Indoor resting behavior of Aedes aegypti and Culex spp. (Diptera: Culicidae) in northeastern Thailand

doi:10.21203/rs.3.rs-2488769/v1

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Research Article

Indoor resting behavior of Aedes aegypti and Culex spp. (Diptera: Culicidae) in northeastern Thailand

https://doi.org/10.21203/rs.3.rs-2488769/v1

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published 14 Apr, 2023

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Background: Aedes aegypti is a vector of several arboviruses, notably dengue virus (DENV), which causes dengue fever and more severe forms such as hemorrhagic fever. Vector control is currently the main method to control dengue outbreaks. Effective vector control strategies require an understanding of aspects of the bioecology of the vector, including resting behavior. The aims of this study were to investigate the resting behavior of Ae. aegypti in selected houses in northeastern Thailand.

Methods: Mosquitoes were collected in 60 houses in each of two rural and two urban sites in northeastern Thailand. Household characteristics were ascertained. Mosquitoes were collected from May to August 2019 during two collection times (morning/afternoon), in four room types (bedroom, bathroom, living room and kitchen) in each house and at three wall heights (<0.75m, 0.75-1.5m, >1.5m) using a battery-driven aspirator and sticky traps. Collected mosquitoes were identified and dengue virus detected in Ae. aegypti. Association analyses between location, household variables, geckos and mosquito abundances were performed.

Results: A total of 2,874 mosquitoes were collected by aspirators and 1,830 by sticky traps. Aedes aegypti and Culexspp. accounted for 44.8% and 53.2% of the specimens, respectively. Only 2.1% were Ae. albopictus. Ae. aegypti and Culex spp. rested most abundantly at intermediate and low heights in bedrooms and bathrooms. Clothes hanging at intermediate heights were associated with higher numbers of Ae. aegypti in rural settings. The absence of eaves, low wind flow and hanging clothes were associated with more Culex spp. in urban settings. Infrequent use of fogging or larval control was associated with high numbers of Culex spp. and Ae. aegypti. Overall, there seemed to be no clear relationships between sticky-trap collected geckos and Ae. aegypti or Culex spp. abundances.

Conclusions: Knowledge of indoor resting behavior of adult mosquitoes and associated environmental factors can guide the choice of the most appropriate and effective vector control method. Our work suggests that vector control using Targeted Indoor Residual Spraying focusing on walls at heights lower than 1.5 m in bedrooms and bathrooms could be part of an integrated effective strategy for dengue vector control.

Mosquito abundance

vector control

indoor residual spraying

height

room

gecko

Dengue is the most widespread mosquito-borne viral disease in the world. The number of dengue cases reported to the World Health Organization has increased more than eight fold over the last two decades [1]. An estimated 50 million dengue infections occur annually and approximately 2.5 billion people live in dengue endemic countries [2]. Aedes aegypti (L.) is a tropical and subtropical mosquito species widely distributed around the world. It is a primary vector of dengue virus (DENV) and is well-adapted to completing its entire life cycle within urban areas and around houses, primarily feeding on humans.

The mainstay of dengue vector control interventions in endemic settings focuses on the immature stages, supplemented with space-spraying insecticides to target the adult mosquito population during an outbreak. Although space-spraying does reduce mosquito numbers, there are no studies showing that such methods are effective in reducing numbers of cases [3–5]. Indoor residual spraying (IRS) is a method commonly used in malaria vector control and has recently become of interest in the dengue control community [6]. The effectiveness of IRS relies on knowledge of where mosquitoes rest and therefore, targeted IRS should focus on areas where adult mosquitoes are most likely to rest. Adult Ae. aegypti generally rest indoors rather than outdoors [7, 8], especially on lower parts of walls and can vary depending on the type of room (kitchen vs. bedroom for example) [9, 10]. Resting preference is believed to be influenced by the type of surface, with a preference for cloth, wood and cement [7]. However, house structures differ worldwide, and global generalizations may not be applicable. As far as we know there are currently no reports on the resting behaviors of adult Ae. aegypti and Culex spp. indoors in SE Asia. Therefore, the main objective of this study was to determine the most preferred indoor resting locations of Ae. aegypti and Culex spp. in urban and rural houses and associated environmental factors to provide information that can be used for effective vector control and dengue prevention. We also compared two mosquito collection methods to assess the relative effectiveness of aspiration vs. sticky traps. Finally, as there are few studies exploring the effect of geckos as a mosquito control tool in the field [11], we took advantage of the fact that sticky traps also collected geckos and assessed the relationship between sticky-trap collected geckos and mosquito abundance.

