Integrating 3D video tracking with the standard WHO tunnel assay — a proof-of-concept to support improving insecticide-treated nets for mosquito control

Integrating 3D video tracking with the standard WHO tunnel assay — a proof-of-concept to support improving insecticide-treated nets for mosquito control | 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 Short Report Integrating 3D video tracking with the standard WHO tunnel assay — a proof-of-concept to support improving insecticide-treated nets for mosquito control Beatrice H. Bredt, Mathurin Fatou, Aidi G. Lugenge, Dismas S. Kamande, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8720695/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract The World Health Organization (WHO) tunnel test is a standardised laboratory method for characterising the biological availability and potency of active ingredients on the surface of an insecticide-treated bed net (ITN) against host-seeking mosquitoes. However, the assay provides only endpoint measurements – the proportions of mosquitoes that are killed and blood-fed – and therefore offers no insight into how mosquitoes interact with the ITN. Therefore, complementary behavioural data could reveal, for example, the extent to which mosquitoes engage with the net – explaining differences in endpoint outcomes – or indicate the minimum duration required for the assay, thereby improving throughput. For capturing mosquito behaviour in detail, automated three-dimensional (3D) video tracking offers a powerful approach. Here, we present a proof-of-concept study combining the standard WHO tunnel assay with Trackit3D, a versatile tracking system, in a laboratory in Tanzania where tunnel assays are routinely conducted. The system tracked multiple mosquitoes simultaneously as they were attracted to a rabbit, despite typical fluctuations in power and lighting. The ability to obtain high-resolution trajectories within the WHO tunnel assay provides new opportunities to enhance the behavioural evaluation of vector control tools and to strengthen the interpretability and utility of the WHO tunnel assay. Mosquito behaviour Flight trajectory analysis Behavioural bioassays Host-seeking behaviour Anopheles mosquitoes Figures Figure 1 Figure 2 Figure 3 Introduction Mosquitoes are the most significant vectors of human pathogens. They transmit a wide array of parasites and viruses, causing diseases such as malaria, filariasis, dengue, yellow fever, chikungunya or Zika. Among these, Anopheles mosquitoes, the vectors of malaria, are of particular global health importance, with an estimated 282 million malaria cases worldwide ( 1 , 2 ). A cornerstone of malaria vector control is the deployment of insecticide-treated nets (ITNs). Beyond providing personal protection from infective mosquito bites, the insecticide treatment confers community-level protection by killing mosquitoes and thereby reducing malaria transmission. Since 2000, the mass distribution of ITNs has contributed substantially to the global decline in malaria incidence ( 3 ). However, since 2015, progress has levelled off as coverage of vector control and antimalarial treatment has stagnated, a situation worsened by the rapid emergence and spread of pyrethroid resistance in mosquito populations ( 2 ) . To address growing pyrethroid resistance in Anopheles vectors, dual-active-ingredient ITNs – combining a pyrethroid with other active ingredients – have been developed and show greater epidemiological impact than pyrethroid-only nets ( 4 , 5 ). However, for proactively slowing resistance resurgence of currently effective interventions, the vector-control toolbox has to be continuously expanded with new insecticides having different modes of action than the existing ones. The development of ITNs with new insecticides requires bioassays that characterise their modes of action, which may elicit diverse behavioural responses in mosquitoes. In the early development phase, the WHO tunnel test is the standard laboratory assay for assessing the biological availability and potency of active ingredients on ITNs ( 6 ). However, the test provides only endpoint measurements – the proportions of mosquitoes killed and blood-fed – and therefore offers no insight into how mosquitoes interact with the net. Complementary behavioural data could reveal the extent to which mosquitoes engage with the ITN, helping to explain differences in endpoint outcomes and improve the utility of the tunnel assay. For capturing mosquito behaviour in detail, automated three-dimensional (3D) video tracking offers a powerful approach ( 7 ), and it has shown how mosquitoes interact with ITNs in modified set-ups ( 8 – 10 ). Here, we present a proof-of-concept study combining a standard WHO tunnel assay that uses a rabbit as a bait with ‘Trackit3D’, a versatile automated tracking system, in a laboratory in Tanzania where tunnel assays are routinely conducted. Main text Experimental set-up We conducted the proof-of-concept study in a test laboratory of the Ifakara Health Institute (IHI) in Bagamoyo, Tanzania (6°26′ S, 38°53′ E). We combined a standardised WHO tunnel assay with a 3D video tracking system to record flight trajectories of mosquitoes negotiating the holes of an untreated net while approaching a rabbit at one end of the tunnel as per the original protocol ( 6 ). The tunnel we used was custom-made to improve video tracking and easy transportation. The side panels were laser-cut from plexiglas and then plugged together (Fig. 1 ; Supplementary information S1) like the cages described in Maire et al., 2025 ( 11 ). This makes the tunnel very easy to transport, as it can be folded tightly together. The front panel was made of transparent Perspex, while the other sides were opaque to provide a homogeneously lit background for the video tracking. For 3D video tracking, we used ‘Trackit3D’, an automated system for recording insect flight trajectories, originally developed by Scitracks GmbH (Bertschikon, Switzerland) and now owned