Individual-based models

2021 ◽  
pp. 213-228
Author(s):  
Viktoriia Radchuk ◽  
Stephanie Kramer-Schadt ◽  
Uta Berger ◽  
Cédric Scherer ◽  
Pia Backmann ◽  
...  
Keyword(s):  
Research Question ◽  
Plant Defence ◽  
Population Cycles ◽  
Population Level ◽  
Adaptive Behaviour ◽  
Heterogeneous Environments ◽  
Individual Level ◽  
Intraspecific Trait Variation ◽  
Individual Based Models ◽  
The Individual

Individual-based models (IBMs, also known as agent-based models) are mechanistic models in which demographic population trends emerge from processes at the individual level. IBMs are used instead of more aggregated approaches whenever one or more of the following aspects are deemed too relevant to be ignored: intraspecific trait variation, local interactions, adaptive behaviour, and response to spatially and temporally heterogeneous environments, which often results in nonlinear feedbacks. IBMs offer a high degree of flexibility and therefore vary widely in structure and resolution, depending on the research question, system under investigation, and available data. Data used to parameterise an IBM can be divided into two categories: species and environmental data. Unlike other model types, qualitative empirical knowledge can be taken into account via probabilistic rules. IBM flexibility is often associated with higher number of parameters and hence higher uncertainty; therefore sensitivity analysis and validation are extremely important tools for analysing these models. The chapter presents three examples: a vole–mustelid model used to understand the mechanisms underlying population cycles in rodents; a wild boar–virus model to study persistence of wildlife diseases in heterogeneous landscapes; and a wild tobacco-moth caterpillar model to study emergence of delayed chemical plant defence against insect herbivores. These examples demonstrate the ability of IBMs to decipher mechanisms driving observed phenomena at the population level and their role in planning applied conservation measures. IBMs typically require more data and effort than other model types, but rewards in terms of structural realism, understanding, and decision support are high.

scholarly journals Testing, tracing and isolation in compartmental models

2021 ◽  
Vol 17 (3) ◽  
pp. e1008633
Author(s):  
Simone Sturniolo ◽  
William Waites ◽  
Tim Colbourn ◽  
David Manheim ◽  
Jasmina Panovska-Griffiths
Keyword(s):  
Computational Cost ◽  
Disease Outbreaks ◽  
Population Level ◽  
Compartmental Models ◽  
Contact Tracing ◽  
Adaptive Planning ◽  
Agent Based ◽  
Individual Level ◽  
Individual Based Models ◽  
The Individual

Existing compartmental mathematical modelling methods for epidemics, such as SEIR models, cannot accurately represent effects of contact tracing. This makes them inappropriate for evaluating testing and contact tracing strategies to contain an outbreak. An alternative used in practice is the application of agent- or individual-based models (ABM). However ABMs are complex, less well-understood and much more computationally expensive. This paper presents a new method for accurately including the effects of Testing, contact-Tracing and Isolation (TTI) strategies in standard compartmental models. We derive our method using a careful probabilistic argument to show how contact tracing at the individual level is reflected in aggregate on the population level. We show that the resultant SEIR-TTI model accurately approximates the behaviour of a mechanistic agent-based model at far less computational cost. The computational efficiency is such that it can be easily and cheaply used for exploratory modelling to quantify the required levels of testing and tracing, alone and with other interventions, to assist adaptive planning for managing disease outbreaks.

scholarly journals Anomalous diffusion of heterogeneous populations characterized by normal diffusion at the individual level

2008 ◽  
Vol 6 (30) ◽  
pp. 111-122 ◽  
Author(s):  
Simona Hapca ◽  
John W Crawford ◽  
Iain M Young
Keyword(s):  
Diffusion Coefficient ◽  
Effective Diffusion ◽  
Continuous Distribution ◽  
Population Level ◽  
Heterogeneous Environments ◽  
Heterogeneous Populations ◽  
Individual Level ◽  
Temporal Correlations ◽  
Normal Diffusion ◽  
The Individual

