The impact of Bacillus thuringiensis var israelensis (Bti) larvicide sprayed using drones for bio-control of malaria vectors in rice fields of Kigali Sub-Urban, Rwanda

The impact of Bacillus thuringiensis var israelensis (Bti) larvicide sprayed using drones for bio-control of malaria vectors in rice fields of Kigali Sub-Urban, Rwanda | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The impact of Bacillus thuringiensis var israelensis (Bti) larvicide sprayed using drones for bio-control of malaria vectors in rice fields of Kigali Sub-Urban, Rwanda Dunia Munyakanage, Elias Niyituma, Alphonse Mutabazi, Xavier Misago, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4257583/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Sep, 2024 Read the published version in Malaria Journal → Version 1 posted 10 You are reading this latest preprint version Abstract Background The core vector control tools used to prevent malaria infection are currently long-lasting insecticide treated nets (LLINs), and the indoor residual spraying (IRS). These indoor methods are threatened by insecticide resistance and behavioral adaptation by malaria vectors. Thus, for effective interruption of malaria transmission, there is a need to experiment further vector control interventions and technologies to address the above vector control challenges. Larviciding using drones-based technologies were experimented as innovative tools that could supplement existing indoor base interventions to control malaria. Methods A non-randomized larviciding trial with control was carried out in irrigated rice fields, in sub-urban of Kigali City, Rwanda. The potential mosquito larval habitats in study sites were prior mapped and subsequently sprayed using multirotor drones. The application of Bti (Vectobac® WDG) followed by the entomological surveys were performed every two weeks for ten months’ period. The sampling of mosquito larvae used the dipping method while adult mosquitoes were collected using CDC miniature light traps (CDC-LT) and pyrethrum spraying collection (PSC) methods, respectively. The malaria cases were routinely collected through community health workers in contingent villages to the study sites. Results The abundance of total mosquito larvae, Anopheles -specific larvae and pupae declined by 68.1%, 74.6% and 99.6% respectively. The larval density was reduced by 93.3% for total larvae, 95.3% for the Anopheles larvae and 61.9% for pupae. The total adult mosquitoes and An. gambiae s.l collected using CDC-Light trap declined by 60.6% and 80% respectively. Malaria incidence also declined significantly between intervention and control sites (U=20, z=-2.268, p=0.023) Conclusions The larviciding using drone technology implemented in Rwanda demonstrated a substantial reduction in abundance and density of mosquito larvae and, concomitant decline in adult mosquito populations and malaria incidence in contingent villages to the treatment sites. The impact of PSC method on adult mosquitoes was not significant on adult culicines spp. The scaling up of larval source management (LSM) has to be integrated in malaria programs in targeted areas of malaria transmission in order to enhance the gains in malaria control. Malaria mosquitoes drones rice fields Bacillus thuringiensis Rwanda Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background Mosquitoes are well established vectors of human pathogens and the main vectors of malaria causing parasites. Female Anopheles mosquitoes seek human blood and in the process act as the primary or secondary transmitters of disease (Mbewe et al., 2022). Malaria is a deleterious public health menace in subtropical and tropical countries (Siya et al., 2020) with more than two billion people exposed to it. According to reports by WHO (2022), mosquitoes transmitted malaria parasites and caused globally around 247 million cases of malaria, with 619 000 deaths, an estimated 95% of malaria cases and 96% deaths occurring in Africa, 78.9% of deaths occurring in children below the age of 5 years (WHO, n.d.), The main mosquitoes responsible are Anopheles arabiensis, An. gambiae , and the An. funestus species (Wiebe et al., 2017) In Rwanda, an increase in malaria morbidity from 208,000 malaria cases in 2011 to 4, 637, 483 cases in 2016 was reported (MOH-Rwanda, 2016). The upsurge in malaria cases was observed in all provinces of Rwanda (MOH-Rwanda, 2016). Malaria still poses a public health burden in Rwanda although the intensity is not uniform in all districts (Karema et al., 2020). Out of more than 465 known species of Anopheline mosquitoes, only three are involved in human malaria transmission, An. gambiae , the An. arabiensis and An. funestus due to their anthropophagic behaviour as well as their survival and longevity (Bamou et al., 2021). Continued incidence of malaria suggests that for successful breeding, the vectors utilize the few available breeding habitats during dry season and subsequently maintain malaria transmission (Animut and Negash, 2018); this poses a challenge in designing vector control interventions. Current malaria control measures in Rwanda have focused on control of adult mosquito. The measures include use of long-lasting insecticides treated nets (LLINs) and indoor residual spraying (IRS) preventing the disease by limiting human-vector contact. The widespread use of IRS and LLINs have not been sufficient as standalone vector control tools to eliminate malaria, mainly due to the insecticide resistance, outdoor and residual transmissions (Vigodny et al., 2023). There is dearth of data on the bioecology of vectors of malaria parasites in the affected region of Gasabo District of Rwanda. Review of the current strategies and combine to form an integrated strategy with novel vector-based control intervention such as larval source management (LSM) using drones for mapping of the water bodies and for spraying of Bti , using a community-based approach would potentially be suitable to sustainably overcome the challenges (Hardy et al., 2022). The proposed study intends to determine the changes in Anopheles spp.bionomics, the population dynamics of larvae, pupae and adults and its ability to transmit malaria following Bti application. Novel LSM applications techniques that use drones and community engagement in the application of LSM will become more appealing as breeding sites become focalized and as new man-made breeding sites such as agriculture-based increase. Methods Study site This study was conducted in Gasabo District which occupies the northern half of Kigali City approximately 9.8Kms from Kigali city with fifteen administrative sectors. It has an area of 430.30 km 2 of which a big portion (84%) is rural while the small portion (16%) represents the developed urban area (16%), with a population of 879,505 residents in 2022 with 81.2% of its population residing in urban areas (National Institute of Statistics of Rwanda et al., n.d.). The elevation is about 1456 meters above sea level. Rainfall is generally bimodal, March to May is marked with long rains, and short rains from September to November. The short dry season starts from December to February and long dry season start from June to mid-September (Muhire et al., 2015). The annual average rainfall received is 927 mm and the temperature ranges from 17°C to 28°C. Most of the population in Gasabo District are employed in Agriculture (31%), Trade (17%), Government (11%) (Gasabo District, 2013). Malaria in Gasabo District is mesoendemic and main vectors are Anopheles gambiae ss and An. Arabiensis . Rice farming is a major agricultural activity. The first farming cycle is from January to June and the second cycle starts in July and ending in December of each year. The expected mosquito breeding sites are mainly made of the stagnant water in the rice fields, expected to be permanent for the first three months of the rice cultivation (July to September and January to March). Other potential mosquito breeding sites are mainly after rain season, include inter-crops water drains, the pits and puddles from mining activities, water dams for harvesting rainwater for irrigation, stagnant water in the peri-domestic, water in different containers in use or unused. Study design The study was non-randomized with control involving a total of five blocks of marshlands located into five sectors of the District of Gasabo. Four blocks of marshlands located in the sectors of Jabana, Gisozi, Gatsata, and Kinyinya, with a total area of 336Ha was the experimental arm and received Bti application (Figure 1&2) . The control arm was in the sector of Nduba with 78 Ha and did not receive any Bti application. Using drones, maps of all water bodies in the experimental and control parts were generated prior to the intervention and each time before Bti application. The experimental sites were treated with 3000 ITU/mg Bacillus thuringiensis israelensis ( Bti ) strain AM 65-52 every 2 weeks using the Unmanned Aerial Vehicles “drones”. Rice farmers were trained to spray Bti into the mosquito breeding sites not accessible by drones mainly the peri-domestic breeding sites and other areas identified as non-eligible for aerial spraying. Considering the recommended dosage of Bti 3000 ITU/mg, strain AM 65-52, commercially traded as VectoBac ® , Water-Dispersible Granules (VectoBac ® WDG), 300 grams were diluted in 10 liters and covering one ha with aerial spraying with drone in 15 minutes, one drone was estimated to cover between 15 to 20 ha per day. For the supplemental hand application, sprayer pumps were calibrated for releasing 30 liters of 300 grams diluted Bti in one ha of water body. Mosquito larval sampling methods To measure the impact of larval control using Bti , baseline surveys on mosquito breeding habitats and larvae were carried out one week before the application of Bti , key entomological indicators were measured on larval densities. Larval sampling continued every two weeks for ten months, starting from two to three days post Bti spraying. The larval monitoring was performed in selected sampling plots purposively chosen using a Global Position System coordinate, sampling points marked at every 100 meters alongside the marshlands in three line transects, middle and two ridges of the marshlands (Figure 3). The overview of the numbers of sampling plots is as following (table 1): Sampling was done using standard dippers (350ml) to make five or ten dips (depending on the type of habitats) in each water body, the presence that were marked as positive or absence marked as negative of mosquito larvae were recorded and categorized according to their development stage. Mosquito adult sampling methods Indoor mosquito collections were done for two successive nights using battery powered CDC miniature light traps and pyrethrum spray collection (PSC) to sample endophagic and endophilic vectors respectively. Female adult mosquitoes were collected in twenty randomly selected houses from five different sites adjacent to the marshlands, three sites (12 houses) in neighborhood of intervention area and two (Eight houses) in control area (Figure 2). Identification of mosquito species ad sprorozoite infection (methods used: morphological and PCR, and ELISA for detection of sporozoite infection) The sampled adult mosquitoes were counted and identified using morphological features such as wing patterns, size, abdomen markings, mesopleural and thoracic hairs as described in the Gillies and Coetzee identification keys (M.T. Gillies and M. Coetzee, 2020). Each collected female anopheline mosquito sample was kept individually in a labeled micro-centrifuge tube with a lid for airtight locking with a desiccant. Siblings of the collected female An . gambiae s.l. were characterized using PCR technique based on DNA which utilizes a mixture of 20 base oligonucleotides primers that target the species nucleotide sequences in the ribosomal DNA (rDNA) intergenic spacers (IGS) (Scott et al., 1993), after genomic DNA extraction from legs and wings using the Cetyl Trimethyl Ammonium Bromide (CTAB) based protocol (de la Cruz-Ramos et al., 2019). To determine presence of a circumsporozoite proteins (CSP), ELISA tests was done on the head and thorax using the CS microplate ELISA to detect P. falciparum, Optical Density (OD) measured using spectrophotometer (Appawu et al., 2003). Blood-meal sources of all collected blood-fed female samples captured by PSC were analyzed using a direct ELISA, using antihost Monoclonal antibodies (IgG) conjugate against human, cattle, goat, sheep, chicken proteins, OD measured using spectrophotometer (Getachew et al., 2019). The balance checks for study The balance check was done to assess the abundance and density of anopheles, and culicines mosquito larvae and pupae in the study sampling plots before the intervention. The initial density was also conducted on adult mosquitoes collected using CDC-LT and the Pyrethrum Spraying Collection methods. Determination of malaria incidence Community health workers (CHWs) patients’ registers were used for monthly data collection of malaria cases from the contingent villages to the study area. Fifteen villages in proximity to the marshlands of the study area, aggregated into twelve nearby the intervention and three in the control area respectively. Statistical Analysis Data were recorded in Excel and transferred into