Plague epizootic cycles in Central Asia.

Infection thresholds, widely used in disease epidemiology, may operate on host abundance and, if present, on vector abundance. For wildlife populations, host and vector abundances often vary greatly across years and consequently the threshold may be crossed regularly, both up- and downward. Moreover, vector and host abundances may be interdependent, which may affect the infection dynamics. Theory predicts that if the relevant abundance, or combination of abundances, is above the threshold, then the infection is able to spread; if not, it is bound to fade out. In practice, though, the observed level of infection may depend more on past than on current abundances. Here, we study the temporal dynamics of plague (Yersinia pestis infection), its vector (flea) and its host (great gerbil) in the PreBalkhash region in Kazakhstan. We describe how host and vector abundances interact over time and how this interaction drives the dynamics of the system around the infection threshold, consequently affecting the proportion of plague-infected sectors. We also explore the importance of the interplay between biological and detectability delays in generating the observed dynamics.

A curve of thresholds governs plague epizootics in Central Asia.

A core concept of infectious disease epidemiology is the abundance threshold, below which an infection is unable to invade or persist. There have been contrasting theoretical predictions regarding the nature of this threshold for vector-borne diseases, but for infections with an invertebrate vector, it is common to assume a threshold defined by the ratio of vector and host abundances. Here, we show in contrast, both from field data and model simulations, that for plague (Yersinia pestis) in Kazakhstan, the invasion threshold quantity is based on the product of its host (Rhombomys opimus) and vector (mainly Xenopsylla spp.) abundances, resulting in a combined threshold curve with hyperbolic shape. This shape implies compensation between host and vector abundances in permitting infection, which has important implications for disease control. Realistic joint thresholds, supported by data, should promote improved understanding, prediction and management of disease occurrence in this and other vector-borne disease systems.

Emergence, spread, persistence and fade-out of sylvatic plague in Kazakhstan.

Predicting the dynamics of zoonoses in wildlife is important not only for prevention of transmission to humans, but also for improving the general understanding of epidemiological processes. A large dataset on sylvatic plague in the Pre-Balkhash area of Kazakhstan (collected for surveillance purposes) provides a rare opportunity for detailed statistical modelling of an infectious disease. Previous work using these data has revealed a host abundance threshold for epizootics, and climatic influences on plague prevalence. Here, we present a model describing the local space-time dynamics of the disease at a spatial scale of 20 × 20 km(2) and a biannual temporal scale, distinguishing between invasion and persistence events. We used a Bayesian imputation method to account for uncertainties resulting from poor data in explanatory variables and response variables. Spatial autocorrelation in the data was accounted for in imputations and analyses through random effects. The results show (i) a clear effect of spatial transmission, (ii) a high probability of persistence compared with invasion, and (iii) a stronger influence of rodent abundance on invasion than on persistence. In particular, there was a substantial probability of persistence also at low host abundance.

Statistical analysis of the dynamics of antibody loss to a disease-causing agent: plague in natural populations of great gerbils as an example.

We propose a new stochastic framework for analysing the dynamics of the immunity response of wildlife hosts against a disease-causing agent. Our study is motivated by the need to analyse the monitoring time-series data covering the period from 1975 to 1995 on bacteriological and serological tests-samples from great gerbils being the main host of Yersinia pestis in Kazakhstan. Based on a four-state continuous-time Markov chain, we derive a generalized nonlinear mixed-effect model for analysing the serological test data. The immune response of a host involves the production of antibodies in response to an antigen. Our analysis shows that great gerbils recovered from a plague infection are more likely to keep their antibodies to plague and survive throughout the summer-to-winter season than throughout the winter-to-summer season. Provided the seasonal mortality rates are similar (which seems to be the case based on a mortality analysis with abundance data), our finding indicates that the immune function of the sampled great gerbils is seasonal.

Plague dynamics are driven by climate variation.

The bacterium Yersinia pestis causes bubonic plague. In Central Asia, where human plague is still reported regularly, the bacterium is common in natural populations of great gerbils. By using field data from 1949-1995 and previously undescribed statistical techniques, we show that Y. pestis prevalence in gerbils increases with warmer springs and wetter summers: A 1 degrees C increase in spring is predicted to lead to a >50% increase in prevalence. Climatic conditions favoring plague apparently existed in this region at the onset of the Black Death as well as when the most recent plague pandemic arose in the same region, and they are expected to continue or become more favorable as a result of climate change. Threats of outbreaks may thus be increasing where humans live in close contact with rodents and fleas (or other wildlife) harboring endemic plague.

Predictive thresholds for plague in Kazakhstan.

In Kazakhstan and elsewhere in central Asia, the bacterium Yersinia pestis circulates in natural populations of gerbils, which are the source of human cases of bubonic plague. Our analysis of field data collected between 1955 and 1996 shows that plague invades, fades out, and reinvades in response to fluctuations in the abundance of its main reservoir host, the great gerbil (Rhombomys opimus). This is a rare empirical example of the two types of abundance thresholds for infectious disease-invasion and persistence- operating in a single wildlife population. We parameterized predictive models that should reduce the costs of plague surveillance in central Asia and thereby encourage its continuance.