title: Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan.
abstract: 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 bacteriumYersinia 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.
  
  
  
  Kazakhstan.
  
  
  
  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'sKstatistic 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.
  
  
  
  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.
  
  
  
  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.
authors.affiliation: Department of Physical Geography Utrecht University Utrecht The Netherlands; Faculty of Veterinary Medicine Utrecht University Utrecht The Netherlands.
authors.forename: Liesbeth I
authors.initials: LI
authors.lastname: Wilschut
authors.affiliation: Ecology Evolution and Genomics of Infectious Disease Research Group Institute of Integrative Biology The University of Liverpool Liverpool UK.
authors.forename: Anne
authors.initials: A
authors.lastname: Laudisoit
authors.affiliation: Evolutionary Ecology Group Department of Biology University of Antwerp Antwerp Belgium.
authors.forename: Nelika K
authors.initials: NK
authors.lastname: Hughes
authors.affiliation: Department of Physical Geography Utrecht University Utrecht The Netherlands.
authors.forename: Elisabeth A
authors.initials: EA
authors.lastname: Addink
authors.affiliation: Department of Physical Geography Utrecht University Utrecht The Netherlands.
authors.forename: Steven M
authors.initials: SM
authors.lastname: de Jong
authors.affiliation: Faculty of Veterinary Medicine Utrecht University Utrecht The Netherlands.
authors.forename: Hans A P
authors.initials: HA
authors.lastname: Heesterbeek
authors.affiliation: Evolutionary Ecology Group Department of Biology University of Antwerp Antwerp Belgium.
authors.forename: Jonas
authors.initials: J
authors.lastname: Reijniers
authors.affiliation: Ecology Evolution and Genomics of Infectious Disease Research Group Institute of Integrative Biology The University of Liverpool Liverpool UK.
authors.forename: Sally
authors.initials: S
authors.lastname: Eagle
authors.affiliation: Stavropol Plague Control Research Institute Stavropol Russian Federation.
authors.forename: Vladimir M
authors.initials: VM
authors.lastname: Dubyanskiy
authors.affiliation: Ecology Evolution and Genomics of Infectious Disease Research Group Institute of Integrative Biology The University of Liverpool Liverpool UK.
authors.forename: Mike
authors.initials: M
authors.lastname: Begon
keywords: Bubonic plague; GIS; Rhombomys opimus; Yersinia pestis; clustering; desert; infectious disease; landscape epidemiology; rodents; spatial point pattern analysis