0.88 [0.80–1.00]	<0.001
	Seasonal swamp	1.35 [1.21–1.51]	<0.001	N/A	N/A	1.01 [0.94–1.08]	0.771
	Turbid water bodies	N/A	N/A	1.68 [1.12–2.54]	0.032	1.26 [1.19–1.33]	<0.001
	Dirty water bodies	0.57 [0.52–0.63]	<0.001	N/A	N/A	1.15 [1.08–1.21]	<0.001
	Open water wells	1.39 [1.28–1.52]	<0.001	N/A	N/A	1.23 [1.16–1.30]	<0.001
	Wetland	1.24 [1.14–1.34]	<0.001	0.73 [0.52–1.02]	0.062	1.59 [1.51–1.68]	<0.001
Land use	Agriculture (rice-field)	0.94 [0.86–1.01]	0.253	1.24 [0.85–1.79]	0.252	0.91 [0.87–0.96]	<0.001
	Number of chickens	1.08 [1.04–1.12]	<0.001	0.84 [0.71–1.00]	0.051	N/A	N/A
	Number of houses	0.85 [0.81–0.88]	<0.001	N/A	N/A	0.75 [0.72–0.77]	<0.001
Human activities	Number of People	N/A	N/A	0.59 [0.44–0.80]	0.012	1.10 [1.06–1.14]	<0.001
Distance (m)	Trap to nearest house	0.84 [0.81–0.88]	<0.001	0.83 [0.66–1.04]	0.122	1.0 [0.96–1.04]	0.933

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RR, Relative risks ratio at the 95% CI, #, stands for the other Anopheles spp. such as An. coustani, An. ziemanni, An. pharoensis and An. wellcomei and N/A: represent the variables which were not selected during the selection of the best models.

Sampling grids where people kept chickens had 8% more An. arabiensis but 16% less An. funestus than grid points with no chickens. Higher house densities were also associated with reduced Anopheles densities (Table 2). However, An. arabiensis catches dropped by 16% for every 1m distance between Suna® trap locations and the nearest house. There was no observable relationship between the trap-house distances and densities of either An. funestus or the other Anopheles species. Similarly, presence of people outdoors influenced the number of Anopheles caught. It reduced An. funestus densities by up to 41%, but increased densities of other Anopheles spp. by 10%.

Temporal patterns of malaria vector densities

Similar temporal patterns were observed for An. arabiensis and other Anopheles species. In the first three months (February to May) there were fewer An. arabiensis compared to An. funestus. From the end of May to September, i.e. after the heavy rains and the start of dry season, there was a general increase in number of malaria vectors (Fig 3). This was followed by a steep decline of vector densities from October to December, which corresponds to the dry season, and an increase from end of December to February, when the short rains began, especially for An. arabiensis.

Spatial patterns of mosquito distribution

Fig 4 shows the interpolated mosquito counts from the Kriging estimations.

There were similar patterns for both the dominant malaria vectors and other Anopheles spp. present in the study villages. A degree of fine-scale heterogeneity was observed between villages, and between species. In Kivukoni village, the hotspots of Anopheles species were small, patchy and isolated, whereas in Minepa, they were larger and uniformly distributed. Mavimba village had only intermediate spatial clustering.

In terms of predicted abundance, An. funestus showed the lowest expected trap’s nightly mosquito count, ranging between 0–2. An. arabiensis count was expected to be between 1–14 mosquitoes per trap per night, whereas the highest abundance was expected for the other Anopheles spp., with expected values ranging from 2–167 (Fig 4). Some differences between the villages emerged in terms of expected abundance, but also for spatial distribution and clustering. In Kivukoni, in fact, besides showing relatively lower abundance for all the considered species, the hotspots seemed to be patchy and more concentrated at the external margins of the village, whereas the central part were characterized by lower abundance. In Minepa high expected counts were observed, with a homogeneous distribution of the vectors without major differences between the central and the marginal part of the village. This was particularly notable for An. arabiensis and An. funestus. In Mavimba, the expected counts were at an intermediate level compared to the other two villages, and the spatial distribution appeared to be patchier and more fragmented. Effects of different ecological variables on vector species distribution are graphically shown in the Supplementary material.

Discussion

Fine-scale surveillance of vector-borne diseases provides important information needed for effective control. Spatial and temporal data allow researchers to draw risk maps, which can be used to predict where and when the disease or disease-vectors will be highest. The present study relied on using exiting odour-baited Suna® trap for outdoor sampling of host-seeking mosquitoes and the RBu trap for sampling outdoor resting mosquitoes which are the proven outdoor mosquito sampling tools [25,31]. The present study assessed both spatial and temporal distribution of residual malaria vectors, the malaria transmission risk, and important ecological factors in three low-altitude villages in rural Tanzania where LLINs are already widely used. The study examined associations between vector densities and multiple environmental, and anthropogenic factors over space and seasons.

Though the initial models included multiple factors as observed, only few were selected in the best models of mosquito abundance. Presence of water bodies covered by vegetation, such as grass and trees, showed a positive association with An. arabiensis vector density, which supports previous observations that this species prefers to breed in temporary shaded water bodies, such as rice paddies [41,42] (S6 Fig). These temporary water bodies were also associated with reduced An. funestus and other Anopheles spp. densities, which tend to prefer permanent water bodies with emergent vegetation [43]. Indeed, An. funestus in this region is now known to prefer permanent or semi-permanent water with emergent vegetation situated at least 100m from the human dwellings [44] (S4 Fig). The map grids point comprised of season swamps has positive associations with An. arabiensis mosquito densities as previously described by (Mala and Irungu) [42] (S7 Fig). Grids consisting of open water wells were shown to have higher numbers of An. arabiensis and other Anopheles spp, most likely because these wells provided temporary oviposition sites for the mosquitoes, as shown by previous studies [42] (S10 Fig). Similarly, wetlands did not seem to affect An. funestus mosquito densities, as this species prefers to breed in the permanent and deep water bodies [43,44] (S11 Fig) (Table 2 & Supplementary materials).