statistical software, version R 4.0.2 for statistical analysis. In preliminary, descriptive analysis was performed to generate tables and curves. The intervention and control groups were constructed to visualize differences in the responses between the two groups. We used mean, median, and standard errors (SE) to present continuous variables and frequencies for categorical variables. We performed a balance check using the T-test to compare means of treatment and control groups for independent variables at baseline (Round 0). Further, the difference analysis was calculated using regression analysis, adjusted with time, to evaluate the effect of larviciding on breeding habitats with anopheles and culicines mosquito larvae and pupae as well as the adult mosquitodensities. The evaluation of differences on malaria incidences between intervention and control sites, a non-parametric test was used, Mann Whitney test. Ethical consideration The study was presented to Rwanda Biomedical Centre, Division of Research, Innovation and Data Sciences for review and clearance and received approval Ref: No 225/RBC/2020. The importation and usage of Bti was authorized by the Ministry of Health, Department of Food and Drug Authority. Before application of Bti and larval monitoring, verbal consent was obtained from local leaders, the head of the rice farmer cooperative, owners of houses used for adult collections and the entomology technicians involved in entomology monitoring. Results The balance checks for study The balance checks on mosquito larvae and pupae using 131 plots as well as on adult mosquitoes using 40 houses-nights showed no difference between the treatment and control arms (table 2) . Larval habitat occupancy At the end of the intervention (Round 20), the comparison of treatment and control blocs showed a statistical significant differences (p < 0.001) between treatment and control blocs with a decline overtime in the overall larval habitat occupancy (Figure 4) . In the experimental sites, the overall habitat occupancy of sampling plots was 16.1% for Anopheles larvae with a decrease of 78.3% (P-Value <0.001) while it was 74.3% in control. The overall habitat occupancy of sampling plots for Culicines larvae was 11.6% in experimental sites with a reduction of 31.4% while was 16.9% in control (P-Value <0.001), pupal occupancy rate was 1.9% with a reduction of 69.2% in experimental sites while was 6% in control (P-Value <0.001) (table 3). Mosquito larval density Analysis of larval density showed that in all blocs of the experimental sites of the study, the treatment intervention significantly reduced the anophelines larval density by 98.7%, culicines larval density by 81.3% and pupal density by 75% (table 5) . The anopheles larval density declined and kept lower in treatment than control arms while a rebound was observed from 10 th rounds in control for culicines and pupal stages (Figure 5). This was due to the significant effects of time, treatment alone or in combination on results (table 4). Adult mosquitoes CDC-LT Overall, out of 14,387 adult mosquitoes collected over ten months in the two study sites, culicines spp. were dominant (85.9%, n =12,354) and anopheles species represented 14.1%. Among Anopheles mosquitoes collected, An. gambiae s.l. was the most abundant (90.3%, n=1836) followed by An. ziemanni (5.8%, n=117), An. squamosus (3%, n=60), An. maculipalpis (0.8%, n=17), and other Anopheles mosquitoes (0.15%, n=3). Out of the total mosquito collections, 74% (n=1510) of Anopheles spp. and 55% (n=6796) of culicines spp were collected from the control arm (table 6). Anopheles arabiensis was found to be the predominant An. gambiae sibling species collected with CDC LT. For a total of 782 specimens of An. gambiae s.l. tested using species-specific PCR, 405 (51.8%) were identified as An. arabiensis and 377 (48.2%) as An. gambiae sensu stricto. ELISA assays to detect P. falciparum CSP protein were performed on the head and thorax of 2,108 specimens of individual female Anopheles mosquitoes collected by both CDC LT (79.6%, n=1678) and PSC (20.4%, n=430) methods to ascertain the malaria parasite infection rates in the study sites. Anopheles gambiae s.l . (n=1,914) made up 90.8% of the total samples, An. ziemani (5.4%, n=114), An. squamosus (3.1%, n=65), An. maculipalpis (0.5%, n=10), An. rufipes (0.1%, n=3), An. coustani (0.05%, n=1), An. funestus (0.05%, n=1). All the samples were tested negative to Plasmodium infection . The larviciding using Bti and sprayed with drones shows a significant impact on adult mosquito densities in villages neighboring the intervention sites (Table 6) . The total adult anopheles spp was significantly reduced by 79.9%, culicines spp by 44.14% and Anopheles gambiae s.l. by 76.05% (p < 0.001). The significant effects of treatment and time alone were observed on anopheles mosquitoes but not on culicines. The combination of the two variables didn’t have any significant effect either on anopheles nor on culicines mosquitoes (Table 7). 4.2 Pyrethrum Spraying Collection Method With PSC method, out of 1,839 adult mosquitoes collected over ten months in the two study sites, culicines spp were representing 79.4% (n =1,460) while total anopheles mosquitoes were 21.6%. Among the catches of Anopheles mosquitoes, An. gambiae s.l. was the most dominant with 96.8% (n=367) followed by An. ziemanni (2.9%, n=11), An. squamosus (0.3%, n=1). Per study arm, 73% (n=379) of Anopheles spp. and 37% (n=536) of culicine mosquitoes were caught from the control arm. Anopheles arabiensis was found to be the predominant An. gambiae sibling specie collected. For a total of 362 specimens of An. gambiae s.l. with species-specific PCR results, 295 (81.5%) were successfully identified as An. arabiensis and 67 (18.5%) as An. gambiae sensu stricto. A total of 155 blood fed Anopheles gambiae sensu lato collected from the experiment and control houses were tested by direct ELISA for blood-meal sources identification. The majority (69.7%) of An. gambiae s.l. had fed on bovine (n=108), human IgG was detected in 12.3% (n=19), remaining An. gambiae s.l. had fed on other vertebrate hosts, which were Goat (5.2%, n=8), Bovine and Goat (3.9, n=6), Human and Bovine (0.6, n=1), and unidentified host in 8.4% (n=13). Following Bti application, the catches of adult anopheles mosquitoes were significantly reduced by 78.74% and by 79.8% for total Anopheles and Anopheles gambiae sl respectively (Table 8) . However, the collections of culicines spp. increased significantly by 10.12% (p < 0.001) in treatment arm with incremental increase from the 5 th round and a decline trend in control arm (Figure 7) . The two variables of time and treatment alone or in combination didn’t have a significant effect on adult mosquitoes collected using PSC method, except the combined effects reported on culicines spp (Table 9). Discussion The findings of this LSM trial performed in irrigated rice fields of sub-urban of Kigali City, Rwanda, using drone based technology showed a significant reduction (P < 0.001) of mosquito habitant occupancies with a decline of 78.3%, 69.2% and 31.4% for anopheles, culicines larvae and pupae stages respectively. The mosquito larval density also declined significantly (p < 0.001) with 98.7%, 75.0% and 81.3% for anopheles and culicine larvae and pupae respectively. The mean number of adult mosquitoes per trap and per night caught with CDC-LT decreased significantly (P < 0.001) with reduction of 79.1% for total anophele s species, 44.1 for culicines and 76.05 for Anopheles gambiae s.l. the primary malaria vector in study site. The mean number of mosquitoes caught per house and per night with PSC method also significantly declined (P < 0.001) compared to the control site for total anopheles and An.gambiae s.l . with respective reduction of 78.7% and 79.8%. However, the culicine mosquitoes increased significantly by 10.1% (p < 0.001). Malaria incidences reported by community health workers in contingent villages were higher in control than intervention sites (U = 20, z=-2.268, p = 0.023). Similarly, another previous larval source management trial conducted for six months in rice fields of Southern East of Rwanda, with Bti solely sprayed with simple knapsack sprayer pumps also proved significant control of mosquito habitat occupancies as well as the density of aquatic stages and adult anopheles mosquitoes collected using CDC-LT. This trial reported a complete interruption of pupal stage in treated arm from the 5th round of the 12 rounds of Bti application (Hakizimana et al., 2022 ). Moreover, the beneficiary communities mainly the rice farmers demonstrated a high perception on Bti safety and acceptance of larviciding intervention (Ingabire et al., 2017 ). Therefore, this study demonstrated the limitations of larviciding using simple knapsack in complex and large mosquito habitats such as the irrigated rice fields. The Bti sprayers reported the difficulties encountered during the Bti application mainly the muddy and slippery soils during rainy seasons, watering of rice plots mainly the first three months of rice farming cycle, and the coverage of upstream water dam for storage of irrigation water (hakizimana et al., 2022 ). The above challenges were addressed during the current larviciding trial by prior mapping of potential mosquito breeding sites and the aerial spraying of Bti using drones instead of simple knapsacks. This trial yielded a high entomological impact compared to the previous trial using hand knapsack sprayer pumps. The moderate impact of larviciding with Bti (VectoBac WDG) was also documented by prior studies in complex mosquito breeding habitats such as flooded ecosystem in Gambia (Silas et al.2010), and irrigated rice fields (Fillinger et al., 2009). Another targeted larviciding trial with only treatment of the most productive anopheles breeding sites and systematic treatment of all potential mosquito breeding areas demonstrated similar reduction of female anopheles mosquitoes respectively by 61% and 70% (Damback et al., 2019). The larviciding trial with VectorMax® G conducted in Yaoundé, Cameroon found out an impact both on malaria vectors and culex mosquitoes with reduction of 69% and 36.6% in aquatic habitats and adult density inside houses for culex species, respectively (Talipouo et al., 2023 ). The impact on other mosquito species such as Aedes spp and Culex mosquitoes was also found to be limited in some settings (Dambach et al., 2021 ). The timing of larviciding, exhaustive and accurate geo-locations and types of mosquito habitats were the primary hindrances to optimize the impact of LSM, and thus requiring the new technologies (Hardy et al., 2017 & 2023 ). The other limitations associated to the impact of larviciding are the accurate detection of water bodies potential to mosquito breeding areas, the human resettlements and nature of constructions. These are to-date sorted out by prior mapping of the study areas with drones and enabling then the improvement of the coverage of mosquito larval habitats with larviciding (Escobar et al., 2019). The recent trial of drones based larviciding carried out in Unguja island, Zanzibar, Tanzania in rice fields showed an improved entomological impact of more than 90% reduction of aquatic stages abundance and density of mosquitoes. This study demonstrated that Unmanned Aerial Vehicles (UAVs) improved the coverage of larviciding and can be used beyond the targeted sites as recommended by WHO for LSM intervention (WHO, 2013 ). The UAVs technologies proved the effectiveness of controlling mosquito population over large and complex areas at low cost. They may also enhance the cost-effective control of malaria and other mosquito borne diseases and elimination efforts (Mukabana et al., 2022 ). Another promising technology is based on high resolution images captured with drones which may also contribute to geo-locating at low costs the potential mosquito larval habitats. The latter are detected through the analysis of presence and type of aquatic vegetation (Stanton et al., 2019). Therefore, the required technical skills (Derua et al., 2019) and the more time for processing of images still the main hindrances for this innovation which guide to tackle directly the positive larval mosquito breeding habitats during larviciding operation (Stanton et al., 2019). The spatial intelligence system (SIS) for larviciding is another promising technology and based on mapping of mosquito breeding areas which was shown cheaper and more accurate than the conventional ground-based mapping method (Hardy et al., 2023 ). The larviciding conducted in many mosquito habitats including the complex ecosystems, with improved coverage and appropriate larvicide product demonstrated a drastic impact on abundance and density of malaria vectors and other mosquito borne diseases. Nowadays, larviciding is a proven and viable intervention enabling to supplement the current core indoor vector control tools in targeted settings even in large and complex mosquito breeding habitats (Olalubi et al., 2016, Damback et al, 2019, Talipouo et al. 2022, Mukabana et al., 2022 ., Mpofu et al., 2016 ) Conclusion Despite the targeted study area was a complex ecosystem of irrigated rice fields with frequent flooded areas and man-made breeding sites, the Unmanned aerial vehicles (drones) contributed to operationalize