Study area

The study was carried out in northeastern Thailand in two rural sites, Ku Thong village (16.4421N, 102.9652E) and Muang Peng village (16.4261N, 102.9806E) in Chiang Yuen district, Mahasarakham province and in two urban sites, Nong Hai (16.4141N, 102.8744E) and Non Tan (16.4189N, 102.8418E) in Mueang district, Khon Kaen province (Fig. 1). The study areas are dengue endemic with typical seasonal increases and occasional outbreaks [12]. The average minimum and maximum seasonal temperatures are 16.7°C (December–January) and 36.4°C (April–May). The monthly minimum and maximum rainfall vary from 0 mm (dry season: November–April) to 240 mm (wet season: May–October). This study was conducted during the rainy season.

Study design and data collections

Cross-sectional entomological surveys were carried out in 60 households in each of the four sites, i.e. 120 in the urban area and 120 in the rural area, totaling 240 households. Collections were done sequentially during the rainy season in May-August 2019 in the following order: May: rural Ku Thong (Fig. 1C), June: urban Nong Hai (Fig. 1A), July: rural Muang Peng (Fig. 1D), and August: urban Non-Tan (Fig. 1B). Collections were completed in 18–20 days in each study site. In addition, five randomly selected houses per village (a total of 20 households) were used for collecting mosquitoes using sheets with insect glue (see below). Mosquitoes were collected in the morning between 08:00–12:00 hours and in the afternoon between 13:00–17:00 hours using a mechanical battery-driven aspirator (as described in [9]). Mosquitoes were collected on the lower part (0-0.75 m) of the walls for 10 minutes in each of the bedroom, bathroom, kitchen and living room, respectively. This procedure was then repeated on the middle part of the wall (0.75–1.5 m) in each room, followed by the upper parts (> 1.5 m) of the walls in each room. The upper parts were reached by fixing the aspirator to a long handle. The total aspiration time per room was 30 minutes.

Sticky traps were deployed in five houses in each of the two rural and two urban sites. Sticky traps consisted of clear plastic sheets (0.1 m × 3.0 m) spread with Crop Pro Sticky Insect Glue (Chemibond Enterprise Sdn Bhd, Malaysia) and placed in the bedroom, bathroom, living room and kitchen (1 trap/room). The sticky trap sheets were replaced every week for a total collection time of three weeks. In addition to mosquitoes, sticky traps also caught house geckos, the numbers of which were recorded. Geckos were not identified to species, but the most common species in residential areas in Southeast Asia include common Asian house gecko, Hemidactylus frenatus and the Flat-tailed house gecko, H. platyurus [13].

Mosquito processing

After collections, mosquitoes were placed in collection cups reinforced by adhesive tape to avoid any possible escape. Each cup was labeled with household ID, room type, height, time, and date. Cups were stored in a styrofoam box and transported back to the laboratory where they were killed at -20°C, identified, sexed, and blood fed status determined (blood-fed or non-bloodfed) under stereomicroscope. Species identification was done by morphological characteristics using keys by Rueda [14]. Mosquitoes on sticky traps were counted and identified to species using a magnifying lens. All specimens were identified to either Ae. aegypti, Ae. albopictus or Culex spp.

Detection of dengue virus (DENV) in mosquitoes

Dengue virus identification in a total of 422 female blood-fed Ae. aegypti, collected from both the rural and urban study areas, was conducted by RT-qPCR assay. The mosquito’s head/thorax was separated from the abdomens and approximately 10 abdomens were pooled, yielding a total of 45 pooled samples. Viral RNA in each pool was sequestered by using a QIAamp Viral RNA mini kit (QIAGEN, Valencia, CA, USA). According to the manufacturer’s protocol of SuperScript™ III First-Strand Synthesis System (Invitrogen, Waltham, MA, USA), the complementary DNA (cDNA) was synthesized from a 1 µg of the isolated viral RNA template with a DENV consensus primer (D2) [15]. The qPCR reaction was performed with a total of 10 µl mixture, containing 1x SsoAdvanced™ Universal SYBR® Green Supermix (Bio-Rad, Hercules, CA, USA), 0.25 µM of each D1 and D2 primer, and 50 ng of cDNA template. The amplification cycle was executed by 35 cycles of 95°C for 15 seconds, 55°C for 30 seconds, and 72°C for 45 seconds on the C1000 Touch™ Thermal Cycler (Bio-Rad, Hercules, CA, USA). The DENV-positive pools were remarked and subsequently subjected to identify the viral serotype. As described by Lanciotti and colleagues [15], DENV serotypes 1–4 were detected by universal DENV primer (D1) and specific reverse primers, including TS1, TS2, TS3, and TS4, respectively. RNA from DENV-infected Ae. aegypti mosquito was used as a positive control and distilled water was retrieved to control the contaminated reaction.

