Kozminskiĭ E V
Parazitologiia. 2002 Jan-Feb;36(1):48-59.
The estimation of parasitic pressure on the host populations is frequently required in parasitological investigations. The empirical values of prevalence of infection are used for this, however the latter one as an estimation of parasitic pressure on the host population is insufficient. For example, the same prevalence of infection can be insignificant for the population with high reproductive potential and excessive for the population with the low reproductive potential. Therefore the development of methods of an estimation of the parasitic pressure on the population, which take into account the features the host population, is necessary. Appropriate parameters are to be independent on view of the researcher, have a clear biological sense and be based on easily available characteristics. The methods of estimation of parasitic pressure on the host at the organism level are based on various individual viability parameters: longevity, resistance to difficult environment etc. The natural development of this approach for population level is the analysis of viability parameters of groups, namely, the changing of extinction probability of host population under the influence of parasites. Obviously, some critical values of prevalence of infection should exist; above theme the host population dies out. Therefore the heaviest prevalence of infection, at which the probability of host population size decreases during the some period is less than probability of that increases or preserves, can serve as an indicator of permissible parasitic pressure on the host population. For its designation the term "parasite capacity of the host population" is proposed. The real parasitic pressure on the host population should be estimated on the comparison with its parasite capacity. Parasite capacity of the host population is the heaviest possible prevalence of infection, at which, with the generation number T approaching infinity, there exists at least one initial population size ni(0) for which the probability of size decrease through T generations is less than the probability of its increase. [formula: see text] The estimation of the probabilities of host population size changes is necessary for the parasite capacity determination. The classical methods for the estimation of extinction probability of population are unsuitable in this case, as these methods require the knowledge of population growth rates and their variances for all possible population sizes. Thus, the development methods of estimate of extinction probability of population, based on the using of available parameters (sex ratio, fecundity, mortality, prevalence of infection PI) is necessary. The population size change can be considered as the Markov process. The probabilities of all changes of population size for a generation in this case are described by a matrix of transition probabilities of Markov process (pi) with dimensions Nmax x Nmax (maximum population size). The probabilities of all possible size changes for T generations can be calculated as pi T. Analyzing the behaviour matrix of transition at various prevalence of infection, it is possible to determine the parasite capacity of the host population. In constructing of the matrix of transition probabilities, should to be taken into account the features the host population and the influence of parasites on its reproductive potential. The set of the possible population size at a generation corresponds to each initial population size. The transition probabilities for the possible population sizes at a generation can be approximated to the binomial distribution. The possible population sizes at a generation nj(t + 1) can be calculated as sums of the number of survived parents N1 and posterities N2; their probabilities--as P(N1) x P(N2). The probabilities of equal sums N1 + N2 and nj(t + 1) > or = Nmax are added. The number of survived parents N1 may range from 0 to (1-PI) x ni(t). The survival probabilities can be estimated for each N1 as [formula: see text] The number of survived posterities N2 may range from 0 to N2max (the maximum number of posterities). N2max is [formula: see text] and the survival probabilities for each N2, is defined as [formula: see text] where [formula: see text], ni(t) is the initial population size (including of males and infected specimens of host), PI is the prevalence of infection, Q1 is the survival probabilities of parents, Pfemales is the frequency of females in the host population, K is the number of posterities per a female, and Q2 is the survival probabilities of posterities. When constructing matrix of transition probabilities of Markov process (pi), the procedure outlined above should be repeated for all possible initial population size. Matrix of transition probabilities for T generations is defined as pi T. This matrix (pi T) embodies all possible transition probabilities from the initial population sizes to the final population sizes and contains a wealth of information by itself. From the practical point of view, however, the plots of the probability of population size decrease are more suitable for analysis. They can be received by summing the probabilities within of lines of matrix from 0 to ni--1 (ni--the population size, which corresponds to the line of the matrix). Offered parameter has the number of advantages. Firstly, it is independent on a view of researcher. Secondly, it has a clear biological sense--this is a limit of prevalence, which is safe for host population. Thirdly, only available parameters are used in the calculation of parasite capacity: population size, sex ratio, fecundity, mortality. Lastly, with the availability of modern computers calculations do not make large labour. Drawbacks of this parameter: 1. The assumption that prevalence of infection, mortality, fecundity and sex ratio are constant in time (the situations are possible when the variability of this parameters can not be neglected); 2. The term "maximum population size" has no clear biological sense; 3. Objective restrictions exist for applications of this mathematical approach for populations with size, which exceeds 1000 specimens (huge quantity of computing operations--order Nmax 3*(T-1), work with very low probabilities). The further evolution of the proposed approach will allow to transfer from the probabilities of size changes of individual populations to be probabilities of size changes of population systems under the influence of parasites. This approach can be used at the epidemiology and in the conservation biology.
