Research Article | | Peer-Reviewed

Mapping Potential Anopheles stephensi Habitats for Implementing “Seek and Destroy” Malaria Larval Source Management in Kwale County, Kenya

Received: 3 October 2023     Accepted: 26 October 2023     Published: 29 November 2023
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Abstract

We will reveal specific locations of potential habitats of Anopheles stephensi, a new and invasive malaria vector, in Kwale, Kenya. Previous regression models have not been able to locate specific habitats of this malaria vector in Kenya. This publication seeks to determine locations of potential artificial water container habitats of An. stephensi via remote visual detection and determine geo-ecological factors that are associated with those habitats. The preliminary signature mapping of potential habitats was done by obtaining GPS coordinates of potential, capture point, sentinel site locations through visual remote sensing of artificial water containers using Google Earth. Using a second-order eigenfunction, eigendecomposition, spatial filter algorithm to determine clustering propensities or non-propensities of those mapped potential capture point, sentinel site larval habitats, we were able to eco-cartographically distinguish hot and cold spots on stratified, georeferenced, Land Use Land Cover (LULC) polygons, a Digital Elevation Model (DEM), and a Normalized Difference Vegetation Index (NDVI) map within ArcGIS Pro. The results showed that there was a strong tendency towards clustering (Moran’s I=0.67, p<0.001) and potential habitat hotspots were more likely to occur in urban classified LULC, grid-stratified areas (51.28% and 46.15% of the hotspot locations were in urban commercial and urban residential land covers respectively). Moreover, the georeferenced hotspot locations of potential habitats were found at higher elevations than the coldspots (409.1± 6.112m vs 379.5 ± 21.51m) and the hotspot habitats were closely associated with soil and low vegetation (mean NDVI=0.121 ± 0.0661). When faced with this new vector, these ecological variables can be employed to spatially target and prioritize potential habitats for implementing “Seek and Destroy” larval source management programs.

Published in American Journal of Entomology (Volume 7, Issue 4)
DOI 10.11648/j.aje.20230704.11
Page(s) 120-129
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), 2023. Published by Science Publishing Group

Keywords

Anopheles stephensi, Artificial Containers, Eigendecomposition Kwale, Kenya

References
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[2] Tadesse, F. G., et al., Anopheles stephensi Mosquitoes as Vectors of Plasmodium vivax and falciparum, Horn of Africa, 2019. Emerg Infect Dis, 2021. 27 (2): p. 603-607.
[3] Ahn, J., et al., Modeling marine cargo traffic to identify countries in Africa with greatest risk of invasion by Anopheles stephensi. Sci Rep, 2023. 13 (1): p. 876.
[4] Ndenga, B. A., et al., Serendipitous detection of Anopheles stephensi in Kisumu, Kenya in June 2022. medRxiv, 2023: p. 2023.05.02.23289394.
[5] Yared, S., et al., Insecticide resistance in Anopheles stephensi in Somali Region, eastern Ethiopia. Malar J, 2020. 19 (1): p. 180.