Household characteristics

A household questionnaire was used to collect data on households and their members by interview of the household head. Questions included: how many people lived in the household, the occupation of the head of the household, number of livestock in/around the house (ducks, chickens, pigs, cows, buffalo), number of pet animals (dogs, cats), sources of drinking and non-drinking water (piped water, groundwater, rain water, bottled water/drinking water vending machines, other), type of house (single house one floor, single house two floors, commercial building, townhouse, apartment, other), number of rooms, wall construction (plaster, cement/bricks, burned bricks, wood, other), house cleanliness (poor, intermediate, good), level of wind flow (high, intermediate, low/none), toilet type (bowl toilet, squat toilet, other) and toilet location (indoors, outdoors), presence of window screens, presence of open eave gaps, and larval and adult mosquito control activities and frequency. The degree of darkness was estimated as light, intermediate, and dark by the lead author in each room where mosquitoes were collected. Similarly, the quantity (none or little, intermediate, a lot) and height of hanging clothes were estimated by eye for each room where clothes were found hanging.

Data analysis

The association of area (urban vs. rural), village and resting location (room and height) and time (morning and afternoon) with male and female mosquito numbers was analyzed by fitting a Generalised Linear Mixed (GLMM) log-linear (i.e. Poisson distribution) model with house fitted as the random factor. A Wald statistic, which follows a χ² distribution, was calculated. Comparison of levels within a factorial variable was performed through calculation of a t statistic (difference between the mean divided by the standard error of the differences). A dispersion parameter was estimated in the model fit to account for any overdispersion of the data. To compare the efficiency of the two mosquito capture methods (aspiration vs. sticky traps) a GLMM loglinear regression was fitted with house as the random factor and area (urban/rural), village, room, height and capture methodology as explanatory variables and ln-transformed collection duration (i.e. 30 minutes for aspirator and 30240 minutes (3 x 7 days × 24 hours × 60 minutes) for the sticky trap) as an offset. The association of socio-environmental variables and mosquito number collected by aspirator was analysed by fitting a GLMM loglinear regression with house ID and room nested within house ID as random factors. The variables were first fitted in univariable analyses and then those found to be associated at P < 0.2 were fitted in a multivariable model. All such variables were fitted in the full model and then the non-significant variables were removed from the model in a stepwise manner until the final adequate model with only significant variables was obtained. Urban and rural areas were analysed separately because of the very large differences in many of the variables across these two types of areas, notably animal husbandry. The number of geckos caught on sticky traps was analysed as an explanatory variable for association with numbers of mosquitoes caught. Associations were first assessed by univariable fitting of the number of geckos with the total number of mosquitoes caught on sticky traps only, then with the aspirator mosquito catch number data from the same houses. Finally, we performed a multivariable association analysis of mosquito number including gecko number and significant socio-environmental variables. All analyses were performed in Genstat Version 20 software [16].

Collections by aspirators

A total of 2,874 mosquitoes were collected by aspirators (Table 1). Ae. aegypti and Culex spp. accounted for the majority of mosquitoes, 44.8% and 53.2% respectively, with Ae. albopictus contributing only 2.1% (59 mosquitoes, mainly from the rural sites). There were significantly more Ae. aegypti collected in the rural villages than the urban villages (959 vs. 328, χ² = 61.8, df = 1, P < 0.001). In addition, the second urban village (Non Tan) had even lower abundance than the first urban village (Nong Hai) (105 mosquitoes vs. 223). More female than male Ae. aegypti were collected overall (708 vs. 579, χ² = 7.99, df = 1, P = 0.005). The abundance of Culex spp. was also higher in rural villages (992 vs. 615, χ² = 17.5, df = 1, P < 0.001), but there was significant variation between villages in the rural and urban sites (χ² = 9.96, df = 2, P = 0.008).