by Swiss TPH. The software was installed on a laptop equipped with an 11th Generation Intel® Core™ i7-1185G7 processor (3 GHz) and 32 GB RAM. We mounted two acA2040-90umNIR USB 3.0 digital cameras (Basler AG, Ahrensburg, Germany), each fitted with a Fujinon DV3.4×3.8SA-SA1 lens (Fujifilm Holdings K.K., Tokyo, Japan) and a MidOpt BP850 near-infrared (NIR) band-pass filter (Midwest Optical Systems, Palatine, IL, USA), on tripods and recorded flight trajectories at 4 MP resolution and 50 fps. To prevent camera desynchronisation during short power outages, we connected the cameras to an APC uninterruptible power supply (Schneider Electric, West Kingston, RI, USA). Other equipment was powered directly from standard outlets, as brief interruptions did not affect performance. Tracking occasionally stopped for negligible pauses (< 1 s) due to insufficient lighting but resumed automatically once illumination was restored. Illumination was provided by 10 850 nm NIR GU10 bulbs (ALLNET GmbH, Germering, Germany) fitted either in FLOTTILJ desk lamp sockets (IKEA AG, Spreitenbach, Switzerland) or into Eurolite GU10 sockets with a 1.8 m cable and integrated toggle switch, allowing flexible placement around the tunnel (Fig. 1 ). Experimental procedure In a first step, we tracked female Aedes aegypti (Kingani strain, in colony since 2018) in the tunnel without a bait and an untreated nine-holed piece of netting inserted in the response chamber (N in Fig. 1 ). This procedure allowed us to assess the tracking system’s initial performance, optimise the placement of the different elements of the set-up, and adjust tracking parameters. We chose Ae. aegypti because they are day-active, allowing calibration under daylight conditions. For each of the 18 calibration runs, we released 10 laboratory-reared adult females into the tunnel and tracked them for 10 min under ambient conditions (28 ± 5°C; 71 ± 10% relative humidity). In a next step, we followed the WHO tunnel test protocol ( 6 ). We expanded the set-up used in the first phase by adding a cage containing a rabbit (owned and breed by IHI Bagamoyo, in colony since 2012) as a bait (Fig. 1 B). To minimise movement and provide a comfortable, burrow-like environment that encouraged a natural posture, we placed the rabbit inside a smaller tunnel, however the rabbit was not given anaesthesia for the experiments. The animal’s head was shielded from light, while its hindquarters remained behind mesh, allowing mosquitoes to land and feed. In addition, we shaved the rabbit’s fur to facilitate mosquito feeding. We released 50 lab-reared, nulliparous females of either Anopheles gambiae s.s. (Ifakara strain, in colony since 1996) or Anopheles arabiensis (Kingani strain, in colony since 2006) into the tunnel and tracked host-seeking behaviour for 12 h in the dark in accordance with the mosquitoes’ circadian rhythm. As in the first phase, we cross-sectionally positioned an untreated piece of netting with nine holes in the middle of the response section, which mosquitoes had to negotiate to reach the rabbit. In total 6 replicates were conducted per strain, and in total 300 An. gambiae and 300 An. arabiensis were exposed to a rabbit bait in the tunnel test. All mosquito strains were established from locally collected mosquitoes and reared in the insectary of IHI Bagamoyo. After the experiment the rabbits are generally not euthanized but they are under veterinary care. Any sick rabbits are euthanized by the vet. Results The video-tracking system successfully reconstructed mosquito flight trajectories within the WHO tunnel assay under both unbaited (with Aedes ) and baited (with Anopheles ) conditions (Figure 2). Figure 2A illustrates representative 3D flight paths of 10 Ae. aegypti females in the absence of a rabbit. Although there was no bait, the experimenters were in the room, breathing CO2 into the tunnel, elicit host-seeking behaviour. When 50 mosquitoes were tracked for 12 h, the resulting plot became saturated with trajectories; therefore, Figure 2B presents a 1 h subset of the full 12 h recording for clarity. 11 out of the 12 measurements could be used for the analysis as one tracking night with 50 An. gambiae had to be excluded, due to tracking errors. The set-up combining Trackit3D with the standardised WHO tunnel assay tracked multiple mosquitoes simultaneously as they flew within the response chamber and moved through the netting holes into the collection chamber containing the rabbit. The tracking system was optimised for the area around the net, where both the quality and quantity of trajectories were highest. If another part of the arena would be the focus area for tracking, such as the rabbit, the system may be adapted accordingly. Adding an additional camera on the opposite side of the arena would reduce blind spots and mitigate the problem of mosquitoes flying behind the rabbit and becoming invisible to the front-facing cameras. The system demonstrated stable performance despite repeated short power cuts and suboptimal lighting conditions. The flexibility and portability of both the video-tracking system and the tunnel design were critical to maintaining functionality. To our knowledge, this is the first study to demonstrate a system capable of recording mosquito flight trajectories within a standardised WHO tunnel assay over a continuous 12 h period. The recordings allowed us to quantify the time mosquitoes spent in different sections of the tunnel, particularly at the net, the response and collection chamber with the rabbit, and to visualise distinct behavioural patterns such as approaching, contacting or resting at the net or the bait. Figure 3 shows the spatial and temporal distribution of mosquito activity over the 12 h observation period and illustrating how long mosquitoes remained in each zone within the tunnel. On average, they had contact with the rabbit 173,419 times, while they approached and touched the net only 12,447 times. A previous study tracked mosquito behaviour for 10 min in a