the larviciding intervention which was guided by prior aerial maps of water bodies. The coverage of all geo-located potential breeding sites was effectively performed alongside the 20 rounds of larviciding operations. In comparison between the intervention and control site, the aquatic mosquito larval habitat occupancies and mosquito larvae density were significantly declined, as well as the adult anopheles collected using CDC-LT and PSC methods. The malaria incidence showed also a significant decline trend in intervention compared to the control site. The scaling up of larviciding using drone technologies for prior mapping of potential mosquito breeding sites and then spraying of larvicide proved its effectiveness not only in targeted sites as recommended by WHO but also in complex anopheles breeding habitats. These vector control technologies have to be integrated by malaria programs to enhance the gains in malaria control and elimination efforts. However, the low impact on culicine mosquitoes may affect the acceptance of LSM intervention by beneficiary communities. Further engagement of local communities are recommended and using appropriate formulations of larvicide for controlling culicines breeding habitats. Abbreviations Bti Bacillus thuringiensis var. israelensis CDC Centers for Disease Control and Prevention CTAB Cetyl Trimethyl Ammonium Bromide ELISA Enzyme-Linked Immunosorbent Assay IRS Indoor residual spraying ITU International toxic units LLIN Long-lasting insecticide treated net LSM Larval source management MOH Ministry of Health PCR Polymerase chain reaction PSC Pyrethrum Spraying Collection UAV Unmanned Aerial Vehicles WDG Water dispersible granules WHO World Health Organization Declarations Ethics approval and consent to participate The study was presented to Rwanda Biomedical Centre, Division of Research, Innovation and Data Sciences for review and clearance and received approval Ref: No 225/RBC/2020. The importation and usage of Bti was authorized by Rwanda Food and Drug Authority. Before application of Bti and larval monitoring, verbal consent was obtained from local leaders, the head of the rice farmer cooperatives, owners of houses used for adult collections and the entomology technicians involved in entomology monitoring. Consent for publication Not applicable Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding The acknowledgement is addressed to Society for Family Health (SFH) Rwanda for the donation of Bti applied during the experiments and to Charis UAS for drone based services for mapping and spraying of Bti with free charge costs. The financial support for entomology monitoring was provided by the Government of Rwanda through Rwanda Biomedical Center. Authors’ contributions DM, EH, EK, CM, SM, AM, AMB and CMM conceived the preliminary study outlines. 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Malaria patterns across altitudinal zones of Mount Elgon following intensified control and prevention programs in Uganda. BMC Infect Dis, 2020, 20 (1). https://doi.org/10.1186/s12879-020-05158-5 Vigodny A, Ben Aharon M, Wharton-Smith A, Fialkoff Y, Houri-Yafin A, Bragança F et al. Digitally managed larviciding as a cost-effective intervention for urban malaria: operational lessons from a pilot in São Tomé and Príncipe guided by the Zzapp system. Malar J, 2023, 22 (1), 114. https://doi.org/10.1186/s12936-023-04543-0 WHO. World malaria report 2022. Geneva: World Health Organization; 2022. p. 293. https://www.who.int/teams/global-malaria-programme Wiebe A, Longbottom J, Gleave K, Shearer F M, Sinka M E, Massey N C et al. Geographical distributions of African malaria vector sibling species and evidence for insecticide resistance. Malar J, 2017, 16 (1) : 65. https://doi.org/10.1186/s12936-017-1734-y Olalubi OA, Chinwe GK. Promoting Larval Source Management as a Vital Supplemental Addendum and More Likely Cost-Effective Approach for Malaria Vector Control in Nigeria. Prev Inf Cntrl, 2016, 2:2. Talipouo A, Doumbe PB, Ngadjeu CS, Djamouko-Djonkam L, Nchoutpouen E, Bamou R et al. Larviciding intervention targeting malaria vectors also affects Culex mosquito distribution in the city of Yaoundé, Cameroon. Current Res Parasitol & Vector-Borne Dis, 2023, 4:100136 Hakizimana E, Ingabire CM, Rulisa A, Kateera F, van den Borne B, Muvunyi CM et al. Community-Based Control of Malaria Vectors Using Bacillus thuringiensis var. Israelensis ( Bti ) in Rwanda. Int. J. Environ. Res. Public Health, 2022, 19:6699. https://doi.org/10.3390/ijerph19116699. Stanton MC, Kalonde P, Zembere K, Spaans RH, Jones CM. The application of drones for mosquito larval habitat identification in rural environments: a practical approach for malaria control? Malar J, 2021, 20 : 244.https://doi.org/10.1186/s12936-021-03759-2 Mukabana WR, Welter G, Ohr P, Tingitana L, Makame MH, Ali AS et al. Drones for Area-Wide Larval Source Management of Malaria Mosquitoes. Drones, 2022, 6 (7):180. https:// doi.org/10.3390/drones6070180 Mpofu M, Becker P, Mudambo K, de Jager C . Field effectiveness of microbial larvicides on mosquito larvae in malaria areas of Botswana and Zimbabwe. Malar J, 2016 , 15 :586 . DOI 10.1186/s12936-016-1642-6 Majambere S, Pinder M, Fillinger U, Ameh D, Conway DJ, Green C, et al. Is mosquito larval source management appropriate for reducing malaria in areas of extensive flooding in the Gambia? A cross-over intervention trial. J Am J Trop Med Hyg. 2010, 82 :176–84. Derua YA, Kweka EJ, Kisinza WN, Githeko AK, Mosha FW. Bacterial larvicides used for malaria vector control in sub-Saharan Africa: review of their effectiveness and operational feasibility. Parasites Vectors (2019) 12:426. https://doi.org/10.1186/s13071-019-3683-5 Fillinger U, Lindsay SW. Larval source management for malaria control in Africa: myths and reality. Malar J , 2011, 10:353. https://www.malariajournal.com/content/10/1/353 Ingabire C M, Hakizimana E, Rulisa A, Kateera F, Van Den Borne B, Muvunyi C M et al. Community‑based biological control of malaria mosquitoes using Bacillus thuringiensis var. israelensis (Bti) in Rwanda: community awareness, acceptance and participation. Malar J, 2017 , 13: 399. WHO. Larval source management: A supplementary measure for malaria vector control, an operational manual . Geneva-Switzerland. World Health Organization, 2013, p.116. Carrasco-Escobar G, Manrique E, Ruiz-Cabrejos J, Saavedra M, Alava F, Bickersmith S, et al . PLoS Negl Trop Dis, 2019, 13 (1): e0007105. https://doi.org/10.1371/journal. e0007105 Dambach P, Bärnighausen T, Yadouleton A, Dambach M, Traoré I, Korir P, et al. Is biological larviciding against malaria a starting point for integrated multi-disease control? Observations from a cluster randomized trial in rural Burkina Faso. PLoS ONE, 2021, 16 (6): e0253597. https://doi.org/10.1371/journal.pone.0253597 Dambach P, Bärnighausen T, Traoré I, Ouedraogo S, Sié A, Sauerborn R et al. Reduction of malaria vector mosquitoes in a large‑scale intervention trial in rural Burkina Faso using Bti based larval source management. Malar J, 2019, 18:311 . https://doi.org/10.1186/s12936-019-2951-3 Hardy A, Makame M, Cross D, Majambere S, Msellem M. Using low-cost drones to map malaria vector habitats. Parasit Vectors , 2017, 10 :29 DOI 10.1186/s13071-017-1973-3. Hardy A, Haji K, Abbas F, Hassan J, Ali A, Yussuf Y et al. Cost and quality of operational larviciding using drones and smartphone technology. Malar J , 2023, 22 :286 https://doi.org/10.1186/s12936-023-04713-0 Tables Table 1: Number of mosquito larval sampling plots per intervention bloc and study arms, Gasabo, Kigali-City, Rwanda. Study sites Bloc number Number of sampling plots Experimental site 1 51 2 35 3 60 4 35 Control site 5 49 Total 230 Table 2: Results of balance checks on aquatic stages and adult mosquitoes between treatment and control arms Methods Variable Number of plots/houses Mean (SE) Control Mean (SE) Treatment Mean (SE) Diff P-Value Dipping (larvae) Anopheles larvae 131 3.53 (1.15) 3.008 (0.88) 0.52 (2.48) >0.05 Culicines larvae 131 9.8 (2.41) 5.23 (1.92) 4.56 (5.43) >0.05 Pupae 131 1.73 (0.55) 1.21 (0.342) 0.526 (.975) >0.05 PSC Anopheles sp 40 0 (0) 0.54 (0.28) -0.54 (0.34) >0.05 Culicines sp 40 2.43(0.81) 1.54 (0.51) 0.895 (0.906) >0.05 CDC Anopheles sp 40 1.56 (0.46) 2.21 (0.62) 1.95 (0.41) >0.05 Culicines sp 40 34.06 (9.41) 13.25 (2.56) 21.57 (4.31) <0.05 Table 3. Mean proportion habitat occupancy of late instars L3+L4 of anopheles, culicines larvae and pupae in control and treatment arms during the 20 rounds of drones-based application of bio-larvicide (Bti), Rwanda. The “*” explains the statistical differences at 95% of confidence interval. Mosquito larval species Control arm (proportion of habitat occupancy in %: n=817) Treatment arm (proportion of habitat occupancy in %: n=3080) Reduction % P-Value Anopheles larvae 74.3% 16.1% 78.3 <0.001* Culicines larvae 16.9% 11.6% 31.4 <0.001* Pupae 6.0% 1.9% 69.2 <0.001* Table 4. Effects of treatment and time on anopheles, culicines larvae and pupal stages Coefficient [95% conf. Interval] Anopheles larval Treatment -0.25*** [-0.32; -0.18] Time -0.43*** [-0.48; -0.37] Time*Treatment 0.24*** [0.17;0.31] Cullicines larval Treatment -0.70*** [-0.85; -0.55] Time -0.90*** [-1.01; -0.78] Time*Treatment 0.70*** [0.55;0.86] Pupa larval Treatment -0.22*** [-0.25; -0.19] Time -0.24*** [-0.26; -0.22] Time*Treatment 0.22*** [0.19;0.25] Table 5. Mean number per dip (density) of late instars L3+L4 of anopheles, culicines larvae and pupae in control and treatment arms during the 20 rounds of drones-based application of bio-larvicide (Bti), in Rwanda. The “*” explains the statistical differences at 95% of confidence interval. Mosquito larval species Control arm (Adjusted mean larvae per dip) Treatment arm (Adjusted mean larvae per dip) Reduction % P-Value Anopheles larvae 0.67 0.01 98.7 <0.001* Culicines larvae 0.08 0.02 81.3 <0.001* Pupae 0.02 0.01 75.0 <0.001* Table 6. Mean number of adult mosquitoes per trap and per night collected using CDC-Light trap in nearby villages of treatment (n=480) and control arms (n=320), during the 20 rounds of drones-based application of bio-larvicide (Bti), Rwanda. The “*” explains the statistical differences at 95% of confidence interval. Mosquito species Control arm: Mean+SE (n=320) Treatment arm: Mean+SE (n=480) Adjusted mean difference Reduction in % P-Value Tota l Anopheles 4.64 0.97 3.66 (0.296) 79.09 <0.001* Culicines spp 19.53 10.91 8.62 (0.99) 44.14 <0.001* Anopheles gambiae s.l. 4.05 0.97 3.08 (0.258) 76.05 <0.001* Table 7. Effect of treatment and time alone or in combination on anopheles, culicines adult mosquitoes collected using CDC-LT method. Coefficient [95% conf. Interval] Anopheles spp Treatment -4.15*** (-5.23; -3.07) Time -0.13*** (-0.2; -0.06) Time*Treatment 0.07 (-0.02;0.16) A.gambiae s.l. Treatment -3.51*** (-4.45; -2.57) Time -0.12*** (-0.18; -0.06) Time*Treatment 0.06 (-0.02;0.14) Culicines spp Treatment -10.29* (-18.38; -2.19) Time -0.18 (-0.43;0.08) Time*Treatment 0.12 (-0.21;0.45) Table 8: Mean number of adult mosquitoes per house and per night collected using Pyrethrum spraying catch (PSC) in nearby villages of treatment (n=480) and control arms (n=320), during the 20 rounds of drones-based application of bio-larvicide (Bti), Rwanda. The “*” explains the statistical differences at 95% of confidence interval. Mosquito species Control arm: Mean+SE ( n=320) Treatment arm: Mean+SE ( n=480) Adjusted mean difference Reduction in % P-Value Total Anopheles 0.87 0.19 0.68 (0.074) 78.74 <0.001* Culicines spp 1.68 1.85 -0.17 (0.167) -10.12 <0.001* Anopheles gambiae s.l. 0.84 0.17 0.66 (0.073) 79.76 <0.001* Table 9. Effect of treatment and time alone or in combination on anopheles, culicines adult mosquitoes collected using PSC method. Coefficient [95% conf. Interval] Anopheles spp Treatment -0.39 (-0.79;0.01) Time 0.00 (-0.02;0.02) Time*Treatment -0.02 (-0.05;0.00) Culicines spp Treatment -0.98 (-3.76;1.81) Time -0.02 (-0.06;0.02) Time*Treatment 0.11*** (0.06;0.16) Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 17 Sep, 2024 Read the published version in Malaria Journal → Version 1 posted Editorial decision: Revision requested 24 Jun, 2024 Reviews received at journal 04 Jun, 2024 Reviewers agreed at journal 13 May, 2024 Reviewers agreed at journal 08 May, 2024 Reviews received at journal 06 May, 2024 Reviewers agreed at journal 18 Apr, 2024 Reviewers invited by journal 17 Apr, 2024 Submission checks completed at journal 12 Apr, 2024 Editor assigned by journal 12 Apr, 2024 First submitted to journal 12 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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3","display":"","copyAsset":false,"role":"figure","size":653862,"visible":true,"origin":"","legend":"\u003cp\u003eSampling plots for mosquito larval stages and community houses for adult mosquito collections in the study site, Gasabo-Kigali-City, Rwanda.\u003c/p\u003e","description":"","filename":"Binder23.png","url":"https://assets-eu.researchsquare.com/files/rs-4257583/v1/1b00d0323d42a3d51b3c3826.png"},{"id":55003697,"identity":"40843a7d-db0a-4a7a-beab-11721760b8c9","added_by":"auto","created_at":"2024-04-19 18:43:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":123768,"visible":true,"origin":"","legend":"\u003cp\u003eTrends of habitat occupancy per survey round in treatment and control arms for\u003cem\u003eAnopheles\u003c/em\u003e larvae (panel A), culicines larvae (Panel B) and pupae (panel C).