Table 1

Number of mosquitoes (%) collected by mechanical battery-driven aspirator and sticky traps in rural and urban areas in northeastern Thailand in 2019.
Species	Methods	Areas	No. of mosquitoes
Species	Methods	Areas	Female	Male	Sum	Total
Ae. aegypti	Aspirator	Rural	524 (74.0)	435 (75.1)	959 (74.5)
		Urban	184 (26.0)	144 (24.9)	328 (25.5)
		Sum	708 (100.0)	579 (100.0)	1,287 (100.0)
	Sticky trap	Rural	334 (64.1)	280 (64.7)	614 (64.4)
		Urban	187 (35.9)	153 (35.3)	340 (35.6)
		Sum	521 (100.0)	433 (100.0)	954 (100.0)	2,241
Ae. albopictus	Aspirator	Rural	36 (83.7)	12 (92.3)	51 (91.5)
		Urban	7 (16.3)	1 (7.7)	8 (8.5)
		Sum	43 (100.0)	13 (100.0)	59 (100.0)
	Sticky trap	Rural	0	4 (100.0)	4 (100.0)
		Urban	0	0	0
		Sum	0	4 (100.0)	4 (100.0)	63
Culex spp.	Aspirator	Rural	515 (71.8)	414 (52.3)	929 (60.8)
		Urban	202 (28.2)	378 (47.7)	599 (39.2)
		Sum	717 (100.0)	792 (100.0)	1,528 (100.0)
	Sticky trap	Rural	293 (62.1)	262 (57.7)	555 (63.6)
		Urban	179 (37.9)	192 (42.3)	317 (36.4)
		Sum	472 (100.0)	454 (100.0)	872 (100.0)	2,400
Overall	Aspirator	Sum	1,468 (59.7)	1,384 (60.8)	2,874 (61.1)
	Sticky trap	Sum	993 (40.3)	891 (39.2)	1,830 (38.9)
		Total	2,461 (100.0)	2,275 (100.0)	4,704 (100.0)	4,704

Male and female Ae. aegypti were most abundant at intermediate heights in rooms where they were most prevalent (i.e., all rooms except the kitchen) (Fig. 2A). Overall, in decreasing order for abundance by height: 0.75–1.5 m > 0-0.75 m > 1.5 + m (all t statistics for the three among-height comparisons, t > 8.5, P < 0.001). In decreasing order of abundance were bedroom > bathroom = living room > kitchen (t statistics for the five significant comparisons t > 3.1, P < 0.01). Both males and females showed the same distribution in heights and rooms.

Culex mosquitoes were more abundant at the two lower heights than at the higher height (t statistics for the two significant comparisons t > 5.8, P < 0.001). There was no difference in the number of male and female Culex mosquitoes caught (χ² = 0.01, df = 1, P = 0.903). Although female Culex were found predominantly in the bedroom and bathroom, males showed very different room and height distributions (Fig. 2B). The full data set summaries of numbers of mosquitoes caught according to place, time and height for Ae. aegypti and Culex spp. are shown in Additional file 1: Table S1 and Additional file 2: Table S2.

There were very few Ae. albopictus mosquitoes overall, but there was a significant association with more Ae. albopictus present in the living room and kitchen than in the bedroom and bathroom (living room vs. bathroom t = 7.39, P < 0.001; living room vs. bedroom t = 5.99, P < 0.001; kitchen vs. bathroom t = 4.24, P < 0.001). There was no significant association with height (χ²₂ = 0.59, P = 0.745).

The abundance of Ae. aegypti decreased from morning to afternoon in the bathroom, bedroom and kitchen but increased in the living room (Fig. 3A). These changes were significant for the female mosquitoes in the bedroom (t = 2.25, P < 0.05), the kitchen (t = 2.71, P < 0.01) and the living room (t = 2.42, P < 0.05). By contrast, the abundance of Culex spp. decreased from morning to afternoon in all rooms (χ² = 15.24, df = 1, P < 0.001) (Fig. 3B). For Ae. albopictus, numbers decreased from morning to afternoon, but this was not significant (χ² = 3.70, df = 1, P = 0.053).