modified WHO tunnel assay using a membrane feeder as an artificial host (8). Larger room assays mimicking experimental hut studies have also been conducted, recording mosquito interactions with ITNs while a human volunteer lay under the net, using two-dimensional video tracking for 2 h (12). In our study, extending tracking to 12 h showed that mosquitoes remained active even towards the end of the assay, indicating that they sustain activity around untreated nets for prolonged periods. Whether assays with ITNs should also be run for such extended durations, or whether shorter periods would suffice to increase throughput, remains to be further investigated. Future studies could use this system to evaluate ITNs across a broader range of settings and mosquito species. They could also investigate how mosquito behaviour varies in response to different hosts, both natural and artificial. Understanding mosquito behaviour within the WHO tunnel assay may prove valuable for interpreting assay outcomes, as video tracking can bridge the gap between standardised endpoint measurements and the underlying behavioural interactions with ITNs. Such insights would provide a more nuanced understanding of mosquito–net interactions and support the refinement of assays for behavioural evaluation. Conclusion Our results demonstrate that Trackit3D, used in combination with the foldable plexiglas tunnel, can effectively capture mosquito behaviour within the standardised WHO tunnel assay when an animal bait, such as a rabbit, is present. The ability to generate high-resolution flight trajectories within this assay opens new opportunities to strengthen the behavioural evaluation of vector control tools and to improve the interpretability and utility of the WHO tunnel test. This proof-of-concept therefore provides a foundation for larger-scale behavioural studies and supports the development of innovative approaches for assessing vector control interventions. Limitations Nonetheless, some limitations remain. The system occasionally lost track of individual mosquitoes, for example when they flew behind the rabbit or when flight paths overlapped. Reliable re-identification across repeated entry and exit events also remains a technical challenge for long-term tracking of individual mosquitoes. Emerging neural-network-based approaches ( 13 ) may help address this by improving object recognition and overall tracking accuracy. Addressing these issues through improved algorithms for object persistence, more efficient illumination and portable energy solutions will enhance future applications. Declarations Ethics approval and consent to participate Ethical approval was obtained from the Ifakara Health Institute Institutional Review Board (IHI/IRB/No: 19–2023) and the National Health Research Ethics Review Committee (NatHREC). In addition, animal welfare regulations are also covered under GLP. The work was done only in Tanzania within these regulations and all required ethical certificates were obtained. Rabbits were not euthanised after each trial; however, if animals became sick, humane euthanasia was performed by a licensed veterinarian, with animals first anaesthetised using ketamine–xylazine (or equivalent agents) and subsequently given an overdose of a barbiturate, in accordance with national regulations and internationally recognised animal welfare guidelines. Consent for publication All authors have approved the manuscript and agree with its submission BMC Research Notes. Availability of data and materials The datasets generated, used and 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. The tracking software Trackit3D is owned by SwissTPH. Funding This study did not receive any specific funding from public, commercial or not-for-profit funding agencies. Authors' contributions BB: Design of the study, conducting the experiments, analysing tracking data, writing manuscript, MF: Design of the study, reviewing manuscript, AL and DK: conducting the experiments, reviewing manuscript, NL: designing dismountable plexiglas tunnel, conducting the experiments, reviewing manuscript, SM: Experiment supervision, reviewing manuscript, PM: Design of the study, Experiment supervision, reviewing manuscript. All authors read and approved the final manuscript. Acknowledgements We thank all laboratory technicians for their invaluable support during the experimental set-up and laboratory work. We are grateful to the Ifakara Health Institute, Bagamoyo branch, for providing access to their facilities and enabling us to conduct this proof-of-concept study. We extend our special thanks to Jason Moore for his generous assistance in sourcing equipment and ensuring that we had everything required for the work. We thank Dr. Richard Newton from the Biozentrum Research Instrumentation Facility for his support and assistance in designing and fabrication of the dismountable tunnel system. Calculations were performed at sciCORE (http://scicore.unibas.ch/) scientific computing center at University of Basel. References Schneider CA, Calvo EA-O, Peterson KA-O, Arboviruses. How Saliva Impacts the Journey from Vector to. Mol Sci. 2021;22:1422–0067. (Electronic)). World Health Organization. World Malaria Report 2025. Geneva: World Health Organisiaiton; 2025. Bhatt S, Weiss DJ, Cameron E, Bisanzio D, Mappin B, Dalrymple U, et al. The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature. 2015;526(7572):207–11. Mosha JF, Kulkarni MA, Lukole E, Matowo NS, Pitt C, Messenger LA, et al. Effectiveness and cost-effectiveness against malaria of three types of dual-active-ingredient long-lasting insecticidal nets (LLINs) compared with pyrethroid-only LLINs in Tanzania: a four-arm, cluster-randomised trial. Lancet. 2022;399(10331):1227–41. Accrombessi M, Cook J, Dangbenon E, Yovogan B, Akpovi H, Sovi A, et al. Efficacy of pyriproxyfen-pyrethroid long-lasting insecticidal nets (LLINs) and chlorfenapyr-pyrethroid LLINs compared with pyrethroid-only LLINs for malaria control in Benin: a cluster-randomised, superiority trial. Lancet. 