Unmanned aerial vehicles for surveillance and control of vectors of malaria and other vector-borne diseases

Frank Mechan, Zikmund Bartonicek, David Malone, Rosemary Susan Lees, Frank Mechan, Zikmund Bartonicek, David Malone, Rosemary Susan Lees

Abstract

The use of Unmanned Aerial Vehicles (UAVs) has expanded rapidly in ecological conservation and agriculture, with a growing literature describing their potential applications in global health efforts including vector control. Vector-borne diseases carry severe public health and economic impacts to over half of the global population yet conventional approaches to the surveillance and treatment of vector habitats is typically laborious and slow. The high mobility of UAVs allows them to reach remote areas that might otherwise be inaccessible to ground-based teams. Given the rapidly expanding examples of these tools in vector control programmes, there is a need to establish the current knowledge base of applications for UAVs in this context and assess the strengths and challenges compared to conventional methodologies. This review aims to summarize the currently available knowledge on the capabilities of UAVs in both malaria control and in vector control more broadly in cases where the technology could be readily adapted to malaria vectors. This review will cover the current use of UAVs in vector habitat surveillance and deployment of control payloads, in comparison with their existing conventional approaches. Finally, this review will highlight the logistical and regulatory challenges in scaling up the use of UAVs in malaria control programmes and highlight potential future developments.

Keywords: Drones; Mosquito control; Public health; Surveillance; Unmanned aerial system (UAS); Unmanned aerial vehicle (UAV); Vector-borne diseases.

Conflict of interest statement

The authors declare that they have no competing interests.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
Examples of UAVs used in vector control and their applications (indicated by bars on top). SIT (Sterile Insect Technique) refers to release of sterile insects
Fig. 2
Fig. 2
An example of A orthomosaic after stitching and B a map that can then be passed to field teams with highlighted waterbodies (red) and access routes and locations. Taken with permission from Hardy et al. [27]

