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Topography and land cover of watersheds predicts the distribution of the environmental pathogen Mycobacterium ulcerans in aquatic insects.

Carolan K, Garchitorena A, García-Peña GE, Morris A, Landier J, Fontanet A, Le Gall P, Texier G, Marsollier L, Gozlan RE, Eyangoh S, Lo Seen D, Guégan JF - PLoS Negl Trop Dis (2014)

Bottom Line: This can result in misleading inferences about the distribution of the pathogen, inhibiting our ability to manage the disease.Future studies of M. ulcerans would benefit from consideration of local structure of the local stream network in future sampling, and further work is needed on the reasons for notable differences in the distribution of this species from one region to another.This work represents a first step in the identification of large-scale environmental drivers of this species, for the purposes of disease risk mapping.

View Article: PubMed Central - PubMed

Affiliation: Unité mixte de recherche (UMR) Maladies Infectieuses et Vecteurs: Écologie, Génétique, Evolution, et Contrôle (MIVEGEC) IRD-CNRS-Universities of Montpellier I and II, Centre IRD de Montpellier, Montpellier, France; UMR Territoires, Environnement, Télédétection et Information Spatiale (TETIS) CIRAD, Montpellier, France; Unité d'Epidémiologie de Maladies Emergentes, Institut Pasteur, Paris, France.

ABSTRACT

Background: An understanding of the factors driving the distribution of pathogens is useful in preventing disease. Often we achieve this understanding at a local microhabitat scale; however the larger scale processes are often neglected. This can result in misleading inferences about the distribution of the pathogen, inhibiting our ability to manage the disease. One such disease is Buruli ulcer, an emerging neglected tropical disease afflicting many thousands in Africa, caused by the environmental pathogen Mycobacterium ulcerans. Herein, we aim to describe the larger scale landscape process describing the distribution of M. ulcerans.

Methodology: Following extensive sampling of the community of aquatic macroinvertebrates in Cameroon, we select the 5 dominant insect Orders, and conduct an ecological niche model to describe how the distribution of M. ulcerans positive insects changes according to land cover and topography. We then explore the generalizability of the results by testing them against an independent dataset collected in a second endemic region, French Guiana.

Principal findings: We find that the distribution of the bacterium in Cameroon is accurately described by the land cover and topography of the watershed, that there are notable seasonal differences in distribution, and that the Cameroon model does not predict the distribution of M. ulcerans in French Guiana.

Conclusions/significance: Future studies of M. ulcerans would benefit from consideration of local structure of the local stream network in future sampling, and further work is needed on the reasons for notable differences in the distribution of this species from one region to another. This work represents a first step in the identification of large-scale environmental drivers of this species, for the purposes of disease risk mapping.

No MeSH data available.


Related in: MedlinePlus

Spatial distribution of habitat suitable for M. ulcerans in Akonolinga, Cameroon.Units of habitat suitability are the proportion of qPCR pools predicted to be positive, based on the field work of [30]. Negative values are a result of the normal distribution of the residuals (Figures S4 and S5). The Gaussian wet and dry season models, based on the original 16 sites, are predicted into each of the pour points (where a stream crosses a road) in the region (top row), resulting in the predicted habitat suitability at each point. The pour points are interpolated (bottom row) using IDW fixed distance 0.05 decimal degrees interpolation (ArcMap10.1) resulting in the first map of spatial distribution of M. ulcerans encounter risk.
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pntd-0003298-g003: Spatial distribution of habitat suitable for M. ulcerans in Akonolinga, Cameroon.Units of habitat suitability are the proportion of qPCR pools predicted to be positive, based on the field work of [30]. Negative values are a result of the normal distribution of the residuals (Figures S4 and S5). The Gaussian wet and dry season models, based on the original 16 sites, are predicted into each of the pour points (where a stream crosses a road) in the region (top row), resulting in the predicted habitat suitability at each point. The pour points are interpolated (bottom row) using IDW fixed distance 0.05 decimal degrees interpolation (ArcMap10.1) resulting in the first map of spatial distribution of M. ulcerans encounter risk.

Mentions: The spatial distribution of M. ulcerans suitable habitat in the wet season predicted at the pour points was non-random, based on Moran's I spatial autocorrelation (Moran's Index: 0.21, z-score: 9.1, p<0.00001), positive sites tend to cluster together (Figure 3).


