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Pattern of tick aggregation on mice: larger than expected distribution tail enhances the spread of tick-borne pathogens.

Ferreri L, Giacobini M, Bajardi P, Bertolotti L, Bolzoni L, Tagliapietra V, Rizzoli A, Rosà R - PLoS Comput. Biol. (2014)

Bottom Line: Moreover, we found that the tail of the distribution significantly changes with seasonal variations in host abundance.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.

View Article: PubMed Central - PubMed

Affiliation: Computational Epidemiology Group, Department of Veterinary Sciences, University of Torino, Torino, Italy; Applied Research on Computational Complex Systems Group, Department of Computer Science, University of Torino, Torino, Italy.

ABSTRACT
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.

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Median (line), interquartile (darker area) and % confidence intervals (lighter area) of the final prevalence as a function of the transmission probability, for different values of  = 2%, 5%, 10%), fraction of nymphs among ticks on a mouse, and by describing the ticks aggregation with the empirical distribution.Other parameters are , .
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pcbi-1003931-g006: Median (line), interquartile (darker area) and % confidence intervals (lighter area) of the final prevalence as a function of the transmission probability, for different values of  = 2%, 5%, 10%), fraction of nymphs among ticks on a mouse, and by describing the ticks aggregation with the empirical distribution.Other parameters are , .

Mentions: To start, we simulated the non-systemic disease spreading of a TBE-like pathogen with a fraction of nymphs among ticks equals to 2%, close to the one observed in our real data (cfr. Table 2), 5%, and 10%, as in literature [8], [40]. We consider the empirical distribution observed on the entire data set. We fixed the number of hosts to which, together with the considered distribution, resulted in a number of vectors pairs equal to . In our simulations, we explored the effects of β, the infection probability, on the observed prevalence at the final time step, , with . (We observed that was larger enough to allow the prevalence to converge toward an endemic pseudo-equilibrium or the disease-free equilibrium). For each we allowed simulations to run starting from an initial prevalence of . In Figure 6 we plotted the prevalences (median value, interquartile intervals and the CI) observed at equilibrium as a function of the transmission probabilities, β. Results showed that the larger the fraction of nymphs among ticks feeding on mice, the larger the probability of pathogen invasion and the infection prevalence.


Pattern of tick aggregation on mice: larger than expected distribution tail enhances the spread of tick-borne pathogens.

Ferreri L, Giacobini M, Bajardi P, Bertolotti L, Bolzoni L, Tagliapietra V, Rizzoli A, Rosà R - PLoS Comput. Biol. (2014)

Median (line), interquartile (darker area) and % confidence intervals (lighter area) of the final prevalence as a function of the transmission probability, for different values of  = 2%, 5%, 10%), fraction of nymphs among ticks on a mouse, and by describing the ticks aggregation with the empirical distribution.Other parameters are , .
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230730&req=5

pcbi-1003931-g006: Median (line), interquartile (darker area) and % confidence intervals (lighter area) of the final prevalence as a function of the transmission probability, for different values of  = 2%, 5%, 10%), fraction of nymphs among ticks on a mouse, and by describing the ticks aggregation with the empirical distribution.Other parameters are , .
Mentions: To start, we simulated the non-systemic disease spreading of a TBE-like pathogen with a fraction of nymphs among ticks equals to 2%, close to the one observed in our real data (cfr. Table 2), 5%, and 10%, as in literature [8], [40]. We consider the empirical distribution observed on the entire data set. We fixed the number of hosts to which, together with the considered distribution, resulted in a number of vectors pairs equal to . In our simulations, we explored the effects of β, the infection probability, on the observed prevalence at the final time step, , with . (We observed that was larger enough to allow the prevalence to converge toward an endemic pseudo-equilibrium or the disease-free equilibrium). For each we allowed simulations to run starting from an initial prevalence of . In Figure 6 we plotted the prevalences (median value, interquartile intervals and the CI) observed at equilibrium as a function of the transmission probabilities, β. Results showed that the larger the fraction of nymphs among ticks feeding on mice, the larger the probability of pathogen invasion and the infection prevalence.

Bottom Line: Moreover, we found that the tail of the distribution significantly changes with seasonal variations in host abundance.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.

View Article: PubMed Central - PubMed

Affiliation: Computational Epidemiology Group, Department of Veterinary Sciences, University of Torino, Torino, Italy; Applied Research on Computational Complex Systems Group, Department of Computer Science, University of Torino, Torino, Italy.

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus