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Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan

AIM: The spatial structure of a population can strongly influence the dynamics of infectious diseases, yet rarely is the underlying structure quantified. A case in point is plague, an infectious zoonotic disease caused by the bacterium Yersinia pestis. Plague dynamics within the Central Asian desert...

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Autores principales: Wilschut, Liesbeth I., Laudisoit, Anne, Hughes, Nelika K., Addink, Elisabeth A., de Jong, Steven M., Heesterbeek, Hans A.P., Reijniers, Jonas, Eagle, Sally, Dubyanskiy, Vladimir M., Begon, Mike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4737218/
https://www.ncbi.nlm.nih.gov/pubmed/26877580
http://dx.doi.org/10.1111/jbi.12534
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author Wilschut, Liesbeth I.
Laudisoit, Anne
Hughes, Nelika K.
Addink, Elisabeth A.
de Jong, Steven M.
Heesterbeek, Hans A.P.
Reijniers, Jonas
Eagle, Sally
Dubyanskiy, Vladimir M.
Begon, Mike
author_facet Wilschut, Liesbeth I.
Laudisoit, Anne
Hughes, Nelika K.
Addink, Elisabeth A.
de Jong, Steven M.
Heesterbeek, Hans A.P.
Reijniers, Jonas
Eagle, Sally
Dubyanskiy, Vladimir M.
Begon, Mike
author_sort Wilschut, Liesbeth I.
collection PubMed
description AIM: The spatial structure of a population can strongly influence the dynamics of infectious diseases, yet rarely is the underlying structure quantified. A case in point is plague, an infectious zoonotic disease caused by the bacterium Yersinia pestis. Plague dynamics within the Central Asian desert plague focus have been extensively modelled in recent years, but always with strong uniformity assumptions about the distribution of its primary reservoir host, the great gerbil (Rhombomys opimus). Yet, while clustering of this species’ burrows due to social or ecological processes could have potentially significant effects on model outcomes, there is currently nothing known about the spatial distribution of inhabited burrows. Here, we address this knowledge gap by describing key aspects of the spatial patterns of great gerbil burrows in Kazakhstan. LOCATION: Kazakhstan. METHODS: Burrows were classified as either occupied or empty in 98 squares of four different sizes: 200 m (side length), 250 m, 500 m and 590–1020 m. We used Ripley's K statistic to determine whether and at what scale there was clustering of occupied burrows, and semi‐variograms to quantify spatial patterns in occupied burrows at scales of 250 m to 9 km. RESULTS: Significant spatial clustering of occupied burrows occurred in 25% and 75% of squares of 500 m and 590–1020 m, respectively, but not in smaller squares. In clustered squares, the clustering criterion peaked around 250 m. Semi‐variograms showed that burrow density was auto‐correlated up to a distance of 7 km and occupied density up to 2.5 km. MAIN CONCLUSIONS: These results demonstrate that there is statistically significant spatial clustering of occupied burrows and that the uniformity assumptions of previous plague models should be reconsidered to assess its significance for plague transmission. This field evidence will allow for more realistic approaches to disease ecology models for both this system and for other structured host populations.
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spelling pubmed-47372182016-02-11 Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan Wilschut, Liesbeth I. Laudisoit, Anne Hughes, Nelika K. Addink, Elisabeth A. de Jong, Steven M. Heesterbeek, Hans A.P. Reijniers, Jonas Eagle, Sally Dubyanskiy, Vladimir M. Begon, Mike J Biogeogr Species Distribution Models and Analyses AIM: The spatial structure of a population can strongly influence the dynamics of infectious diseases, yet rarely is the underlying structure quantified. A case in point is plague, an infectious zoonotic disease caused by the bacterium Yersinia pestis. Plague dynamics within the Central Asian desert plague focus have been extensively modelled in recent years, but always with strong uniformity assumptions about the distribution of its primary reservoir host, the great gerbil (Rhombomys opimus). Yet, while clustering of this species’ burrows due to social or ecological processes could have potentially significant effects on model outcomes, there is currently nothing known about the spatial distribution of inhabited burrows. Here, we address this knowledge gap by describing key aspects of the spatial patterns of great gerbil burrows in Kazakhstan. LOCATION: Kazakhstan. METHODS: Burrows were classified as either occupied or empty in 98 squares of four different sizes: 200 m (side length), 250 m, 500 m and 590–1020 m. We used Ripley's K statistic to determine whether and at what scale there was clustering of occupied burrows, and semi‐variograms to quantify spatial patterns in occupied burrows at scales of 250 m to 9 km. RESULTS: Significant spatial clustering of occupied burrows occurred in 25% and 75% of squares of 500 m and 590–1020 m, respectively, but not in smaller squares. In clustered squares, the clustering criterion peaked around 250 m. Semi‐variograms showed that burrow density was auto‐correlated up to a distance of 7 km and occupied density up to 2.5 km. MAIN CONCLUSIONS: These results demonstrate that there is statistically significant spatial clustering of occupied burrows and that the uniformity assumptions of previous plague models should be reconsidered to assess its significance for plague transmission. This field evidence will allow for more realistic approaches to disease ecology models for both this system and for other structured host populations. John Wiley and Sons Inc. 2015-05-19 2015-07 /pmc/articles/PMC4737218/ /pubmed/26877580 http://dx.doi.org/10.1111/jbi.12534 Text en © 2015 The Authors. Journal of Biogeography Published by John Wiley & Sons Ltd This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Species Distribution Models and Analyses
Wilschut, Liesbeth I.
Laudisoit, Anne
Hughes, Nelika K.
Addink, Elisabeth A.
de Jong, Steven M.
Heesterbeek, Hans A.P.
Reijniers, Jonas
Eagle, Sally
Dubyanskiy, Vladimir M.
Begon, Mike
Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan
title Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan
title_full Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan
title_fullStr Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan
title_full_unstemmed Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan
title_short Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan
title_sort spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in kazakhstan
topic Species Distribution Models and Analyses
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4737218/
https://www.ncbi.nlm.nih.gov/pubmed/26877580
http://dx.doi.org/10.1111/jbi.12534
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