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Geospatial Artificial Intelligence Infused into a Smartphone Drone Application for Implementing 'Seek and Destroy' in Uganda

Received: 10 August 2021     Accepted: 28 September 2021     Published: 5 November 2021
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Abstract

This study provided important insights into new, real time, control measures at reducing larval, vector density [Macro Seek and Destroy (S&D) and blood parasite level [Micro S&D] in a malaria treated and suspected intervened population. Initially, this study employed a low-cost (< $1000) drone (DJI Phantom) for eco-geographically locating, water bodies including natural water bodies, irrigated rice paddies, cultivated swamps, ditches, ponds, and other geolocations, which are among the common breeding sites for Anopheles mosquitoes in Gulu district of Northern Uganda. Our hypothesis was that by integrating real time, scaled up, sentinel site, spectral signature, unmanned aerial vehicle (UAV) or drone imagery with satellite data using geospatial artificial intelligence [geo-AI] infused into an iOS application (app), a local, vector control officer could retrieve a ranked list of visually similar, breeding site, aquatic foci of An.gambiae s.l. arabiensis s.s. fuentsus s.s. mosquitoes, and their respective district-level, capture point, GPS indexed, centroid coordinates. We real time retrieved (hence, no lag time between seasonal, aquatic, Anopheles, larval habitat, mapping and treatment of foci) each georeferenced sentinel site signature which was subsequently archived in the drone dashboard spectral library using the smartphone app. Each georeferenced, UAV sensed, capture point was inspected using a mobile field team (i.e., trained local village residents led by a vector control officer) on the same day the habitats were geo-AI signature mapped, spatially forecasted and treated. A second hypothesis was that a real time, environmentally friendly, habitat alteration [i.e., Macro S&D] could reduce vector larval habitat density and blood parasite levels in treated and not suspected malaria patients at an entomological intervention site. A third hypothesis was: timely malaria diagnosis and treatment [Micro S&D] is associated with low population parasitemia and lower malaria incidences. In 31 days post-Macro S&D intervention, there was zero vector density, indoor, adult, female, Anopheles count as ascertained by pyrethrum spray catch at the intervention site. After a mean average of 62 days, blood parasite levels revealed a mean 0 count in timely diagnosed suspected and treated malaria patients. Implementing a real time Macro and Micro S&D intervention tool along with other existing tools [insecticide-treated mosquito nets (ITNs) and indoor residual spraying of insecticides (IRS)] in an entomological district-level intervention site can lower seasonal malaria prevalence either through timely modification of aquatic, Anopheles, larval habitats or through precisely targeted larvicide interventions.

Published in American Journal of Entomology (Volume 5, Issue 4)
DOI 10.11648/j.aje.20210504.11
Page(s) 92-109
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Drone, Seek and Destroy, ArcGIS, Artificial Intelligence iOS, Anopheles

References
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[4] Musiime, A. K., Smith, D. L., Kilama, M., Geoffrey, O., Kyagamba, P., Rek, J., Conrad, M. D., Nankabirwa, J. I., Arinaitwe, E., Akol, A. M., Kamya, M. R., Dorsey, G., Staedke, S. G., Drakeley, C., & Lindsay, S. W. (2020). Identification and characterization of immature Anopheles and Culicines (Diptera: Culicidae) at three sites of varying malaria transmission intensities in Uganda. Malaria journal, 19 (1), 221.
[5] Jensen, J. R., Introductory digital image processing: a remote sensing perspective. 2005, Upper Saddle River, N. J.: Prentice Hall.
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[7] Jacob BG. (2019). Efficaciously targeting unknown deleterious Aedes aegypti waste tire larval habitat capture points employing krigable photogrammetric Rayleigh optical depths as a function of sub-meter resolution semi-infinite anisotropically scattering landscape signature spectroscopic frequencies under disproportionate solar exoatmospheric irradiance conditions in q-dimensional Euclidean space in a semi-autonomous unmanned aircraft real-time object-based classifier. Ann Biostat Biometric App. Pp. 105. Iris Publishers.
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Cite This Article
  • APA Style