At these fine-scale resolutions, rice cultivation was not shown to affect An. arabiensis densities, though it reduced the abundance of the other Anopheles spp. Although not confirmed by statistical significance, the presence of rice paddies was associated with an increase of An. funestus densities, (Table 2), (S12 Fig). One possible explanation for this is that most of the rice fields found in the study area were closer to human houses, and proximity to human settlements has been observed as a factor favouring An. funestus breeding habitats [44]. The rice cultivation performed in this study area involves a considerable use of pesticides, which are also likely to have an effect on mosquitoes susceptibility to insecticides [45]. The An. funestus mosquitoes are known to exhibit high resistance level towards pyrethroids which is an active ingredient present in many pesticide [3,46], possibly confounding these results.

As shown in a similar study conducted in the same area and time [47], densities of small livestock such as chickens in the map grid significantly increased An. arabiensis mosquito densities indoors (S13 Fig). The correlation between the An. arabiensis and chicken densities in the map grid point was partly due to feeding behaviour of these mosquito species on livestock such as chickens. However, the relationship between chicken densities and malaria mosquitoes was inverse for An. funestus mosquitoes, thus contradicting previous studies [8,47]. It was hard to estimate the effect of the number of chickens in relation to An. funestus densities due to the lower population of these mosquito species outdoors as they prefers to bite and rest indoors [48].

There was a negative association between the number of people outdoors and the number of An. funestus mosquitoes caught, (S15 Fig). This may be partly due to competition between the host-seeking traps and humans in the vicinity, as this species has a high preference for feeding on humans over other vertebrates [48]. However, for the other Anopheles spp., there was an increase of the number of mosquitoes during the trapping nights with more people outdoors. This difference can be explained by the fact that the other Anopheles spp. are opportunistic feeders, as they feed on both human and other hosts, and are also more attracted by synthetic attractants such as those used in the Suna® trap [49]. Also, these other Anopheles spp showed high potential of maintaining malaria transmission at some settings where major malaria vectors are limited [50,51]. The negative effect of distance from the houses observed in the models suggests that the main malaria vectors, An. arabiensis and An. funestus are generally concentrated near dwellings houses, where humans and cattle also reside (Table 2, S16 Fig).

The abundance of both An. arabiensis and the other Anopheles species was highest just after the long rains and the beginning of the dry season (June-September). A possible explanation might be that heavy rains, in addition to creating breeding habitats for the mosquitoes, also washed away the aquatic stages of the mosquitoes (Fig 3). This was also seen in the previous study conducted in Italy that heavy rainfall had negative effect with host-seeking behaviour of Aedes albopictus [52]. An. funestus however exhibited less fluctuation compared to other malaria vectors, most likely due to its preference for semi-permanent or permanent habitats [44]. Also, this is another sign of heterogeneity of malaria vector densities at small scale and that there may be more factors influencing these densities than we assessed.

A small proportion of female resting mosquitoes were caught by using RBu-traps, majority were Culicines and a small proportion of Anopheline mosquitoes. Blood-fed An. arabiensis mosquitoes were mostly fed on bovine hosts followed by human and dog hosts. In this study area, Culex pipiens complex was previously found in large proportion and contributed 79% of the overall indoor biting [53]. The Culex pipiens complex has ability to exhibit a wide range of host blood-meals [54]. All of the malaria vectors subjected to P. falciparum ELISA detection were found to be negative. This finding is different from previous studies which involve sampling indoors in the same villages and reported the presence of parasite positive An. arabiensis and An. funestus mosquitoes [55]. The high proportion of non-human blood-meals in the Anopheles mosquitoes as well as the lack of Plasmodium-infected specimen even after 12 months of sampling, suggests that the risk of malaria transmission in the outdoor environments in these specific villages is very low. If interpreted alongside previous studies, which found infected mosquitoes indoors [55], it can be concluded that the majority of the residual transmission events in the villages actually happens inside houses. Also this might be caused by our outdoor sampling methods which mainly caught younger mosquitoes which are most likely to be uninfected compared to the older mosquitoes [56]. It is also known that young mosquitoes are found in close proximity to the breeding habitats, hence collection of young mosquitoes might have been influenced by the presence of breeding sites in our study areas [57]. It is important therefore to continue improving indoor vector control tools, e.g. LLINs, IRS and mosquito-proof housing as the primary interventions against malaria. In addition, larval source management may be effective for controlling mosquitoes in areas where the habitats can be clearly identified.

Unlike other studies relying on remotely sensed images of climatic and environmental data, this study has demonstrated fine-scale spatial and temporal patterns of Anopheles mosquitoes in the outdoor environments, relying on empirical mosquito trap data and directly observed environmental and human factors. The resulting trends can aid improvements in the prediction of transmission risks even in low-malaria endemic communities where the transmission is heterogeneous.

Conclusion

Outdoor densities of both host-seeking and resting Anopheles mosquitoes had significant heterogeneities between and within villages, and were influenced by multiple environmental and anthropogenic factors. Despite the high Anopheles densities outside dwellings, the high proportion of non-human blood-meals and absence of malaria-infected mosquitoes after 12 months of nightly trapping suggests very low-levels of outdoor malaria transmission in the villages. It is important therefore to continue improving indoor vector control tools, e.g. LLINs, IRS and mosquito-proof housing as the primary interventions against malaria. In addition, larval source management may be effective for controlling mosquitoes in areas where the habitats can be clearly identified.

Supporting information

S1 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of grassland in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(1,020KB, docx)}

S2 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of shrubs in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(977.2KB, docx)}

S3 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of natural waterbodies in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(773.1KB, docx)}

S4 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of artificial waterbodies in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(828.6KB, docx)}

S5 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of covered waterbodies in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(776.4KB, docx)}

S6 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of sunlight waterbodies in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(799.6KB, docx)}

S7 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of seasonal swamps in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(772.9KB, docx)}

S8 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of turbid waterbodies in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(787.5KB, docx)}

S9 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of dirty waterbodies in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(836.5KB, docx)}

S10 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of open water well in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(796.3KB, docx)}

S11 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of wetland in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(864.8KB, docx)}

S12 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of rice fields in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(940KB, docx)}

S13 Fig. Map of predicted hotspots of female mosquitoes’ density and number of chickens in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(875.7KB, docx)}

S14 Fig. Map of predicted hotspots of female mosquitoes’ density and number of houses in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(934KB, docx)}

S15 Fig. Map of predicted hotspots of female mosquitoes’ density and number of people in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(896.5KB, docx)}

S16 Fig. Map of predicted hotspots of female mosquitoes’ density and distance from trap to the nearest house in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(880.7KB, docx)}

Acknowledgments

A special thanks to volunteers who allowed us to install the traps at their premises and the ones who involved in trapping and retrieving the mosquito traps during the study. Many thanks to Miss Claudia Eichenberger for her critical review of this manuscript prior submission, and to Miss Keila Meginnis for her English proofreading and editing suggestions. Mr. Godfrey P. Lingamba died before the submission of the final version of this manuscript. Arnold Sadikiel Mmbando accepts responsibility for the integrity and validity of the data collected and analysed.