References

    1. WHO . Vector-borne diseases. Geneva: World Health Organization; 2017.
    1. WHO Malaria Policy Advisory Committee and Secretariat Malaria Policy Advisory Committee to the WHO: conclusions and recommendations of eighth biannual meeting (September 2015) Malar J. 2016;15:117.
    1. Fornace KM, Diaz AV, Lines J, Drakeley CJ. Achieving global malaria eradication in changing landscapes. Malar J. 2021;20:1–14.
    1. Knapp J, Macdonald M, Malone D, Hamon N, Richardson JH. Disruptive technology for vector control: the innovative Vector Control Consortium and the US Military join forces to explore transformative insecticide application technology for mosquito control programmes. Malar J. 2015;14:371.
    1. Ahirwar S, Swarnkar R, Bhukya S, Namwade G. Application of drone in agriculture. Int J Curr Microbiol Appl Sci. 2019;8:2500–5.
    1. Roslim MHM, Juraimi AS, Che’Ya NN, Sulaiman N, Manaf MNHA, Ramli Z, et al. Using remote sensing and an unmanned aerial system for weed management in agricultural crops: a review. Agronomy. 2021;11:1809.
    1. Khan S, Tufail M, Khan MT, Khan ZA, Iqbal J, Alam M. A novel semi-supervised framework for UAV based crop/weed classification. PLoS ONE. 2021;16:e0251008.
    1. Honkavaara E, Näsi R, Oliveira R, Viljanen N, Suomalainen J, Khoramshahi E, et al. Using multitemporal hyper- and multispectral UAV imaging for detecting bark beetle infestation on Norway spruce. Int Arch Photogrammetry Remote Sens Spatial Inform Sci. 2020;43:B3.
    1. Vanegas F, Bratanov D, Powell K, Weiss J, Gonzalez F. A novel methodology for improving plant pest surveillance in vineyards and crops using UAV-based hyperspectral and spatial data. Sensors. 2018;18:260.
    1. Yu Q, Liu H, Xiao N. Unmanned aerial vehicles: potential tools for use in zoonosis control. Infect Dis Poverty. 2018;7:49.
    1. Bravo RZB, Leiras A, Cyrino Oliveira FL. The use of UAV s in humanitarian relief: an application of POMDP-based methodology for finding victims. Prod Oper Manage. 2019;28:421–40.
    1. Kyriakakis NA, Marinaki M, Matsatsinis N, Marinakis Y. A cumulative unmanned aerial vehicle routing problem approach for humanitarian coverage path planning. Eur J Oper Res. 2022;300:992–1004.
    1. Bhattacharya S, Hossain MM, Hoedebecke K, Bacorro M, Gökdemir Ö, Singh A. Leveraging unmanned aerial vehicle technology to improve public health practice: prospects and barriers. Indian J Commun Medicine. 2020;45:396.
    1. Neto JC, Resque IS, Avelino RA, Santos VBd, Leite LS, Cesar LO, et al. An adapted unmanned aerial vehicle for environmental water sampling. Química Nova. 2022;45:734–41.
    1. Bonnin N, Van Andel AC, Kerby JT, Piel AK, Pintea L, Wich SA. Assessment of chimpanzee nest detectability in drone-acquired images. Drones. 2018;2:17.
    1. Poljak M, Šterbenc A. Use of drones in clinical microbiology and infectious diseases: current status, challenges and barriers. Clin Microbiol Infect. 2020;26:425–30.
    1. Kim J, Kim S, Ju C, Son HI. Unmanned aerial vehicles in agriculture. A review of perspective of platform, control, and applications. IEEE Access. 2019;7:105100–15.
    1. Kim DH. Regulations and laws pertaining to the use of unmanned aircraft systems (UAS) by ICAO, USA, China, Japan, Australia, India, and Korea. Unmanned aerial vehicles in civilian logistics and supply chain management; 2019. p. 169–207.
    1. Fornace KM, Drakeley CJ, William T, Espino F, Cox J. Mapping infectious disease landscapes: unmanned aerial vehicles and epidemiology. Trends Parasitol. 2014;30:514–9.
    1. Byrne I, Chan K, Manrique E, Lines J, Wolie RZ, Trujillano F, et al. Technical workflow development for integrating drone surveys and entomological sampling to characterise aquatic larval habitats of Anopheles funestus in agricultural landscapes in Côte d’Ivoire. J Environ Public Health. 2021;2021:3220244.
    1. Mehra M, Bagri A, Jiang X, Ortiz J. Image analysis for identifying mosquito breeding grounds. In: 2016 IEEE International conference on sensing, communication and networking (SECON workshops); 2016.
    1. Case E, Shragai T, Harrington L, Ren Y, Morreale S, Erickson D. Evaluation of unmanned aerial vehicles and neural networks for integrated mosquito management of Aedes albopictus (Diptera: Culicidae) J Med Entomol. 2020;57:1588–95.