There were more bloodfed Ae. aegypti collected than unfed (χ² = 9.35, df = 1, P = 0.002), but they did not differentially distribute by height (χ² = 0.47, df = 2, P = 0.791) or room (χ² = 2.75, df = 3, P = 0.432) (Fig. 4A). By contrast, fewer bloodfed Culex spp. female mosquitoes were collected than unfed (χ² = 86.6, df = 1, P < 0.001) (Fig. 4B), there was a distinctly different height distribution for bloodfed mosquitoes in the bedroom as compared to the other rooms. There were too few bloodfed Ae. albopictus for analysis.

Sticky traps

A total of 1,830 mosquitoes were collected by sticky traps (Table 1). Aedes aegypti and Culex spp. accounted for 52.1% and 47.7% respectively, and Ae. albopictus contributing only 0.2% (only 4 mosquitoes, all from the urban sites). The full data set summaries of numbers of mosquitoes caught according to place, time and height for Ae. aegypti and Culex spp. are shown in Additional file 3: Table S3 and Additional file 4: Table S4.

Aedes aegypti abundance, as measured by sticky traps, was higher in the rural areas than the urban areas (χ² = 60.46, df = 1, P < 0.001), but did not differ further at the village level (χ² = 0.92, df = 2, P = 0.63). There were more female than male mosquitoes (χ² = 10.2, df = 1, P = 0.002), but no sex differences in height or room resting preference were found. There were significant differences in overall resting behaviour, irrespective of sex, for both rooms (χ² = 195.4, df = 3, P < 0.001) and heights (χ² = 212.02, df = 2, P < 0.001) (Fig. 5A). The mosquito abundance in rooms and by height was in decreasing order, bedroom > bathroom > living room > kitchen (all t statistics t > 3.5, P < 0.001) and 0.75-1.5m > 0-0.75m > 1.5 + m (all t statistics t > 7.0, P < 0.001), respectively. There was no interaction between room and height for mosquito abundance.

Culex spp. sticky trap abundances were higher in the rural areas (χ² = 18.06, df = 1, P < 0.001), but did not differ further at the village level (χ² = 0.92, df = 2, P = 0.63). The numbers of female and male Culex mosquitoes did not significantly differ (χ² = 0.17, df = 1, P = 0.68). There was a small interaction effect between room and height (χ² = 14.16, df = 6, P = 0.03), reflecting the relatively lower mid-height abundance in the bathroom as compared to the other rooms (Fig. 5B). Otherwise, there were no significant differences in abundance by height (χ² = 2.01, df = 2, P = 0.38) or room (χ² = 5.27, df = 3, P = 0.154).

Only four Ae. albopictus were collected and thus were not analysed.

Comparison of mosquito collections by an aspirator and sticky traps

Overall, in houses where mosquitoes were collected both by aspiration and sticky traps, the sticky traps collected more mosquitoes (Ae. aegypti: aspirator mean: 0.58, standard error of the mean (SEM) 0.13 vs. sticky trap mean: 3.98, SEM: 0.22. Culex spp. aspirator mean: 0.91, SEM: 0.19 vs. sticky trap mean: 3.86, SEM: 0.19). However, per sampling sticky traps were deployed for a lot longer (i.e. 3 times 7 days vs. 30 minutes). For the comparison, only aspirator mosquito collections from houses that had sticky traps deployed were used. Taking into account the differences between area, village, room and height, the aspirator method was more efficient per sampling time effort in collecting Ae. aegypti (χ² = 1165.0, df = 1, P < 0.001) and Culex spp. (χ² = 1372.6, df = 1, P < 0.001) mosquitoes. Aspirators collected a mean of 0.019 Ae. aegypti/minute and 0.029 Culex spp./minute, whereas sticky traps collected a mean of 1.3 x 10^− 4 Ae. aegypti/minute and 1.28 x 10^− 4 Culex spp./minute. Although the efficiency of capture was higher at all heights, for Ae. aegypti there was a significant interaction effect where aspiration was even better at higher heights (vs. lowest height, t = 1.98, P = 0.048; vs. intermediate height, t = 3.38, P < 0.001).

DENV positive mosquitoes

Of the 422 Ae. aegypti females assessed for DENV infection only five specimens (1.7%) were positive for the virus and too few to analyze with respect to their distribution in rooms and across heights. All DENV positives were, however, collected in the rural area. Two specimens were positive for DENV-1 (0.7%), one for DENV-3 (0.3%), and one had a mixed DENV-1 and DENV-3 infection (0.3%). One specimen was positive for DENV-1, DENV-2 and DENV-3 combined (0.3%).