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

Fredros Okumu was funded by the Wellcome Trust Intermediate Research Fellowship (Grant number: WT102350/Z/13/Z) which funded this research. Arnold Mmbando was also supported by the Wellcome Trust Masters Fellowship in Public Health and the Association of Physicians of Great Britain and Ireland for funding this research (Grant number 106356/Z/14/Z).

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PLoS One. doi: 10.1371/journal.pone.0245750.r001

Decision Letter 0

Luzia Helena Carvalho

5 Aug 2020

PONE-D-20-16651

Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages

PLOS ONE

Dear Dr. Mmbando,

Thank you for submitting your manuscript for review to PLoS ONE.After careful consideration, we have concluded that your manuscript requires substantial revision, following which it can possibly be reconsidered. According to reviewers some statements were not supported by the manuscript findings. Study design should be clarified and conclusion must be restricted to the authors’ findings. As quoted by the reviewer #1, for example, only 28 blood-fed mosquitoes may not allow concluding about the feeding habits of a vector. It is possible that inappropriate collection sites may have influenced the results. Reviewer #2 complains that the picture showed in the paper is more linked to host-seeking and not resting mosquitoes because of the high number of the host seeking versus resting mosquitoes. For your guidance, a copy of the reviewers' comments was included below

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Reviewer #2: Yes

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PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages

It is generally acknowledged that a greater understanding of the distribution and dynamics of malaria vectors outside of houses is becoming increasingly important and so efforts such as this paper are useful. The methods used in the present paper were sufficiently rigorous for possible conclusions to be determined. I am not sure, however, that despite their best efforts the authors have been able to contribute anything of significance to the scientific canon.

Overall a total of 28 blood-fed mosquitoes is hardly sufficient to draw conclusions about the feeding habits of a mosquito (even though they fit within the accepted framework of what An. arabiensis will feed on) – to quote percentages in the abstract (without providing sample size) is specious.

One problem might be that the collection sites were determined from a map rather than from the ground. Thus, potentially high-density areas may not have been sampled even though they might have been identified by the researchers during a preliminary visit or two. For example, if I am correct the village of Kivukoni is close to the Kilombero River. Previous work has indicated that densities of insects (particularly An. arabiensis) are very high close to the river margins (where the old ferry used to cross) but I notice that this was not actually sampled in the present study.

My own opinion (and it is no more than an opinion) is that in the future, following interventions that significantly reduce vector densities, sampling should be undertaken in high density locations (‘hot spots’ as described by the authors). I am not sure that studies like theirs enable the easy identification of such hot spots, which presumably exist everywhere.

On another point it has been suggested that younger insects are more likely to bite outdoors compared to older ones (e.g. PeerJ 5155) which may explain the lack of infected insects (but which might also mean that targeting such insects would be a useful control technique).

Given that rainfall patterns in many parts of the world are now less predictable than they used to be an indication of the actual rainfall observed during the study (in one of the villages at least) would be useful rather than merely saying that densities were highest at the end of the wet season. Both of the vectors are known to show such patterns – and indeed they have been described (with included rainfall) from areas close to the study villages.

As I understand it the efficacy of the Suna trap is dependent on the placement of the trap in relation to other objects and/or hosts. Thus, whilst putting the traps in the centroids of their sampling grid makes sense from one perspective it might mean that the efficiency (and therefore estimated estimate of population density) is affected. A more concentrated study (with traps in a finer scale grid) might help evaluate this.

The other thing that is, of course, missing from the study is an evaluation of the indoor density of mosquitoes in the study villages. Perhaps the authors undertook such sampling but are hoping to publish this data at another time. As far as I know Suna traps have not yet been used indoors but there is no reason why they should not be used in this way. The elegant stand shown could be placed inside a house to obtain an equivalent sample to the outdoor one.

Although a number of other species have been identified as being possible vectors (such as their reference #5) it has not been suggested that these ‘can become important’ in the absence of the primary vectors. What they may do is maintain a low level of transmission that might result in an epidemic if the principal vectors return (following say the decline in insecticidal effect of an IRS treatment).

The authors state that ‘…. presence of people outdoors influenced the number of Anopheles caught. It reduced An. funestus densities by up to 41%, but increased densities of other Anopheles spp. by 10%’. I would suggest that the reduction in the numbers of the anthropogenic An. funestus in their traps was because the insects were off biting people under those circumstances and were at the same time increasing the number of catholic feeders such as the non-vectors which (by being attracted to the carbon dioxide more than anything else) would then also be caught in the trap.

There are a number of relatively trivial corrections required to the English in the manuscript.

Reviewer #2: GENERAL COMMENTS

The micro geographic level, the transmission is no the same from house to another house. The factor explaining this micro variation is not well understood. Therefore, the problematic is interesting and deserves to be raised. Understanding this variation facilitates delivery of targeted, cost-effective preventative antivectorial interventions against malaria. The paper is well written and the methodology is well-designed to address the question. However, some part of the paper as presented, needs revisions to make it more precise and challenging:

ABSTRACT: Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages

BACKGROUND

Line 2: long-lasting insecticidal bed nets (LLINs) : add the IRS in the list of prevention measures that contribute to reduce malaria cases during the last decade

“…….notably mosquito resistance to commonly used insecticides…” insert a reference confirming the statement.