    1. Li C-X, Zhang Y-M, Dong Y-D, Zhou M-H, Zhang H-D, Chen H-N, et al. An unmanned aerial vehicle-mounted cold mist spray of permethrin and tetramethylfluthrin targeting Aedes albopictus in China. J Am Mosq Control Assoc. 2016;32:59–62.
    1. Rasmussen E. Drones against vector-borne diseases. Sci Robot. 2020;5:eabc7642.
    1. Müllerová J, Brůna J, Bartaloš T, Dvořák P, Vítková M, Pyšek P. Timing is important: unmanned aircraft vs. satellite imagery in plant invasion monitoring. Front Plant Sci. 2017;8:887.
    1. Aragà FV, Zola FC, Marinho LHN, de Genaro Chiroli DM, Junior AB. Choice of unmanned aerial vehicles for identification of mosquito breeding sites. Geospat Health. 2020;15:1.
    1. Hardy A, Makame M, Cross D, Majambere S, Msellem M. Using low-cost drones to map malaria vector habitats. Parasit Vectors. 2017;10:29.
    1. Annan E, Guo J, Angulo-Molina A, Yaacob WFW, Aghamohammadi N, Guetterman TC, et al. Community acceptability of dengue fever surveillance using unmanned aerial vehicles: a cross-sectional study in Malaysia, Mexico, and Turkey. Travel Med Infect Dis. 2022;49:102360.
    1. Fillinger U, Lindsay SW. Larval source management for malaria control in Africa: myths and reality. Malar J. 2011;10:353.
    1. McCann RS, van den Berg H, Diggle PJ, van Vugt M, Terlouw DJ, Phiri KS, et al. Assessment of the effect of larval source management and house improvement on malaria transmission when added to standard malaria control strategies in southern Malawi: study protocol for a cluster-randomised controlled trial. BMC Infect Dis. 2017;17:639.
    1. Tusting LS, Thwing J, Sinclair D, Fillinger U, Gimnig J, Bonner KE, et al. Mosquito larval source management for controlling malaria. Cochrane Database Syst Rev. 2013;2013:CD008923.
    1. Winskill P, Walker PG, Cibulskis RE, Ghani AC. Prioritizing the scale-up of interventions for malaria control and elimination. Malar J. 2019;18:122.
    1. Bhatt S, Weiss D, 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;526:207–11.
    1. Stanton MC, Kalonde P, Zembere K, Hoek Spaans R, 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.
    1. Sarira TV, Clarke K, Weinstein P, Koh LP, Lewis M. Rapid identification of shallow inundation for mosquito disease mitigation using drone-derived multispectral imagery. Geospat Health. 2020;15:1.
    1. Pádua L, Vanko J, Hruška J, Adão T, Sousa JJ, Peres E, et al. UAS, sensors, and data processing in agroforestry: a review towards practical applications. Int J Remote Sens. 2017;38:2349–91.
    1. Johnson BJ, Manby R, Devine GJ. Performance of an aerially applied liquid Bacillus thuringiensis var. Israelensis formulation (strain AM65-52) against mosquitoes in mixed saltmarsh–mangrove systems and fine‐scale mapping of mangrove canopy cover using affordable drone‐based imagery. Pest Manage Sci. 2020;76:3822–31.
    1. Valdez-Delgado KM, Moo-Llanes DA, Danis-Lozano R, Cisneros-Vázquez LA, Flores-Suarez AE, Ponce-García G, et al. Field effectiveness of drones to identify potential Aedes aegypti breeding sites in household environments from Tapachula, a dengue-endemic city in southern Mexico. Insects. 2021;12:663.
    1. Carrasco-Escobar G, Manrique E, Ruiz-Cabrejos J, Saavedra M, Alava F, Bickersmith S, et al. High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery. PLoS Negl Trop Dis. 2019;13:e0007105.
    1. Suduwella C, Amarasinghe A, Niroshan L, Elvitigala C, De Zoysa K, Keppetiyagama C. Identifying mosquito breeding sites via drone images. In: proceedings of the 3rd workshop on micro aerial vehicle networks, systems, and applications. 2017.
    1. Amarasinghe A, Suduwella C, Niroshan L, Elvitigala C, De Zoysa K, Keppetiyagama C. Suppressing dengue via a drone system. In: 2017 seventeenth int conference on advances in ICT for emerging regions (ICTer); 2017.
    1. Chamberlin AJ, Jones IJ, Lund AJ, Jouanard N, Riveau G, Ndione R, et al. Visualization of schistosomiasis snail habitats using light unmanned aerial vehicles. Geospat Health. 2021;15:1.
    1. Wood CL, Sokolow SH, Jones IJ, Chamberlin AJ, Lafferty KD, Kuris AM, et al. Precision mapping of snail habitat provides a powerful indicator of human schistosomiasis transmission. Proc Natl Acad Sci USA. 2019;116:23182–91.
    1. Hay S, Snow R, Rogers D. From predicting mosquito habitat to malaria seasons using remotely sensed data: practice, problems and perspectives. Parasitol Today. 1998;14:306–13.