2023;401(10375):435–46. WHO Prequalification of Vector Control Products. Bioassay methods for insecticide-treated nets: tunnel test. Implementation guidance World Health Organisation; 2023. Bredt BH, Tripet F, Müller P. Revealing complex mosquito behaviour: a review of current automated video tracking systems suitable for tracking mosquitoes in the field. Parasites Vectors. 2025;18(1):66. Fatou M, Müller P. 3D video tracking analysis reveals that mosquitoes pass more likely through holes in permethrin-treated than in untreated nets. Sci Rep. 2024;14(1). Parker JE, Angarita-Jaimes N, Abe M, Towers CE, Towers D, McCall PJ. Infrared video tracking of Anopheles gambiae at insecticide-treated bed nets reveals rapid decisive impact after brief localised net contact. Sci Rep. 2015;5:13392. Fatou M, Müller P. In the arm-in-cage test, topical repellents activate mosquitoes to disengage upon contact instead of repelling them at distance. Sci Rep. 2024;14(1). Maire T, Wan Z, Lambrechts L, Hol FJH. BuzzWatch: uncovering multi-scale temporal patterns in mosquito behavior through continuous long-term monitoring. bioRxiv. 2025:2025.01.24.634688. Gleave K, Guy A, Mechan F, Emery M, Murphy A, Voloshin V, et al. Impacts of dual active-ingredient bed nets on the behavioural responses of pyrethroid resistant Anopheles gambiae determined by room-scale infrared video tracking. Malar J. 2023;22(1):132. Haalck L, Thiele S, Risse B. Tracking Tiny Insects in Cluttered Natural Environments using Refinable Recurrent Neural Networks. IEEE/CVF Winter Conference on Applications of Computer Vision2024. Additional Declarations No competing interests reported. Supplementary Files TrackingtheWHOtestBMCSUPPLEMENTARY.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 19 Mar, 2026 Reviews received at journal 16 Mar, 2026 Reviewers agreed at journal 25 Feb, 2026 Reviewers agreed at journal 24 Feb, 2026 Reviews received at journal 23 Feb, 2026 Reviewers agreed at journal 20 Feb, 2026 Reviewers invited by journal 10 Feb, 2026 Editor assigned by journal 05 Feb, 2026 Editor invited by journal 04 Feb, 2026 Submission checks completed at journal 04 Feb, 2026 First submitted to journal 04 Feb, 2026 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8720695","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":589097921,"identity":"8a2d5f8d-fd3c-49f1-beb6-22229a4b2e49","order_by":0,"name":"Beatrice H. 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Lugenge","email":"","orcid":"","institution":"Ifakara Health Institute","correspondingAuthor":false,"prefix":"","firstName":"Aidi","middleName":"G.","lastName":"Lugenge","suffix":""},{"id":589097932,"identity":"e0c11465-6392-4448-bcb6-dbcfa4e6de09","order_by":3,"name":"Dismas S. 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WHO tunnel comprising of three sections: a netted release chamber (not shown), a response chamber (T), measuring 60 cm x 25 cm x 25 cm, and a collection chamber housing the rabbit as a bait (R), measuring 27 cm x 25 cm x 25 cm. A piece of netting (N) is inserted into the response chamber. The tunnel was illuminated with near-infrared light from three different sides, from the bottom (B), top (H) and back (F). Two cameras (C) tracked the mosquitoes, powered by an uninterrupted power supply (U). The camera images were processed on a laptop (L). \u003cstrong\u003eA\u003c/strong\u003e View from the back. The response chamber with the rabbit is not visible but its position indicated with blue tape. \u0026nbsp;\u003cstrong\u003eB\u003c/strong\u003e View from the front with the rabbit bait (R) on the left.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8720695/v1/29e5c41d7e8426a1e64b6fa7.png"},{"id":103504395,"identity":"bf4044e4-b3bb-4db4-9eae-f5b19c51d898","added_by":"auto","created_at":"2026-02-26 13:19:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":347276,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExample of flight trajectories of mosquitoes in the WHO tunnel assay. \u003c/strong\u003eThe colour scale corresponds to the time since the start of tracking with blue being the beginning and dark red being the end. \u0026nbsp;\u003cstrong\u003eA\u003c/strong\u003e \u0026nbsp;Flight trajectories recorded from 10 mosquitoes for 10 min without a bait and an untreated net. \u003cstrong\u003eB\u003c/strong\u003e Flight trajectories recorded from 50 mosquitoes for 1h (between hour 3-4) with a rabbit as a bait and an untreated net. The position of the rabbit cage is indicated by the yellow box.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8720695/v1/cd4f9cf7e222a0ad37b0c807.png"},{"id":102962385,"identity":"3a71ed85-a0ad-41bd-b675-f5db491ea0f0","added_by":"auto","created_at":"2026-02-19 04:07:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":109909,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpatial and temporal distribution of mosquitoes within the tunnel over the 12 h recording period\u003c/strong\u003e. After releasing, the mosquitoes were either on the release side of the net or on the collection side with the rabbit or at the net in between. The symbols show the mean percentage across all runs (\u003cem\u003en \u003c/em\u003e= 11) while the shaded areas indicate the 95% confidence interval around the means.