MATERIAL AND METHODS

Selection of outdoor mosquito sampling units

“Mosquitoes were sampled from each of these sentinel grid points for ten nights each round (totalling 30 trap-nights/month)….” Check this sentence it is no clear. you mentioned 30 trap-nights/month. You have two sentinel sites per village. One round is ten days. I suppose there is one trap per sentinel sites. I guess the total trap per site is 20trap-nights so for the 3 sites you are 60 trap-nights the month

Data analysis

Even it is not state in the paper, the analysis is done by pooling outdoor host-seeking mosquito's fraction and those resting outside. I don’t understand this rational. I suggest to split the two populations and look how the different parameters influence host seeking and resting habits separately. The way the author pool the two population makes some confusion because the host-seeking mosquitoes can bite and goes to rest indoor. And also the outdoor resting mosquitoes may come from the indoor biting fraction. I understand that the number of malaria vector specimens are very low in the resting population but we can’t pool. The picture you showed in the paper is more linked to host-seeking and not resting mosquitoes because of the high number of the host-seeking (all mosquitoes: 8089 host-seeking versus 903 resting and vectors (arabiensis and funestus):1556+155 host seeking versus 17 resting))

FIGURES AND LEGEND

Figure 1: Study area: I suggest to show in the map the location of the two sentinel sites within each village

Figure 3: the legend of the Y axis need more precision (Mean number of malaria vector per trap caught per month???)

Figure 4: is unclear, because the resolution is low. Please improve it.

**********

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Reviewer #1: Yes: J D Charlwood

Reviewer #2: No

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PLoS One. 2021 Jan 28;16(1):e0245750. doi: 10.1371/journal.pone.0245750.r002

Author response to Decision Letter 0

23 Sep 2020

12th August 2020

Dear Editor, PLOS ONE

Re: Research paper re-submission (Manuscript code: PONE-D-20-16651)

We thank the reviewers for reviewing this manuscript titled “Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages”. We kindly thank reviewers and Editor for their constructive comments on this manuscript. Please find all the comments/suggestion addressed in the revised version of the manuscript. All of the edits were highlighted in yellow which can now be included in the new version of the manuscript ready for publication.

In short all of the edits were made as suggested by the reviewers as point by point below, which include rephrasing the sentences, figures improvements, data analysis section, adding references, clarifying some details in the experimental setups and improving the discussion of the findings and compare it with previous studies and all these changes were left highlighted in yellow in the revised manuscript.

Once again thank you so much for your support and hope to hear from you.

Yours sincerely

Arnold

ammbando@ihi.or.tz

Response to reviewer’s comments

Reviewer #1:

Response: Thank you so much for the above concern, and we totally agree with you on the need to accelerate effort on outdoor mosquito control which at some settings mediate even lower level of malaria and other mosquito-borne illnesses. Also, by considering the limited resource countries like Tanzania, malaria control campaigns need to rely on small/little resource we have to fight against malaria which still kills a lot of <5 years old and pregnant women in our country. To do this we need to know exactly location and time to target these malaria-vectors at fine scale and even to predict on mosquito densities based on time and space. Thus, this study brings an insight to the focal malaria vector control experts so that they know where and when to apply vector-control interventions with limited resources we have rather than focusing on the entire villages which will consume a lot of resources and time.

Response: Thank you so much for bring this up. We have now added the sample size in the abstract section, and acknowledged the limitations of having these small numbers. Please find it in the result section, page 1, lines 62-63.

Response: Thank you this comment. The target of this study was to assess the spatial and temporal distribution patterns of malaria vectors outdoors for which the sampling location was selected based on the previous study conducted in the same villages by Mwangungulu et al 2013. To be able to cover the entire study villages map grip points were first selected based on the settlement patterns which are concentrated at the middle of the village which also where most of mosquitoes are concentrated. The grid points which met the inclusion criterial for mosquito sampling were then randomly selected in such a way that they represent the entire study villages to avoid the positional biasness. Since, along the river margins where no/fewer human dwellings led us to have fewer sampling locations as compared to the center of Kivukoni village. This is well explained in the method section in page 5 first paragraph, lines 142-148.

Response: Thank you for the above explanation. This study was designed to also capture the variations of vector densities across the sampled grids/areas at a specific time. We agree that sampling should be done in high mosquito density areas, but first we need to identify those high density areas, which was the exactly the target of this study. This is clearly found in the method section page 5, lines 142-157.

Response: Thank you very much for this comment. This is a valid point. We have added a paragraph under the discussion section to capture the concept that younger insects are more likely to bite outdoors compared to older ones hence our study might have been affected by the outdoor collection which may have led to limited collection of infected mosquitoes. This also was well explained in a separate study done in the same study area at the same time which showed more malaria transmission occurred indoors and it was mostly mediated by Anopheles funestus mosquitoes and small extent Anopheles arabiensis, (Kaindoa et al 2018). The combination of these two surveillances could answer why most of the transmission occurred indoors compared to the outdoor. See addition information in the discussion section page 15, lines 411-415.

Response: Thank you so much for pointing this out. We have now added the rainfall data gathered from the previous study (Ngowo et al 2017) done at the same time at 30km from Kivukoni village. See it in page 4, lines 131-133.

Response: Thank you for this. We did dot evaluate the impact of Suna trap on mosquito collection based on the finer scale as we relied on the previous evidence on the efficacy of Suna trap for outdoor mosquito sampling, however, we have other separate studies which are currently ongoing which evaluate the effectiveness of different outdoor mosquito sampling tools which are conducted in one village. This is well explained in page 13, first paragraph, 333-335.

Response: Thank you reviewer for this. Suna trap use attractants hence it is discouraged to put mosquito attractants inside human houses. Ethically it is not acceptable to attract mosquitoes toward humans inside the houses. Furthermore, adding attraction inside human dwellings may overestimate the indoor vector densities. However, we do have another study by which was done to assess indoor vector densities using CDC LT and Prockpack. (Kaindoa et al 2018) which was done in the same study village at the same time which assessed the impact of indoor residual malaria vectors as well as how settlements and human biomass patterns affect mosquito densities, (Kaindoa et al 2018). See it in page 14, lines 369-371.

Response: We have added a paragraph in the discussion section to highlight the potential of other vector species in maintaining malaria transmission though at lower levels. See it page 14, lines 384-386.

Response: Thank you for the above concern. We agree with you that, there were competition in terms of mosquito attractions between carbon dioxide baited Suna-traps and humans outdoors during the sampling time. This is more seen in An. funestus mosquitoes than other malaria vectors because these mosquitoes are high anthropophilic as well as they prefer to bite indoors than outdoors. Other, malaria mosquitoes such as An. arabiensis and secondary vectors are opportunistic feeders for which they had a wide range of feeding hosts. This is well explained in page 14, lines 376-384.

There are a number of relatively trivial corrections required to the English in the manuscript.