Topography and land cover of watersheds predicts the distribution of the environmental pathogen Mycobacterium ulcerans in aquatic insects.

Carolan K, Garchitorena A, García-Peña GE, Morris A, Landier J, Fontanet A, Le Gall P, Texier G, Marsollier L, Gozlan RE, Eyangoh S, Lo Seen D, Guégan JF - PLoS Negl Trop Dis (2014)

Spatial distribution of habitat suitable for M. ulcerans in Akonolinga, Cameroon.Units of habitat suitability are the proportion of qPCR pools predicted to be positive, based on the field work of [30]. Negative values are a result of the normal distribution of the residuals (Figures S4 and S5). The Gaussian wet and dry season models, based on the original 16 sites, are predicted into each of the pour points (where a stream crosses a road) in the region (top row), resulting in the predicted habitat suitability at each point. The pour points are interpolated (bottom row) using IDW fixed distance 0.05 decimal degrees interpolation (ArcMap10.1) resulting in the first map of spatial distribution of M. ulcerans encounter risk.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4222759&req=5

pntd-0003298-g003: Spatial distribution of habitat suitable for M. ulcerans in Akonolinga, Cameroon.Units of habitat suitability are the proportion of qPCR pools predicted to be positive, based on the field work of [30]. Negative values are a result of the normal distribution of the residuals (Figures S4 and S5). The Gaussian wet and dry season models, based on the original 16 sites, are predicted into each of the pour points (where a stream crosses a road) in the region (top row), resulting in the predicted habitat suitability at each point. The pour points are interpolated (bottom row) using IDW fixed distance 0.05 decimal degrees interpolation (ArcMap10.1) resulting in the first map of spatial distribution of M. ulcerans encounter risk.
Mentions: The spatial distribution of M. ulcerans suitable habitat in the wet season predicted at the pour points was non-random, based on Moran's I spatial autocorrelation (Moran's Index: 0.21, z-score: 9.1, p<0.00001), positive sites tend to cluster together (Figure 3).

Bottom Line: This can result in misleading inferences about the distribution of the pathogen, inhibiting our ability to manage the disease.Future studies of M. ulcerans would benefit from consideration of local structure of the local stream network in future sampling, and further work is needed on the reasons for notable differences in the distribution of this species from one region to another.This work represents a first step in the identification of large-scale environmental drivers of this species, for the purposes of disease risk mapping.

View Article: PubMed Central - PubMed

Affiliation: Unité mixte de recherche (UMR) Maladies Infectieuses et Vecteurs: Écologie, Génétique, Evolution, et Contrôle (MIVEGEC) IRD-CNRS-Universities of Montpellier I and II, Centre IRD de Montpellier, Montpellier, France; UMR Territoires, Environnement, Télédétection et Information Spatiale (TETIS) CIRAD, Montpellier, France; Unité d'Epidémiologie de Maladies Emergentes, Institut Pasteur, Paris, France.

ABSTRACT

Background: An understanding of the factors driving the distribution of pathogens is useful in preventing disease. Often we achieve this understanding at a local microhabitat scale; however the larger scale processes are often neglected. This can result in misleading inferences about the distribution of the pathogen, inhibiting our ability to manage the disease. One such disease is Buruli ulcer, an emerging neglected tropical disease afflicting many thousands in Africa, caused by the environmental pathogen Mycobacterium ulcerans. Herein, we aim to describe the larger scale landscape process describing the distribution of M. ulcerans.

Methodology: Following extensive sampling of the community of aquatic macroinvertebrates in Cameroon, we select the 5 dominant insect Orders, and conduct an ecological niche model to describe how the distribution of M. ulcerans positive insects changes according to land cover and topography. We then explore the generalizability of the results by testing them against an independent dataset collected in a second endemic region, French Guiana.

Principal findings: We find that the distribution of the bacterium in Cameroon is accurately described by the land cover and topography of the watershed, that there are notable seasonal differences in distribution, and that the Cameroon model does not predict the distribution of M. ulcerans in French Guiana.

Conclusions/significance: Future studies of M. ulcerans would benefit from consideration of local structure of the local stream network in future sampling, and further work is needed on the reasons for notable differences in the distribution of this species from one region to another. This work represents a first step in the identification of large-scale environmental drivers of this species, for the purposes of disease risk mapping.

No MeSH data available.


Related in: MedlinePlus