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An annotated synthesis of textbook definitions of parasitism is presented. Most definitions declare parasitism is a long-lasting relationship between individuals of different species harming the hosts. The infection-induced costs are interpreted as diseases in the medical-veterinary literature. Alternatively, evolutionary ecologists interpret it as a reduction of host's fitness (longevity, fertility or both). Authors often assume that such effects decrease host population growth and select for antiparasitic defences, which is not necessarily true because infections may simultaneously express opposite effects at different levels of biological organization. (i) At the cellular level, infection-induced cell growth, longevity and multiplication may yield tumours maladaptive at higher levels. (ii) At the individual level, reduced host longevity, fertility or both are interpreted as disease symptoms or reduced fitness. (iii) Contrary to common sense, the growth rate of infected host lineages may increase in parallel with the individuals' reduced survival and fertility. This is because selection favours not only the production of more offspring but also their faster production. (iv) Finally, infections that reduce host individuals' or lineages' fitness may still increase infected host populations' growth rate in the context of ecological competition. Therefore, differences between parasitism and mutualism may depend on which level of organization one focuses on.

Predators negatively affect prey outside of direct attack, and these nonconsumptive effects (NCEs) may cause over half the impacts of predators on prey populations. This “ecology of fear” framework has been extended to host–parasite interactions. The NCEs of parasites are thought to be small relative to those of predators. However, recent research shows ectoparasites exert NCEs on multiple life stages of Drosophila. In this study, we apply recent data to a matrix‐based model of fly populations experiencing infection/consumption and NCEs from an ectoparasitic mite. We found the NCEs of parasites on larvae, which are not actively parasitized, decreased the size of simulated host populations. By contrast, the NCEs on adult flies increased population size through compensatory egg production. The negative NCEs on larvae outweighed the positive effects on adults to reduce population size. This study suggests that parasitic NCEs can suppress host populations independent of infection. Using simulations we tested if the nonconsumptive effects on different life stages of flies from ectoparasites affected population growth. Nonconsumptive effects on larvae and adults had conflicting outcomes, NCEs on larvae reduced population growth, and NCEs on adults slightly increased growth. When the NCEs were combined, the negative effect on larvae overpowered the positive effect on adults and reduced population size.

Background Host population structure is a key determinant of pathogen and infectious disease transmission patterns. Pathogen phylogenetic trees are useful tools to reveal the population structure underlying an epidemic. Determining whether a population is structured or not is useful in informing the type of phylogenetic methods to be used in a given study. We employ tree statistics derived from phylogenetic trees and machine learning classification techniques to reveal an underlying population structure. Results In this paper, we simulate phylogenetic trees from both structured and non-structured host populations. We compute eight statistics for the simulated trees, which are: the number of cherries; Sackin, Colless and total cophenetic indices; ladder length; maximum depth; maximum width, and width-to-depth ratio. Based on the estimated tree statistics, we classify the simulated trees as from either a non-structured or a structured population using the decision tree (DT), K-nearest neighbor (KNN) and support vector machine (SVM). We incorporate the basic reproductive number ( R 0 ) in our tree simulation procedure. Sensitivity analysis is done to investigate whether the classifiers are robust to different choice of model parameters and to size of trees. Cross-validated results for area under the curve (AUC) for receiver operating characteristic (ROC) curves yield mean values of over 0.9 for most of the classification models. Conclusions Our classification procedure distinguishes well between trees from structured and non-structured populations using the classifiers, the two-sample Kolmogorov-Smirnov, Cucconi and Podgor-Gastwirth tests and the box plots. SVM models were more robust to changes in model parameters and tree size compared to KNN and DT classifiers. Our classification procedure was applied to real -world data and the structured population was revealed with high accuracy of 92.3 % using SVM-polynomial classifier.

