scholarly journals How host heterogeneity governs tuberculosis reinfection?

2012 ◽  
Vol 279 (1737) ◽  
pp. 2473-2478 ◽  
Author(s):  
M. Gabriela M. Gomes ◽  
Ricardo Águas ◽  
João S. Lopes ◽  
Marta C. Nunes ◽  
Carlota Rebelo ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Population Level ◽  
Underlying Mechanism ◽  
Individual Risk ◽  
Model Framework ◽  
Differential Host ◽  
Individual Level ◽  
Relative Contribution ◽  
The Individual ◽  
Epidemiology Studies

Recurrent episodes of tuberculosis (TB) can be due to relapse of latent infection or exogenous reinfection, and discrimination is crucial for control planning. Molecular genotyping of Mycobacterium tuberculosis isolates offers concrete opportunities to measure the relative contribution of reinfection in recurrent disease. Here, a mathematical model of TB transmission is fitted to data from 14 molecular epidemiology studies, enabling the estimation of relevant epidemiological parameters. Meta-analysis reveals that rates of reinfection after successful treatment are higher than rates of new TB, raising an important question about the underlying mechanism. We formulate two alternative mechanisms within our model framework: (i) infection increases susceptibility to reinfection or (ii) infection affects individuals differentially, thereby recruiting high-risk individuals to the group at risk for reinfection. The second mechanism is better supported by the fittings to the data, suggesting that reinfection rates are inflated through a population phenomenon that occurs in the presence of heterogeneity in individual risk of infection. As a result, rates of reinfection are higher when measured at the population level even though they might be lower at the individual level. Finally, differential host recruitment is modulated by transmission intensity, being less pronounced when incidence is high.

scholarly journals Variation in seed dormancy of the wetland sedge, Carex elongata, between populations and individuals in two consecutive years

2003 ◽  
Vol 13 (4) ◽  
pp. 315-322 ◽  
Author(s):  
Wolfgang Schütz ◽  
Gerhard Rave
Keyword(s):  
Total Variation ◽  
Population Level ◽  
Population Variation ◽  
Individual Level ◽  
Relative Contribution ◽  
Weak Evidence ◽  
Main Effect ◽  
Mother Plants ◽  
The Individual ◽  
Germination Experiments

Variation in dormancy of the wetland sedge, Carex elongata L., was tested using seeds from three wild populations and the garden-grown progeny of one population. Germination experiments, comprising four combinations of temperature and light, were conducted either with fresh-matured or cold-stratified seeds, to assess the relative contribution of populations and mother plants to the total variation. Between-year variation was tested at the population level and, partly, at the individual level, using seeds collected in two consecutive years. Among-population variation accounted for 72%, and among-individual variation for 23%, of the total variance in the first experiment. Significant differences were apparent between one wild population and its garden-grown descendants. Differences in germinability among populations were maintained in the two consecutive years, but a proportion of the variance was due to the contribution of the maternal environment. Weak evidence for genetic control at the individual level was shown by a correlation across years in one population. However, the lack of a main effect at the individual level in the first experiment makes it difficult to assess the relative contribution of the mother plants to the total variation. Our results imply that germination patterns of C. elongata have a genetic basis, but are markedly modified by environmental conditions.

Pharmacovigilance

2021 ◽  
pp. 87-129
Keyword(s):  
Adverse Drug Events ◽  
Population Level ◽  
Individual Risk ◽  
Individual Level ◽  
Safety Event ◽  
Additional Level ◽  
Health Organization ◽  
The Individual ◽  
Specific Reactions ◽  
Event Rates

This chapter describes how pharmacovigilance systems detect safety signals from the use of medicines that are on the market. Drug safety litigation has driven turning points in regulation and provides an additional level of public health protection from the potential harm of medicines. The World Health Organization (WHO) defines pharmacovigilance as the science and activities relating to the detection, evaluation, understanding, and prevention of adverse drug reactions (ADR), or any other drug related health problems. This important definition refers to reactions, where causality is proven or assumed, rather than event rates, where causality can only be inferred for a population and not for an individual. Risk–benefit analysis at the population level mostly refers to differences in efficacy and safety event rates. At the individual level, it is possible to look at person-specific reactions. Overall risk–benefit based on reported ADRs can differ from one based on adverse drug events (ADEs).