The characterization of the dispersal of populations of non-identical individuals is relevant to most ecological and epidemiological processes. In practice, the movement is quantified by observing relatively few individuals, and averaging to estimate the rate of dispersal of the population as a whole. Here, we show that this can lead to serious errors in the predicted movement of the population if the individuals disperse at different rates. We develop a stochastic model for the diffusion of heterogeneous populations, inspired by the movement of the parasitic nematode Phasmarhabditis hermaphrodita . Direct observations of this nematode in homogeneous and heterogeneous environments reveal a large variation in individual behaviour within the population as reflected initially in the speed of the movement. Further statistical analysis shows that the movement is characterized by temporal correlations and in a heterogeneously structured environment the correlations that occur are of shorter range compared with those in a homogeneous environment. Therefore, by using the first-order correlated random walk techniques, we derive an effective diffusion coefficient for each individual, and show that there is a significant variation in this parameter among the population that follows a gamma distribution. Based on these findings, we build a new dispersal model in which we maintain the classical assumption that individual movement can be described by normal diffusion, but due to the variability in individual dispersal rates, the diffusion coefficient is not constant at the population level and follows a continuous distribution. The conclusions and methodology presented are relevant to any heterogeneous population of individuals with widely different diffusion rates.

A Culture of Organizational Grit From the Perspective of U.S. Military Officers: A Qualitative Inquiry

2021 ◽  
pp. 0095327X2098519
Author(s):  
Celeste Raver Luning ◽  
Prince A. Attoh ◽  
Tao Gong ◽  
James T. Fox
Keyword(s):  
Research Question ◽  
Qualitative Inquiry ◽  
Growth Mindset ◽  
Organizational Level ◽  
Military Officers ◽  
Individual Level ◽  
Qualitative Research Design ◽  
Professional Pride ◽  
The Individual ◽  
The Military

With the backdrop of the utility of grit at the individual level, speculation has begun to circulate that grit may exist as an organizational level phenomenon. To explore this potential construct, this study used an exploratory, qualitative research design. This study explored grit at the organizational level by interviewing leaders’ perceptions of what may be a culture of organizational grit. Participants included 14 U.S. military officers. Seven themes emerged relative to the research question: “What do U.S. military officers perceive as a culture of organizational grit?” Themes included professional pride, team unity, resilience-determination, mission accomplishment, core values, growth mindset, and deliberate practice. This study indicated that a culture of organizational grit is likely a combination of converging organizational elements. Overall, findings indicate that there may be a culture of organizational grit in the military and at the least, more research examining the concept is warranted.

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.

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.

Ecological Research for Studies of Violence: A Methodological Guide

2019 ◽  
Vol 34 (23-24) ◽  
pp. 4860-4880
Author(s):  
April M. Zeoli ◽  
Jennifer K. Paruk ◽  
Jesenia M. Pizarro ◽  
Jason Goldstick
Keyword(s):  
Research Question ◽  
Population Level ◽  
Ecological Research ◽  
Ecological Studies ◽  
Individual Level ◽  
Research Guidelines ◽  
Units Of Analysis ◽  
Research Designs ◽  
Ecological Unit ◽  
Existing Data

Ecological research is important to the study of violence in communities. The phrases “ecological research” and “ecologic study” describe those research studies that use grouped or geographic units of analysis, such as zip codes, cities, or states. This type of research allows for the investigation of group-level effects and can be inexpensive and relatively quick to conduct if the researcher uses existing data. And, importantly, ecological studies are an efficient means for hypothesis generation prior to, and can be used to justify, costlier individual-level studies. Ecological research designs may be employed to study violence outcomes when the research question is at the population level, either for theoretical reasons, or when an exposure or intervention is at the population level, or when individual-level studies are not feasible; however, ecological research results must not be used to make individual-level inferences. This article will discuss reasons to conduct ecological-level research, guidelines for choosing the ecological unit of analysis, frequently used research designs, common limitations of ecological research, including the ecological fallacy, and issues to consider when using existing data.

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