Effect Of Population Heterogeneity Research Articles

Information Propagation Influenced by Population Heterogeneity Behavioral Adoption on Weighted Network

In the realistic world, various individuals have distinct personalities, preferences, and attitudes toward new information and behavior acceptance, called population heterogeneity. It is seldom taken into account and theoretically analyzed in information propagation on a weighted network. Therefore, we divide individuals into fashionable and conservative individuals according to their passion degree and willingness for novel behaviors acceptance. Then, we build two behavior adoption threshold models corresponding to fashionable and conservative individuals on the weighted network to explore the effect of population heterogeneity on information propagation. Next, a partition theory based on edge weight and population heterogeneity is proposed to qualitatively analyze the information propagation mechanism. The theoretical analyses and simulation results show that fashionable individuals promote information propagation and behavior adoption. More importantly, the crossover phenomena of phase transition appear. When the fraction of fashionable individuals is relatively large, the increasing pattern of the final adoption size shows a second‐order continuous phase transition. In comparison, the increasing pattern alters to first‐order discontinuous phase transition with the decrease of the fraction of fashionable individuals. Moreover, reducing weight distribution heterogeneity promotes information propagation and slightly accelerates the change of the phase transition pattern from the first‐order discontinuous to the second‐order continuous. Besides, increasing the degree distribution heterogeneity accelerates the change of the phase transition pattern. Finally, our theoretical analyses coincide well with the simulation results.

Effect of population heterogeneity on herd immunity and on vaccination decision making process

We study the influence of population heterogeneity on herd immunity level and on individual’s vaccination decision making process. We first formulate the mathematical model in a population with two subgroups, based on different activity levels or different susceptibilities. The herd immunity threshold is derived and discussed. It is calculated that the required vaccine coverage level for herd immunity in a heterogeneous mixing population can be varied significantly. The required vaccine coverage level is lower than the classical herd immunity level, if the vaccine coverage level in the more active group or more susceptible group is higher than the other subgroup. It is suggested that the classical herd immunity levels can be misleading in the process of planning mass vaccination programs. The analysis is further extended to study the population with more subgroups. We then study the formal vaccination games to simulate the process of vaccination decision making, in either homogeneous or heterogeneous mixing populations. It is proved that the Nash equilibrium in the vaccination game is not unique if population heterogeneity is considered. Moreover, herd immunity is not achieved if individuals are solely driven by self-interests.

Individual differences in predicting occupational success: The effect of population heterogeneity

Using a sample of 339 university graduates from the University of Alicante (Spain) three years after completion of their studies, we studied the relationships between general intelligence (GI), personality traits, emotional intelligence (EI), academic performance, and occupational attainment and compared the results of conventional regression analysis with the results obtained from applying regression mixture models. The results reveal the influence of unobserved population heterogeneity (latent class) on the relationship between predictors and criteria and the improvement in the prediction obtained from applying regression mixture models compared to applying a conventional regression model.

Extended Lotka–Volterra equations incorporating population heterogeneity: Derivation and analysis of the predator–prey case

Extended logistic and competitive Lotka–Volterra equations were developed by Eizi Kuno to understand the implications of population heterogeneity (especially spatial) for population growth. Population heterogeneity, defined as the presence of individuals in some patches of population and not others, is the resulting expression of a number of processes, including dispersal, habitat heterogeneity and searching behaviour. Kuno's models allow the effect of population heterogeneity (thus defined) on a population at equilibrium to be accounted for without using multi-patch models. This paper demonstrates this for the first time using numerical simulations and presents a more complete mathematical derivation of his models. An extension of Kuno's equations to model predator–prey scenarios with heterogeneity in the prey population is also developed. Analysis of this predator–prey case shows that a patchy distribution of prey facilitates their stable coexistence with predators. This paper has broad implications for ecological modelling because it shows how the effects of a number of population processes, including dispersal, are reflected in the density of populations at equilibrium. Therefore, by adjusting the equilibrium solutions of models, the effects of a number of processes are captured without representing the processes themselves in an explicit way.