Population Densities Allowed Around Dutch SEVESO Establishments

2000 ◽  
Author(s):  
G. M. H. Laheij ◽  
B. J. M. Ale ◽  
J. G. Post
Keyword(s):  
Population Density ◽  
The Netherlands ◽  
Individual Risk ◽  
Population Densities ◽  
Planning Policy ◽  
Relative Contribution ◽  
Societal Risk ◽  
Dangerous Substances ◽  
The Individual ◽  
Uniform Population

Abstract In the Netherlands, the individual risk and societal risk are used in efforts to reduce the number of people exposed to the effect of an accident at an establishment with dangerous substances. To facilitate the societal risk planning policy an investigation was carried out for the Dutch SEVESO establishments to investigate the possibility of determining a generic uniform population density for the zone between the individual risk contours of 10−5 and 10−6 per year. The indicative limit for the societal risk at this density was not to be exceeded. Also there was to be enough space left for a significantly higher population density outside the individual risk contour of 10−6 per year. The RORISC methodology and the actual data for the 124 Dutch SEVESO establishments were used to determine the generic uniform population density. Based on the data available it can be concluded that the maximum allowed uniform population density in the zone between the individual risk contours of 10−5 and 10−6 per year is lower than one person per hectare. At this density there is no space left for a higher population density outside the individual risk contour of 10−6 per year. For uniform population densities the relative contribution to the societal risk has been found significant up to the individual risk contour of 10−7 per year.

scholarly journals Migration, acculturation, and the maintenance of between-group cultural variation

2017 ◽  
Author(s):  
Alex Mesoudi
Keyword(s):  
Social Learning ◽  
Cultural Values ◽  
Cultural Evolution ◽  
Population Level ◽  
Empirical Literature ◽  
Cultural Variation ◽  
Individual Level ◽  
And Migration ◽  
The Individual ◽  
Social Learning Processes

AbstractHow do migration and acculturation (i.e. psychological or behavioral change resulting from migration) affect within- and between-group cultural variation? Here I answer this question by drawing analogies between genetic and cultural evolution. Population genetic models show that migration rapidly breaks down between-group genetic structure. In cultural evolution, however, migrants or their descendants can acculturate to local behaviors via social learning processes such as conformity, potentially preventing migration from eliminating between-group cultural variation. An analysis of the empirical literature on migration suggests that acculturation is common, with second and subsequent migrant generations shifting, sometimes substantially, towards the cultural values of the adopted society. Yet there is little understanding of the individual-level dynamics that underlie these population-level shifts. To explore this formally, I present models quantifying the effect of migration and acculturation on between-group cultural variation, for both neutral and costly cooperative traits. In the models, between-group cultural variation, measured using F statistics, is eliminated by migration and maintained by conformist acculturation. The extent of acculturation is determined by the strength of conformist bias and the number of demonstrators from whom individuals learn. Acculturation is countered by assortation, the tendency for individuals to preferentially interact with culturally-similar others. Unlike neutral traits, cooperative traits can additionally be maintained by payoff-biased social learning, but only in the presence of strong sanctioning institutions. Overall, the models show that surprisingly little conformist acculturation is required to maintain realistic amounts of between-group cultural diversity. While these models provide insight into the potential dynamics of acculturation and migration in cultural evolution, they also highlight the need for more empirical research into the individual-level learning biases that underlie migrant acculturation.

scholarly journals General intelligence disentangled via a generality metric for natural and artificial intelligence

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Hernández-Orallo ◽  
Bao Sheng Loe ◽  
Lucy Cheke ◽  
Fernando Martínez-Plumed ◽  
Seán Ó hÉigeartaigh
Keyword(s):  
Task Difficulty ◽  
Population Level ◽  
Limited Resources ◽  
General Intelligence ◽  
Individual Level ◽  
Cognitive Efficiency ◽  
Comprehensive Performance ◽  
Individual Measure ◽  
Level Of Difficulty ◽  
The Individual

AbstractSuccess in all sorts of situations is the most classical interpretation of general intelligence. Under limited resources, however, the capability of an agent must necessarily be limited too, and generality needs to be understood as comprehensive performance up to a level of difficulty. The degree of generality then refers to the way an agent’s capability is distributed as a function of task difficulty. This dissects the notion of general intelligence into two non-populational measures, generality and capability, which we apply to individuals and groups of humans, other animals and AI systems, on several cognitive and perceptual tests. Our results indicate that generality and capability can decouple at the individual level: very specialised agents can show high capability and vice versa. The metrics also decouple at the population level, and we rarely see diminishing returns in generality for those groups of high capability. We relate the individual measure of generality to traditional notions of general intelligence and cognitive efficiency in humans, collectives, non-human animals and machines. The choice of the difficulty function now plays a prominent role in this new conception of generality, which brings a quantitative tool for shedding light on long-standing questions about the evolution of general intelligence and the evaluation of progress in Artificial General Intelligence.