在寄生虫学研究中,经常需要估计寄生虫对宿主种群的压力。为此使用感染率的经验值,然而,后者作为对宿主种群寄生虫压力的估计是不够的。例如,相同的感染率对于具有高繁殖潜力的种群可能无关紧要,而对于具有低繁殖潜力的种群则可能过高。因此,有必要开发考虑宿主种群特征的估计种群寄生虫压力的方法。合适的参数应独立于研究者的观点,具有明确的生物学意义,并基于易于获得的特征。在个体水平上估计宿主寄生虫压力的方法基于各种个体生存能力参数:寿命、对恶劣环境的抵抗力等。这种方法在种群水平上的自然发展是分析群体的生存能力参数,即寄生虫影响下宿主种群灭绝概率的变化。显然,应该存在一些感染率的临界值;超过这些值,宿主种群就会灭绝。因此,在某一时期内宿主种群数量减少的概率小于增加或保持的概率的最高感染率,可以作为宿主种群允许寄生虫压力的指标。为了表示这个指标,提出了“宿主种群的寄生虫容量”这一术语。对宿主种群的实际寄生虫压力应该通过与它的寄生虫容量进行比较来估计。宿主种群的寄生虫容量是可能的最高感染率,在代数T趋近于无穷大时,至少存在一个初始种群大小ni(0),对于该初始种群大小,经过T代后种群数量减少的概率小于增加的概率。[公式:见原文]确定寄生虫容量需要估计宿主种群数量变化的概率。在这种情况下,经典的估计种群灭绝概率的方法不合适,因为这些方法需要知道所有可能种群大小的种群增长率及其方差。因此,有必要开发基于可用参数(性别比、繁殖力、死亡率、感染率PI)估计种群灭绝概率的方法。种群数量变化可以被视为马尔可夫过程。在这种情况下,一代中种群数量所有变化的概率由马尔可夫过程的转移概率矩阵(pi)描述,其维度为Nmax x Nmax(最大种群大小)。T代中所有可能大小变化的概率可以计算为pi T。通过分析不同感染率下的转移行为矩阵,可以确定宿主种群的寄生虫容量。在构建转移概率矩阵时,应该考虑宿主种群的特征以及寄生虫对其繁殖潜力的影响。一代中可能的种群大小集合对应于每个初始种群大小。一代中可能种群大小的转移概率可以近似为二项分布。一代中可能的种群大小nj(t + 1)可以计算为存活亲本数量N1和后代数量N2的总和;它们的概率——为P(N1) x P(N2)。相等总和N1 + N2以及nj(t + 1) >或= Nmax的概率相加。存活亲本数量N1的范围可以从0到(1 - PI) x ni(t)。可以为每个N1估计存活概率为[公式:见原文]存活后代数量N2的范围可以从0到N2max(最大后代数量)。N2max为[公式:见原文],每个N2的存活概率定义为[公式:见原文]其中[公式:见原文],ni(t)是初始种群大小(包括宿主的雄性和感染标本),PI是感染率,Q1是亲本的存活概率,Pfemales是宿主种群中雌性的频率,K是每个雌性的后代数量,Q2是后代 的存活概率。在构建马尔可夫过程的转移概率矩阵(pi)时,应该对所有可能的初始种群大小重复上述过程。T代的转移概率矩阵定义为pi T。这个矩阵(pi T)体现了从初始种群大小到最终种群大小的所有可能转移概率,并且本身包含丰富的信息。然而,从实际角度来看,种群数量减少概率的图表更适合分析。它们可以通过将矩阵从0到ni - 1行内的概率相加得到(ni——对应于矩阵行的种群大小)。提出的参数有很多优点。首先,它独立于研究者的观点。其次,它有明确的生物学意义——这是对宿主种群安全的感染率极限。第三,在计算寄生虫容量时只使用可用参数:种群大小、性别比、繁殖力、死亡率。最后,随着现代计算机的可用性,计算不会带来大量劳动。这个参数的缺点:1. 假设感染率、死亡率、繁殖力和性别比在时间上是恒定的(在某些情况下,这些参数的变异性不能被忽略);2. “最大种群大小”这个术语没有明确的生物学意义;3. 对于大小超过1000个标本的种群应用这种数学方法存在客观限制(大量的计算操作——阶数为Nmax 3*(T - 1),处理非常低的概率)。所提出方法的进一步发展将允许从个体种群大小变化的概率转移到寄生虫影响下种群系统大小变化的概率。这种方法可以用于流行病学和保护生物学。