Association of socio-environmental variables

Summary household information collected using the questionnaire is shown in Additional file 5: Table S5. There were several notable differences between rural and urban areas. Overall, there were more people per household in urban settings (urban mean: 4.08 standard deviation (SD): 1.71 vs. rural mean: 3.37, SD 1.58). Urban household heads were predominantly people with permanent jobs, shopkeepers and casual labourers (87%), whereas rural household heads were predominantly farmers and casual labourers. Almost no urban houses had any livestock and relatively few rural houses had livestock (15%). Approximately half of the rural houses had wooden walls (53%), whereas 82% of urban houses had plaster walls. 87% of rural houses had squat toilets vs. 67% of urban houses having bowl toilets. 87% of urban houses had window screens, whereas only 12% of rural houses had screens. Larval control either with temephos or via cleaning of containers was carried out more frequently (> 90% on a weekly basis) in urban areas than in rural areas (50% of houses at a monthly rate).

The P-values for the univariable analyses of the association of socio-environmental variables with Ae. aegypti or Culex spp. mosquito numbers are shown in Additional file: Table S6 and Additional file: Table S7. In urban settings, in the final adequate multivariable model, only use of repellent (Yes/No) was associated with total Ae. aegypti number and the Yes category was found to associate with increased numbers of mosquitoes (χ² = 5.29, df = 1, P = 0.022). In rural settings, the following variables were found to be associated with higher Ae. aegypti number: use of temephos for larval control with low use (only every 3 months) was associated with higher numbers of mosquitoes (χ² = 9.55, df = 3, P = 0.024); cement walls (χ² = 8.62, df = 2, P = 0.014), outdoor toilets (χ² = 5.75, df = 1, P = 0.017) and increasing number of rooms (χ² = 8.91, df = 1, P = 0.003). Clothing location was also associated with mosquito numbers (χ² = 12.78, df = 2, P = 0.002), with intermediate height of hung clothing being associated with more mosquitoes than lower or higher levels (intermediate vs. low levels: t = 2.19, P < 0.05; intermediate vs. high levels: t = 3.25, P < 0.01).

For Culex spp. mosquitoes, in urban settings the following variables were found to be associated with higher mosquito numbers: absence of open eaves (χ² = 6.34, df = 1, P = 0.012), infrequent use of fogging (every 3 months) (χ² = 25.97, df = 2, P < 0.001) and low levels of wind flow (χ² = 9.83, df = 2, P = 0.008). In rural settings, use of fogging (χ² = 16.9, df = 1, P < 0.001) was associated with lower numbers of mosquitoes and quantity of hung clothing (χ² = 6.23, df = 2, P = 0.045; none/little vs. a lot, t = 2.46, P < 0.05) was associated with higher numbers of mosquitoes. Shopkeeping as the household occupation was also associated with higher mosquito numbers (χ² = 11.29, df = 4, P = 0.024).

Geckos and mosquito abundance

A total of 297 geckos were caught, of which 133 (45%) were in the urban area and 164 (55%) in the rural area. Close to 28% of the geckos were collected in bathrooms (n = 82), followed by bedrooms (n = 75; 25%), living rooms (n = 74; 25%), and kitchens (n = 66; 22%). Geckos were caught on the lower (n = 102; 34%), intermediate (n = 94; 32%) and upper levels (n = 101; 34%).

Univariable fitting of the gecko number caught revealed no significant association of gecko number with either the Ae. aegypti or Culex spp. number caught on sticky traps. Using the total number of mosquitoes caught by aspiration again revealed no association of gecko number with Ae. aegypti or Culex spp. mosquito number in rural settings. However, there were significant associations of mosquito numbers with gecko numbers in the urban sites. There was a negative association between gecko number and total number of Ae. aegypti caught by aspiration (χ² = 12.61, df = 1, P < 0.001). By contrast, there was a positive association between gecko number and the total number of Culex spp. caught by aspiration (χ² = 7.32, df = 1, P = 0.008). These associations remained in a multivariable analysis that included above-identified significant socio-environmental variables.