scholarly journals Ecology and Prediction of Compensatory Growth: From Theory to Application in Forestry

2021 ◽  
Vol 12 ◽  
Author(s):  
Chao Li ◽  
Hugh Barclay ◽  
Bernard Roitberg ◽  
Robert Lalonde
Keyword(s):  
Compensatory Growth ◽  
Population Level ◽  
Human Society ◽  
Common Phenomenon ◽  
Partial Mortality ◽  
Individual Level ◽  
State Dependent ◽  
Dependent Model ◽  
Accelerated Growth ◽  
The Individual

Compensatory growth has been observed in forests, and it also appears as a common phenomenon in biology. Though it sometimes takes different names, the essential meanings are the same, describing the accelerated growth of organisms when recovering from a period of unfavorable conditions such as tissue damage at the individual level and partial mortality at the population level. Diverse patterns of compensatory growth have been reported in the literature, ranging from under-, to compensation-induced-equality, and to over-compensation. In this review and synthesis, we provide examples of analogous compensatory growth from different fields, clarify different meanings of it, summarize its current understanding and modeling efforts, and argue that it is possible to develop a state-dependent model under the conceptual framework of compensatory growth, aimed at explaining and predicting diverse observations according to different disturbances and environmental conditions. When properly applied, compensatory growth can benefit different industries and human society in various forms.

scholarly journals Opposite outcomes of coinfection at individual and population scales

2018 ◽  
Vol 115 (29) ◽  
pp. 7545-7550 ◽  
Author(s):  
Erin E. Gorsich ◽  
Rampal S. Etienne ◽  
Jan Medlock ◽  
Brianna R. Beechler ◽  
Johannie M. Spaan ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Negative Impact ◽  
Scale Up ◽  
Population Level ◽  
Clear Understanding ◽  
African Buffalo ◽  
Global Public Health ◽  
Individual Level ◽  
Secondary Infections ◽  
The Individual

Coinfecting parasites and pathogens remain a leading challenge for global public health due to their consequences for individual-level infection risk and disease progression. However, a clear understanding of the population-level consequences of coinfection is lacking. Here, we constructed a model that includes three individual-level effects of coinfection: mortality, fecundity, and transmission. We used the model to investigate how these individual-level consequences of coinfection scale up to produce population-level infection patterns. To parameterize this model, we conducted a 4-y cohort study in African buffalo to estimate the individual-level effects of coinfection with two bacterial pathogens, bovine tuberculosis (bTB) and brucellosis, across a range of demographic and environmental contexts. At the individual level, our empirical results identified bTB as a risk factor for acquiring brucellosis, but we found no association between brucellosis and the risk of acquiring bTB. Both infections were associated with reductions in survival and neither infection was associated with reductions in fecundity. The model reproduced coinfection patterns in the data and predicted opposite impacts of coinfection at individual and population scales: Whereas bTB facilitated brucellosis infection at the individual level, our model predicted the presence of brucellosis to have a strong negative impact on bTB at the population level. In modeled populations where brucellosis was present, the endemic prevalence and basic reproduction number (R0) of bTB were lower than in populations without brucellosis. Therefore, these results provide a data-driven example of competition between coinfecting pathogens that occurs when one pathogen facilitates secondary infections at the individual level.

Leveraging data science to enhance suicide prevention research: a literature review

2021 ◽  
pp. injuryprev-2021-044322
Author(s):  
Avital Rachelle Wulz ◽  
Royal Law ◽  
Jing Wang ◽  
Amy Funk Wolkin
Keyword(s):  
Risk Factors ◽  
Literature Review ◽  
Injury Prevention ◽  
Suicide Prevention ◽  
Data Science ◽  
Population Level ◽  
Individual Risk ◽  
Prevention Research ◽  
Science Method ◽  
Individual Level

