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

Ariel Isabelle Burnett; Ricardo Izurieta; Ismael Hoare; Namit Choudhari; Jesse Casanova; Brooke Yost; Charles Mbogo; Joseph Mwangangi; Martin Rono; Anthony Masys; Benjamin George Jacob

doi:doi:10.11648/j.aje.20230704.11

Research Article |

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

Ariel Isabelle Burnett^*, Ricardo Izurieta, Ismael Hoare, Namit Choudhari, Jesse Casanova, Brooke Yost, Charles Mbogo, Joseph Mwangangi, Martin Rono, Anthony Masys, Benjamin George Jacob

Published in American Journal of Entomology (Volume 7, Issue 4)

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), 2024. 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.
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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

Ariel Isabelle Burnett

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

Contact Email
Ricardo Izurieta

College of Public Health, University of South Florida, Tampa, USA
Ismael Hoare

College of Public Health, University of South Florida, Tampa, USA
Namit Choudhari

School of Geosciences, University of South Florida, Tampa, USA
Jesse Casanova

USF Health International, University of South Florida, Tampa, USA
Brooke Yost

College of Public Health, University of South Florida, Tampa, USA
Charles Mbogo

Kenya Medical Research Institute, Nairobi, Kenya
Joseph Mwangangi

Kenya Medical Research Institute, Kilifi, Kenya
Martin Rono

Kenya Medical Research Institute, Kilifi, Kenya
Anthony Masys

College of Public Health, University of South Florida, Tampa, USA
Benjamin George Jacob

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

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Plain Text BibTeX RIS

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

Copy | Download

@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}
}

Copy | Download

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  -

Copy | Download