Highlights► Local topography, Tasselled Cap Greenness and Tasselled Cap Brightness were used to create a landscape map using object-based analysis. ► A multi-scale object-based stratification approach improved accuracy of classification of burrows. ► The burrow maps provide realistic patterns to study the spread and persistence of plague.

Abstract. The prevalence and identity of Rickettsia and Bartonella in urban rat and flea populations were evaluated in Kisangani, Democratic Republic of the Congo (DRC) by molecular tools. An overall prevalence of 17% Bartonella species and 13% Rickettsia typhi, the agent of murine typhus, was found in the cosmopolitan rat species, Rattus rattus and Rattus norvegicus that were infested by a majority of Xenopsylla cheopis fleas. Bartonella queenslandensis, Bartonella elizabethae, and three Bartonella genotypes were identified by sequencing in rat specimens, mostly in R. rattus. Rickettsia typhi was detected in 72% of X. cheopis pools, the main vector and reservoir of this zoonotic pathogen. Co-infections were observed in rodents, suggesting a common mammalian host shared by R. typhi and Bartonella spp. Thus, both infections are endemic in DRC and the medical staffs need to be aware knowing the high prevalence of impoverished populations or immunocompromised inhabitants in this area.

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.

BackgroundPlague (Yersinia pestis infection) is a vector-borne disease which caused millions of human deaths in the Middle Ages. The hosts of plague are mostly rodents, and the disease is spread by the fleas that feed on them. Currently, the disease still circulates amongst sylvatic rodent populations all over the world, including great gerbil (Rhombomys opimus) populations in Central Asia. Great gerbils are social desert rodents that live in family groups in burrows, which are visible on satellite images. In great gerbil populations an abundance threshold exists, above which plague can spread causing epizootics. The spatial distribution of the host species is thought to influence the plague dynamics, such as the direction of plague spread, however no detailed analysis exists on the possible functional or structural corridors and barriers that are present in this population and landscape. This study aims to fill that gap.MethodsThree 20 by 20 km areas with known great gerbil burrow distributions were used to analyse the spatial distribution of the burrows. Object-based image analysis was used to map the landscape at several scales, and was linked to the burrow maps. A novel object-based method was developed – the mean neighbour absolute burrow density difference (MNABDD) – to identify the optimal scale and evaluate the efficacy of using landscape objects as opposed to square cells. Multiple regression using raster maps was used to identify the landscape-ecological variables that explain burrow density best. Functional corridors and barriers were mapped using burrow density thresholds. Cumulative resistance of the burrow distribution to potential disease spread was evaluated using cost distance analysis. A 46-year plague surveillance dataset was used to evaluate whether plague spread was radially symmetric.ResultsThe burrow distribution was found to be non-random and negatively correlated with Greenness, especially in the floodplain areas. Corridors and barriers showed a mostly NWSE alignment, suggesting easier spreading along this axis. This was confirmed by the analysis of the plague data.ConclusionsPlague spread had a predominantly NWSE direction, which is likely due to the NWSE alignment of corridors and barriers in the burrow distribution and the landscape. This finding may improve predictions of plague in the future and emphasizes the importance of including landscape analysis in wildlife disease studies.

Speculation on how the bacterium Yersinia pestis re-emerges after years of absence in the Prebalkhash region in Kazakhstan has been ongoing for half a century, but the mechanism is still unclear. One of the theories is that plague persists in its reservoir host (the great gerbil) in so-called hotspots, i.e. small regions in which the conditions remain favourable for plague to persist during times where the conditions in the Prebalkhash region as a whole have become unfavourable for plague persistence. In this paper we use a metapopulation model that describes the dynamics of the great gerbil. With this model we study the minimum size of an individual hotspot and the combined size of multiple hotspots in the Prebalkhash region that would be required for Y. pestis to persist through an inter-epizootic period. We show that the combined area of hotspots required for plague persistence is so large that it would be unlikely to have been missed by existing plague surveillance. This suggests that persistence of plague in that region cannot solely be explained by the existence of hotspots, and therefore other hypotheses, such as survival in multiple host species, and persistence in fleas or in the soil should be considered as well.

HighlightsOccupancy of great gerbil burrows can be determined from space using high-resolution satellite images.NDVI was successfully used to distinguish between occupied and empty, using the differences in vegetation cover.This finding allows predicting plague outbreaks with much greater ease and accuracy, and for much larger areas, than before.

IntroductionThe wildlife plague system in the Pre-Balkhash desert of Kazakhstan has been a subject of study for many years. Much progress has been made in generating a method of predicting outbreaks of the disease (infection by the gram negative bacterium Yersinia pestis) but existing methods are not yet accurate enough to inform public health planning. The present study aimed to identify characteristics of individual mammalian host (Rhombomys opimus) burrows related to and potentially predictive of the presence of R.opimus and the dominant flea vectors (Xenopsylla spp.).MethodsOver four seasons, burrow characteristics, their current occupancy status, and flea and tick burden of the occupants were recorded in the field. A second data set was generated of long term occupancy trends by recording the occupancy status of specific burrows over multiple occasions. Generalised linear mixed models were constructed to identify potential burrow properties predictive of either occupancy or flea burden.ResultsAt the burrow level, it was identified that a burrow being occupied by Rhombomys, and remaining occupied, were both related to the characteristics of the sediment in which the burrow was constructed. The flea burden of Rhombomys in a burrow was found to be related to the tick burden. Further larger scale properties were also identified as being related to both Rhombomys and flea presence, including latitudinal position and the season.ConclusionsTherefore, in advancing our current predictions of plague in Kazakhstan, we must consider the landscape at this local level to increase our accuracy in predicting the dynamics of gerbil and flea populations. Furthermore this demonstrates that in other zoonotic systems, it may be useful to consider the distribution and location of suitable habitat for both host and vector species at this fine scale to accurately predict future epizootics.