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第14行： − + − 在流行病传播研究中，若已知传播的平均速率，则对传播过程作泊松近似可能存在合理的情况（Lambiotte等人，2013），但这种假设在大多数疾病的传播中并不合理，例如实证中感染时间的分布通常是具有一个以平均值为中心的峰，同时显示出明显的非指数尾巴（Blythe和Anderson，1988）。此外，最近关于个体之间的社交和通信交流的相关文献也观察到事件发生时间的间隔具有长尾特征，激发了人们对非指数传播过程研究的兴趣。若事件发生时间间隔所服从的分布不为指数分布，即传播过程为非泊松过程，则其传播过程具有记忆性，也即为非马尔科夫过程。+ + +
→非马尔科夫疾病传播
== 非马尔科夫疾病传播 ==
== 非马尔科夫疾病传播 ==
While the Poisson approximation may be justified when only the average rates are known <ref name=Lambiotte2013>Lambiotte R, Tabourier L, Delvenne J C. Burstiness and spreading on temporal networks[J]. The European Physical Journal B, 2013, 86(7): 320.</ref>, it is at odds with empirical evidence for the time duration of the infective period in most diseases <ref name=Blythe1988>Blythe S P, Anderson R M. Variable infectiousness in HFV transmission models[J]. Mathematical Medicine and Biology: A Journal of the IMA, 1988, 5(3): 181-200.</ref>, whose distribution usually features a peak centered on the average value but exhibits strongly nonexponential tails. Furthermore, the interest in nonexponential transmission processes has also been fueled by the recent evidence on the patterns of social and communication contacts between individuals, which have been observed to be ruled by heavy-tailed distributions of interevent times.
While the Poisson approximation may be justified when only the average rates are known <ref name=Lambiotte2013></ref>, it is at odds with empirical evidence for the time duration of the infective period in most diseases <ref name=Blythe1988></ref>, whose distribution usually features a peak centered on the average value but exhibits strongly nonexponential tails. Furthermore, the interest in nonexponential transmission processes has also been fueled by the recent evidence on the patterns of social and communication contacts between individuals, which have been observed to be ruled by heavy-tailed distributions of interevent times.
在传播研究中，当平均传播速率已知时，则对传播过程作泊松近似，可能是合理的（Lambiotte等人，2013）<ref name=Lambiotte2013>Lambiotte R, Tabourier L, Delvenne J C. Burstiness and spreading on temporal networks[J]. The European Physical Journal B, 2013, 86(7): 320.</ref>，但实际情况并非如此，实证的感染时间的分布特征，通常具有一个以平均值为中心的峰，同时显示出明显的非指数尾巴（Blythe和Anderson，1988）<ref name=Blythe1988>Blythe S P, Anderson R M. Variable infectiousness in HFV transmission models[J]. Mathematical Medicine and Biology: A Journal of the IMA, 1988, 5(3): 181-200.</ref>。此外，关于个体之间的社交和通信交流的模式，最近的证据，也观察到事件发生时间的间隔具有长尾特征，激发了人们对非指数传播过程研究的兴趣。
若事件发生时间间隔所服从的分布不为指数分布，即传播过程为非泊松过程，则其传播过程具有记忆性，也即为非马尔科夫过程。