    1. Tokarz R, Novak RJ. Spatial–temporal distribution of Anopheles larval habitats in Uganda using GIS/remote sensing technologies. Malar J. 2018;17:420.
    1. Manfreda S, McCabe MF, Miller PE, Lucas R, Pajuelo Madrigal V, Mallinis G, et al. On the use of unmanned aerial systems for environmental monitoring. Remote Sens. 2018;10:641.
    1. Kalluri S, Gilruth P, Rogers D, Szczur M. Surveillance of arthropod vector-borne infectious diseases using remote sensing techniques: a review. PLoS Pathog. 2007;3:e116.
    1. Rogers DJ, Randolph SE, Snow RW, Hay SI. Satellite imagery in the study and forecast of malaria. Nature. 2002;415:710–5.
    1. Vergouw B, Nagel H, Bondt G, Custers B. Drone technology: types, payloads, applications, frequency spectrum issues and future developments. In: Custers B, editor. The future of drone use. Springer: Berlin; 2016. pp. 21–45.
    1. Aircraft FFSSU. Regulations (part 107) Washington, DC: FAA; 2014.
    1. Authority CA. Unmanned aircraft and drones. Accessed May 2020.
    1. Dubin S, Greve A, Triche R. Drones in international development. USAID GOV; 2020.
    1. Calantropio A, Chiabrando F, Comino J, Lingua A, Maschio P, Juskauskas T. UP4DREAM capacity building project: UAS based mapping in developing countries. Int Arch Photogrammetry Remote Sens Spatial Inform Sci. 2021;43:65–72.
    1. Anderson K, Westoby MJ, James MR. Low-budget topographic surveying comes of age: structure from motion photogrammetry in geography and the geosciences. Progr Phys Geogr Earth Environ. 2019;43:163–73.
    1. Zhu Z, Bao T, Hu Y, Gong J. A novel method for fast positioning of non-standardized ground control points in drone images. Remote Sens. 2021;13:2849.
    1. Joo Y-D. Drone image classification based on convolutional neural networks. J Inst Internet Broadcasting Commun. 2017;17:97–102.
    1. Yin N, Liu R, Zeng B, Liu N. A review: UAV-based remote sensing. In: IOP conference series: materials science and engineering. IOP Publishing; 2019. p. 062014.
    1. Lien MR, Barker RJ, Ye Z, Westphall MH, Gao R, Singh A, et al. A low-cost and open-source platform for automated imaging. Plant Methods. 2019;15:6.
    1. Dlamini SN, Beloconi A, Mabaso S, Vounatsou P, Impouma B, Fall IS. Review of remotely sensed data products for disease mapping and epidemiology. Remote Sens Appl Soc Environ. 2019;14:108–18.
    1. Singh KK, Frazier AE. A meta-analysis and review of unmanned aircraft system (UAS) imagery for terrestrial applications. Int J Remote Sens. 2018;39:5078–98.
    1. 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;6:180.
    1. Puri V, Nayyar A, Raja L. Agriculture drones: a modern breakthrough in precision agriculture. J Stat Manage Syst. 2017;20:507–18.
    1. Giles D, Billing R. Deployment and performance of a UAV for crop spraying. Chem Eng Trans. 2015;44:307–12.
    1. Pryce J, Choi L, Richardson M, Malone D. Insecticide space spraying for preventing malaria transmission. Cochrane Database Syst Rev. 2018;11:CD012689.
    1. Raghavendra K, Barik TK, Reddy B, Sharma P, Dash AP. Malaria vector control: from past to future. Parasitol Res. 2011;108:757–79.
    1. Zhai J, Reynolds B, Huang MH. Unmanned aerial system—new vector control technology. Int Pest Control. 2019;61:152–4.
    1. Williams GM, Wang Y, Suman DS, Unlu I, Gaugler R. The development of autonomous unmanned aircraft systems for mosquito control. PLoS ONE. 2020;15:e0235548.
    1. Bonds J. Ultra-low‐volume space sprays in mosquito control: a critical review. Med Vet Entomol. 2012;26:121–30.
    1. Zhan Y, Chen S, Wang G, Fu J, Lan Y. Biological control technology and application based on agricultural unmanned aerial vehicle (UAV) intelligent delivery of insect natural enemies (Trichogramma) carrier. Pest Manage Sci. 2021;77:3259–72.
    1. Winskill P, Carvalho DO, Capurro ML, Alphey L, Donnelly CA, McKemey AR. Dispersal of engineered male Aedes aegypti mosquitoes. PLoS Negl Trop Dis. 2015;9:e0004156.
    1. Benedict MQ. Sterile insect technique: lessons from the past. J Med Entomol. 2021;58:1974–9.
    1. Gentile JE, Rund SS, Madey GR. Modelling sterile insect technique to control the population of Anopheles gambiae. Malar J. 2015;14:92.
