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

Abstract

AimThe 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.LocationKazakhstan.MethodsBurrows 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.ResultsSignificant 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 conclusionsThese 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.

Small-Scale Die-Offs in Woodrats Support Long-Term Maintenance of Plague in the U.S. Southwest

“…Spatial structure of rodent populations has been recognized as an important factor for the invasion and spread of infectious agents (Rotshild 1975 , Keeling 1999 , Wilschut et al 2015 ). Analyzing the distribution of the burrows of great gerbils ( Rhombomys opimus ) in Kazakhstan, Wilschut et al ( 2015 ) concluded that spatial clustering of occupied burrows should be considered to assess its significance for plague transmission.…”

“…Spatial structure of rodent populations has been recognized as an important factor for the invasion and spread of infectious agents (Rotshild 1975 , Keeling 1999 , Wilschut et al 2015 ). Analyzing the distribution of the burrows of great gerbils ( Rhombomys opimus ) in Kazakhstan, Wilschut et al ( 2015 ) concluded that spatial clustering of occupied burrows should be considered to assess its significance for plague transmission. In another study, an investigation of plague outbreaks in prairie dog ( Cynomys ludovicianus ) populations, the authors argued that plague can persist in the highly susceptible hosts because their movement is very constrained (Salkeld et al 2010 ).…”

Detecting plague-host abundance from space: Using a spectral vegetation index to identify occupancy of great gerbil burrows

“…All squares were located in one so-called ‘sector’ ( Fig. 1 ), a monitoring unit of the plague monitoring stations in Kazakhstan, approximately 9.3 km by 9.8 km in size ( Wilschut et al, 2013b , Wilschut et al, 2015 ). The squares are all located in the older part of the river Ili delta consisting of floodplains covered by river sediments, scattered sand dunes and semi-arid vegetation.…”

Fine-Scale Distribution Patterns of Phragmites australis Populations Across an Environmental Gradient in the Salt Marsh Wetland of Dunhuang, China

“…At present, the methods of studying population spatial patterns include hierarchical analysis of variance, species-juxtaposition and point pattern analysis. Among them, point pattern analysis has been widely used for studying the spatial distribution patterns of plant populations [9,29], animal populations [30,31] and geographical landscapes [32,33].…”