ObjectiveThe purpose of this research is to identify how data science is applied in suicide prevention literature, describe the current landscape of this literature and highlight areas where data science may be useful for future injury prevention research.DesignWe conducted a literature review of injury prevention and data science in April 2020 and January 2021 in three databases.MethodsFor the included 99 articles, we extracted the following: (1) author(s) and year; (2) title; (3) study approach (4) reason for applying data science method; (5) data science method type; (6) study description; (7) data source and (8) focus on a disproportionately affected population.ResultsResults showed the literature on data science and suicide more than doubled from 2019 to 2020, with articles with individual-level approaches more prevalent than population-level approaches. Most population-level articles applied data science methods to describe (n=10) outcomes, while most individual-level articles identified risk factors (n=27). Machine learning was the most common data science method applied in the studies (n=48). A wide array of data sources was used for suicide research, with most articles (n=45) using social media and web-based behaviour data. Eleven studies demonstrated the value of applying data science to suicide prevention literature for disproportionately affected groups.ConclusionData science techniques proved to be effective tools in describing suicidal thoughts or behaviour, identifying individual risk factors and predicting outcomes. Future research should focus on identifying how data science can be applied in other injury-related topics.

scholarly journals Smart Sanitation—Biosensors as a Public Health Tool in Sanitation Infrastructure

2020 ◽  
Vol 17 (14) ◽  
pp. 5146 ◽  
Author(s):  
Emma Rary ◽  
Sarah M. Anderson ◽  
Brandon D. Philbrick ◽  
Tanvi Suresh ◽  
Jasmine Burton
Keyword(s):  
Public Health ◽  
Health Monitoring ◽  
Disease Surveillance ◽  
Population Level ◽  
Cost Effective ◽  
Small Scale ◽  
Individual Level ◽  
Emergent Technologies ◽  
The Individual ◽  
Sanitation Infrastructure

The health of individuals and communities is more interconnected than ever, and emergent technologies have the potential to improve public health monitoring at both the community and individual level. A systematic literature review of peer-reviewed and gray literature from 2000-present was conducted on the use of biosensors in sanitation infrastructure (such as toilets, sewage pipes and septic tanks) to assess individual and population health. 21 relevant papers were identified using PubMed, Embase, Global Health, CDC Stacks and NexisUni databases and a reflexive thematic analysis was conducted. Biosensors are being developed for a range of uses including monitoring illicit drug usage in communities, screening for viruses and diagnosing conditions such as diabetes. Most studies were nonrandomized, small-scale pilot or lab studies. Of the sanitation-related biosensors found in the literature, 11 gathered population-level data, seven provided real-time continuous data and 14 were noted to be more cost-effective than traditional surveillance methods. The most commonly discussed strength of these technologies was their ability to conduct rapid, on-site analysis. The findings demonstrate the potential of this emerging technology and the concept of Smart Sanitation to enhance health monitoring at the individual level (for diagnostics) as well as at the community level (for disease surveillance).

scholarly journals Individual-Level and Population-Level Lateralization: Two Sides of the Same Coin

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 739 ◽  
Author(s):  
Elisa Frasnelli ◽  
Giorgio Vallortigara
Keyword(s):  
Evolutionarily Stable Strategy ◽  
Population Level ◽  
Point Of View ◽  
Theoretical Point ◽  
Evolutionarily Stable Strategies ◽  
Functional Roles ◽  
Individual Level ◽  
Social Species ◽  
The Individual ◽  
Evolutionarily Stable

Lateralization, i.e., the different functional roles played by the left and right sides of the brain, is expressed in two main ways: (1) in single individuals, regardless of a common direction (bias) in the population (aka individual-level lateralization); or (2) in single individuals and in the same direction in most of them, so that the population is biased (aka population-level lateralization). Indeed, lateralization often occurs at the population-level, with 60–90% of individuals showing the same direction (right or left) of bias, depending on species and tasks. It is usually maintained that lateralization can increase the brain’s efficiency. However, this may explain individual-level lateralization, but not population-level lateralization, for individual brain efficiency is unrelated to the direction of the asymmetry in other individuals. From a theoretical point of view, a possible explanation for population-level lateralization is that it may reflect an evolutionarily stable strategy (ESS) that can develop when individually asymmetrical organisms are under specific selective pressures to coordinate their behavior with that of other asymmetrical organisms. This prediction has been sometimes misunderstood as it is equated with the idea that population-level lateralization should only be present in social species. However, population-level asymmetries have been observed in aggressive and mating displays in so-called “solitary” insects, suggesting that engagement in specific inter-individual interactions rather than “sociality” per se may promote population-level lateralization. Here, we clarify that the nature of inter-individuals interaction can generate evolutionarily stable strategies of lateralization at the individual- or population-level, depending on ecological contexts, showing that individual-level and population-level lateralization should be considered as two aspects of the same continuum.

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