Response: Thank for pointing out this concern. We have now revised the manuscript accordingly.

Reviewer #2:

GENERAL COMMENTS

Response: Thank you so much for the acknowledgements and we have now revised the manuscript in point by point below

ABSTRACT: Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages

BACKGROUND

Line 2: long-lasting insecticidal bed nets (LLINs) : add the IRS in the list of prevention measures that contribute to reduce malaria cases during the last decade

Response: Thank you for pointing out this. We have added IRS in the revised manuscript as suggested. Changes are found in the first paragraph, page 3, lines 77-79.

“…….notably mosquito resistance to commonly used insecticides…” insert a reference confirming the statement.

Response: Thank you reviewer for this. The reference has been added in the revised manuscript in paragraph 1 page 2, line 83.

MATERIAL AND METHODS

Selection of outdoor mosquito sampling units

Response: Thank you for pointing this out. It is true that we have two fixed grids point/village and four randomly selected map grid points which changed each night. We had 30 trap-nights/month because the four randomly selected grids/site/night were sampled together with the two sentinel grids points/site which totaling 6-grids points/site/night. This is well explained in page 5 lines 142-148.

Data analysis

Response: Thank you so much for pointing this up. This was added into the main manuscript that, resting malaria vectors were dropped during the analysis of anthropogenic, environmental and distance related factors impact on malaria vectors. The resting malaria vectors caught were lower in number for the model to select. We did descriptive statistics (proportions and percentage) to determine the composition of resting malaria vectors. Reason for splitting host-seeking and resting malaria vectors was due to huge difference in numbers of mosquitoes caught by these two methods. However, all of the malaria vectors caught by both Suna and Resting bucket traps were packed and submitted to the laboratory for different assays, i.e. specie ID, sporozoite analysis and blood meal ELISA. Please revised data analysis section in page 7,lines 210-234.

FIGURES AND LEGEND

Figure 1: Study area: I suggest to show in the map the location of the two sentinel sites within each village

Response: Thank you so much for this. Please see the revised study area map, Figure 1.

Figure 3: the legend of the Y axis need more precision (Mean number of malaria vector per trap caught per month???)

Response: Thank you for this. Please find revised Y-axis legend in the Figure 3.

Figure 4: is unclear, because the resolution is low. Please improve it.

Response: Thank you for this. Please find high resolution of the Figure 4 in the revised manuscript.

________________________________________

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #1: Yes: J D Charlwood

Reviewer #2: No

PLoS One. doi: 10.1371/journal.pone.0245750.r003

Decision Letter 1

Luzia Helena Carvalho

16 Nov 2020

PONE-D-20-16651R1

Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages

PLOS ONE

Dear Dr. Mmbando,

Thank you for submitting your manuscript to PLoS ONE. After careful consideration, we felt that your manuscript requires revision, following which it can possibly be reconsidered. At this time, two major concerns need to be clarified by the authors. First, about the choice of traps that might not be the best to study outdoor transmission (bias towards the anthropophilic An. Funestus). Second, The paper would gain in clarity and robustness if the other Anopheles species were also taken into consideration, especially as the data are already available. Finally, the authors should still address a number of minor corrections and comments raised by the reviewer #3.

Please submit your revised manuscript by November 30. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Luzia Helena Carvalho, Ph.D.

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

Reviewer #3: Yes

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6. Review Comments to the Author

Reviewer #2: One of my big concern is the pooling of hostseeking and resting population for the analysis. Now the authors have considered all comments.

Reviewer #3: This study is a sound work on the spatio-temporal analysis of the malaria vectors collected outdoors in 3 villages of Tanzania. The manuscript has already been improved after a first review process, but few concerns remain that need to be taken into consideration, especially 2 main comments.

1. The choice of traps might not be the best to study outdoor transmission, as raised by the authors themselves on lines 387-389, because host-seeking traps and humans in the vicinity introduced a bias, An. funestus being highly anthropophilic, this species will avoid the traps to feed on humans. This is particularly obvious in Table 1a in which only 155 specimens of An. funestus s.l. where collected compared to 1556 specimens of An. arabiensis. Is this small number due to the traps that were not appropriate for this species or to its low density? Therefore, the choice of the 2 types of traps should be better explained.

2. Seven mosquito taxa have been collected during the 12 months collection (Table 1b). However, the manuscript is focusing on 2 species only, An. arabiensis and An. funestus. The third category is named "Other Anopheles". The paper would gain in clarity and robustness if the other species were also taken into consideration, especially as the data are already available (Table 1b). When possible, the spatio-temporal analysis should be more specific, including for instance An. zeimanni which was collected in high numbers (n=5607 specimens), 5 times more than An. arabiensis.

They are also a good number of minor corrections and comments that have been included into the attached manuscript for its improvement (see attached file). For instance, they are some statements that need further explanation to increase their understanding.

Besides, the choice of the analysis as shown in Figure 4 and many supplementary ones (S1.1-16) is quite pertinent and well representative of the factors influencing the presence of malaria vectors.

As a suggestion in the discussion, a GIS mapping of the spatio-temporal factors influencing the presence and abundance of each malaria vector could be developed if a follow up of this work is to be done.

**********

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Reviewer #2: No

Reviewer #3: Yes: Sylvie MANGUIN

Attachment

Submitted filename: 20 PLoS One Mmbando Mosq Tanzania-edited.docx

Click here for additional data file.^{(83.4KB, docx)}

PLoS One. 2021 Jan 28;16(1):e0245750. doi: 10.1371/journal.pone.0245750.r004

Author response to Decision Letter 1

27 Nov 2020

24th November 2020

Dear Editor, PLOS ONE

Re: Research paper re-submission (Manuscript code: PONE-D-20-16651)

We would like to thank you and the reviewers for constructive comments and for offering us the opportunity to resubmit a revised version of our paper entitled “Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages”.

With regards to reviewer #3’s main concern (i.e. choice of traps that might not be the best to study outdoor transmission), we have provided further clarification on the rationale behind the choice of Suna and Resting bucket traps, including key references to justify our experimental design in this specific ecological setting.