Analysis of survival, gene expression and behavior following chill-coma in the medfly Ceratitis capitata: Effects of population heterogeneity and age

The medfly Ceratitis capitata is an agricultural pest distributed worldwide thanks, in part, to its phenotypic plasticity of thermal tolerance. Cold exposure has been shown to reduce C. capitata survival, which may affect its distribution in areas with subfreezing temperatures. When insects are increasingly cooled, they attain a critical thermal threshold and enter a chill-coma state characterized by cessation of movement. It is not clear how a rapid cold exposure affects the physiological state of medflies, and how this is influenced by age and population heterogeneity. In order to approach these questions, C. capitata single-sex laboratory populations of 15 and 30days old were subjected to a chill-coma recovery assay, and separated according to their recovery time in three subgroups: Fast-Subgroups, Intermediate-Subgroups, and Slow-Subgroups. Thereafter, we analyzed their survival, behavioral, and gene expression outputs. In female and old male populations, we found that flies with the slowest recovery time had a reduced life expectancy, a higher initial mortality rate, and a worse climbing performance compared with flies that recovered faster. Therefore, we were able to separate subgroups that developed chilling-injury from subgroups that had a reversible full recovery after cold exposure. The gene expression analysis of the heat shock protein genes hsp70 and hsp83 showed no clear association with the parameters studied. Interestingly, thorax expression levels of the Cu/Zn superoxide dismutase gene were elevated during the recovery phase in the Fast-Subgroups, but remained constant in the Slow-Subgroups that developed chilling-injury. On the other hand, none of the young male subgroups seemed to have suffered irreversible damage. Thus, we concluded that depending on age and population heterogeneity, chill-coma recovery time points out significant differences on individual cold tolerance. Moreover, the inability to properly induce the antioxidant defense system to counteract the oxidative damage caused by cold seems to contribute to the development of chilling-injury.

Effects of Population Heterogeneity on Accuracy of DIF Detection

Heterogeneity within English language learners (ELLs) groups has been documented. Previous research on differential item functioning (DIF) analyses suggests that accurate DIF detection rates are reduced greatly when groups are heterogeneous. In this simulation study, we investigated the effects of heterogeneity within linguistic (ELL) groups on the accuracy of DIF detection. Heterogeneity within such groups may occur for a myriad of reasons including differential lengths of time residing in English-speaking countries, degrees of exposure to English-speaking environments, and amounts of English instruction. Our findings revealed that at high levels of within-group heterogeneity, DIF detection is at the level of chance, implying that a large proportion of DIF items might remain undetected when assessing heterogeneous populations potentially leading to developing biased tests. Based on our findings, we urge test development organizations to consider heterogeneity within ELL and other heterogeneous focus groups in their routine DIF analyses.

Low Levels of Genetic Divergence across Geographically and Linguistically Diverse Populations from India

Ongoing modernization in India has elevated the prevalence of many complex genetic diseases associated with a western lifestyle and diet to near-epidemic proportions. However, although India comprises more than one sixth of the world's human population, it has largely been omitted from genomic surveys that provide the backdrop for association studies of genetic disease. Here, by genotyping India-born individuals sampled in the United States, we carry out an extensive study of Indian genetic variation. We analyze 1,200 genome-wide polymorphisms in 432 individuals from 15 Indian populations. We find that populations from India, and populations from South Asia more generally, constitute one of the major human subgroups with increased similarity of genetic ancestry. However, only a relatively small amount of genetic differentiation exists among the Indian populations. Although caution is warranted due to the fact that United States–sampled Indian populations do not represent a random sample from India, these results suggest that the frequencies of many genetic variants are distinctive in India compared to other parts of the world and that the effects of population heterogeneity on the production of false positives in association studies may be smaller in Indians (and particularly in Indian-Americans) than might be expected for such a geographically and linguistically diverse subset of the human population.

