Ecological niche modeling of Aedes mosquito vectors of chikungunya virus in southeastern Senegal

Rebecca Richman, Diawo Diallo, Mawlouth Diallo, Amadou A. Sall, Oumar Faye, Cheikh T. Diagne, Ibrahima Dia, Scott Weaver, Kathryn A. Hanley, Michaela Buenemann

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Background: Chikungunya virus (CHIKV) originated in a sylvatic cycle of transmission between non-human animal hosts and vector mosquitoes in the forests of Africa. Subsequently the virus jumped out of this ancestral cycle into a human-endemic transmission cycle vectored by anthropophilic mosquitoes. Sylvatic CHIKV cycles persist in Africa and continue to spill over into humans, creating the potential for new CHIKV strains to enter human-endemic transmission. To mitigate such spillover, it is first necessary to delineate the distributions of the sylvatic mosquito vectors of CHIKV, to identify the environmental factors that shape these distributions, and to determine the association of mosquito presence with key drivers of virus spillover, including mosquito and CHIKV abundance. We therefore modeled the distribution of seven CHIKV mosquito vectors over two sequential rainy seasons in Kédougou, Senegal using Maxent. Methods: Mosquito data were collected in fifty sites distributed in five land cover classes across the study area. Environmental data representing land cover, topographic, and climatic factors were included in the models. Models were compared and evaluated using area under the receiver operating characteristic curve (AUROC) statistics. The correlation of model outputs with abundance of individual mosquito species as well as CHIKV-positive mosquito pools was tested. Results: Fourteen models were produced and evaluated; the environmental variables most strongly associated with mosquito distributions were distance to large patches of forest, landscape patch size, rainfall, and the normalized difference vegetation index (NDVI). Seven models were positively correlated with mosquito abundance and one (Aedes taylori) was consistently, positively correlated with CHIKV-positive mosquito pools. Eight models predicted high relative occurrence rates of mosquitoes near the villages of Tenkoto and Ngary, the areas with the highest frequency of CHIKV-positive mosquito pools. Conclusions: Of the environmental factors considered here, landscape fragmentation and configuration had the strongest influence on mosquito distributions. Of the mosquito species modeled, the distribution of Ae. taylori correlated most strongly with abundance of CHIKV, suggesting that presence of this species will be a useful predictor of sylvatic CHIKV presence.

Original languageEnglish (US)
Article number255
JournalParasites and Vectors
Volume11
Issue number1
DOIs
StatePublished - Apr 19 2018

Fingerprint

Chikungunya virus
Senegal
Aedes
Culicidae
Mosquito Vectors
Viruses
ROC Curve

Keywords

  • Aedes
  • Arbovirus
  • Chikungunya virus
  • Ecological niche model
  • Environmental factors
  • Maxent
  • Mosquitoes
  • Senegal

ASJC Scopus subject areas

  • Parasitology
  • Infectious Diseases

Cite this

Richman, R., Diallo, D., Diallo, M., Sall, A. A., Faye, O., Diagne, C. T., ... Buenemann, M. (2018). Ecological niche modeling of Aedes mosquito vectors of chikungunya virus in southeastern Senegal. Parasites and Vectors, 11(1), [255]. https://doi.org/10.1186/s13071-018-2832-6

Ecological niche modeling of Aedes mosquito vectors of chikungunya virus in southeastern Senegal. / Richman, Rebecca; Diallo, Diawo; Diallo, Mawlouth; Sall, Amadou A.; Faye, Oumar; Diagne, Cheikh T.; Dia, Ibrahima; Weaver, Scott; Hanley, Kathryn A.; Buenemann, Michaela.

In: Parasites and Vectors, Vol. 11, No. 1, 255, 19.04.2018.