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8720695/v1/11f373cfdaeaf2d89a68ea41.png"},{"id":103509203,"identity":"9c86e547-8cc4-463e-9f4a-11ad7dfd658e","added_by":"auto","created_at":"2026-02-26 13:57:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1939370,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8720695/v1/7468004c-b6cb-4b8f-adea-d8b7466c32cc.pdf"},{"id":102764951,"identity":"47724015-4e02-4003-b689-5c7dcc5d647d","added_by":"auto","created_at":"2026-02-16 11:17:59","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":63499,"visible":true,"origin":"","legend":"","description":"","filename":"TrackingtheWHOtestBMCSUPPLEMENTARY.docx","url":"https://assets-eu.researchsquare.com/files/rs-8720695/v1/fee6c67cfc07839fbef7a0e4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrating 3D video tracking with the standard WHO tunnel assay — a proof-of-concept to support improving insecticide-treated nets for mosquito control","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMosquitoes are the most significant vectors of human pathogens. They transmit a wide array of parasites and viruses, causing diseases such as malaria, filariasis, dengue, yellow fever, chikungunya or Zika. Among these, \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes, the vectors of malaria, are of particular global health importance, with an estimated 282\u0026nbsp;million malaria cases worldwide (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). A cornerstone of malaria vector control is the deployment of insecticide-treated nets (ITNs). Beyond providing personal protection from infective mosquito bites, the insecticide treatment confers community-level protection by killing mosquitoes and thereby reducing malaria transmission. Since 2000, the mass distribution of ITNs has contributed substantially to the global decline in malaria incidence (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). However, since 2015, progress has levelled off as coverage of vector control and antimalarial treatment has stagnated, a situation worsened by the rapid emergence and spread of pyrethroid resistance in mosquito populations (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) .\u003c/p\u003e \u003cp\u003eTo address growing pyrethroid resistance in \u003cem\u003eAnopheles\u003c/em\u003e vectors, dual-active-ingredient ITNs \u0026ndash; combining a pyrethroid with other active ingredients \u0026ndash; have been developed and show greater epidemiological impact than pyrethroid-only nets (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). However, for proactively slowing resistance resurgence of currently effective interventions, the vector-control toolbox has to be continuously expanded with new insecticides having different modes of action than the existing ones.\u003c/p\u003e \u003cp\u003eThe development of ITNs with new insecticides requires bioassays that characterise their modes of action, which may elicit diverse behavioural responses in mosquitoes. In the early development phase, the WHO tunnel test is the standard laboratory assay for assessing the biological availability and potency of active ingredients on ITNs (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). However, the test provides only endpoint measurements \u0026ndash; the proportions of mosquitoes killed and blood-fed \u0026ndash; and therefore offers no insight into how mosquitoes interact with the net. Complementary behavioural data could reveal the extent to which mosquitoes engage with the ITN, helping to explain differences in endpoint outcomes and improve the utility of the tunnel assay.\u003c/p\u003e \u003cp\u003eFor capturing mosquito behaviour in detail, automated three-dimensional (3D) video tracking offers a powerful approach (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), and it has shown how mosquitoes interact with ITNs in modified set-ups (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Here, we present a proof-of-concept study combining a standard WHO tunnel assay that uses a rabbit as a bait with \u0026lsquo;Trackit3D\u0026rsquo;, a versatile automated tracking system, in a laboratory in Tanzania where tunnel assays are routinely conducted.\u003c/p\u003e"},{"header":"Main text","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExperimental set-up\u003c/h2\u003e \u003cp\u003eWe conducted the proof-of-concept study in a test laboratory of the Ifakara Health Institute (IHI) in Bagamoyo, Tanzania (6\u0026deg;26\u0026prime; S, 38\u0026deg;53\u0026prime; E). We combined a standardised WHO tunnel assay with a 3D video tracking system to record flight trajectories of mosquitoes negotiating the holes of an untreated net while approaching a rabbit at one end of the tunnel as per the original protocol (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). The tunnel we used was custom-made to improve video tracking and easy transportation. The side panels were laser-cut from plexiglas and then plugged together (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Supplementary information S1) like the cages described in Maire et al., 2025 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). This makes the tunnel very easy to transport, as it can be folded tightly together. The front panel was made of transparent Perspex, while the other sides were opaque to provide a homogeneously lit background for the video tracking.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor 3D video tracking, we used \u0026lsquo;Trackit3D\u0026rsquo;, an automated system for recording insect flight trajectories, originally developed by Scitracks GmbH (Bertschikon, Switzerland) and now owned by Swiss TPH. The software was installed on a laptop equipped with an 11th Generation Intel\u0026reg; Core\u0026trade; i7-1185G7 processor (3 GHz) and 32 GB RAM. We mounted two acA2040-90umNIR USB 3.0 digital cameras (Basler AG, Ahrensburg, Germany), each fitted with a Fujinon DV3.4\u0026times;3.8SA-SA1 lens (Fujifilm Holdings K.K., Tokyo, Japan) and a MidOpt BP850 near-infrared (NIR) band-pass filter (Midwest Optical Systems, Palatine, IL, USA), on tripods and recorded flight trajectories at 4 MP resolution and 50 fps.\u003c/p\u003e \u003cp\u003eTo prevent camera desynchronisation during short power outages, we connected the cameras to an APC uninterruptible power supply (Schneider Electric, West Kingston, RI, USA). Other equipment was powered directly from standard outlets, as brief interruptions did not affect performance. Tracking occasionally stopped for negligible pauses (\u0026lt;\u0026thinsp;1 s) due to insufficient lighting but resumed automatically once illumination was restored.