An exact relationship between invasion probability and endemic prevalence for Markovian SIS dynamics on networks.
An exact relationship between invasion probability and endemic prevalence for Markovian SIS dynamics on networks.
复制标题
Markovian SIS动力学在网络上的入侵概率与流行率之间的确切关系。
DOI：
10.1371/journal.pone.0069028
复制
发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Sharkey KJ
中科院分区：
文献类型：
--
作者：
Wilkinson RR;Sharkey KJ
理解代表传染性病原体入侵基于网络的系统的模型可以对许多现实世界的情况提供重要的见解，包括预防和控制传染病和计算机病毒。在这里，我们考虑马尔可夫易感传染病（SIS）有限强连接网络的动力学，适用于几种性传播疾病和计算机病毒。在这种情况下，地方病流行率的理论定义很容易通过准平稳分布（QSD）获得。通过将模型表示为一个渗流过程，并利用对偶的性质，我们还提供了入侵概率的理论定义。然后，我们表明，对于无向网络，从任何给定的个人入侵的概率等于（概率）地方病流行率，成功入侵后，在个人（我们也提供了一个有向的情况下的关系）。因此，人群中的总（分数）地方病流行率等于平均入侵概率（在所有个体中）。因此，对于这样的系统，已经支持高水平感染的区域或个体很可能是另一种感染因子成功入侵的来源。当出现新出现的传染病威胁时，这可用于为有针对性的干预措施提供信息。
Understanding models which represent the invasion of network-based systems by infectious agents can give important insights into many real-world situations, including the prevention and control of infectious diseases and computer viruses. Here we consider Markovian susceptible-infectious-susceptible (SIS) dynamics on finite strongly connected networks, applicable to several sexually transmitted diseases and computer viruses. In this context, a theoretical definition of endemic prevalence is easily obtained via the quasi-stationary distribution (QSD). By representing the model as a percolation process and utilising the property of duality, we also provide a theoretical definition of invasion probability. We then show that, for undirected networks, the probability of invasion from any given individual is equal to the (probabilistic) endemic prevalence, following successful invasion, at the individual (we also provide a relationship for the directed case). The total (fractional) endemic prevalence in the population is thus equal to the average invasion probability (across all individuals). Consequently, for such systems, the regions or individuals already supporting a high level of infection are likely to be the source of a successful invasion by another infectious agent. This could be used to inform targeted interventions when there is a threat from an emerging infectious disease.
登录
查看更多内容
DOI：
10.1098/rstb.1994.0028
发表时间：
1994-02-28
期刊：
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY OF LONDON SERIES B-BIOLOGICAL SCIENCES
影响因子：
--
作者：
DURRETT, R;LEVIN, SA
通讯作者：
LEVIN, SA
影响因子：
2.3
作者：
Chatterjee, Shirshendu;Durrett, Rick
通讯作者：
Durrett, Rick
DOI：
10.1098/rstb.1986.0072
发表时间：
1986-12-15
影响因子：
6.3
作者：
ANDERSON, RM;MAY, RM
通讯作者：
MAY, RM
影响因子：
2.4
作者：
Kenah, Eben;Robins, James M.
通讯作者：
Robins, James M.
影响因子：
3.9
作者：
Jonkers, A. R. T.;Sharkey, K. J.;Christley, R. M.
通讯作者：
Christley, R. M.