Background In the past few decades, there has been a significant increase in the number of refugees worldwide. Every individual deserves access to the fundamental right to health, and migration can have a substantial beneficial or detrimental effect on one’s health. Foreign invasions and political instability in Afghanistan affected neighboring countries with the large influx of refugees. Discrepancies in quality of life between the host and refugee populations may lead to health inequalities. Investigations in Pakistan on the quality of life of Afghan refugees were scarce despite more than four decades of refugee status. Therefore, this study was initiated to assess the sociocultural determinants influencing health-associated quality of life among Afghan refugees in Pakistan. Methods The Punjab province and Khyber Pakhtunkhwa province refugee populations were selected as the study population for cross-sectional research based on the inclusion criteria of majority refugee representation and female participation. Quantitative research methodology with pre-validated WHOQOL-BREF questionnaires was used for data collection via multi-stage probability sampling techniques. We collected data from 1,185 study participants and applied univariate and bivariate analyses. Inferential analyses included independent t-tests and ANOVA. Results The average scores for the entire sample of Afghan refugees were highest for the social domain (58.78 ± 22.74), followed by the physical domain (53.29 ± 19.46), the general health domain (50.44 ± 20.10), the environmental domain (48.43 ± 16.30), and the psychological domain (46.52 ± 14.78). Age, marital status, family setup, mother language, number of years in the host country, residence type, family monthly income, access to health care, current health status, chronic health illness, substance abuse (smoking), cultural compatibility, linguistic barriers, and social inclusion were non-significant with all the subdomains in the inferential analysis using the independent t-test and analysis of variance. Conclusion The Afghan refugees’ average scores across all health-associated quality-of-life domains were lower than Pakistan’s host population and the standard cutoff criteria (< 60 indicates poor quality of life). The development of a national policy to include refugees in health insurance programs seems essential to improve the health-associated quality of life among Afghan refugees in Pakistan.

The recently-emerged amphibian chytrid fungus Batrachochytrium dendrobatidis (Bd) has had an unprecedented impact on global amphibian populations, and highlights the urgent need to develop effective mitigation strategies. We conducted in-situ antifungal treatment experiments in wild populations of the endangered mountain yellow-legged frog during or immediately after Bd-caused mass die-off events. The objective of treatments was to reduce Bd infection intensity (“load”) and in doing so alter frog-Bd dynamics and increase the probability of frog population persistence despite ongoing Bd infection. Experiments included treatment of early life stages (tadpoles and subadults) with the antifungal drug itraconazole, treatment of adults with itraconazole, and augmentation of the skin microbiome of subadults with Janthinobacterium lividum , a commensal bacterium with antifungal properties. All itraconazole treatments caused immediate reductions in Bd load, and produced longer-term effects that differed between life stages. In experiments focused on early life stages, Bd load was reduced in the 2 months immediately following treatment and was associated with increased survival of subadults. However, Bd load and frog survival returned to pre-treatment levels in less than 1 year, and treatment had no effect on population persistence. In adults, treatment reduced Bd load and increased frog survival over the entire 3-year post-treatment period, consistent with frogs having developed an effective adaptive immune response against Bd. Despite this protracted period of reduced impacts of Bd on adults, recruitment into the adult population was limited and the population eventually declined to near-extirpation. In the microbiome augmentation experiment, exposure of subadults to a solution of J. lividum increased concentrations of this potentially protective bacterium on frogs. However, concentrations declined to baseline levels within 1 month and did not have a protective effect against Bd infection. Collectively, these results indicate that our mitigation efforts were ineffective in causing long-term changes in frog-Bd dynamics and increasing population persistence, due largely to the inability of early life stages to mount an effective immune response against Bd. This results in repeated recruitment failure and a low probability of population persistence in the face of ongoing Bd infection.

Although recent advances in sequencing and computational analyses have facilitated use of endogenous retroviruses (ERVs) for deciphering coevolution among retroviruses and their hosts, sampling effects from different host populations present major challenges. Here we utilize available whole-genome data from wild and domesticated European rabbit (Oryctolagus cuniculus sp.) populations, sequenced as DNA pools by paired-end Illumina technology, for identifying segregating reference as well as nonreference ERV loci, to reveal their variation along the host phylogeny and domestication history. To produce new viruses, retroviruses must insert a proviral DNA copy into the host nuclear DNA. Occasional proviral insertions into the host germline have been passed down through generations as inherited ERVs during millions of years. These ERVs represent retroviruses that were active at the time of infection and thus present a remarkable record of historical virus–host associations. To examine segregating ERVs in host populations, we apply a reference library search strategy for anchoring ERV-associated short-sequence read pairs from pooled wholegenome sequences to reference genome assembly positions. We show that most ERVs segregate along host phylogeny but also uncover radiation of some ERVs, identified as segregating loci among wild and domestic rabbits. The study targets pertinent issues regarding genome sampling when examining virus–host evolution from the genomic ERV record and offers improved scope regarding common strategies for single-nucleotide variant analyses in host population comparative genomics.