\u003c/p\u003e \u003cp\u003eIllumination was provided by 10 850 nm NIR GU10 bulbs (ALLNET GmbH, Germering, Germany) fitted either in FLOTTILJ desk lamp sockets (IKEA AG, Spreitenbach, Switzerland) or into Eurolite GU10 sockets with a 1.8 m cable and integrated toggle switch, allowing flexible placement around the tunnel (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExperimental procedure\u003c/h3\u003e\n\u003cp\u003eIn a first step, we tracked female \u003cem\u003eAedes aegypti\u003c/em\u003e (Kingani strain, in colony since 2018) in the tunnel without a bait and an untreated nine-holed piece of netting inserted in the response chamber (N in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This procedure allowed us to assess the tracking system\u0026rsquo;s initial performance, optimise the placement of the different elements of the set-up, and adjust tracking parameters. We chose \u003cem\u003eAe. aegypti\u003c/em\u003e because they are day-active, allowing calibration under daylight conditions. For each of the 18 calibration runs, we released 10 laboratory-reared adult females into the tunnel and tracked them for 10 min under ambient conditions (28\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u0026deg;C; 71\u0026thinsp;\u0026plusmn;\u0026thinsp;10% relative humidity).\u003c/p\u003e \u003cp\u003eIn a next step, we followed the WHO tunnel test protocol (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). We expanded the set-up used in the first phase by adding a cage containing a rabbit (owned and breed by IHI Bagamoyo, in colony since 2012) as a bait (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). To minimise movement and provide a comfortable, burrow-like environment that encouraged a natural posture, we placed the rabbit inside a smaller tunnel, however the rabbit was not given anaesthesia for the experiments. The animal\u0026rsquo;s head was shielded from light, while its hindquarters remained behind mesh, allowing mosquitoes to land and feed. In addition, we shaved the rabbit\u0026rsquo;s fur to facilitate mosquito feeding.\u003c/p\u003e \u003cp\u003eWe released 50 lab-reared, nulliparous females of either \u003cem\u003eAnopheles gambiae\u003c/em\u003e s.s. (Ifakara strain, in colony since 1996) or \u003cem\u003eAnopheles arabiensis\u003c/em\u003e (Kingani strain, in colony since 2006) into the tunnel and tracked host-seeking behaviour for 12 h in the dark in accordance with the mosquitoes\u0026rsquo; circadian rhythm. As in the first phase, we cross-sectionally positioned an untreated piece of netting with nine holes in the middle of the response section, which mosquitoes had to negotiate to reach the rabbit. In total 6 replicates were conducted per strain, and in total 300 \u003cem\u003eAn. gambiae\u003c/em\u003e and 300 \u003cem\u003eAn. arabiensis\u003c/em\u003e were exposed to a rabbit bait in the tunnel test. All mosquito strains were established from locally collected mosquitoes and reared in the insectary of IHI Bagamoyo. After the experiment the rabbits are generally not euthanized but they are under veterinary care. Any sick rabbits are euthanized by the vet.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe video-tracking system successfully reconstructed mosquito flight trajectories within the WHO tunnel assay under both unbaited (with \u003cem\u003eAedes\u003c/em\u003e) and baited (with \u003cem\u003eAnopheles\u003c/em\u003e) conditions (Figure 2). Figure 2A illustrates representative 3D flight paths of 10 \u003cem\u003eAe. aegypti\u003c/em\u003e females in the absence of a rabbit. Although there was no bait, the experimenters were in the room, breathing CO2 into the tunnel, elicit host-seeking behaviour. When 50 mosquitoes were tracked for 12 h, the resulting plot became saturated with trajectories; therefore, Figure 2B presents a 1 h subset of the full 12 h recording for clarity. 11 out of the 12 measurements could be used for the analysis as one tracking night with 50 \u003cem\u003eAn. gambiae\u003c/em\u003e had to be excluded, due to tracking errors.\u003c/p\u003e\n\u003cp\u003eThe set-up combining Trackit3D with the standardised WHO tunnel assay tracked multiple mosquitoes simultaneously as they flew within the response chamber and moved through the netting holes into the collection chamber containing the rabbit. The tracking system was optimised for the area around the net, where both the quality and quantity of trajectories were highest. If another part of the arena would be the focus area for tracking, such as the rabbit, the system may be adapted accordingly. Adding an additional camera on the opposite side of the arena would reduce blind spots and mitigate the problem of mosquitoes flying behind the rabbit and becoming invisible to the front-facing cameras.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe system demonstrated stable performance despite repeated short power cuts and suboptimal lighting conditions. The flexibility and portability of both the video-tracking system and the tunnel design were critical to maintaining functionality. To our knowledge, this is the first study to demonstrate a system capable of recording mosquito flight trajectories within a standardised WHO tunnel assay over a continuous 12 h period.\u003c/p\u003e\n\u003cp\u003eThe recordings allowed us to quantify the time mosquitoes spent in different sections of the tunnel, particularly at the net, the response and collection chamber with the rabbit, and to visualise distinct behavioural patterns such as approaching, contacting or resting at the net or the bait. Figure 3 shows the spatial and temporal distribution of mosquito activity over the 12 h observation period and illustrating how long mosquitoes remained in each zone within the tunnel. On average, they had contact with the rabbit 173,419 times, while they approached and touched the net only 12,447 times.