Analysis of urban-rural population dynamics of China: a multiregional life table approach.
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Random mating is the null model central to population genetics. One assumption behind random mating is that individuals mate an infinite number of times. This is obviously unrealistic. Here we show that when each female mates a finite number of times, the effective size of the population is substantially decreased.
The Penna model is a strategy to simulate the genetic dynamics of age-structured populations, in which the individual genomes are represented by bit strings. It provides a simple metaphor for the evolutionary process in terms of the mutation accumulation theory. In its original version, an individual dies due to inherited diseases when its current number of accumulated mutations, n, reaches a threshold value T. Since the mean number of diseases increases with age, the probability to die is zero for very young ages (n < T) and equals 1 for the old ones (n > or = T). Here, instead of using a step function to determine the genetic death age, we test several other functions that may or may not slightly increase the death probability at young ages (n < T), but that decrease this probability at old ones. Our purpose is to study the oldest old effect, that is, a plateau in the mortality curves at advanced ages. By imposing certain conditions, it has been possible to obtain a clear plateau using the Penna model. However, a more realistic one appears when a modified version, that keeps the population size fixed without fluctuations, is used. We also find a relation between the birth rate, the age structure of the population, and the death probability.
An island model of migration is used to study the effects of subdivision within populations and species on sample genealogies and on between-population or between-species measures of genetic variation. The model assumes that the number of demes within each population or species is large. When populations (or species), connected either by gene flow or historical association, are themselves subdivided into demes, changes in the migration rate among demes alter both the structure of genealogies and the time scale of the coalescent process. The time scale of the coalescent is related to the effective size of the population, which depends on the migration rate among demes. When the migration rate among demes within populations is low, isolation (or speciation) events seem more recent and migration rates among populations seem higher because the effective size of each population is increased. This affects the probability of reciprocal monophyly of two samples, the chance that a gene tree of a sample matches the species tree, and relative likelihoods of different types of polymorphic sites. It can also have a profound effect on the estimation of divergence times.
This review examines the equity, efficiency and effectiveness of federal rural primary care policy as documented by the existing literature. The focus is on the Community Health Center and National Health Service Corps programs which have constituted the major components of the policy. The literature relating to the policy is limited in the number of studies available and in the quality of the research. The available evidence indicates that the policy is associated with an improvement in the distribution of health resources between rural and urban areas,and among rural areas. There is also partial evidence that the policy has been cost-efficient. For federally subsidized practices,the cost of delivering a similar quality of health care is shown to be up to 50 percent less in rural than in urban areas. Rural private practitioners, though, may be more cost-efficient than federally subsidized rural practitioners, at least under certain conditions which have yet to be fully delineated. Program effectiveness is the least well documented, but the literature does suggest that the policy has had a positive effect on the health status of rural populations. Substantially more research on the efficiency, and particular the effectiveness, of federal rural primary care policy is required for the development of a rational basis for the policy.
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Determining the evolutionary relationships between fossil hominid groups such as Neanderthals and modern humans has been a question of enduring interest in human evolutionary genetics. Here we present a new method for addressing whether archaic human groups contributed to the modern gene pool (called ancient admixture), using the patterns of variation in contemporary human populations. Our method improves on previous work by explicitly accounting for recent population history before performing the analyses. Using sequence data from the Environmental Genome Project, we find strong evidence for ancient admixture in both a European and a West African population (p approximately 10(-7)), with contributions to the modern gene pool of at least 5%. While Neanderthals form an obvious archaic source population candidate in Europe, there is not yet a clear source population candidate in West Africa.
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Well constructed sub-population databases are fundamental to the application of DNA-based forensic statistics. The size of such databases can affect the ability to examine adequately statistical or population genetic features, and the integrity of both the DNA profile and associated ethnicity information is also of importance. Use of short tandem repeat (STR) DNA profiling technology and the thoughtful construction of the governing legislation has seen large databases of DNA profiles collated for the four major sub-populations of New Zealand. Examination of the data illustrates the suitability of self-declaration as a means of categorizing samples on the basis of ethnicity.
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