With regards to the reviewer’s second concern (i.e. pooling the other Anopheles species or keeping them separated), we have discussed this extensively between ourselves, and the large number of field collaborators taking part in the extended project. Given the low contribution to malaria transmission given by non-An. arabiensis and non-An. funestus vectors, we decided not to put too much emphasis on the other Anopheles species. In addition, if we should consider each species separately, the length of the manuscript would increase substantially, and would pull the reader’s attention out of the main focus of our manuscript (i.e. focusing on vectors known to be responsible for malaria transmission in our study area).

We have now included further clarification with respect to the previous points, by modifying some paragraphs in the data analysis and discussion sections, and by adding mor relevant references.

Finally, we made several minor changes (and typos corrections) to further improve the reading flow. We believe our manuscript has substantially improved.

Please find our detailed point-by-point response to each reviewer’s report. We have highlighted in yellow the specific changes/additions made, in the manuscript main body.

Once again thank you very much for your support and hope to hear from you.

Yours sincerely

Arnold

ammbando@ihi.or.tz

Response to reviewer’s comments

Reviewer # 3

Comments 1: The choice of traps might not be the best to study outdoor transmission, as raised by the authors themselves on lines 387-389, because host-seeking traps and humans in the vicinity introduced a bias, An. funestus being highly anthropophilic, this species will avoid the traps to feed on humans. This is particularly obvious in Table 1a in which only 155 specimens of An. funestus s.l. where collected compared to 1556 specimens of An. arabiensis. Is this small number due to the traps that were not appropriate for this species or to its low density? Therefore, the choice of the 2 types of traps should be better explained.

Response: Thank you very much for this constructive comment. The higher number of Anopheles arabiensis vector abundance over Anopheles funestus reflects the specific ecological setting of our study area. In Kilombero valley previous malaria vector surveillance works caught significant higher number of An. arabiensis as compared to An. funestus mosquitoes (see for example Kaindoa,.et al 2017) [1]. However, about 80% of malaria transmission occurring in the study area are dominated by An. funestus and only 20% was due to An. arabiensis [1]. Apart from the difference in vector composition of these primary vectors, feeding and resting behaviours shown by these two vectors are highly different, with An. funestus showing preference for indoor biting and resting and An. arabiensis outdoor.

In our study we based the choice of our traps (Suna-traps, and Resting bucket (RBu)) based on the results of several other studies focusing on outdoor sampling in both malaria and non-malaria vectors [2-4]. We have now expanded the method section providing further justification for the choice the traps. Please see lines 159 - 164 in the revised version. Furthermore, we could have used HLC method, however this sampling methods is currently not recommended due to ethical concerns of exposing volunteers to mosquito bites.

Comment 2: Seven mosquito taxa have been collected during the 12 months collection (Table 1b). However, the manuscript is focusing on 2 species only, An. arabiensis and An. funestus. The third category is named "Other Anopheles". The paper would gain in clarity and robustness if the other species were also taken into consideration, especially as the data are already available (Table 1b). When possible, the spatio-temporal analysis should be more specific, including for instance An. zeimanni which was collected in high numbers (n=5607 specimens), 5 times more than An. arabiensis.

Response: Thank you very much for pointing this out. We agree that splitting the other malaria vectors by each species would be of interest. However, please note that the relative contribution of non- An. arabiensis and non-An. funestus vectors to malaria transmission in this specific ecological setting is low (as we also highlighted in the revised introduction section). Therefore, we deliberately decided not to put too much emphasis on the other Anopheles species, to avoid distracting the reader from the main focus of our work (i.e. outdoor biting and resting of vectors responsible for malaria transmission). Furthermore, please note that if we should expand the analysis to each separate species, the length of our manuscript (and figures and tables) would increase substantially at the cost of losing conciseness

Additional comment: They are also a good number of minor corrections and comments that have been included into the attached manuscript for its improvement (see attached file). For instance, they are some statements that need further explanation to increase their understanding.

Response: We really appreciate your additional efforts in providing these editorial suggestions. We have revised the manuscript accordingly. Please find the revised edits highlighted in yellow in the manuscript with track changes.

References

1. Kaindoa EW, Matowo NS, Ngowo HS, Mkandawile G, Mmbando A, Finda M: Interventions that effectively target Anopheles funestus mosquitoes could significantly improve control of persistent malaria transmission in south-eastern Tanzania. PLoS One 2017, 12.

2. Hiscox A, Otieno B, Kibet A, Mweresa CK, Omusula P, Geier M, Rose A, Mukabana WR, Takken W: Development and optimization of the Suna trap as a tool for mosquito monitoring and control. Malaria journal 2014, 13(1):257.

3. Mburu MM, Zembere K, Hiscox A, Banda J, Phiri KS, Van Den Berg H, Mzilahowa T, Takken W, McCann RS: Assessment of the Suna trap for sampling mosquitoes indoors and outdoors. Malaria journal 2019, 18(1):51.

4. Kreppel KS, Johnson P, Govella N, Pombi M, Maliti D, Ferguson H: Comparative evaluation of the Sticky-Resting-Box-Trap, the standardised resting-bucket-trap and indoor aspiration for sampling malaria vectors. Parasites & vectors 2015, 8(1):462.

Attachment

Submitted filename: Reviewrs comments_MRV_outdoo_surve_Nov_2020.docx

Click here for additional data file.^{(20.8KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0245750.r005

Decision Letter 2

Luzia Helena Carvalho

11 Dec 2020

PONE-D-20-16651R2

Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages

PLOS ONE

Dear Dr. Mmbando,

Thank you for submitting your manuscript for review to PLoS ONE. After careful consideration, we feel that your manuscript will likely be suitable for publication if the authors revise it to address additional points raised by the reviewer. According to reviewer, there are some specific areas where further improvements would be of substantial benefit to the readers.

Please submit your revised manuscript by December 30. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Luzia Helena Carvalho, Ph.D.

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #3: The authors have properly addressed the two main comments raised in the first review of the manuscript.

However, there are stlll some minor revisions that need to be done for improving the manuscript (see below).

Page 2, lines 49-50, write: "in the Anopheles gambiae complex and ...".

Page 5, lines 162-164, write: "The Suna® traps proved to catch significantly higher number of Anopheles species in field conditions, as well as it significantly reduced entry of malaria vectors ...". Write "Anopheles" in italics (line 163).

Page 8, line 254, add "%" after 52.3%.

Page 12, in Table 2, write "Anopheles" in italics in "Other Anopheles species" (top right side of table).