\u003c/p\u003e","description":"","filename":"Binder24.png","url":"https://assets-eu.researchsquare.com/files/rs-4257583/v1/98f5d0b832a1384cc248a88d.png"},{"id":55003696,"identity":"8359674f-bcfb-4cc4-ae66-3609e1f8c5a2","added_by":"auto","created_at":"2024-04-19 18:43:24","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":124672,"visible":true,"origin":"","legend":"\u003cp\u003eTrends of mosquito larval and pupal density per survey round in treatment and control arms for\u003cem\u003e Anopheles\u003c/em\u003e larvae (panel A), culicines larvae (Panel B) and pupae (panel C).\u003c/p\u003e","description":"","filename":"Binder25.png","url":"https://assets-eu.researchsquare.com/files/rs-4257583/v1/288288aacdfd1ab9b20679f1.png"},{"id":55005687,"identity":"89829226-36db-4f14-a8e9-b62758ba702c","added_by":"auto","created_at":"2024-04-19 18:51:25","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":110997,"visible":true,"origin":"","legend":"\u003cp\u003eMean number of adult mosquitoes per house and per survey round collected using CDC-Light trap in treatment and control arms for anopheles spp (panel A), and culicines spp (Panel B).\u003c/p\u003e","description":"","filename":"Binder26.png","url":"https://assets-eu.researchsquare.com/files/rs-4257583/v1/c6edfdf0c32b6b8e6ed46f4f.png"},{"id":55005686,"identity":"9c641ff1-f38b-4818-beaa-59c30740d503","added_by":"auto","created_at":"2024-04-19 18:51:25","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":279082,"visible":true,"origin":"","legend":"\u003cp\u003eMean number of adult mosquitoes per house and per survey round collected using pyrethrum spraying catching (PSC) method in nearby villages to the treatment (n=24 houses) and control (n=16 houses) arms for anopheles spp (panel A), and culicines spp (Panel B).\u003c/p\u003e","description":"","filename":"Binder27.png","url":"https://assets-eu.researchsquare.com/files/rs-4257583/v1/c5f12345a71d898d0e2c8868.png"},{"id":65104132,"identity":"77fa02b0-a1c8-41a4-a336-1753c80a58f9","added_by":"auto","created_at":"2024-09-23 16:12:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3897615,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4257583/v1/e068ca31-2db7-4f8d-a605-3fb275a39f35.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The impact of Bacillus thuringiensis var israelensis (Bti) larvicide sprayed using drones for bio-control of malaria vectors in rice fields of Kigali Sub-Urban, Rwanda","fulltext":[{"header":"Background","content":"\u003cp\u003eMosquitoes are well established vectors of human pathogens and the main vectors of malaria causing parasites. Female \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes seek human blood and in the process act as the primary or secondary transmitters of disease\u0026nbsp;(Mbewe et al., 2022).\u0026nbsp;Malaria is a deleterious public health menace in subtropical and tropical countries\u0026nbsp;(Siya et al., 2020)\u0026nbsp;with more than two billion people exposed to it. According to reports by WHO (2022), mosquitoes transmitted malaria parasites and caused globally around 247 million cases of malaria, with 619 000 deaths, an estimated 95% of malaria cases and 96% deaths occurring in Africa, 78.9% of deaths occurring in children below the age of 5 years\u0026nbsp;(WHO, n.d.), The main mosquitoes responsible are \u003cem\u003eAnopheles arabiensis, An. gambiae\u003c/em\u003e, and the \u003cem\u003eAn. funestus\u0026nbsp;\u003c/em\u003especies\u0026nbsp;(Wiebe et al., 2017)\u003c/p\u003e\n\u003cp\u003eIn Rwanda, an increase in malaria morbidity from 208,000\u0026nbsp;malaria cases in 2011 to 4, 637, 483 cases in 2016 was reported\u0026nbsp;(MOH-Rwanda, 2016). The upsurge in malaria cases was observed in all provinces of Rwanda\u0026nbsp;(MOH-Rwanda, 2016). Malaria still poses a public health burden in Rwanda although the intensity is not uniform in all districts (Karema et al., 2020). Out of more than 465 known species of Anopheline mosquitoes, only three are involved in human malaria transmission, An. \u003cem\u003egambiae\u003c/em\u003e, the An. \u003cem\u003earabiensis\u003c/em\u003e and An. \u003cem\u003efunestus\u003c/em\u003e due to their anthropophagic behaviour as well as their survival and longevity (Bamou et al., 2021).\u0026nbsp;Continued incidence of malaria suggests that for successful breeding, the vectors utilize the few available breeding habitats during dry season and subsequently maintain malaria transmission (Animut and Negash, 2018); this poses a challenge in designing vector control interventions.\u003c/p\u003e\n\u003cp\u003eCurrent malaria control measures in Rwanda have focused on control of adult mosquito. The measures include use of long-lasting insecticides treated nets (LLINs) and indoor residual spraying (IRS) preventing the disease by limiting human-vector contact.\u0026nbsp;The widespread use of\u0026nbsp;IRS and LLINs have not been sufficient as standalone vector control tools to eliminate malaria, mainly due to the insecticide resistance, outdoor and residual transmissions\u0026nbsp;(Vigodny et al., 2023).\u0026nbsp;\u0026nbsp;There is dearth of data on the bioecology of vectors of malaria\u0026nbsp;parasites in the affected region of Gasabo District of Rwanda. Review of the current strategies and combine to form an integrated strategy with novel vector-based control intervention such as larval source management\u0026nbsp;(LSM) using drones for mapping of the water bodies and for spraying of \u003cem\u003eBti\u003c/em\u003e, using a community-based approach would potentially be suitable to sustainably overcome the challenges\u0026nbsp;(Hardy et al., 2022).\u0026nbsp;The proposed study intends to determine the changes in \u003cem\u003eAnopheles\u0026nbsp;\u003c/em\u003espp.bionomics, the population dynamics of larvae, pupae and adults and its ability to transmit malaria following \u003cem\u003eBti\u003c/em\u003e application. Novel LSM applications techniques that use drones and community engagement in the application of LSM will become more appealing as breeding sites become focalized and as new man-made breeding sites such as agriculture-based increase.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy site\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in Gasabo District which occupies the northern half of Kigali City approximately 9.8Kms from Kigali city with fifteen administrative sectors. \u0026nbsp;It has an area of 430.30\u0026nbsp;km\u003csup\u003e2\u003c/sup\u003e of which a big portion (84%) is rural while the small portion (16%) represents the developed urban area (16%), with a population of 879,505 residents in 2022 with 81.2% of its population residing in urban areas (National Institute of Statistics of Rwanda et al., n.d.). The elevation is about 1456 meters above sea level. Rainfall is generally bimodal, March to May is marked with long rains, and short rains from September to November. The short dry season starts from December to February and long dry season start from June to mid-September (Muhire et al., 2015). The annual average rainfall received is 927 mm and the temperature ranges from 17°C to 28°C. Most\u0026nbsp;of the population in Gasabo District are employed in Agriculture (31%), Trade (17%), Government (11%) (Gasabo District, 2013). Malaria in Gasabo District is mesoendemic and main vectors are \u003cem\u003eAnopheles gambiae ss\u003c/em\u003e and \u003cem\u003eAn. Arabiensis\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRice farming is a major agricultural activity. The first farming cycle is from January to June and the second cycle starts in July and ending in December of each year. The expected mosquito breeding sites are mainly made of the stagnant water in the rice fields, expected to be permanent for the first three months of the rice cultivation (July to September and January to March). Other potential mosquito breeding sites are mainly after rain season, include inter-crops water drains, the pits and puddles from mining activities, water dams for harvesting rainwater for irrigation, stagnant water in the peri-domestic, water in different containers in use or unused.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was non-randomized with control involving a total of five blocks of marshlands located into five sectors of the District of Gasabo. Four blocks of marshlands located in the sectors of Jabana, Gisozi, Gatsata, and Kinyinya, with a total area of 336Ha was the experimental arm and received \u003cem\u003eBti\u003c/em\u003e application \u003cstrong\u003e(Figure 1\u0026amp;2)\u003c/strong\u003e. \u0026nbsp;The control arm was in the sector of Nduba with 78 Ha and did not receive any \u003cem\u003eBti\u003c/em\u003e application. Using drones,\u0026nbsp;maps of all water bodies in the experimental and control parts were generated prior to the intervention and each time before \u003cem\u003eBti\u003c/em\u003e application.\u003c/p\u003e\n\u003cp\u003eThe experimental sites were treated with 3000 ITU/mg \u003cem\u003eBacillus thuringiensis israelensis\u0026nbsp;\u003c/em\u003e(\u003cem\u003eBti\u003c/em\u003e)\u0026nbsp;strain AM 65-52 every 2 weeks using the Unmanned Aerial Vehicles “drones”. Rice farmers were trained to spray \u003cem\u003eBti\u003c/em\u003e into the mosquito breeding sites not accessible by drones mainly the peri-domestic breeding sites and other areas identified as non-eligible for aerial spraying.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsidering the recommended dosage of \u003cem\u003eBti\u003c/em\u003e 3000 ITU/mg,\u0026nbsp;strain AM 65-52, commercially traded as VectoBac\u003csup\u003e®\u003c/sup\u003e, Water-Dispersible Granules (VectoBac\u003csup\u003e®\u003c/sup\u003e WDG), 300 grams were diluted in 10 liters and covering one ha with aerial spraying with drone in 15 minutes, one drone was estimated to cover between 15 to 20 ha per day. For the supplemental hand application, sprayer pumps were calibrated for releasing 30 liters of 300 grams diluted \u003cem\u003eBti\u003c/em\u003e in one ha of water body.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMosquito larval sampling methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo measure the impact of larval control using \u003cem\u003eBti\u003c/em\u003e, baseline surveys on mosquito breeding habitats and larvae were carried out one week before the application of \u003cem\u003eBti\u003c/em\u003e, key entomological indicators were measured on larval densities. Larval sampling continued every two weeks for ten months, starting from two to three days post \u003cem\u003eBti\u003c/em\u003e spraying. The larval monitoring was performed in selected sampling plots purposively chosen using a Global Position System coordinate, sampling points marked at every 100 meters alongside the marshlands in three line transects, middle and two ridges of the marshlands \u003cstrong\u003e(Figure 3).\u003c/strong\u003e The overview of the numbers of sampling plots is as following \u003cstrong\u003e(table 1):\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSampling was done using standard dippers (350ml) to make five or ten dips (depending on the type of habitats) in each water body, the presence that were marked as positive or absence marked as negative of mosquito larvae were recorded and categorized according to their development stage.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMosquito adult sampling methods\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIndoor mosquito collections were done for two successive nights using battery powered CDC miniature light traps and pyrethrum spray collection (PSC) to sample endophagic and endophilic vectors respectively. Female adult mosquitoes were collected in twenty randomly selected houses from five different sites adjacent to the marshlands, three sites (12 houses) in neighborhood of intervention area and two (Eight houses) in control area \u003cstrong\u003e(Figure 2).\u0026nbsp;\u003c/strong\u003eIdentification of mosquito species ad sprorozoite infection (methods used: morphological and PCR, and ELISA for detection of sporozoite infection)\u003c/p\u003e\n\u003cp\u003eThe sampled\u0026nbsp;adult mosquitoes were counted and identified\u0026nbsp;using morphological features such as wing patterns, size, abdomen markings, mesopleural and thoracic hairs as described in the Gillies and Coetzee identification keys (M.T. Gillies and M. Coetzee, 2020).\u0026nbsp;Each collected female anopheline mosquito sample was kept individually in a labeled\u0026nbsp;micro-centrifuge tube\u0026nbsp;with a lid for airtight locking\u0026nbsp;with a desiccant.\u003c/p\u003e\n\u003cp\u003eSiblings of the collected female \u003cem\u003eAn\u003c/em\u003e. \u003cem\u003egambiae\u0026nbsp;\u003c/em\u003es.l. were characterized using PCR technique based on DNA which utilizes a mixture of 20 base oligonucleotides primers that target the species nucleotide sequences in the ribosomal DNA (rDNA) intergenic spacers (IGS)\u0026nbsp;(Scott et al., 1993), after genomic DNA extraction from legs and wings using the\u0026nbsp;Cetyl Trimethyl Ammonium Bromide (CTAB)\u0026nbsp;based protocol\u0026nbsp;(de la Cruz-Ramos et al., 2019). To determine presence of a\u0026nbsp;circumsporozoite proteins (CSP),\u0026nbsp;ELISA tests was done on the head and thorax using the\u0026nbsp;CS microplate ELISA to detect \u003cem\u003eP. falciparum,\u003c/em\u003e Optical Density (OD) measured using spectrophotometer (Appawu et al., 2003). Blood-meal sources of all collected blood-fed female samples captured by PSC were analyzed using a direct ELISA, using antihost\u0026nbsp;Monoclonal antibodies\u0026nbsp;(IgG) conjugate against human,\u0026nbsp;cattle, goat, sheep, chicken\u0026nbsp;proteins, OD measured using spectrophotometer (Getachew et al., 2019).