    Benjamin George Jacob, Denis Loum, Martha Kaddumukasa, Joseph Kamgno, Hugues Nana Djeunga, et al. (2021). Geospatial Artificial Intelligence Infused into a Smartphone Drone Application for Implementing 'Seek and Destroy' in Uganda. American Journal of Entomology, 5(4), 92-109. https://doi.org/10.11648/j.aje.20210504.11

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    ACS Style

    Benjamin George Jacob; Denis Loum; Martha Kaddumukasa; Joseph Kamgno; Hugues Nana Djeunga, et al. Geospatial Artificial Intelligence Infused into a Smartphone Drone Application for Implementing 'Seek and Destroy' in Uganda. Am. J. Entomol. 2021, 5(4), 92-109. doi: 10.11648/j.aje.20210504.11

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    AMA Style

    Benjamin George Jacob, Denis Loum, Martha Kaddumukasa, Joseph Kamgno, Hugues Nana Djeunga, et al. Geospatial Artificial Intelligence Infused into a Smartphone Drone Application for Implementing 'Seek and Destroy' in Uganda. Am J Entomol. 2021;5(4):92-109. doi: 10.11648/j.aje.20210504.11

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  • @article{10.11648/j.aje.20210504.11,
      author = {Benjamin George Jacob and Denis Loum and Martha Kaddumukasa and Joseph Kamgno and Hugues Nana Djeunga and André Domche and Philip Nwane and Joseph Mwangangi and Santiago Hernandez Bojorge and Jeegan Parikh and Jesse Casanova and Ricardo Izureta and Edwin Micheal and Thomas Mason and Alfred Mubangizi},
      title = {Geospatial Artificial Intelligence Infused into a Smartphone Drone Application for Implementing 'Seek and Destroy' in Uganda},
      journal = {American Journal of Entomology},
      volume = {5},
      number = {4},
      pages = {92-109},
      doi = {10.11648/j.aje.20210504.11},
      url = {https://doi.org/10.11648/j.aje.20210504.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aje.20210504.11},
      abstract = {This study provided important insights into new, real time, control measures at reducing larval, vector density [Macro Seek and Destroy (S&D) and blood parasite level [Micro S&D] in a malaria treated and suspected intervened population. Initially, this study employed a low-cost (Anopheles mosquitoes in Gulu district of Northern Uganda. Our hypothesis was that by integrating real time, scaled up, sentinel site, spectral signature, unmanned aerial vehicle (UAV) or drone imagery with satellite data using geospatial artificial intelligence [geo-AI] infused into an iOS application (app), a local, vector control officer could retrieve a ranked list of visually similar, breeding site, aquatic foci of An.gambiae s.l. arabiensis s.s. fuentsus s.s. mosquitoes, and their respective district-level, capture point, GPS indexed, centroid coordinates. We real time retrieved (hence, no lag time between seasonal, aquatic, Anopheles, larval habitat, mapping and treatment of foci) each georeferenced sentinel site signature which was subsequently archived in the drone dashboard spectral library using the smartphone app. Each georeferenced, UAV sensed, capture point was inspected using a mobile field team (i.e., trained local village residents led by a vector control officer) on the same day the habitats were geo-AI signature mapped, spatially forecasted and treated. A second hypothesis was that a real time, environmentally friendly, habitat alteration [i.e., Macro S&D] could reduce vector larval habitat density and blood parasite levels in treated and not suspected malaria patients at an entomological intervention site. A third hypothesis was: timely malaria diagnosis and treatment [Micro S&D] is associated with low population parasitemia and lower malaria incidences. In 31 days post-Macro S&D intervention, there was zero vector density, indoor, adult, female, Anopheles count as ascertained by pyrethrum spray catch at the intervention site. After a mean average of 62 days, blood parasite levels revealed a mean 0 count in timely diagnosed suspected and treated malaria patients. Implementing a real time Macro and Micro S&D intervention tool along with other existing tools [insecticide-treated mosquito nets (ITNs) and indoor residual spraying of insecticides (IRS)] in an entomological district-level intervention site can lower seasonal malaria prevalence either through timely modification of aquatic, Anopheles, larval habitats or through precisely targeted larvicide interventions.},
     year = {2021}
    }
    

