Adaptive Dynamics of Infectious Diseases: Contact Networks and the Evolution of Virulence
Adaptive Dynamics of Infectious Diseases: Contact Networks and the Evolution of Virulence
复制标题
传染病的适应性动力学：接触网络和毒力的进化
DOI：
10.1017/cbo9780511525728.010
复制
发表时间：
2002
期刊：
影响因子：
56.9
通讯作者：
M. Baalen
中科院分区：
文献类型：
--
作者：
M. Baalen
毒力管理可以定义为一组政策，不仅旨在最大限度地减少寄生虫对其宿主种群的短期影响（例如，发病率，死亡率和发病率），但也要考虑这些寄生虫的进化反应的长期后果，例如通过采取措施，选择毒性较低的菌株。与毒力管理范围有关的一个重要问题涉及宿主种群中接触结构的影响。为了成功传播，许多寄生虫需要它们感染的宿主和新的易感宿主之间的密切接触。因此，他们在东道国人口中的社会联系网络至关重要。已经很清楚，不同结构的网络导致不同类型的流行病学（Keeling 1999）。例如，稀疏连接的宿主种群比密集连接的宿主种群更难入侵。但是，它们的宿主种群的接触结构会在多大程度上影响寄生虫的进化，特别是它们的毒力？我们能通过改变这些接触结构来改变寄生虫的选择压力吗？Claessen和de鲁什（1995）以及兰德等人（1995）对空间结构化的宿主种群中进化的寄生虫进行了计算机模拟，并得出结论认为，相对于充分混合的系统，毒性较小（低毒性）的寄生虫更受青睐。显然，寄生虫的进化确实取决于宿主的种群结构。然而，对人口结构的相关方面，即社交网络，仍然缺乏定性的了解（Wallinga等人，1999年）。社交联系人的网络可以以多种方式变化。首先，每个主机的社交联系的数量可能会有所不同（在主机人口和时间上）。寄生虫的宿主是否与大量或少量其他宿主相互作用的相关性并不明显，如下所述。其次，社交网络的整体结构可能会有所不同。考虑图7.1a和7.1b所示的接触结构。在这两个网络中，每台主机都与另外三台主机相连，但在一个网络中，整个结构是以规则的方式排列的（图7.1 a），而在另一个网络中，它是完全随机的（图7.1 b）。Watts和Strogatz（1998）以及Keeling（1999）表明，网络结构的这种变化可能对流行病学等方面产生深远的影响。例如，寄生虫在随机接触网络中比在规则网络中扩张得更快，如图7.1 a和7.1 b中阴影节点所示。但
Virulence management can be defined as that set of policies that not only aims to minimize the short-term impact of parasites on their host population (e.g., incidence, mortality, and morbidity), but also to account for the longer-term consequences of the evolutionary responses of these parasites, for example by adopting measures that select for less virulent strains. An important question pertaining to the scope of virulence management concerns the effect of contact structures in the host population. For successful transmission many parasites require close contact between the host they are infecting and new susceptible hosts. Consequently, the network of social contact in their host population is of paramount importance. It has already become clear that differently structured networks lead to different types of epidemiology (Keeling 1999). For example, a sparsely connected host population is more difficult to invade than a densely connected host population. But to what extent will the contact structure of their host population affect the evolution of the parasites, in particular of their virulence? Can we change the selective pressures on the parasites by modifying these contact structures? Claessen and de Roos (1995) and Rand et al. (1995) carried out computer simulations of evolving parasites in spatially structured host populations and concluded that less virulent (hypovirulent) parasites are favored with respect to well-mixed systems. Clearly, parasite evolution does depend on host population structure. Qualitative insight into the pertinent aspects of population structure, in the form of social networks, is still lacking, however (Wallinga et al. 1999). Networks of social contacts may vary in a number of ways. First, the number of social contacts per host may vary (across the host population and in time). The relevance of whether a parasite’s host interacts with a large or small number of other hosts is not immediately obvious, as explained below. Second, the overall structure of the social network may vary. Consider the contact structures depicted in Figures 7.1a and 7.1b. In both networks every host is connected to three other hosts, but in one the overall structure is laid out in a regular fashion (Figure 7.1a) whereas in the other it is completely random (Figure 7.1b). Watts and Strogatz (1998) and Keeling (1999) showed that such variations in network structure may have far-reaching consequences for, among other things, epidemiology. For example, a parasite can expand more rapidly in a random contact network than in a regular network, as suggested by the shaded nodes in Figures 7.1a and 7.1b. But