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe balance checks for study\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe balance check was done to assess the abundance and density of anopheles, and culicines mosquito larvae and pupae in the study sampling plots before the intervention. The initial density was also conducted on adult mosquitoes collected using CDC-LT and the Pyrethrum Spraying Collection methods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of malaria incidence\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCommunity health workers (CHWs) patients’ registers were used for monthly data collection of malaria cases from the contingent villages to the study area. Fifteen villages in proximity to the marshlands of the study area, aggregated into twelve nearby the intervention and three in the control area respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were recorded in Excel and transferred into statistical software, version R 4.0.2 for statistical analysis. In preliminary, descriptive analysis was performed to generate tables and curves. The intervention and control groups were constructed to visualize differences in the responses between the two groups. We used mean, median, and standard errors (SE) to present continuous variables and frequencies for categorical variables.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe performed a balance check using the T-test to compare means of treatment and control groups for independent variables at baseline (Round 0). Further, the difference analysis was calculated using regression analysis, adjusted with time, to evaluate the effect of larviciding on breeding habitats with anopheles and culicines mosquito larvae and pupae as well as the adult mosquitodensities. The evaluation of differences on malaria incidences between intervention and control sites, a non-parametric test was used, Mann Whitney test.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical consideration\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was presented to Rwanda Biomedical Centre, Division of Research, Innovation and Data Sciences for review and clearance and received approval Ref: No 225/RBC/2020. The importation and usage of \u003cem\u003eBti\u0026nbsp;\u003c/em\u003ewas authorized by the Ministry of Health, Department of Food and Drug Authority. \u0026nbsp;Before application of \u003cem\u003eBti\u003c/em\u003e and larval monitoring, verbal consent was obtained from local leaders, the head of the rice farmer cooperative, owners of houses used for adult collections and the entomology technicians involved in entomology monitoring.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eThe balance checks for study\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe balance checks on mosquito larvae and pupae using 131 plots as well as on adult mosquitoes using 40 houses-nights showed no difference between the treatment and control arms \u003cstrong\u003e(table 2)\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLarval habitat occupancy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt the end of the intervention (Round 20), the comparison of treatment and control blocs showed a statistical significant differences (p \u0026lt; 0.001) between treatment and control blocs with a decline overtime in the overall larval habitat occupancy \u003cstrong\u003e(Figure 4)\u003c/strong\u003e. In the experimental sites, the overall habitat occupancy of sampling plots was 16.1% for \u003cem\u003eAnopheles\u003c/em\u003e larvae with a decrease of 78.3% (P-Value \u0026lt;0.001) while it was 74.3% in control. The overall habitat occupancy of sampling plots for Culicines larvae was 11.6% in experimental sites with a reduction of 31.4% while was 16.9% in control (P-Value \u0026lt;0.001), pupal occupancy rate was 1.9% with a reduction of 69.2% in experimental sites while was 6% in control (P-Value \u0026lt;0.001) \u003cstrong\u003e(table 3).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMosquito larval density\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis of larval density showed that in all blocs of the experimental sites of the study, the treatment intervention significantly reduced the anophelines larval density by 98.7%, culicines larval density by 81.3% and pupal density by 75% \u003cstrong\u003e(table 5)\u003c/strong\u003e. \u0026nbsp;The anopheles larval density declined and kept lower in treatment than control arms while a rebound was observed from 10\u003csup\u003eth\u003c/sup\u003e rounds in control for culicines and pupal stages \u003cstrong\u003e(Figure 5).\u003c/strong\u003e This was due to the significant effects of time, treatment alone or in combination on results \u003cstrong\u003e(table 4).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdult mosquitoes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCDC-LT\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall, out of 14,387 adult mosquitoes collected over ten months in the two study sites, culicines spp. were dominant (85.9%, n =12,354) and anopheles species represented 14.1%. \u0026nbsp;Among \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes collected, \u003cem\u003eAn. gambiae s.l.\u003c/em\u003e was the most abundant (90.3%, n=1836) followed by \u003cem\u003eAn. ziemanni\u003c/em\u003e (5.8%, n=117), \u003cem\u003eAn. squamosus\u0026nbsp;\u003c/em\u003e(3%, n=60), \u003cem\u003eAn. maculipalpis\u003c/em\u003e (0.8%, n=17), and other \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes (0.15%, n=3). Out of the total mosquito collections, 74% (n=1510) of \u003cem\u003eAnopheles\u003c/em\u003e spp. and 55% (n=6796) of culicines spp were collected from the control arm \u003cstrong\u003e(table 6).\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnopheles arabiensis\u003c/em\u003e was found to be the predominant \u003cem\u003eAn. gambiae\u003c/em\u003e sibling species collected with CDC LT. For a total of 782 specimens of An. \u003cem\u003egambiae\u003c/em\u003e s.l. tested using\u0026nbsp;species-specific PCR,\u0026nbsp;405 (51.8%) were identified as \u003cem\u003eAn. arabiensis\u003c/em\u003e and 377 (48.2%) as \u003cem\u003eAn. gambiae\u003c/em\u003e sensu stricto.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eELISA assays to detect \u003cem\u003eP. falciparum\u003c/em\u003e CSP protein were performed on the head and thorax of 2,108 specimens of individual female Anopheles mosquitoes collected by both CDC LT (79.6%, n=1678) and PSC (20.4%, n=430) methods to ascertain the malaria parasite infection rates in the study sites.\u0026nbsp;\u003cem\u003eAnopheles gambiae s.l\u003c/em\u003e. (n=1,914) made up 90.8% of the total samples, \u003cem\u003eAn. ziemani\u003c/em\u003e (5.4%, n=114), \u003cem\u003eAn. squamosus\u003c/em\u003e (3.1%, n=65), \u003cem\u003eAn. maculipalpis\u003c/em\u003e (0.5%, n=10), \u003cem\u003eAn. rufipes\u003c/em\u003e (0.1%, n=3), \u003cem\u003eAn. coustani\u003c/em\u003e (0.05%, n=1), \u003cem\u003eAn. funestus\u003c/em\u003e (0.05%, n=1). All the samples were tested negative to Plasmodium infection\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe larviciding using Bti and sprayed with drones shows a significant impact on adult mosquito densities in villages neighboring the intervention sites \u003cstrong\u003e(Table 6)\u003c/strong\u003e. The total adult anopheles spp was significantly reduced by 79.9%, culicines spp by 44.14% and \u003cem\u003eAnopheles gambiae s.l.\u003c/em\u003e by 76.05% (p \u0026lt; 0.001). The significant effects of treatment and time alone were observed on \u003cem\u003eanopheles\u003c/em\u003e mosquitoes but not on culicines. The combination of the two variables didn\u0026rsquo;t have any significant effect either on anopheles nor on culicines mosquitoes \u003cstrong\u003e(Table 7).\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2 Pyrethrum Spraying Collection Method\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWith PSC method, out of 1,839 adult mosquitoes collected over ten months in the two study sites, culicines spp were representing 79.4% (n =1,460) while total anopheles mosquitoes were 21.6%. Among the catches of \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes, \u003cem\u003eAn. gambiae s.l.\u003c/em\u003e was the most dominant with 96.8% (n=367) followed by An. ziemanni (2.9%, n=11), \u003cem\u003eAn. squamosus\u0026nbsp;\u003c/em\u003e(0.3%, n=1). Per study arm, 73% (n=379) of \u003cem\u003eAnopheles\u003c/em\u003e spp. and 37% (n=536) of culicine mosquitoes were caught from the control arm.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnopheles arabiensis\u003c/em\u003e was found to be the predominant \u003cem\u003eAn. gambiae\u003c/em\u003e sibling specie collected. For a total of 362 specimens of An. \u003cem\u003egambiae\u003c/em\u003e s.l. with \u0026nbsp;species-specific PCR results,\u0026nbsp;295 (81.5%) were successfully identified as \u003cem\u003eAn. arabiensis\u003c/em\u003e and 67 (18.5%) as \u003cem\u003eAn. gambiae\u003c/em\u003e sensu stricto.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA total of 155 blood fed \u003cem\u003eAnopheles\u003c/em\u003e \u003cem\u003egambiae\u003c/em\u003e sensu lato collected from the experiment and control houses were tested by direct ELISA for blood-meal sources identification. The majority (69.7%) of An. \u003cem\u003egambiae\u003c/em\u003e s.l. had fed on bovine (n=108), human IgG was detected in 12.3% (n=19), remaining An. \u003cem\u003egambiae\u003c/em\u003e s.l. had fed on other vertebrate hosts, which were Goat (5.2%, n=8), Bovine and Goat (3.9, n=6), Human and Bovine (0.6, n=1), and unidentified host in 8.4% (n=13).\u003c/p\u003e\n\u003cp\u003eFollowing Bti application, the catches of adult anopheles mosquitoes were significantly reduced by 78.74% and by 79.8% for total Anopheles and \u003cem\u003eAnopheles gambiae\u003c/em\u003e sl respectively \u003cstrong\u003e(Table 8)\u003c/strong\u003e. \u0026nbsp;However, the collections of culicines spp. increased significantly by 10.12% (p \u0026lt; 0.001) in treatment arm with incremental increase from the 5\u003csup\u003eth\u003c/sup\u003e round and a decline trend in control arm \u003cstrong\u003e(Figure 7)\u003c/strong\u003e. The two variables of time and treatment alone or in combination didn\u0026rsquo;t have a significant effect on adult mosquitoes collected using PSC method, except the combined effects reported on culicines spp \u003cstrong\u003e(Table 9).\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings of this LSM trial performed in irrigated rice fields of sub-urban of Kigali City, Rwanda, using drone based technology showed a significant reduction (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) of mosquito habitant occupancies with a decline of 78.3%, 69.2% and 31.4% for anopheles, culicines larvae and pupae stages respectively. The mosquito larval density also declined significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with 98.7%, 75.0% and 81.3% for anopheles and culicine larvae and pupae respectively. The mean number of adult mosquitoes per trap and per night caught with CDC-LT decreased significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with reduction of 79.1% for total anophele\u003cem\u003es\u003c/em\u003e species, 44.1 for culicines and 76.05 for \u003cem\u003eAnopheles gambiae\u003c/em\u003e s.l. the primary malaria vector in study site. The mean number of mosquitoes caught per house and per night with PSC method also significantly declined (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to the control site for total anopheles and \u003cem\u003eAn.gambiae s.l\u003c/em\u003e. with respective reduction of 78.7% and 79.8%. \u003cb\u003eHowever, the culicine mosquitoes increased significantly by 10.1% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/b\u003e Malaria incidences reported by community health workers in contingent villages were higher in control than intervention sites (U\u0026thinsp;=\u0026thinsp;20, z=-2.268, p\u0026thinsp;=\u0026thinsp;0.023).\u003c/p\u003e \u003cp\u003eSimilarly, another previous larval source management trial conducted for six months in rice fields of Southern East of Rwanda, with Bti solely sprayed with simple knapsack sprayer pumps also proved significant control of mosquito habitat occupancies as well as the density of aquatic stages and adult anopheles mosquitoes collected using CDC-LT. This trial reported a complete interruption of pupal stage in treated arm from the 5th round of the 12 rounds of Bti application (Hakizimana et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Moreover, the beneficiary communities mainly the rice farmers demonstrated a high perception on Bti safety and acceptance of larviciding intervention (Ingabire et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Therefore, this study demonstrated the limitations of larviciding using simple knapsack in complex and large mosquito habitats such as the irrigated rice fields. The Bti sprayers reported the difficulties encountered during the Bti application mainly the muddy and slippery soils during rainy seasons, watering of rice plots mainly the first three months of rice farming cycle, and the coverage of upstream water dam for storage of irrigation water (hakizimana et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The above challenges were addressed during the current larviciding trial by prior mapping of potential mosquito breeding sites and the aerial spraying of Bti using drones instead of simple knapsacks. This trial yielded a high entomological impact compared to the previous trial using hand knapsack sprayer pumps.