    1. Bouyer J, Culbert NJ, Dicko AH, Pacheco MG, Virginio J, Pedrosa MC, et al. Field performance of sterile male mosquitoes released from an uncrewed aerial vehicle. Sci Robot. 2020;5:eaba6251.
    1. Maciel-De-Freitas R, Codeco CT, Lourenco-De-Oliveira R. Daily survival rates and dispersal of Aedes aegypti females in Rio de Janeiro, Brazil. Am J Trop Med Hyg. 2007;76:659–65.
    1. Harrington LC, Scott TW, Lerdthusnee K, Coleman RC, Costero A, Clark GG, et al. Dispersal of the dengue vector aedes aegypti within and between rural communities. Am J Trop Med Hyg. 2005;72:209–20.
    1. Marina CF, Liedo P, Bond JG, Osorio R, Valle A, Angulo-Kladt J, et al. Comparison of ground release and drone-mediated aerial release of Aedes aegypti sterile males in southern Mexico: efficacy and challenges. Insects. 2022;13:347.
    1. Embention. Drones against TseTse. . Accessed 9 Jan 2023.
    1. Torr SJ, Vale GA. Know your foe: lessons from the analysis of tsetse fly behaviour. Trends Parasitol. 2015;31:95–9.
    1. Vreysen MJ, Saleh KM, Ali MY, Abdulla AM, Zhu Z-R, Juma KG, et al. Glossina austeni (Diptera: Glossinidae) eradicated on the island of Unguja, Zanzibar, using the sterile insect technique. J Econ Entomol. 2000;93:123–35.
    1. Watts AC, Ambrosia VG, Hinkley EA. Unmanned aircraft systems in remote sensing and scientific research: classification and considerations of use. Remote Sens. 2012;4:1671–92.
    1. Faraji A, Haas-Stapleton E, Sorensen B, Scholl M, Goodman G, Buettner J, et al. Toys or tools? Utilization of unmanned aerial systems in mosquito and vector control programs. J Econ Entomol. 2021;114:1896–909.
    1. Dewi PT, Hadi GS, Kusnaedi MR, Budiyarto A, Budiyono A. Design of separate lift and thrust hybrid unmanned aerial vehicle. J Instrum Autom Syst. 2015;2:45–51.
    1. Boon MA, Drijfhout AP, Tesfamichael S. Comparison of a fixed-wing and multi-rotor UAV for environmental mapping applications: a case study. Int Arch Photogrammetry Remote Sens Spatial Inform Sci. 2017;42:W6.
    1. Ozdemir U, Aktas YO, Vuruskan A, Dereli Y, Tarhan AF, Demirbag K, et al. Design of a commercial hybrid VTOL UAV system. J Intell Robot Syst. 2014;74:371–93.
    1. Clarke R. The regulation of civilian drones’ impacts on behavioural privacy. Comput Law Secur Rev. 2014;30:286–305.
    1. Stöcker C, Bennett R, Nex F, Gerke M, Zevenbergen J. Review of the current state of UAV regulations. Remote Sens. 2017;9:459.
    1. Unija E. Commission implementing regulation (EU) 2019/947 of 24 May 2019 on the rules and procedures for the operation of unmanned aircraft. Official Journal of the European Union; 2019.
    1. Petty RV, Chang EBE. Drone use in aerial pesticide application faces outdated regulatory hurdles. Harvard J Law Tech Dig. 2018. . Accessed 9 Jan 2023.
    1. Global Drone Regulations Database. 2017. . Accessed 9 Jan 2023.
    1. Boucher P. ‘You wouldn’t have your granny using them’: drawing boundaries between acceptable and unacceptable applications of civil drones. Sci Engin Ethics. 2016;22:1391–418.
    1. Aydin B. Public acceptance of drones: knowledge, attitudes, and practice. Technol Soc. 2019;59:101180.
    1. Lee D, Hess DJ, Heldeweg MA. Safety and privacy regulations for unmanned aerial vehicles: a multiple comparative analysis. Technol Soc. 2022;71:102079.
    1. Bousema T, Griffin JT, Sauerwein RW, Smith DL, Churcher TS, Takken W, et al. Hitting hotspots: spatial targeting of malaria for control and elimination. PLoS Med. 2012;9:e1001165.
    1. Holst C, Sukums F, Radovanovic D, Ngowi B, Noll J, Winkler AS. Sub-Saharan Africa—the new breeding ground for global digital health. Lancet Digit Health. 2020;2:e160–2.
    1. MACONDO. Network for the use of drones for malaria vector control. . Accessed 9 Jan 2023.
    1. Hardy A, Proctor M, MacCallum C, Shawe J, Abdalla S, Ali R, et al. Conditional trust: community perceptions of drone use in malaria control in Zanzibar. Technol Soc. 2022;68:101895.
    1. Matese A, Toscano P, Di Gennaro SF, Genesio L, Vaccari FP, Primicerio J, et al. Intercomparison of UAV, aircraft and satellite remote sensing platforms for precision viticulture. Remote Sens. 2015;7:2971–90.
    1. Kirschstein T. Comparison of energy demands of drone-based and ground-based parcel delivery services. Transp Res D. 2020;78:102209.

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