Research output: Contribution to journalArticle

Richman, R, Diallo, D, Diallo, M, Sall, AA, Faye, O, Diagne, CT, Dia, I, Weaver, S, Hanley, KA & Buenemann, M 2018, 'Ecological niche modeling of Aedes mosquito vectors of chikungunya virus in southeastern Senegal', Parasites and Vectors, vol. 11, no. 1, 255. https://doi.org/10.1186/s13071-018-2832-6
Richman, Rebecca ; Diallo, Diawo ; Diallo, Mawlouth ; Sall, Amadou A. ; Faye, Oumar ; Diagne, Cheikh T. ; Dia, Ibrahima ; Weaver, Scott ; Hanley, Kathryn A. ; Buenemann, Michaela. / Ecological niche modeling of Aedes mosquito vectors of chikungunya virus in southeastern Senegal. In: Parasites and Vectors. 2018 ; Vol. 11, No. 1.
@article{8d709646bfe74fdf9ed0d307f859151c,
title = "Ecological niche modeling of Aedes mosquito vectors of chikungunya virus in southeastern Senegal",
abstract = "Background: Chikungunya virus (CHIKV) originated in a sylvatic cycle of transmission between non-human animal hosts and vector mosquitoes in the forests of Africa. Subsequently the virus jumped out of this ancestral cycle into a human-endemic transmission cycle vectored by anthropophilic mosquitoes. Sylvatic CHIKV cycles persist in Africa and continue to spill over into humans, creating the potential for new CHIKV strains to enter human-endemic transmission. To mitigate such spillover, it is first necessary to delineate the distributions of the sylvatic mosquito vectors of CHIKV, to identify the environmental factors that shape these distributions, and to determine the association of mosquito presence with key drivers of virus spillover, including mosquito and CHIKV abundance. We therefore modeled the distribution of seven CHIKV mosquito vectors over two sequential rainy seasons in K{\'e}dougou, Senegal using Maxent. Methods: Mosquito data were collected in fifty sites distributed in five land cover classes across the study area. Environmental data representing land cover, topographic, and climatic factors were included in the models. Models were compared and evaluated using area under the receiver operating characteristic curve (AUROC) statistics. The correlation of model outputs with abundance of individual mosquito species as well as CHIKV-positive mosquito pools was tested. Results: Fourteen models were produced and evaluated; the environmental variables most strongly associated with mosquito distributions were distance to large patches of forest, landscape patch size, rainfall, and the normalized difference vegetation index (NDVI). Seven models were positively correlated with mosquito abundance and one (Aedes taylori) was consistently, positively correlated with CHIKV-positive mosquito pools. Eight models predicted high relative occurrence rates of mosquitoes near the villages of Tenkoto and Ngary, the areas with the highest frequency of CHIKV-positive mosquito pools. Conclusions: Of the environmental factors considered here, landscape fragmentation and configuration had the strongest influence on mosquito distributions. Of the mosquito species modeled, the distribution of Ae. taylori correlated most strongly with abundance of CHIKV, suggesting that presence of this species will be a useful predictor of sylvatic CHIKV presence.",
keywords = "Aedes, Arbovirus, Chikungunya virus, Ecological niche model, Environmental factors, Maxent, Mosquitoes, Senegal",
author = "Rebecca Richman and Diawo Diallo and Mawlouth Diallo and Sall, {Amadou A.} and Oumar Faye and Diagne, {Cheikh T.} and Ibrahima Dia and Scott Weaver and Hanley, {Kathryn A.} and Michaela Buenemann",
year = "2018",
month = "4",
day = "19",
doi = "10.1186/s13071-018-2832-6",
language = "English (US)",
volume = "11",
journal = "Parasites and Vectors",
issn = "1756-3305",
publisher = "BioMed Central",
number = "1",

}

TY - JOUR

T1 - Ecological niche modeling of Aedes mosquito vectors of chikungunya virus in southeastern Senegal

AU - Richman, Rebecca

AU - Diallo, Diawo

AU - Diallo, Mawlouth

AU - Sall, Amadou A.

AU - Faye, Oumar

AU - Diagne, Cheikh T.

AU - Dia, Ibrahima

AU - Weaver, Scott

AU - Hanley, Kathryn A.