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA previous study tracked mosquito behaviour for 10 min in a modified WHO tunnel assay using a membrane feeder as an artificial host (8). Larger room assays mimicking experimental hut studies have also been conducted, recording mosquito interactions with ITNs while a human volunteer lay under the net, using two-dimensional video tracking for 2 h (12). In our study, extending tracking to 12 h showed that mosquitoes remained active even towards the end of the assay, indicating that they sustain activity around untreated nets for prolonged periods. Whether assays with ITNs should also be run for such extended durations, or whether shorter periods would suffice to increase throughput, remains to be further investigated. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFuture studies could use this system to evaluate ITNs across a broader range of settings and mosquito species. They could also investigate how mosquito behaviour varies in response to different hosts, both natural and artificial. Understanding mosquito behaviour within the WHO tunnel assay may prove valuable for interpreting assay outcomes, as video tracking can bridge the gap between standardised endpoint measurements and the underlying behavioural interactions with ITNs. Such insights would provide a more nuanced understanding of mosquito\u0026ndash;net interactions and support the refinement of assays for behavioural evaluation.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur results demonstrate that Trackit3D, used in combination with the foldable plexiglas tunnel, can effectively capture mosquito behaviour within the standardised WHO tunnel assay when an animal bait, such as a rabbit, is present. The ability to generate high-resolution flight trajectories within this assay opens new opportunities to strengthen the behavioural evaluation of vector control tools and to improve the interpretability and utility of the WHO tunnel test. This proof-of-concept therefore provides a foundation for larger-scale behavioural studies and supports the development of innovative approaches for assessing vector control interventions.\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eNonetheless, some limitations remain. The system occasionally lost track of individual mosquitoes, for example when they flew behind the rabbit or when flight paths overlapped. Reliable re-identification across repeated entry and exit events also remains a technical challenge for long-term tracking of individual mosquitoes. Emerging neural-network-based approaches (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) may help address this by improving object recognition and overall tracking accuracy. Addressing these issues through improved algorithms for object persistence, more efficient illumination and portable energy solutions will enhance future applications.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Ifakara Health Institute Institutional Review Board (IHI/IRB/No: 19\u0026ndash;2023) and the National Health Research Ethics Review Committee (NatHREC). In addition, animal welfare regulations are also covered under GLP. The work was done only in Tanzania within these regulations and all required ethical certificates were obtained.\u003c/p\u003e\n\u003cp\u003eRabbits were not euthanised after each trial; however, if animals became sick, humane euthanasia was performed by a licensed veterinarian, with animals first anaesthetised using ketamine\u0026ndash;xylazine (or equivalent agents) and subsequently given an overdose of a barbiturate, in accordance with national regulations and internationally recognised animal welfare guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have approved the manuscript and agree with its submission BMC Research Notes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated, used and analysed during the current study are available from the corresponding author on reasonable request.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\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. The tracking software Trackit3D is owned by SwissTPH.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive any specific funding from public, commercial or not-for-profit funding agencies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBB: Design of the study, conducting the experiments, analysing tracking data, writing manuscript, MF: Design of the study, reviewing manuscript, AL and DK: conducting the experiments, reviewing manuscript, NL: designing dismountable plexiglas tunnel, conducting the experiments, reviewing manuscript, SM: Experiment supervision, reviewing manuscript, PM: Design of the study, Experiment supervision, reviewing manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all laboratory technicians for their invaluable support during the experimental set-up and laboratory work. We are grateful to the Ifakara Health Institute, Bagamoyo branch, for providing access to their facilities and enabling us to conduct this proof-of-concept study. We extend our special thanks to Jason Moore for his generous assistance in sourcing equipment and ensuring that we had everything required for the work.\u003c/p\u003e\n\u003cp\u003eWe thank Dr. Richard Newton from the Biozentrum Research Instrumentation Facility for his support and assistance in designing and fabrication of the dismountable tunnel system.\u003c/p\u003e\n\u003cp\u003eCalculations were performed at sciCORE (http://scicore.unibas.ch/) scientific computing center at University of Basel.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSchneider CA, Calvo EA-O, Peterson KA-O, Arboviruses. How Saliva Impacts the Journey from Vector to. Mol Sci. 2021;22:1422\u0026ndash;0067. (Electronic)).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. World Malaria Report 2025. Geneva: World Health Organisiaiton; 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhatt S, Weiss DJ, Cameron E, Bisanzio D, Mappin B, Dalrymple U, et al. The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature. 