\u003c/p\u003e \u003cp\u003eThe moderate impact of larviciding with Bti (VectoBac WDG) was also documented by prior studies in complex mosquito breeding habitats such as flooded ecosystem in Gambia (Silas et al.2010), and irrigated rice fields (Fillinger et al., 2009). Another targeted larviciding trial with only treatment of the most productive anopheles breeding sites and systematic treatment of all potential mosquito breeding areas demonstrated similar reduction of female anopheles mosquitoes respectively by 61% and 70% (Damback et al., 2019). The larviciding trial with VectorMax\u0026reg; G conducted in Yaound\u0026eacute;, Cameroon found out an impact both on malaria vectors and culex mosquitoes with reduction of 69% and 36.6% in aquatic habitats and adult density inside houses for culex species, respectively (Talipouo et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The impact on other mosquito species such as \u003cem\u003eAedes\u003c/em\u003e spp and \u003cem\u003eCulex\u003c/em\u003e mosquitoes was also found to be limited in some settings (Dambach et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The timing of larviciding, exhaustive and accurate geo-locations and types of mosquito habitats were the primary hindrances to optimize the impact of LSM, and thus requiring the new technologies (Hardy et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e \u0026amp; \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The other limitations associated to the impact of larviciding are the accurate detection of water bodies potential to mosquito breeding areas, the human resettlements and nature of constructions. These are to-date sorted out by prior mapping of the study areas with drones and enabling then the improvement of the coverage of mosquito larval habitats with larviciding (Escobar et al., 2019).\u003c/p\u003e \u003cp\u003eThe recent trial of drones based larviciding carried out in Unguja island, Zanzibar, Tanzania in rice fields showed an improved entomological impact of more than 90% reduction of aquatic stages abundance and density of mosquitoes. This study demonstrated that Unmanned Aerial Vehicles (UAVs) improved the coverage of larviciding and can be used beyond the targeted sites as recommended by WHO for LSM intervention (WHO, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The UAVs technologies proved the effectiveness of controlling mosquito population over large and complex areas at low cost. They may also enhance the cost-effective control of malaria and other mosquito borne diseases and elimination efforts (Mukabana et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Another promising technology is based on high resolution images captured with drones which may also contribute to geo-locating at low costs the potential mosquito larval habitats. The latter are detected through the analysis of presence and type of aquatic vegetation (Stanton et al., 2019). Therefore, the required technical skills (Derua et al., 2019) and the more time for processing of images still the main hindrances for this innovation which guide to tackle directly the positive larval mosquito breeding habitats during larviciding operation (Stanton et al., 2019). The spatial intelligence system (SIS) for larviciding is another promising technology and based on mapping of mosquito breeding areas which was shown cheaper and more accurate than the conventional ground-based mapping method (Hardy et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe larviciding conducted in many mosquito habitats including the complex ecosystems, with improved coverage and appropriate larvicide product demonstrated a drastic impact on abundance and density of malaria vectors and other mosquito borne diseases. Nowadays, larviciding is a proven and viable intervention enabling to supplement the current core indoor vector control tools in targeted settings even in large and complex mosquito breeding habitats (Olalubi et al., 2016, Damback et al, 2019, Talipouo et al. 2022, Mukabana et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e., Mpofu et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eDespite the targeted study area was a complex ecosystem of irrigated rice fields with frequent flooded areas and man-made breeding sites, the Unmanned aerial vehicles (drones) contributed to operationalize the larviciding intervention which was guided by prior aerial maps of water bodies. The coverage of all geo-located potential breeding sites was effectively performed alongside the 20 rounds of larviciding operations. In comparison between the intervention and control site, the aquatic mosquito larval habitat occupancies and mosquito larvae density were significantly declined, as well as the adult anopheles collected using CDC-LT and PSC methods. The malaria incidence showed also a significant decline trend in intervention compared to the control site. The scaling up of larviciding using drone technologies for prior mapping of potential mosquito breeding sites and then spraying of larvicide proved its effectiveness not only in targeted sites as recommended by WHO but also in complex anopheles breeding habitats. These vector control technologies have to be integrated by malaria programs to enhance the gains in malaria control and elimination efforts. However, the low impact on culicine mosquitoes may affect the acceptance of LSM intervention by beneficiary communities. Further engagement of local communities are recommended and using appropriate formulations of larvicide for controlling culicines breeding habitats.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cem\u003eBti\u003c/em\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eBacillus thuringiensis\u003c/em\u003e var. \u003cem\u003eisraelensis\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCDC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCenters for Disease Control and Prevention\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCTAB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCetyl Trimethyl Ammonium Bromide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eELISA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEnzyme-Linked Immunosorbent Assay\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIRS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIndoor residual spraying\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eITU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational toxic units\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLLIN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLong-lasting insecticide treated net\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLSM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLarval source management\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMOH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMinistry of Health\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePolymerase chain reaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePyrethrum Spraying Collection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUAV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnmanned Aerial Vehicles\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWDG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWater dispersible granules\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was presented to Rwanda Biomedical Centre, Division of Research, Innovation and Data Sciences for review and clearance and received approval Ref: No 225/RBC/2020. The importation and usage of \u003cem\u003eBti\u0026nbsp;\u003c/em\u003ewas authorized by Rwanda Food and Drug Authority. \u0026nbsp;Before application of \u003cem\u003eBti\u003c/em\u003e and larval monitoring, verbal consent was obtained from local leaders, the head of the rice farmer cooperatives, owners of houses used for adult collections and the entomology technicians involved in entomology monitoring.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe acknowledgement is addressed to Society for Family Health (SFH) Rwanda for the donation of \u003cem\u003eBti\u0026nbsp;\u003c/em\u003eapplied during the experiments and to Charis UAS for drone based services for mapping and spraying of Bti with free charge costs. The financial support for entomology monitoring was provided by the Government of Rwanda through Rwanda Biomedical Center.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDM, EH, EK, CM, SM, AM, AMB and CMM conceived the preliminary study outlines. DM, SM, CM, EK, ERU and EH developed, revised and approved the study protocol. DM, EN, AM, XM, ERU, EH coordinated the laboratory and field works. EH, DM, and ER carried out the data cleaning, analysis and interpretation. DM, ER and EH drafted the manuscript. All authors contributed to the reading, critical review and approved of the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors sincerely thank the leaders of Kabuye study site and particularly the executive Secretary of the administrative sector, the head of health center of Kabuye, the cooperative of rice famers of Kabuye; the community health workers, the entomology technicians and the lay community members for their kind collaboration.\u0026nbsp;\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAnimut A and Negash Y. Dry season occurrence of Anopheles mosquitoes and implications in Jabi Tehnan District, West Gojjam Zone, Ethiopia. Malar J 2018, 17:1. https://doi.org/10.1186/s12936-018-2599-4\u003c/li\u003e\n\u003cli\u003eAppawu MA, Bosompem KM, Dadzie S, McKakpo U S, Anim-Baidoo I, Dykstra E et al. 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Larval source management: A supplementary measure for malaria vector control, an operational manual\u003cstrong\u003e.\u003c/strong\u003e Geneva-Switzerland. World Health Organization, 2013, p.116. \u003c/li\u003e\n\u003cli\u003eCarrasco-Escobar G, Manrique E, Ruiz-Cabrejos J, Saavedra M, Alava F, Bickersmith S, et al\u003cstrong\u003e.\u003c/strong\u003e PLoS Negl Trop Dis, 2019, \u003cstrong\u003e13\u003c/strong\u003e (1): e0007105. https://doi.org/10.1371/journal. e0007105\u003c/li\u003e\n\u003cli\u003eDambach P, B\u0026auml;rnighausen T, Yadouleton A, Dambach M, Traor\u0026eacute; I, Korir P, \u003cem\u003eet\u003c/em\u003e al. Is biological larviciding against malaria a starting point for integrated multi-disease control? Observations from a cluster randomized trial in rural Burkina Faso. PLoS ONE, 2021, \u003cstrong\u003e16\u003c/strong\u003e (6): e0253597. https://doi.org/10.1371/journal.pone.0253597\u003c/li\u003e\n\u003cli\u003eDambach P, B\u0026auml;rnighausen T, Traor\u0026eacute; I, Ouedraogo S, Si\u0026eacute; A, Sauerborn R\u003cem\u003e et\u003c/em\u003e al. Reduction of malaria vector mosquitoes in a large‑scale intervention trial in rural Burkina Faso using \u003cem\u003eBti \u003c/em\u003ebased larval source management. \u003cem\u003eMalar J,\u003c/em\u003e 2019, 18:311\u003cem\u003e. \u003c/em\u003ehttps://doi.org/10.1186/s12936-019-2951-3\u003c/li\u003e\n\u003cli\u003eHardy A, Makame M, Cross D, Majambere S, Msellem M. Using low-cost drones to map malaria vector habitats. \u003cem\u003eParasit Vectors\u003c/em\u003e, 2017, \u003cstrong\u003e10\u003c/strong\u003e:29 DOI 10.1186/s13071-017-1973-3. \u003c/li\u003e\n\u003cli\u003eHardy A, Haji K, Abbas F, Hassan J, Ali A, Yussuf Y \u003cem\u003eet \u003c/em\u003eal. Cost and quality of operational larviciding using drones and smartphone technology. \u003cem\u003eMalar J\u003c/em\u003e, 2023, \u003cem\u003e22\u003c/em\u003e:286 https://doi.org/10.1186/s12936-023-04713-0 \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eNumber of mosquito larval sampling plots per intervention bloc and study arms, Gasabo, Kigali-City, Rwanda.