In deterministic models of epidemics, there is a host abundance threshold above which the introduction of a few infected individuals leads to a severe epidemic. Studies of weather-driven animal pathogens often assume that abundance thresholds will be overwhelmed by weather-driven stochasticity, but tests of this assumption are lacking. We collected observational and experimental data for a fungal pathogen, Entomophaga maimaiga, that infects the gypsy moth, Lymantria dispar. We used an advanced statistical-computing algorithm to fit mechanistic models to our data, such that different models made different assumptions about the effects of host density and weather on E. maimaiga epizootics (epidemics in animals). We then used Akaike information criterion analysis to choose the best model. In the best model, epizootics are driven by a combination of weather and host density, and the model does an excellent job of explaining the data, whereas models that allow only for weather effects or only for density-dependent effects do a poor job of explaining the data. Density-dependent transmission in our best model produces a host density threshold, but this threshold is strongly blurred by the stochastic effects of weather. Our work shows that host-abundance thresholds may be important even if weather strongly affects transmission, suggesting that epidemiological models that allow for weather have an important role to play in understanding animal pathogens. The success of our model means that it could be useful for managing the gypsy moth, an important pest of hardwood forests in North America.

The northeast region of China plays a crucial role in crop production. The leaf beetle Monolepta hieroglyphica (Motschulsky, 1858) (Coleoptera: Chrysomelidae) has emerged as a potential threat to food security in the region. With a wide distribution spanning Asia and Russia, this beetle affects various crops. However, limited information is available regarding its occurrence patterns and genetic diversity among major crops in the region. Based on systematic observations across various hosts, coupled with genetic variation analysis using mitochondrial DNA markers, the main results were as follows. Leaf beetle occurrence varied among hosts, peaking from late July to mid-August, with maize and soybean fields exhibiting higher infestation rates compared with other crops. Notably, late-cultivated maize fields harbored the highest beetle numbers due to the species’ preference for young leaves. The host transfer trajectory may have originated in soybean and weeds, with subsequent alternation between host plants and other crops, before the final migration to cabbage and late-cultivated maize fields. Genetic analysis revealed nine COI haplotypes, four COII haplotypes, eleven Cytb haplotypes, and twenty-one combined haplotypes. No clear relationship existed between genetic diversity and occurrence, and no distinct host-based genetic patterns emerged from neighbor-joining tree and haplotype network analyses. High gene flow rates were observed, likely contributing to decreased genetic variation. An analysis of molecular variance results indicated major genetic variation within populations, although genetic distance and haplotype distribution indicated divergence among host populations. These results provide foundational data for developing effective M. hieroglyphica pest management strategies.

Due to the error-prone nature of viral RNA-dependent RNA polymerases, the replication of RNA viruses results in a diversity of viral genomes harboring point mutations, deletions, insertions, and genome rearrangements. Citrus tristeza virus (CTV), a causal agent of diseases of economically important citrus species, shows intrinsic genetic stability. While the virus appears to have some mechanism that limits the accumulation of single-nucleotide variants, the production of defective viral genomes (DVGs) during virus infection has been reported for certain variants of CTV. The intra-host diversity generated during plant infection with variant T36 (CTV-T36) remains unclear. To address this, we analyzed the RNA species accumulated in the initially infected and systemic leaves of Nicotiana benthamiana plants inoculated with an infectious cDNA clone of CTV-T36, which warranted that infection was initiated by a known, well-defined sequence variant of the virus. CTV-T36 limited the accumulation of single-nucleotide mutants during infection. With that, four types of DVGs—deletions, insertions, and copy- and snap-backs—were found in all the samples, with deletions and insertions being the most common types. Hot-spots across the genome for DVG recombination and short direct sequence repeats suggest that sequence complementarity could mediate DVG formation. In conclusion, our study illustrates the formation of diverse DVGs during CTV-T36 infection. To the best of our knowledge, this is the first study that has analyzed the genetic variability and recombination of a well-defined sequence variant of CTV in an herbaceous host.

Objective: We investigated the association between the density of internal human migration, in the urban neighborhood, on frailty in the older adult population in Colombia. Methods: The data used in this study are from four Colombian population surveys. We analyzed 633 census tracts with a sample of 2,194 adults 60 years and over for frailty (measured using the Fried criteria). We considered the proportion of inhabitants in a census tract with a history of internal migration as the exposure variable considering three temporalities. For contextual forced migration, we identified two types: 5-year, and 1-year. Poisson multivariable regression models with two hierarchical levels (individual and census tracts) were estimated. Results: The prevalence of pre-fragile/frailty was 80.63% [CI 95%: 77.67, 83.28]. The prevalence ratio were significantly higher for the older adults who live in neighborhoods where a higher proportion of internal migrants reside. Conclusion: We conclude that older adults who lived in neighborhoods with a high proportion of internal migrants experience more frailty. Potential explanations are that neighborhoods with high internal migration could experience social (l increase in cultural heterogeneity, in the perception of insecurity, violence and physical conditions (pressure on local economies and services, leading elderly residents to compete for neighborhood resources), translated into social stress.