This study identified a number of aspects of Ae. aegypti and Culex spp. mosquito resting behaviour and environmental factors therewith associated. We found that the majority of female Ae. aegypti mosquitoes rested in bedrooms (35–39% of specimens) and bathrooms (ca. 30%) and at intermediate heights (48–53% of specimens). Similar results were found in Trinidad, Mexico and Panama where female Ae. aegypti generally rested in bedrooms, but less so in bathrooms [7, 8, 10]. Culex spp. were also predominantly found in bedrooms and bathrooms and at low and intermediate heights. Mosquitoes are abundant in bedrooms likely because people spend a comparatively long time in this room while sleeping, attracting blood-seeking mosquitoes by their body heat and carbon dioxide [17]. Bathrooms in Thailand commonly have open water storage containers for washing and flushing, creating a humid environment that may attract ovipositing mosquitoes [18].

The tendency for resting to predominantly occur at low (< 0.75m) to intermediate heights (0.75-1.5m) was observed for both genera, and notably even more so for blood fed Culex spp. than their unfed counterparts. At lower heights, there is less air movement and generally darker than the wall near the ceiling and often lit by light bulbs. Furthermore, ceiling fans are often installed, and which may interfere with mosquito resting. Finally, at lower heights, there are often hanging objects such as clothes, towels and mosquito nets as well as furniture that creates sheltered dark sites, offering an ideal hiding place to rest and digest [19]. Mosquitoes will rest on hanging objects or are attracted to used clothes emitting human odours [20].

For both genera of mosquitoes, there was a tendency for numbers to decrease in the afternoon, suggesting that the mosquitoes were heading outdoors, potentially looking for oviposition sites. Oviposition has been found to peak in late afternoon to early evening [21]. This might explain why numbers of Ae. aegypti were observed to increase in the living room in the afternoons, such rooms being the most juxtaposed to the outdoors. Such exiting behaviour is thus likely important to take into account for other such studies.

Several of these explanations as to why the mosquitoes were thus distributed are supported by observed associations with environmental features of the houses. Notably, the absence of eaves, low wind flow and hanging clothes were associated with more Culex spp. in urban settings. Cloth hanging at intermediate heights was associated with increased numbers of Ae. aegypti in rural settings. In addition to such house characteristics, it was notable that infrequent use of fogging or larval control was associated with increased numbers of Culex spp. and Ae. aegypti. Identifying household features that provide a conducive environment for mosquitoes can contribute to efforts for implementing push-pull strategies to make houses less attractive [22]. Coupled with knowledge on resting behaviour with respect to height and room type can also guide the physical implementation of irritant and spatial repellent insecticides [23].

Comparing the performance of active aspiration vs. passive sticky traps to measure mosquito abundance, we found that, broadly, both methods revealed the same resting behavior tendencies, suggesting that low cost, low man-power sticky traps offer a viable alternative to aspirators, even if their efficiency (mosquitoes per time) is lower.

Few have studied potential links between mosquito predators, food web interactions and mosquito vector control [24, 25]. Geckos frequently feed on mosquitoes and could thus act as a vector control measure under the right spatial, temporal, and optimal forage conditions [13]. However, geckos also prey on common mosquito predators, such as spiders; therefore, geckos might affect mosquito abundance both positively and negatively depending on their foraging preferences [13]. This has led to the proposal that geckos might reduce predator populations and increase the risk of dengue epidemics [26]. Our study did identify a relationship between geckos caught on the sticky trap and mosquitoes collected by aspiration. Ae. aegypti presence was negatively associated and Culex spp. positively associated with geckos. This might suggest that the predation by geckos favored Culex spp. potentially through the intermediate predation of spiders, whereas Ae. aegypti was directly affected by gecko predation. However, these conclusions seem implausible without a more detailed study.

Limitations

The major limitation of the study was the absence of meteorological data. However, as the villages were sampled sequentially and were taken into account in the analyses, the major findings of the work are unlikely to have been significantly altered by inclusion of meteorological data. Furthermore, the results were so consistent across the sites whether using aspirators or sticky traps, that although the effect of changes in humidity, rainfall and temperature may have altered total numbers, the behavioral trends remain. Although data were analyzed separately by urban-rural setting, there might be heterogeneities within areas, especially urban areas, e.g. depending on rich and poor neighborhoods. We did not capture this potential urban heterogeneity.