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"342\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.70967741935484%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy sites\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.75366568914956%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eBloc number\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.5366568914956%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of sampling plots\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.70967741935484%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eExperimental site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.75366568914956%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.5366568914956%\" valign=\"bottom\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.75598086124402%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.24401913875598%\" valign=\"bottom\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.75598086124402%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.24401913875598%\" valign=\"bottom\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.75598086124402%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.24401913875598%\" valign=\"bottom\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.70967741935484%\" valign=\"bottom\"\u003e\n \u003cp\u003eControl site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.75366568914956%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.5366568914956%\" valign=\"bottom\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.70967741935484%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.75366568914956%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.5366568914956%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e230\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: \u0026nbsp;Results of balance checks on aquatic stages and adult mosquitoes between treatment and control arms\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"676\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.225997045790251%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75923190546529%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.032496307237814%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of plots/houses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.623338257016249%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SE) Control\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.42983751846381%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SE) Treatment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.771048744460856%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SE) Diff\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.15805022156573%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.225997045790251%\" rowspan=\"3\"\u003e\n \u003cp\u003eDipping (larvae)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75923190546529%\"\u003e\n \u003cp\u003eAnopheles larvae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.032496307237814%\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.623338257016249%\"\u003e\n \u003cp\u003e3.53 (1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.42983751846381%\"\u003e\n \u003cp\u003e3.008 (0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.771048744460856%\"\u003e\n \u003cp\u003e0.52 (2.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.15805022156573%\"\u003e\n \u003cp\u003e\u0026gt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.13144758735441%\"\u003e\n \u003cp\u003eCulicines larvae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.806988352745424%\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.472545757071547%\"\u003e\n \u003cp\u003e9.8 (2.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.633943427620633%\"\u003e\n \u003cp\u003e5.23 (1.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.638935108153078%\"\u003e\n \u003cp\u003e4.56 (5.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.316139767054908%\"\u003e\n \u003cp\u003e\u0026gt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.13144758735441%\"\u003e\n \u003cp\u003ePupae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.806988352745424%\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.472545757071547%\"\u003e\n \u003cp\u003e1.73 (0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.633943427620633%\"\u003e\n \u003cp\u003e1.21 (0.342)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.638935108153078%\"\u003e\n \u003cp\u003e0.526 (.975)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.316139767054908%\"\u003e\n \u003cp\u003e\u0026gt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.225997045790251%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003ePSC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75923190546529%\"\u003e\n \u003cp\u003eAnopheles sp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.032496307237814%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.623338257016249%\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.42983751846381%\"\u003e\n \u003cp\u003e0.54 (0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.771048744460856%\"\u003e\n \u003cp\u003e-0.54 (0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.15805022156573%\"\u003e\n \u003cp\u003e\u0026gt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.13144758735441%\"\u003e\n \u003cp\u003eCulicines sp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.806988352745424%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.472545757071547%\"\u003e\n \u003cp\u003e2.43(0.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.633943427620633%\"\u003e\n \u003cp\u003e1.54 (0.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.638935108153078%\"\u003e\n \u003cp\u003e0.895 (0.906)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.316139767054908%\"\u003e\n \u003cp\u003e\u0026gt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.225997045790251%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eCDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75923190546529%\"\u003e\n \u003cp\u003eAnopheles sp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.032496307237814%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.623338257016249%\"\u003e\n \u003cp\u003e1.56 (0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.42983751846381%\"\u003e\n \u003cp\u003e2.21 (0.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.771048744460856%\"\u003e\n \u003cp\u003e1.95 (0.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.15805022156573%\"\u003e\n \u003cp\u003e\u0026gt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.13144758735441%\"\u003e\n \u003cp\u003eCulicines sp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.806988352745424%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.472545757071547%\"\u003e\n \u003cp\u003e34.06 (9.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.633943427620633%\"\u003e\n \u003cp\u003e13.25 (2.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.638935108153078%\"\u003e\n \u003cp\u003e21.57 (4.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.316139767054908%\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eMean proportion habitat occupancy of late instars L3+L4 of anopheles, culicines larvae and pupae in control and treatment arms during the 20 rounds of drones-based application of bio-larvicide (Bti), Rwanda. The \u0026ldquo;*\u0026rdquo; explains the statistical differences at 95% of confidence interval.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"628\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.063694267515924%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMosquito larval species\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.28025477707006%\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl arm (proportion of habitat occupancy in %: n=817)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.726114649681527%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment arm (proportion of habitat occupancy in %: n=3080)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReduction %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.713375796178344%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.063694267515924%\"\u003e\n \u003cp\u003e\u003cem\u003eAnopheles\u0026nbsp;\u003c/em\u003elarvae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.28025477707006%\"\u003e\n \u003cp\u003e74.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.726114649681527%\"\u003e\n \u003cp\u003e16.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\" valign=\"bottom\"\u003e\n \u003cp\u003e78.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.713375796178344%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.063694267515924%\"\u003e\n \u003cp\u003e\u003cem\u003eCulicines larvae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.28025477707006%\"\u003e\n \u003cp\u003e16.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.726114649681527%\"\u003e\n \u003cp\u003e11.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\" valign=\"bottom\"\u003e\n \u003cp\u003e31.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.713375796178344%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.063694267515924%\"\u003e\n \u003cp\u003e\u003cem\u003ePupae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.28025477707006%\"\u003e\n \u003cp\u003e6.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.726114649681527%\"\u003e\n \u003cp\u003e1.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\" valign=\"bottom\"\u003e\n \u003cp\u003e69.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.713375796178344%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eEffects of treatment and time on anopheles, culicines larvae and pupal stages\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"399\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e\u003cstrong\u003e[95% conf. Interval]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"61.152882205513784%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnopheles larval\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-0.25***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e[-0.32; -0.18]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-0.43***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e[-0.48; -0.37]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime*Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e0.24***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e[0.17;0.31]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCullicines larval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-0.70***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e[-0.85; -0.55]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-0.90***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e[-1.01; -0.78]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime*Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e0.70***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e[0.55;0.86]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePupa larval\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-0.22***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e[-0.25; -0.19]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-0.24***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e[-0.26; -0.22]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime*Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e0.22***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e[0.19;0.25]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003eMean number per dip (density) of late instars L3+L4 of anopheles, culicines larvae and pupae in control and treatment arms during the 20 rounds of drones-based application of bio-larvicide (Bti), in Rwanda. The \u0026ldquo;*\u0026rdquo; explains the statistical differences at 95% of confidence interval.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"628\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.477707006369428%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMosquito larval species\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.866242038216562%\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl arm (Adjusted mean larvae per dip)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.726114649681527%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment arm (Adjusted mean larvae per dip)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReduction %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.713375796178344%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.477707006369428%\"\u003e\n \u003cp\u003e\u003cem\u003eAnopheles\u0026nbsp;\u003c/em\u003elarvae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.866242038216562%\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.726114649681527%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\" valign=\"bottom\"\u003e\n \u003cp\u003e98.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.713375796178344%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.477707006369428%\"\u003e\n \u003cp\u003e\u003cem\u003eCulicines larvae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.866242038216562%\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.726114649681527%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\" valign=\"bottom\"\u003e\n \u003cp\u003e81.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.713375796178344%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.477707006369428%\"\u003e\n \u003cp\u003e\u003cem\u003ePupae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.866242038216562%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.726114649681527%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.21656050955414%\" valign=\"bottom\"\u003e\n \u003cp\u003e75.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.713375796178344%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6.\u0026nbsp;\u003c/strong\u003eMean number of adult mosquitoes per trap and per night collected using CDC-Light trap in nearby villages of treatment (n=480) and control arms (n=320), during the 20 rounds of drones-based application of bio-larvicide (Bti), Rwanda. The \u0026ldquo;*\u0026rdquo; explains the statistical differences at 95% of confidence interval.