AU - Buenemann, Michaela

PY - 2018/4/19

Y1 - 2018/4/19

N2 - Background: Chikungunya virus (CHIKV) originated in a sylvatic cycle of transmission between non-human animal hosts and vector mosquitoes in the forests of Africa. Subsequently the virus jumped out of this ancestral cycle into a human-endemic transmission cycle vectored by anthropophilic mosquitoes. Sylvatic CHIKV cycles persist in Africa and continue to spill over into humans, creating the potential for new CHIKV strains to enter human-endemic transmission. To mitigate such spillover, it is first necessary to delineate the distributions of the sylvatic mosquito vectors of CHIKV, to identify the environmental factors that shape these distributions, and to determine the association of mosquito presence with key drivers of virus spillover, including mosquito and CHIKV abundance. We therefore modeled the distribution of seven CHIKV mosquito vectors over two sequential rainy seasons in Kédougou, Senegal using Maxent. Methods: Mosquito data were collected in fifty sites distributed in five land cover classes across the study area. Environmental data representing land cover, topographic, and climatic factors were included in the models. Models were compared and evaluated using area under the receiver operating characteristic curve (AUROC) statistics. The correlation of model outputs with abundance of individual mosquito species as well as CHIKV-positive mosquito pools was tested. Results: Fourteen models were produced and evaluated; the environmental variables most strongly associated with mosquito distributions were distance to large patches of forest, landscape patch size, rainfall, and the normalized difference vegetation index (NDVI). Seven models were positively correlated with mosquito abundance and one (Aedes taylori) was consistently, positively correlated with CHIKV-positive mosquito pools. Eight models predicted high relative occurrence rates of mosquitoes near the villages of Tenkoto and Ngary, the areas with the highest frequency of CHIKV-positive mosquito pools. Conclusions: Of the environmental factors considered here, landscape fragmentation and configuration had the strongest influence on mosquito distributions. Of the mosquito species modeled, the distribution of Ae. taylori correlated most strongly with abundance of CHIKV, suggesting that presence of this species will be a useful predictor of sylvatic CHIKV presence.

AB - Background: Chikungunya virus (CHIKV) originated in a sylvatic cycle of transmission between non-human animal hosts and vector mosquitoes in the forests of Africa. Subsequently the virus jumped out of this ancestral cycle into a human-endemic transmission cycle vectored by anthropophilic mosquitoes. Sylvatic CHIKV cycles persist in Africa and continue to spill over into humans, creating the potential for new CHIKV strains to enter human-endemic transmission. To mitigate such spillover, it is first necessary to delineate the distributions of the sylvatic mosquito vectors of CHIKV, to identify the environmental factors that shape these distributions, and to determine the association of mosquito presence with key drivers of virus spillover, including mosquito and CHIKV abundance. We therefore modeled the distribution of seven CHIKV mosquito vectors over two sequential rainy seasons in Kédougou, Senegal using Maxent. Methods: Mosquito data were collected in fifty sites distributed in five land cover classes across the study area. Environmental data representing land cover, topographic, and climatic factors were included in the models. Models were compared and evaluated using area under the receiver operating characteristic curve (AUROC) statistics. The correlation of model outputs with abundance of individual mosquito species as well as CHIKV-positive mosquito pools was tested. Results: Fourteen models were produced and evaluated; the environmental variables most strongly associated with mosquito distributions were distance to large patches of forest, landscape patch size, rainfall, and the normalized difference vegetation index (NDVI). Seven models were positively correlated with mosquito abundance and one (Aedes taylori) was consistently, positively correlated with CHIKV-positive mosquito pools. Eight models predicted high relative occurrence rates of mosquitoes near the villages of Tenkoto and Ngary, the areas with the highest frequency of CHIKV-positive mosquito pools. Conclusions: Of the environmental factors considered here, landscape fragmentation and configuration had the strongest influence on mosquito distributions. Of the mosquito species modeled, the distribution of Ae. taylori correlated most strongly with abundance of CHIKV, suggesting that presence of this species will be a useful predictor of sylvatic CHIKV presence.

KW - Aedes

KW - Arbovirus

KW - Chikungunya virus

KW - Ecological niche model

KW - Environmental factors

KW - Maxent

KW - Mosquitoes

KW - Senegal

UR - http://www.scopus.com/inward/record.url?scp=85045691783&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85045691783&partnerID=8YFLogxK

U2 - 10.1186/s13071-018-2832-6

DO - 10.1186/s13071-018-2832-6

M3 - Article

VL - 11

JO - Parasites and Vectors

JF - Parasites and Vectors

SN - 1756-3305

IS - 1

M1 - 255

ER -