[6] Sinka, M. E., et al., The dominant Anopheles vectors of human malaria in the Asia-Pacific region: occurrence data, distribution maps and bionomic précis. Parasit Vectors, 2011. 4: p. 89.
[7] Kumar, D. S., et al., Spatial trend, environmental and socioeconomic factors associated with malaria prevalence in Chennai. Malar J, 2014. 13: p. 14.
[8] Thomas, S., et al., Overhead tank is the potential breeding habitat of Anopheles stephensi in an urban transmission setting of Chennai, India. Malar J, 2016. 15 (1): p. 274.
[9] Singh, H., et al., The impact of mosquito proof lids of underground tanks "tanka" on the breeding of Anopheles stephensi in a village in western Rajasthan, India. Malar J, 2021. 20 (1): p. 412.
[10] Tyagi, B. K. and S. P. Yadav, Malariological and sociological significance of ‘tanka’ and ‘beri’ in the Thar Desert, Western Rajasthan, India. Journal of Arid Environments, 1996. 33 (4): p. 497-501.
[11] Jacob, B. G., et al., Environmental abundance of Anopheles (Diptera: Culicidae) larval habitats on land cover change sites in Karima Village, Mwea Rice Scheme, Kenya. Am J Trop Med Hyg, 2007. 76 (1): p. 73-80.
[12] Jacob, B. G., et al., Geospatial artificial intelligence infused into a smartphone drone application for implementing 'Seek and Destroy' in Uganda. American Journal of Entomology, 2021. 5 (4): p. 92-109.
[13] Kenya National Bureau of Statistics, The 2019 Kenya Population and Housing Census Volume I: Population by County and Sub-County, Kenya National Bureau of Statistics, Editor. 2019: Nairobi, Kenya.
[14] Snow, R. W., et al., Changing Malaria Prevalence on the Kenyan Coast since 1974: Climate, Drugs and Vector Control. PLoS One, 2015. 10 (6): p. e0128792.
[15] The Ministry of Agriculture, Livestock and Fisheries (MoALF), Climate Risk Profile for Kwale County. Kenya County Climate Risk Profile Series, MoALF, Editor. 2016: Nairobi, Kenya.
[16] Wikimedia Foundation, Kwale County. June 23, 2023; Available from: https://en.wikipedia.org/wiki/Kwale_County.
[17] Wikimedia Foundation, Kwale. April 1, 2023; Available from: https://en.wikipedia.org/wiki/Kwale.
[18] Kenya National Bureau of Statistics, 2019 Kenya Population and Housing Census Volume II: Distribution of Population by Administrative Units, Kenya National Bureau of Statistics, Editor. 2019.
[19] Griffith, D., Spatial Autocorrelation and Spatial Filtering: Gaining Understanding through Theory and Scientific Visualization. 2003.
[20] Hosmer, D. W. and S. Lemeshow, Applied Logistic Regression. 2000.
[21] Cressie, N. A. C., Statistics for Spatial Data. 1993, John WIley & Sons, Inc.
[22] Surendran, S. N., et al., Anthropogenic Factors Driving Recent Range Expansion of the Malaria Vector Anopheles stephensi. Front Public Health, 2019. 7: p. 53.
[23] Balkew, M., et al., Geographical distribution of Anopheles stephensi in eastern Ethiopia. Parasit Vectors, 2020. 13 (1): p. 35.
[24] Pemola Devi, N. and R. K. Jauhari, Mosquito species associated within some Western Himalayas phytogeographic zones in the Garhwal region of India. J Insect Sci, 2007. 7: p. 1-10.
Cite This Article
  • APA Style