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  • TY  - JOUR
    T1  - Geospatial Artificial Intelligence Infused into a Smartphone Drone Application for Implementing 'Seek and Destroy' in Uganda
    AU  - Benjamin George Jacob
    AU  - Denis Loum
    AU  - Martha Kaddumukasa
    AU  - Joseph Kamgno
    AU  - Hugues Nana Djeunga
    AU  - André Domche
    AU  - Philip Nwane
    AU  - Joseph Mwangangi
    AU  - Santiago Hernandez Bojorge
    AU  - Jeegan Parikh
    AU  - Jesse Casanova
    AU  - Ricardo Izureta
    AU  - Edwin Micheal
    AU  - Thomas Mason
    AU  - Alfred Mubangizi
    Y1  - 2021/11/05
    PY  - 2021
    N1  - https://doi.org/10.11648/j.aje.20210504.11
    DO  - 10.11648/j.aje.20210504.11
    T2  - American Journal of Entomology
    JF  - American Journal of Entomology
    JO  - American Journal of Entomology
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    EP  - 109
    PB  - Science Publishing Group
    SN  - 2640-0537
    UR  - https://doi.org/10.11648/j.aje.20210504.11
    AB  - This study provided important insights into new, real time, control measures at reducing larval, vector density [Macro Seek and Destroy (S&D) and blood parasite level [Micro S&D] in a malaria treated and suspected intervened population. Initially, this study employed a low-cost (Anopheles mosquitoes in Gulu district of Northern Uganda. Our hypothesis was that by integrating real time, scaled up, sentinel site, spectral signature, unmanned aerial vehicle (UAV) or drone imagery with satellite data using geospatial artificial intelligence [geo-AI] infused into an iOS application (app), a local, vector control officer could retrieve a ranked list of visually similar, breeding site, aquatic foci of An.gambiae s.l. arabiensis s.s. fuentsus s.s. mosquitoes, and their respective district-level, capture point, GPS indexed, centroid coordinates. We real time retrieved (hence, no lag time between seasonal, aquatic, Anopheles, larval habitat, mapping and treatment of foci) each georeferenced sentinel site signature which was subsequently archived in the drone dashboard spectral library using the smartphone app. Each georeferenced, UAV sensed, capture point was inspected using a mobile field team (i.e., trained local village residents led by a vector control officer) on the same day the habitats were geo-AI signature mapped, spatially forecasted and treated. A second hypothesis was that a real time, environmentally friendly, habitat alteration [i.e., Macro S&D] could reduce vector larval habitat density and blood parasite levels in treated and not suspected malaria patients at an entomological intervention site. A third hypothesis was: timely malaria diagnosis and treatment [Micro S&D] is associated with low population parasitemia and lower malaria incidences. In 31 days post-Macro S&D intervention, there was zero vector density, indoor, adult, female, Anopheles count as ascertained by pyrethrum spray catch at the intervention site. After a mean average of 62 days, blood parasite levels revealed a mean 0 count in timely diagnosed suspected and treated malaria patients. Implementing a real time Macro and Micro S&D intervention tool along with other existing tools [insecticide-treated mosquito nets (ITNs) and indoor residual spraying of insecticides (IRS)] in an entomological district-level intervention site can lower seasonal malaria prevalence either through timely modification of aquatic, Anopheles, larval habitats or through precisely targeted larvicide interventions.
    VL  - 5
    IS  - 4
    ER  - 

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Author Information
  • College of Public Health, University of South Florida, Tampa, USA

  • Nwoya District Local Government, Nwoya, Uganda

  • Department of Parasitology and Entomology, Makerere University, Kampala, Uganda

  • The Center for Research on Filariasis and other Tropical Diseases, Yaounde, Cameroon

  • The Center for Research on Filariasis and other Tropical Diseases, Yaounde, Cameroon

  • The Center for Research on Filariasis and other Tropical Diseases, Yaounde, Cameroon

  • The University of Yaoundé I, Yaounde Cameroon

  • Center for Geographic Medicine Research, Coast, Kilifi, Kenya

  • College of Public Health, University of South Florida, Tampa, USA

  • College of Public Health, University of South Florida, Tampa, USA

  • USF Health International University of South Florida, Tampa, USA

  • College of Public Health, University of South Florida, Tampa, USA

  • College of Public Health, University of South Florida, Tampa, USA

  • College of Public Health, University of South Florida, Tampa, USA

  • Uganda Ministry of Health, Kampala, Uganda

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