Page 13, line 364, write "as previously described by Mala and Irungu [41]". Line 369, delete the coma between Ref No 42, 43 and (Fig. S1.11).

Page 14, line 386, delete "was" after "partly".

Page 15, lines 407-412, this paragraph is still not logical. High abundance is contradictory with the fact larval stages are washed away during the rainy season. This paragraph still needs improvement and more clarity. Line 428, delete the space after "studies".

Page 20, Ref 35, line 587, write "Anopheles" in italics. Line 597, complete Ref 40 with volume, pages, journal, etc.

Page 21, Ref 55, line 646, write "Anopheles" in italics.

One of the 4 references mentioned in the response to reviewers is missing from the manuscript. It's the one by Mburu et al 2019.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #3: Yes: Sylvie MANGUIN

PLoS One. 2021 Jan 28;16(1):e0245750. doi: 10.1371/journal.pone.0245750.r006

Author response to Decision Letter 2

28 Dec 2020

28th December 2020

Dear Editor, PLOS ONE

Re: Research paper re-submission (Manuscript code: PONE-D-20-16651)

Please find the detail explanation of the minor comments from Review #3 listed in point by point below. We also included further clarification with respect to the previous points, by modifying some sentence in the main manuscript, and by adding more relevant references.

Finally, we made several minor changes (and typos corrections) to further improve the reading flow. We believe our manuscript has substantially improved.

Please find our detailed point-by-point response to each reviewer’s report. We have highlighted in yellow the specific changes/additions made, in the manuscript main body.

Once again thank you very much for your support and hope to hear from you.

Yours sincerely

Arnold

ammbando@ihi.or.tz

Response to reviewer’s comments

Reviewer # 3

Comments 1: The authors have properly addressed the two main comments raised in the first review of the manuscript.

However, there are stlll some minor revisions that need to be done for improving the manuscript (see below).

Response: Thank you very much for point out this minor comments. Please find the edits listed below and highlighted in yellow in each respective page number.

Comment 2: Page 2, lines 49-50, write: "in the Anopheles gambiae complex and ..

Response: We really appreciate the additional edits. This is now added in the respective page in the main manuscript body.

Comment 3: Page 5, lines 162-164, write: "The Suna® traps proved to catch significantly higher number of Anopheles species in field conditions, as well as it significantly reduced entry of malaria vectors ...". Write "Anopheles" in italics (line 163).

Response: We really appreciate the additional edits. This is now italicized in the respective page in the main manuscript body.

Comment 4: Page 8, line 254, add "%" after 52.3%.

Response: Thank you so much reviewer for this edit. This is now added in the respective page in the main manuscript body.

Comment 5: Page 12, in Table 2, write "Anopheles" in italics in "Other Anopheles species" (top right side of table).

Response: Thank you so much reviewer for this edit. This is now italicized in the respective page in the main manuscript body.

Comment 6: Page 13, line 364, write "as previously described by Mala and Irungu [41]". Line 369, delete the coma between Ref No 42, 43 and (Fig. S1.11).

Response: Thank you so much reviewer for the edits. This is commas are now removed in the main manuscript body.

Comment 7: Page 14, line 386, delete "was" after "partly"

Response: Thank you so much reviewer for the edits. This is commas are now removed in the main manuscript body.

Comment 8: Page 15, lines 407-412, this paragraph is still not logical. High abundance is contradictory with the fact larval stages are washed away during the rainy season. This paragraph still needs improvement and more clarity. Line 428, delete the space after "studies".

Response: Thank you so much reviewer pointing out this. This is caused by heterogeneity of malaria vector densities at small scale and that there may be more factors influencing these densities than we assessed. This line is now added in the main manuscript body, in Page 15, Line 415-416.

Comment 9: Page 20, Ref 35, line 587, write "Anopheles" in italics. Line 597, complete Ref 40 with volume, pages, journal, etc.

Response: Thank you for point this out. The references are now edited.

Comment 10: Page 21, Ref 55, line 646, write "Anopheles" in italics.

Response: This is well noted. Please see it italicized in the main manuscript.

Comment 11: One of the 4 references mentioned in the response to reviewers is missing from the manuscript. It's the one by Mburu et al 2019.

Response: Thank you for this suggestion. The reference is now added in the main manuscript, Page 5, line 164

Attachment

Submitted filename: MRV_out_surveillance_PlosOne_review response.docx

Click here for additional data file.^{(15.9KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0245750.r007

Decision Letter 3

Luzia Helena Carvalho

5 Jan 2021

PONE-D-20-16651R3

Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages

PLOS ONE

Dear Dr. Mmbando,

Thank you for resubmitting your manuscript for review to PLoS ONE. After careful consideration, we feel that your manuscript will likely be suitable for publication if it is revised to address specific queries raised by the reviewer. As quoted by the reviewer, the authors did not properly address relevant topics raised during the peer review process. At this time, we strongly recommend that the authors include/clarify all topics raised by the reviewer.

Please submit your revised manuscript by January 20. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Luzia Helena Carvalho, Ph.D.

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #3: I noticed that some comments have been taken into consideration, while others not.

The previous comments listed and sent to the authors have been made to improve the manuscript. I believe the authors forgot to integrate some of them or misunderstood some of my comments. Another possibility is that they disagreed with some of my comments, in this case an answer is expected to be provided.

I'm listing some comments again hoping this time they will all be taken into consideration.

- Page 2, line 49, add "the" before "Anopheles gambiae complex".

- Page 5, lines 162-164, improve English syntax in writing: "proved ... significantly higher ... in field conditions, ... significantly reduced ... malaria vectors ...".

- Page 8, line 254, delete space before %.

- Page 13, line 364, write "by Mala and Irungu". There are 2 authors only, so Mala et al is not appropriate.

- Page 15, line 418, write "Anopheline", not Anopeline".

- Page 20, lines 612-613, complete Ref 41 by Coosemans & Mouchet with volume, pages, journal, etc.

All references must follow the journal recommendations.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #3: No

PLoS One. 2021 Jan 28;16(1):e0245750. doi: 10.1371/journal.pone.0245750.r008

Author response to Decision Letter 3

6 Jan 2021

6th January 2021

Dear Editor, PLOS ONE

Re: Research paper re-submission (Manuscript code: PONE-D-20-16651R3)

Once again thank you very much for your support and so sorry for the comments which were not well addressed during the previous review. We have now addressed all the comments which can be found in the main manuscript body.

