Luca Ferreri

Interplay of network dynamics and heterogeneity of ties on spreading dynamics.

The structure of a network dramatically affects the spreading phenomena unfolding upon it. The contact distribution of the nodes has long been recognized as the key ingredient in influencing the outbreak events. However, limited knowledge is currently available on the role of the weight of the edges on the persistence of a pathogen. At the same time, recent works showed a strong influence of temporal network dynamics on disease spreading. In this work we provide an analytical understanding, corroborated by numerical simulations, about the conditions for infected stable state in weighted networks. In particular, we reveal the role of heterogeneity of edge weights and of the dynamic assignment of weights on the ties in the network in driving the spread of the epidemic. In this context we show that when weights are dynamically assigned to ties in the network, a heterogeneous distribution is able to hamper the diffusion of the disease, contrary to what happens when weights are fixed in time.

Pattern of Tick Aggregation on Mice: Larger Than Expected Distribution Tail Enhances the Spread of Tick-Borne Pathogens

The spread of tick-borne pathogens represents an important threat to human and animal health in many parts of Eurasia. Here, we analysed a 9-year time series of Ixodes ricinus ticks feeding on Apodemus flavicollis mice (main reservoir-competent host for tick-borne encephalitis, TBE) sampled in Trentino (Northern Italy). The tail of the distribution of the number of ticks per host was fitted by three theoretical distributions: Negative Binomial (NB), Poisson-LogNormal (PoiLN), and Power-Law (PL). The fit with theoretical distributions indicated that the tail of the tick infestation pattern on mice is better described by the PL distribution. Moreover, we found that the tail of the distribution significantly changes with seasonal variations in host abundance. In order to investigate the effect of different tails of tick distribution on the invasion of a non-systemically transmitted pathogen, we simulated the transmission of a TBE-like virus between susceptible and infective ticks using a stochastic model. Model simulations indicated different outcomes of disease spreading when considering different distribution laws of ticks among hosts. Specifically, we found that the epidemic threshold and the prevalence equilibria obtained in epidemiological simulations with PL distribution are a good approximation of those observed in simulations feed by the empirical distribution. Moreover, we also found that the epidemic threshold for disease invasion was lower when considering the seasonal variation of tick aggregation.

Do diseases spreading on bipartite networks have some evolutionary advantage

In this work we analyze the complexity of a disease that spreads among two populations and in which the transmission routes are available only throught individuals of the two different families. This peculiar route is typical of diseases such as sexual transmitted diseases on heterosexual populations or vector-host diseases such as tick-borne encephalitis or Lyme borreliosis. In such epidemiological scenarios, the contact network is naturally represented by a bipartite graphs. In this article we determine that a pathogen agent spreading on a bipartite network can have some evolutionary benefits with respect to diffusing on standard unipartite networks.

Non-systemic transmission of tick-borne diseases: a network approach.

Abstract Tick-borne diseases can be transmitted via non-systemic (NS) transmission. This occurs when tick gets the infection by co-feeding with infected ticks on the same host resulting in a direct pathogen transmission between the vectors, without infecting the host. This transmission is peculiar, as it does not require any systemic infection of the host. The NS transmission is the main efficient transmission for the persistence of the tick-borne encephalitis virus in nature. By describing the heterogeneous ticks aggregation on hosts through a bipartite graphs representation, we are able to mathematically define the NS transmission and to depict the epidemiological conditions for the pathogen persistence. Despite the fact that the underlying network is largely fragmented, analytical and computational results show that the larger is the variability of the aggregation, and the easier is for the pathogen to persist in the population.

A CAEV epidemiological model for goat breeding

A model for the genotype B Caprine Arthritis Encephalitis virus disease is presented.Only endemic and disease-free equilibria arise, and a transcritical bifurcation.Eradication is possible only for very small economically unaffordable herds.In absence of vaccination new strategies for fighting the disease are needed. In this paper we analyze the Caprine Arthritis Encephalitis virus disease. We construct a very general model for its epidemiology, for the case when the disease is caused only by a specific viral strain, called the genotype B. The model has only the endemic and the disease-free equilibria, with a transcritical bifurcation connecting the two. Eradication based on this analysis is possible only for very small herds, so that it can hardly be considered economically affordable. The study suggests that in absence of control measures new means of fighting the disease are needed, paving the road for further theoretical and field work.

Modeling the effects of variable feeding patterns of larval ticks on the transmission of Borrelia lusitaniae and Borrelia afzelii

Spirochetes belonging to the Borrelia burgdoferi sensu lato (sl) group cause Lyme Borreliosis (LB), which is the most commonly reported vector-borne zoonosis in Europe. B. burgdorferi sl is maintained in nature in a complex cycle involving Ixodes ricinus ticks and several species of vertebrate hosts. The transmission dynamics of B. burgdorferi sl is complicated by the varying competence of animals for different genospecies of spirochetes that, in turn, vary in their capability of causing disease. In this study, a set of difference equations simplifying the complex interaction between vectors and their hosts (competent and not for Borrelia) is built to gain insights into conditions underlying the dominance of B. lusitaniae (transmitted by lizards to susceptible ticks) and the maintenance of B. afzelii (transmitted by wild rodents) observed in a study area in Tuscany, Italy. Findings, in agreement with field observations, highlight the existence of a threshold for the fraction of larvae feeding on rodents below which the persistence of B. afzelii is not possible. Furthermore, thresholds change as nonlinear functions of the expected number of nymph bites on mice, and the transmission and recovery probabilities. In conclusion, our model provided an insight into mechanisms underlying the relative frequency of different Borrelia genospecies, as observed in field studies.

Sport, how people choose it: A network analysis approach

Abstract In order to investigate the behaviour of athletes in choosing sports, we analyse data from part of the We-Sport® database, a vertical social network that links athletes through sports. In particular, we explore connections between people sharing common sports and the role of age and gender by applying “network science” approaches and methods. The results show a disassortative tendency of athletes in choosing sports, a negative correlation between age and number of chosen sports and a positive correlation between age of connected athletes. Some interesting patterns of connection between age classes are depicted. In addition, we propose a method to classify sports, based on the analyses of the behaviour of people practising them. Thanks to this brand new classifications, we highlight the links of class of sports and their unexpected features. We emphasise some gender dependency affinity in choosing sport classes.