    Isabelle Burnett, A., Izurieta, R., Hoare, I., Choudhari, N., Casanova, J., et al. (2023). Mapping Potential Anopheles stephensi Habitats for Implementing “Seek and Destroy” Malaria Larval Source Management in Kwale County, Kenya. American Journal of Entomology, 7(4), 120-129. https://doi.org/10.11648/j.aje.20230704.11

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    ACS Style

    Isabelle Burnett, A.; Izurieta, R.; Hoare, I.; Choudhari, N.; Casanova, J., et al. Mapping Potential Anopheles stephensi Habitats for Implementing “Seek and Destroy” Malaria Larval Source Management in Kwale County, Kenya. Am. J. Entomol. 2023, 7(4), 120-129. doi: 10.11648/j.aje.20230704.11

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    AMA Style

    Isabelle Burnett A, Izurieta R, Hoare I, Choudhari N, Casanova J, et al. Mapping Potential Anopheles stephensi Habitats for Implementing “Seek and Destroy” Malaria Larval Source Management in Kwale County, Kenya. Am J Entomol. 2023;7(4):120-129. doi: 10.11648/j.aje.20230704.11

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  • @article{10.11648/j.aje.20230704.11,
      author = {Ariel Isabelle Burnett and Ricardo Izurieta and Ismael Hoare and Namit Choudhari and Jesse Casanova and Brooke Yost and Charles Mbogo and Joseph Mwangangi and Martin Rono and Anthony Masys and Benjamin George Jacob},
      title = {Mapping Potential Anopheles stephensi Habitats for Implementing “Seek and Destroy” Malaria Larval Source Management in Kwale County, Kenya},
      journal = {American Journal of Entomology},
      volume = {7},
      number = {4},
      pages = {120-129},
      doi = {10.11648/j.aje.20230704.11},
      url = {https://doi.org/10.11648/j.aje.20230704.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aje.20230704.11},
      abstract = {We will reveal specific locations of potential habitats of Anopheles stephensi, a new and invasive malaria vector, in Kwale, Kenya. Previous regression models have not been able to locate specific habitats of this malaria vector in Kenya. This publication seeks to determine locations of potential artificial water container habitats of An. stephensi via remote visual detection and determine geo-ecological factors that are associated with those habitats. The preliminary signature mapping of potential habitats was done by obtaining GPS coordinates of potential, capture point, sentinel site locations through visual remote sensing of artificial water containers using Google Earth. Using a second-order eigenfunction, eigendecomposition, spatial filter algorithm to determine clustering propensities or non-propensities of those mapped potential capture point, sentinel site larval habitats, we were able to eco-cartographically distinguish hot and cold spots on stratified, georeferenced, Land Use Land Cover (LULC) polygons, a Digital Elevation Model (DEM), and a Normalized Difference Vegetation Index (NDVI) map within ArcGIS Pro. The results showed that there was a strong tendency towards clustering (Moran’s I=0.67, p<0.001) and potential habitat hotspots were more likely to occur in urban classified LULC, grid-stratified areas (51.28% and 46.15% of the hotspot locations were in urban commercial and urban residential land covers respectively). Moreover, the georeferenced hotspot locations of potential habitats were found at higher elevations than the coldspots (409.1± 6.112m vs 379.5 ± 21.51m) and the hotspot habitats were closely associated with soil and low vegetation (mean NDVI=0.121 ± 0.0661). When faced with this new vector, these ecological variables can be employed to spatially target and prioritize potential habitats for implementing “Seek and Destroy” larval source management programs.
    },
     year = {2023}
    }
    

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  • TY  - JOUR
    T1  - Mapping Potential Anopheles stephensi Habitats for Implementing “Seek and Destroy” Malaria Larval Source Management in Kwale County, Kenya
    AU  - Ariel Isabelle Burnett
    AU  - Ricardo Izurieta
    AU  - Ismael Hoare
    AU  - Namit Choudhari
    AU  - Jesse Casanova
    AU  - Brooke Yost
    AU  - Charles Mbogo
    AU  - Joseph Mwangangi
    AU  - Martin Rono
    AU  - Anthony Masys
    AU  - Benjamin George Jacob
    Y1  - 2023/11/29
    PY  - 2023
    N1  - https://doi.org/10.11648/j.aje.20230704.11
    DO  - 10.11648/j.aje.20230704.11
    T2  - American Journal of Entomology
    JF  - American Journal of Entomology
    JO  - American Journal of Entomology
    SP  - 120
    EP  - 129
    PB  - Science Publishing Group
    SN  - 2640-0537
    UR  - https://doi.org/10.11648/j.aje.20230704.11
    AB  - We will reveal specific locations of potential habitats of Anopheles stephensi, a new and invasive malaria vector, in Kwale, Kenya. Previous regression models have not been able to locate specific habitats of this malaria vector in Kenya. This publication seeks to determine locations of potential artificial water container habitats of An. stephensi via remote visual detection and determine geo-ecological factors that are associated with those habitats. The preliminary signature mapping of potential habitats was done by obtaining GPS coordinates of potential, capture point, sentinel site locations through visual remote sensing of artificial water containers using Google Earth. Using a second-order eigenfunction, eigendecomposition, spatial filter algorithm to determine clustering propensities or non-propensities of those mapped potential capture point, sentinel site larval habitats, we were able to eco-cartographically distinguish hot and cold spots on stratified, georeferenced, Land Use Land Cover (LULC) polygons, a Digital Elevation Model (DEM), and a Normalized Difference Vegetation Index (NDVI) map within ArcGIS Pro. The results showed that there was a strong tendency towards clustering (Moran’s I=0.67, p<0.001) and potential habitat hotspots were more likely to occur in urban classified LULC, grid-stratified areas (51.28% and 46.15% of the hotspot locations were in urban commercial and urban residential land covers respectively). Moreover, the georeferenced hotspot locations of potential habitats were found at higher elevations than the coldspots (409.1± 6.112m vs 379.5 ± 21.51m) and the hotspot habitats were closely associated with soil and low vegetation (mean NDVI=0.121 ± 0.0661). When faced with this new vector, these ecological variables can be employed to spatially target and prioritize potential habitats for implementing “Seek and Destroy” larval source management programs.
    
    VL  - 7
    IS  - 4
    ER  - 

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Author Information
  • 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

  • School of Geosciences, 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

  • Kenya Medical Research Institute, Nairobi, Kenya

  • Kenya Medical Research Institute, Kilifi, Kenya

  • Kenya Medical Research Institute, Kilifi, Kenya

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

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

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