Yours sincerely

Arnold

ammbando@ihi.or.tz

Response to reviewer’s comments

Reviewer # 3

Comments 1: I noticed that some comments have been taken into consideration, while others not.

Response: Thank you very much for point out additional minor comments. Please find the edits listed below and highlighted in yellow in each respective page number.

Comment 2: Page 2, line 49, add "the" before "Anopheles gambiae complex

Response: We really appreciate the additional edits. This is now added in the respective page in the main manuscript body.

Comment 3: Page 5, lines 162-164, improve English syntax in writing: "proved ... significantly higher ... in field conditions, ... significantly

Response: We really appreciate the additional edits. This is now revised in the respective page in the main manuscript body. Please see it in Page 162-164.

Comment 4: Page 8, line 254, delete space before %.

Response: Thank you so much reviewer for this edit. The space is now removed in the respective page in the main manuscript body.

Comment 5: Page 13, line 364, write "by Mala and Irungu". There are 2 authors only, so Mala et al is not appropriate.

Response: Thank you so much reviewer for this edit. The reference is now edited accordingly in the main manuscript body.

Comment 6: Page 15, line 418, write "Anopheline", not Anopeline".

Response: Thank you so much reviewer for the edits. This is now edited and can be found in the main manuscript body.

Comment 7: Page 20, lines 612-613, complete Ref 41 by Coosemans & Mouchet with volume, pages, journal, etc.

Response: Thank you so much reviewer for the edits. The reference number 41 is now edited accordingly in manuscript body.

Attachment

Submitted filename: Reviwers comments_revised_060121.docx

Click here for additional data file.^{(14.7KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0245750.r009

Decision Letter 4

Luzia Helena Carvalho

7 Jan 2021

Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages

PONE-D-20-16651R4

Dear Dr. Mmbando,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Luzia Helena Carvalho, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0245750.r010

Acceptance letter

Luzia Helena Carvalho

12 Jan 2021

PONE-D-20-16651R4

Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages

Dear Dr. Mmbando:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Luzia Helena Carvalho

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of grassland in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(1,020KB, docx)}

S2 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of shrubs in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(977.2KB, docx)}

S3 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of natural waterbodies in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(773.1KB, docx)}

S4 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of artificial waterbodies in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(828.6KB, docx)}

S5 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of covered waterbodies in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(776.4KB, docx)}

S6 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of sunlight waterbodies in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(799.6KB, docx)}

S7 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of seasonal swamps in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(772.9KB, docx)}

S8 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of turbid waterbodies in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(787.5KB, docx)}

S9 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of dirty waterbodies in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(836.5KB, docx)}

S10 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of open water well in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(796.3KB, docx)}

S11 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of wetland in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(864.8KB, docx)}

S12 Fig. Map of predicted hotspots of female mosquitoes’ density and presence of rice fields in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(940KB, docx)}

S13 Fig. Map of predicted hotspots of female mosquitoes’ density and number of chickens in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(875.7KB, docx)}

S14 Fig. Map of predicted hotspots of female mosquitoes’ density and number of houses in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(934KB, docx)}

S15 Fig. Map of predicted hotspots of female mosquitoes’ density and number of people in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(896.5KB, docx)}

S16 Fig. Map of predicted hotspots of female mosquitoes’ density and distance from trap to the nearest house in the sampled grid cells in three villages in Kilombero Valley, South-Eastern Tanzania.

a) Anopheles arabiensis, b) Anopheles funestus, c) other Anopheles.

(DOCX)

Click here for additional data file.^{(880.7KB, docx)}

Attachment

Submitted filename: 20 PLoS One Mmbando Mosq Tanzania-edited.docx

Click here for additional data file.^{(83.4KB, docx)}

Attachment

Submitted filename: Reviewrs comments_MRV_outdoo_surve_Nov_2020.docx

Click here for additional data file.^{(20.8KB, docx)}

Attachment

Submitted filename: MRV_out_surveillance_PlosOne_review response.docx

Click here for additional data file.^{(15.9KB, docx)}

Attachment

Submitted filename: Reviwers comments_revised_060121.docx

Click here for additional data file.^{(14.7KB, docx)}

Data Availability Statement

All relevant data are within the manuscript and its Supporting Information files.

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PERMALINK

Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages

Arnold S Mmbando

Emmanuel W Kaindoa

Halfan S Ngowo

Johnson K Swai

Nancy S Matowo

Masoud Kilalangongono

Godfrey P Lingamba

Joseph P Mgando

Isaac H Namango

Fredros O Okumu

Luca Nelli

Roles

Abstract

Background

Methods

Results

Conclusion

Background

Methods

Study area

Fig 1. Location of the study area in Tanzania and sampling points (administrative borders source: Data.humdata.org.

Selection of outdoor mosquito sampling units

Mosquito traps and attractant

Fig 2.

Assessment of environmental and anthropogenic conditions in the sampling areas

Mosquito identification

Detection Plasmodium sporozoite infection in malaria vectors

Identification of mosquito blood-meal hosts

Ethics statement

Data analysis

Results

Host-seeking and resting mosquitoes caught

Table 1. a: Sibling species identification of primary malaria vectors. 1b: Blood-meal and sporozoite detection in Anopheles species caught.

Blood-meal preferences and Plasmodium infection status of Anopheles mosquitoes

Environmental and anthropogenic factors influencing malaria vector densities

Table 2. Factors affecting outdoor malaria vector abundance in the three study villages in the Kilombero Valley, south-Eastern Tanzania.

Temporal patterns of malaria vector densities

Fig 3. Seasonal variation of abundances of outdoor host-seeking malaria vectors by month; as predicted by generalized additive mixed-effect model (GAMM) model.

Spatial patterns of mosquito distribution

Fig 4.

Discussion

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Luzia Helena Carvalho

Roles

Author response to Decision Letter 0

Decision Letter 1

Luzia Helena Carvalho

Roles

Author response to Decision Letter 1

Decision Letter 2

Luzia Helena Carvalho

Roles

Author response to Decision Letter 2

Decision Letter 3

Luzia Helena Carvalho

Roles

Author response to Decision Letter 3

Decision Letter 4

Luzia Helena Carvalho

Roles

Acceptance letter

Luzia Helena Carvalho

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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