Our study findings about indoor resting behavior of adult Ae. aegypti will be helpful in guiding methods for low-cost operable mosquito surveillance and implementation of targeted IRS and spatial repellents as part of an integrated vector control program. Whilst predominantly focused on dengue, Culex spp. are vectors of a number of arboviruses in the region, notably Japanese Encephalitis virus and thus our work provides an evidence base for such vector-borne pathogens. Finally, this study highlights the major household factors that contribute to the resting behavior of mosquitoes inside houses in northeastern Thailand and which can thus be targeted through education programs.

cDNA – complementary DNA

DENV – dengue virus

DNA –Deoxyribonucleic acid

GLMM – Generalised Linear Mixed Model

TBE – Tris/Borate/EDTA

IRS – Indoor Residual Spraying

L. – Linneus

spp. - species

RNA – Ribonuclic acid

SD – Standard deviation

SEM – Standard error of the mean

Acknowledgements

We thank the following: Prof. Tatsanee Jaemjaya, Ass. Prof. Ubon Tangkhwanit, Ass. Prof. Plang Suriyahan, Ass Prof. Yaowarat Sriwaranan and Dr. Yoichi Kobori, all from Khon Kaen University.

Funding

This research was funded by the Research Council of Norway (grant ref. no. 281077). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Availability of data and materials

Relevant data available are found in the Supplementary Information Additional file 8-9.

Authors’ contributions

Conceptualization: HJO, CS, RP, YH. Data curation: CS, RP, TE. Formal analysis: CS, VM, RP, HJO, YH, TE. Funding acquisition: HJO, RE, JR. Investigation: CS, VM, HJO, RE, YH, RE. Methodology: HJO, CS, YH, VM, YH, RE, JR, TE. Project administration: HJO, YH, VM. Supervision: YH, VM, TE, HJO. Validation: CS, RP, TE. Visualization: CS, RP. Writing—original draft: CS, HJO, RP. Writing—review and editing: CS, YH, VM, TE, JR, UH, RP, HJO. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors have no competing interests.

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No competing interests reported.

Additionalfile1TableS1Ae.aegyptiaspiratorcollections.docx
Additional file 1: Table S1. Ae. aegypti mosquitoes collected by mechanical battery-driven aspirator differentiated by collection time, room and wall height above floor in A) rural areas and B) urban areas in northeastern Thailand, 2019.
Additionalfile2TableS2Culexspp.aspiratorcollections.docx
Additional file 2: Table S2. Culex spp. mosquitoes collected by mechanical battery-driven aspirator differentiated by collection time, room and wall height above floor in A) rural areas and B) urban areas in northeastern Thailand, 2019.
Additionalfile3TableS3Ae.aegyptistickytrapcollections.docx
Additional file 3: Table S3. Ae. aegypti mosquitoes collected by sticky traps differentiated by collection room and wall height above floor in A) rural areas and B) urban areas in northeastern Thailand, 2019.
Additionalfile4TableS4Culexspp.stickytrapcollections.docx
Additional file 4: Table S4. Culex spp. mosquitoes collected by sticky traps differentiated by collection room and wall height above floor in A) rural areas and B) urban areas in northeastern Thailand, 2019.
Additionalfile5TableS5Householdcharacteristics.xlsx
Additional file 5: Table S5. Household environmental and socio-economic characteristics.
Additionalfile6TableS6UnivariableresultsSEanalysesAedesaegypti.xlsx
Additional file 6: Table S6. Univariable P-values for association analyses of socio-economic and environmental variables with Aedes aegyptiabundance.
Additionalfile7TableS7UnivariableresultsSEanalysesCulex.xlsx
Additional file 7: Table S7. Univariable P-values for association analyses of socio-economic and environmental variables with Culex spp. abundance.
Additionalfile8DatasetS1Mosquitorestingandgeckocollections.xlsx
Additional file 8: Dataset S1. Dataset on mosquito resting and gecko collections.
Additionalfile9DatasetS2Socioenvironmentalcharacteristics.xlsx
Additional file 9: Dataset S2. Dataset on socioenvironmental characteristics.

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Indoor resting behavior of Aedes aegypti and Culex spp. (Diptera: Culicidae) in northeastern Thailand

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Journal Publication

Version 1

Abstract

Figures

Background

Methods

Study area

Study design and data collections

Mosquito processing

Detection of dengue virus (DENV) in mosquitoes

Household characteristics

Data analysis

Results

Collections by aspirators

Sticky traps

Comparison of mosquito collections by an aspirator and sticky traps

DENV positive mosquitoes

Association of socio-environmental variables

Geckos and mosquito abundance

Discussion

Limitations

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1