On the effect of population heterogeneity on dynamics of epidemic diseases

The paper investigates a class of SIS models of the evolution of an infectious disease in a heterogeneous population. The heterogeneity reflects individual differences in the susceptibility or in the contact rates and leads to a distributed parameter system, requiring therefore, distributed initial data, which are often not available. It is shown that there exists a corresponding homogeneous (ODE) population model that gives the same aggregated results as the distributed one, at least in the expansion phase of the disease. However, this ODE model involves a nonlinear "prevalence-to-incidence" function which is not constructively defined. Based on several established properties of this function, a simple class of approximating function is proposed, depending on three free parameters that could be estimated from scarce data. How the behaviour of a population depends on the level of heterogeneity (all other parameters kept equal) - this is the second issue studied in the paper. It turns out that both for the short run and for the long run behaviour there exist threshold values, such that more heterogeneity is advantageous for the population if and only if the initial (weighted) prevalence is above the threshold.

Does within‐population variation in egg size reduce intraspecific competition in Atlantic Salmon, Salmo salar?

Summary If phenotypes differ in habitat preferences there may be a decrease in intraspecific competition with increasing phenotypic variation, causing heterogeneous populations to perform better than homogeneous ones. Furthermore, if the relative performance of different phenotypes depends on environmental conditions, population heterogeneity may buffer populations against temporal environmental variation. Here these hypotheses are tested using 10 experimental populations of juvenile Atlantic Salmon (Salmo salar L.) reared across a range of five different water discharges. Each population consisted of fish of identical parental origins to control for genetic differences among populations, but differed in body size heterogeneity owing to differences in egg size distributions. No effect of population heterogeneity on final body size or dispersal rates was detected. Thus, egg size heterogeneity does not appear to influence the average level of intraspecific competition in Atlantic Salmon. There was a strong positive effect of water discharge on body size, but no effects of phenotypic heterogeneity on variation in final body size among discharge levels. Thus, the relative growth performance of juveniles arising from different egg sizes may not change sufficiently with environmental changes for egg size variation to create a strong buffering effect against year‐to‐year variation in environmental conditions.

The effects of population heterogeneity on disease invasion

The incorporation of population heterogeneity is a central issue in theoretical biology, and it has received considerable attention in epidemiology recently. This paper presents general conclusions and interpretations about the effects of heterogeneity, with and without positive assortative mating, on the ability of a disease to establish itself. We show that the invasion of a disease into a population with random mixing is determined by an average of reproductive numbers for each subgroup, weighted by the total amount of mixing activity of the subgroup. In particular, if the mixing rate is constant across the population, invasion occurs if and only if the average reproductive number for the population exceeds 1. In the case of “preferred mixing,” one can find a critical number for each subgroup such that invasion occurs if and only if a suitably defined average over subgroups exceeds 1.

Logistic Regression in Capture-Recapture Models

The effect of population heterogeneity in capture-recapture, or dual registration, models is discussed. An estimator of the unknown population size based on a logistic regression model is introduced. The model allows different capture probabilities across individuals and across capture times. The probabilities are estimated from the observed data using conditional maximum likelihood. The resulting population estimator is shown to be consistent and asymptotically normal. A variance estimator under population heterogeneity is derived. The finite-sample properties of the estimators are studied via simulation. An application to Finnish occupational disease registration data is presented.

Estimation of Exposure Time Distributions

In many demographic analyses, such as the assessment of environmental cancer risks, one may be interested not only in the age-by-state distribution of the population but also in the distribution of the population by time spent in a given state. States can represent geographic areas, marital statuses, labor force participation, or states of epidemiologic exposure. Recursive formulas for the calculation of the distribution of the population according to exposure time are derived under time-invariant state transition rates. Although populations can have identical growth rates and identical age-by-state distributions, they can have very different distributions by exposure time. An application to the analysis of carcinogenic exposure states is given, using data from Finland. The effect of population heterogeneity on the estimated exposure time distributions is studied.

HLA polymorphisms in a Shanghai Chinese population.

The frequencies of the HLA-A, B, C, D, DR and MB antigens have been determined in a homogeneous Shanghai Chinese population. Comparisons with the HLA-A and -B frequencies in other subsets of the Chinese population revealed some marked differences. No comparisons were possible for the D, DR and MB antigens since there were no previous studies of the antigens in those loci. We suggest that studies of the Chinese population should be confined to clearly defined homogeneous subsets. In this manner, the confounding effect of population heterogeneity may be avoided, and it is this heterogeneity which calls for extensive surveys of the huge Chinese population.