2015;526(7572):207\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMosha JF, Kulkarni MA, Lukole E, Matowo NS, Pitt C, Messenger LA, et al. Effectiveness and cost-effectiveness against malaria of three types of dual-active-ingredient long-lasting insecticidal nets (LLINs) compared with pyrethroid-only LLINs in Tanzania: a four-arm, cluster-randomised trial. Lancet. 2022;399(10331):1227\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAccrombessi M, Cook J, Dangbenon E, Yovogan B, Akpovi H, Sovi A, et al. Efficacy of pyriproxyfen-pyrethroid long-lasting insecticidal nets (LLINs) and chlorfenapyr-pyrethroid LLINs compared with pyrethroid-only LLINs for malaria control in Benin: a cluster-randomised, superiority trial. Lancet. 2023;401(10375):435\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO Prequalification of Vector Control Products. Bioassay methods for insecticide-treated nets: tunnel test. Implementation guidance World Health Organisation; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBredt BH, Tripet F, M\u0026uuml;ller P. Revealing complex mosquito behaviour: a review of current automated video tracking systems suitable for tracking mosquitoes in the field. Parasites Vectors. 2025;18(1):66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFatou M, M\u0026uuml;ller P. 3D video tracking analysis reveals that mosquitoes pass more likely through holes in permethrin-treated than in untreated nets. Sci Rep. 2024;14(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParker JE, Angarita-Jaimes N, Abe M, Towers CE, Towers D, McCall PJ. Infrared video tracking of Anopheles gambiae at insecticide-treated bed nets reveals rapid decisive impact after brief localised net contact. Sci Rep. 2015;5:13392.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFatou M, M\u0026uuml;ller P. In the arm-in-cage test, topical repellents activate mosquitoes to disengage upon contact instead of repelling them at distance. Sci Rep. 2024;14(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaire T, Wan Z, Lambrechts L, Hol FJH. BuzzWatch: uncovering multi-scale temporal patterns in mosquito behavior through continuous long-term monitoring. bioRxiv. 2025:2025.01.24.634688.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGleave K, Guy A, Mechan F, Emery M, Murphy A, Voloshin V, et al. Impacts of dual active-ingredient bed nets on the behavioural responses of pyrethroid resistant Anopheles gambiae determined by room-scale infrared video tracking. Malar J. 2023;22(1):132.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaalck L, Thiele S, Risse B. Tracking Tiny Insects in Cluttered Natural Environments using Refinable Recurrent Neural Networks. IEEE/CVF Winter Conference on Applications of Computer Vision2024.\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mosquito behaviour, Flight trajectory analysis, Behavioural bioassays, Host-seeking behaviour, Anopheles mosquitoes","lastPublishedDoi":"10.21203/rs.3.rs-8720695/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8720695/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe World Health Organization (WHO) tunnel test is a standardised laboratory method for characterising the biological availability and potency of active ingredients on the surface of an insecticide-treated bed net (ITN) against host-seeking mosquitoes. However, the assay provides only endpoint measurements \u0026ndash; the proportions of mosquitoes that are killed and blood-fed \u0026ndash; and therefore offers no insight into how mosquitoes interact with the ITN. Therefore, complementary behavioural data could reveal, for example, the extent to which mosquitoes engage with the net \u0026ndash; explaining differences in endpoint outcomes \u0026ndash; or indicate the minimum duration required for the assay, thereby improving throughput. For capturing mosquito behaviour in detail, automated three-dimensional (3D) video tracking offers a powerful approach. Here, we present a proof-of-concept study combining the standard WHO tunnel assay with Trackit3D, a versatile tracking system, in a laboratory in Tanzania where tunnel assays are routinely conducted. The system tracked multiple mosquitoes simultaneously as they were attracted to a rabbit, despite typical fluctuations in power and lighting. The ability to obtain high-resolution trajectories within the WHO tunnel assay provides new opportunities to enhance the behavioural evaluation of vector control tools and to strengthen the interpretability and utility of the WHO tunnel assay.\u003c/p\u003e","manuscriptTitle":"Integrating 3D video tracking with the standard WHO tunnel assay — a proof-of-concept to support improving insecticide-treated nets for mosquito control","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-16 11:17:54","doi":"10.21203/rs.3.rs-8720695/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-19T14:27:55+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-16T19:15:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166755327282465299036359664072156357764","date":"2026-02-25T18:50:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"255933418262385444810841689915917621238","date":"2026-02-24T13:25:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-23T10:31:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"197536690930743010989597670201678211946","date":"2026-02-20T16:39:18+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-10T16:00:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-05T15:25:16+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-04T12:13:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-04T11:32:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Research Notes","date":"2026-02-04T11:03:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2958e96f-b483-45de-95bf-312dc60c4987","owner":[],"postedDate":"February 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-29T12:54:48+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-16 11:17:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8720695","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8720695","identity":"rs-8720695","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}