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"574\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.041811846689896%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003cstrong\u003eMosquito species\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37630662020906%\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl arm: Mean+SE \u0026nbsp; \u0026nbsp; (n=320)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.034843205574912%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment arm: Mean+SE (n=480)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.550522648083625%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted mean difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.89198606271777%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eReduction in %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.104529616724738%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.041811846689896%\"\u003e\n \u003cp\u003eTota\u003cem\u003el Anopheles\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37630662020906%\"\u003e\n \u003cp\u003e4.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.034843205574912%\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.550522648083625%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.66 (0.296)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.89198606271777%\" valign=\"bottom\"\u003e\n \u003cp\u003e79.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.104529616724738%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.041811846689896%\"\u003e\n \u003cp\u003e\u003cem\u003eCulicines spp\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37630662020906%\"\u003e\n \u003cp\u003e19.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.034843205574912%\"\u003e\n \u003cp\u003e10.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.550522648083625%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;8.62 (0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.89198606271777%\" valign=\"bottom\"\u003e\n \u003cp\u003e44.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.104529616724738%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.041811846689896%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eAnopheles gambiae s.l.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37630662020906%\"\u003e\n \u003cp\u003e4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.034843205574912%\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.550522648083625%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.08 (0.258)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.89198606271777%\" valign=\"bottom\"\u003e\n \u003cp\u003e76.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.104529616724738%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7.\u0026nbsp;\u003c/strong\u003eEffect of treatment and time alone or in combination on anopheles, culicines adult mosquitoes collected using CDC-LT method.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"399\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e\u003cstrong\u003e[95% conf. Interval]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnopheles spp\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-4.15***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-5.23; -3.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-0.13***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-0.2; -0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime*Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-0.02;0.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eA.gambiae s.l.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-3.51***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-4.45; -2.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-0.12***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-0.18; -0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime*Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-0.02;0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCulicines spp\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-10.29*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-18.38; -2.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-0.43;0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime*Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-0.21;0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8:\u003c/strong\u003e Mean number of adult mosquitoes per house and per night collected using Pyrethrum spraying catch (PSC) in nearby villages of treatment (n=480) and control arms (n=320), during the 20 rounds of drones-based application of bio-larvicide (Bti), Rwanda. \u0026nbsp;The \u0026ldquo;*\u0026rdquo; explains the statistical differences at 95% of confidence interval.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"613\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.491027732463294%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMosquito species\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597063621533444%\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl arm: Mean+SE ( \u0026nbsp;n=320)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.22838499184339%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment arm: Mean+SE ( n=480)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.986949429037521%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted mean difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.908646003262643%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eReduction in %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.787928221859707%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.491027732463294%\"\u003e\n \u003cp\u003e\u003cem\u003eTotal\u0026nbsp;\u003c/em\u003eAnopheles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597063621533444%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.22838499184339%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.986949429037521%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.68 (0.074)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.908646003262643%\" valign=\"bottom\"\u003e\n \u003cp\u003e78.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.787928221859707%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.491027732463294%\"\u003e\n \u003cp\u003e\u003cem\u003eCulicines spp\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597063621533444%\" valign=\"top\"\u003e\n \u003cp\u003e1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.22838499184339%\" valign=\"top\"\u003e\n \u003cp\u003e1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.986949429037521%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.17 (0.167)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.908646003262643%\" valign=\"bottom\"\u003e\n \u003cp\u003e-10.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.787928221859707%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.491027732463294%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eAnopheles gambiae s.l.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.597063621533444%\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.22838499184339%\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.986949429037521%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.66 (0.073)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.908646003262643%\" valign=\"bottom\"\u003e\n \u003cp\u003e79.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.787928221859707%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 9.\u0026nbsp;\u003c/strong\u003eEffect of treatment and time alone or in combination on anopheles, culicines adult mosquitoes collected using PSC method.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"399\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e\u003cstrong\u003e[95% conf. Interval]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnopheles spp\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-0.79;0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-0.02;0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime*Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-0.05;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCulicines spp\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-3.76;1.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(-0.06;0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.34586466165413%\"\u003e\n \u003cp\u003eTime*Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.80701754385965%\"\u003e\n \u003cp\u003e0.11***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.847117794486216%\"\u003e\n \u003cp\u003e(0.06;0.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Malaria, mosquitoes, drones, rice fields, Bacillus thuringiensis, Rwanda","lastPublishedDoi":"10.21203/rs.3.rs-4257583/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4257583/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe core vector control tools used to prevent malaria infection are currently long-lasting insecticide treated nets (LLINs), and the indoor residual spraying (IRS). These indoor methods are threatened by insecticide resistance and behavioral adaptation by malaria vectors. Thus, for effective interruption of malaria transmission, there is a need to experiment further vector control interventions and technologies to address the above vector control challenges. Larviciding using drones-based technologies were experimented as innovative tools that could supplement existing indoor base interventions to control malaria.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA non-randomized larviciding trial with control was carried out in irrigated rice fields, in sub-urban of Kigali City, Rwanda. The potential mosquito larval habitats in study sites were prior mapped and subsequently sprayed using multirotor drones. The application of Bti (Vectobac® WDG) followed by the entomological surveys were performed every two weeks for ten months’ period. The sampling of mosquito larvae used the dipping method while adult mosquitoes were collected using CDC miniature light traps (CDC-LT) and pyrethrum spraying collection (PSC) methods, respectively. The malaria cases were routinely collected through community health workers in contingent villages to the study sites.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe abundance of total mosquito larvae, \u003cem\u003eAnopheles\u003c/em\u003e-specific larvae and pupae declined by 68.1%, 74.6% and 99.6% respectively. The larval density was reduced by 93.3% for total larvae, 95.3% for the \u003cem\u003eAnopheles\u003c/em\u003elarvae and 61.9% for pupae. The total adult mosquitoes and An.\u003cem\u003e gambiae\u003c/em\u003e s.l collected using CDC-Light trap declined by 60.6% and 80% respectively. Malaria incidence also declined significantly between intervention and control sites (U=20, z=-2.268, p=0.023)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe larviciding using drone technology implemented in Rwanda demonstrated a substantial reduction in abundance and density of mosquito larvae and, concomitant decline in adult mosquito populations and malaria incidence in contingent villages to the treatment sites. The impact of PSC method on adult mosquitoes was not significant on adult culicines spp. The scaling up of larval source management (LSM) has to be integrated in malaria programs in targeted areas of malaria transmission in order to enhance the gains in malaria control.\u003c/p\u003e","manuscriptTitle":"The impact of Bacillus thuringiensis var israelensis (Bti) larvicide sprayed using drones for bio-control of malaria vectors in rice fields of Kigali Sub-Urban, Rwanda","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-19 18:43:20","doi":"10.21203/rs.3.rs-4257583/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-24T22:05:51+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-04T08:23:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"103084652392040924670875422522919457846","date":"2024-05-13T08:00:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"52dd0ee2-0e7b-4da3-9c26-6e52f969ad02","date":"2024-05-08T07:10:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-06T14:13:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"c0b608dd-5c97-41e8-9795-9eecd3f5ab87","date":"2024-04-18T07:47:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-17T16:55:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-12T13:40:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-12T13:40:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Malaria Journal","date":"2024-04-12T11:50:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"03c50067-5f02-478f-ad9a-8760c60d034d","owner":[],"postedDate":"April 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-09-23T16:06:48+00:00","versionOfRecord":{"articleIdentity":"rs-4257583","link":"https://doi.org/10.1186/s12936-024-05104-9","journal":{"identity":"malaria-journal","isVorOnly":false,"title":"Malaria Journal"},"publishedOn":"2024-09-17 15:58:12","publishedOnDateReadable":"September 17th, 2024"},"versionCreatedAt":"2024-04-19 18:43:20","video":"","vorDoi":"10.1186/s12936-024-05104-9","vorDoiUrl":"https://doi.org/10.1186/s12936-024-05104-9","workflowStages":[]},"version":"v1","identity":"rs-4257583","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4257583","identity":"rs-4257583","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}