Ferreri Luca, Giacobini Mario, Bajardi Paolo, Bertolotti Luigi, Bolzoni Luca, Tagliapietra Valentina, Rizzoli Annapaola, Rosà Roberto
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.
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; Complex Systems Unit, Molecular Biotechnology Centre, University of Torino, Torino, Italy.
PLoS Comput Biol. 2014 Nov 13;10(11):e1003931. doi: 10.1371/journal.pcbi.1003931. eCollection 2014 Nov.
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.
蜱传病原体的传播对欧亚大陆许多地区的人类和动物健康构成了重大威胁。在此,我们分析了在意大利北部特伦蒂诺采集的以黄颈姬鼠(蜱传脑炎的主要储存宿主)为食的蓖麻硬蜱的9年时间序列。每个宿主上蜱数量分布的尾部由三种理论分布拟合:负二项分布(NB)、泊松对数正态分布(PoiLN)和幂律分布(PL)。与理论分布的拟合表明,小鼠蜱感染模式的尾部用PL分布能更好地描述。此外,我们发现分布的尾部会随着宿主数量的季节变化而显著改变。为了研究蜱分布的不同尾部对非系统传播病原体入侵的影响,我们使用随机模型模拟了一种类似蜱传脑炎病毒在易感蜱和感染性蜱之间的传播。模型模拟表明,在考虑宿主间蜱的不同分布规律时,疾病传播会有不同结果。具体而言,我们发现在用PL分布进行的流行病学模拟中获得的流行阈值和患病率平衡点与由经验分布提供的模拟中观察到的结果非常接近。此外,我们还发现,考虑蜱聚集的季节变化时,疾病入侵的流行阈值较低。