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Qian W, Cooke A, Stanley KG, Osgood ND. Comparing Contact Tracing Through Bluetooth and GPS Surveillance Data: Simulation-Driven Approach. J Med Internet Res 2024; 26:e38170. [PMID: 38422493 PMCID: PMC11025599 DOI: 10.2196/38170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 11/15/2023] [Accepted: 02/27/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND Accurate and responsive epidemiological simulations of epidemic outbreaks inform decision-making to mitigate the impact of pandemics. These simulations must be grounded in quantities derived from measurements, among which the parameters associated with contacts between individuals are notoriously difficult to estimate. Digital contact tracing data, such as those provided by Bluetooth beaconing or GPS colocating, can provide more precise measures of contact than traditional methods based on direct observation or self-reporting. Both measurement modalities have shortcomings and are prone to false positives or negatives, as unmeasured environmental influences bias the data. OBJECTIVE We aim to compare GPS colocated versus Bluetooth beacon-derived proximity contact data for their impacts on transmission models' results under community and types of diseases. METHODS We examined the contact patterns derived from 3 data sets collected in 2016, with participants comprising students and staff from the University of Saskatchewan in Canada. Each of these 3 data sets used both Bluetooth beaconing and GPS localization on smartphones running the Ethica Data (Avicenna Research) app to collect sensor data about every 5 minutes over a month. We compared the structure of contact networks inferred from proximity contact data collected with the modalities of GPS colocating and Bluetooth beaconing. We assessed the impact of sensing modalities on the simulation results of transmission models informed by proximate contacts derived from sensing data. Specifically, we compared the incidence number, attack rate, and individual infection risks across simulation results of agent-based susceptible-exposed-infectious-removed transmission models of 4 different contagious diseases. We have demonstrated their differences with violin plots, 2-tailed t tests, and Kullback-Leibler divergence. RESULTS Both network structure analyses show visually salient differences in proximity contact data collected between GPS colocating and Bluetooth beaconing, regardless of the underlying population. Significant differences were found for the estimated attack rate based on distance threshold, measurement modality, and simulated disease. This finding demonstrates that the sensor modality used to trace contact can have a significant impact on the expected propagation of a disease through a population. The violin plots of attack rate and Kullback-Leibler divergence of individual infection risks demonstrated discernible differences for different sensing modalities, regardless of the underlying population and diseases. The results of the t tests on attack rate between different sensing modalities were mostly significant (P<.001). CONCLUSIONS We show that the contact networks generated from these 2 measurement modalities are different and generate significantly different attack rates across multiple data sets and pathogens. While both modalities offer higher-resolution portraits of contact behavior than is possible with most traditional contact measures, the differential impact of measurement modality on the simulation outcome cannot be ignored and must be addressed in studies only using a single measure of contact in the future.
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Affiliation(s)
- Weicheng Qian
- Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada
| | - Aranock Cooke
- Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada
| | - Kevin Gordon Stanley
- Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada
| | - Nathaniel David Osgood
- Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada
- Department of Community Health & Epidemiology, University of Saskatchewan, Saskatoon, SK, Canada
- Bioengineering Division, University of Saskatchewan, Saskatoon, SK, Canada
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Lee S, Zabinsky ZB, Wasserheit JN, Ross JM, Chen S, Liu S. Impact of Vaccination and Nonpharmaceutical Interventions With Possible COVID-19 Viral Evolutions Using an Agent-Based Simulation. AJPM Focus 2024; 3:100155. [PMID: 38130803 PMCID: PMC10733698 DOI: 10.1016/j.focus.2023.100155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Introduction The COVID-19 pandemic continues with highly contagious variants and waning immunity. As the virus keeps evolving to be more infectious and immune evasive, some question whether the COVID-19 pandemic can be managed through sustainable public health measures. Methods We developed an agent-based simulation to explore the impact of COVID-19 mutations, periodic vaccinations, and nonpharmaceutical interventions on reducing COVID-19 deaths. The model is calibrated to the greater Seattle area by observing local epidemic data. We perform scenario analyses on viral mutations that change infectiousness, disease severity, and immune evasiveness from previous infections and vaccination every 6 months. The simulation is run until the end of year 2023. Results Variants with increased infectivity or increased immune evasion dominate previous strains. With enhanced immune protection from a pancoronavirus vaccine, the most optimistic periodic vaccination rate reduces average total deaths by 44.6% compared with the most pessimistic periodic vaccination rate. A strict threshold nonpharmaceutical intervention policy reduces average total deaths by 71.3% compared with an open society, whereas a moderate nonpharmaceutical intervention policy results in a 33.6% reduction. Conclusions Our findings highlight the potential benefits of pancoronavirus vaccines that offer enhanced and longer-lasting immunity. We emphasize the crucial role of nonpharmaceutical interventions in reducing COVID-19 deaths regardless of virus mutation scenarios. Owing to highly immune evasive and contagious SARS-CoV-2 variants, most scenarios in this study fail to reduce the mortality of COVID-19 to the level of influenza and pneumonia. However, our findings indicate that periodic vaccinations and a threshold nonpharmaceutical intervention policy may succeed in achieving this goal. This indicates the need for caution and vigilance in managing a continuing COVID-19 epidemic.
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Affiliation(s)
- Serin Lee
- Department of Industrial & Systems Engineering, University of Washington, Seattle, Washington
| | - Zelda B. Zabinsky
- Department of Industrial & Systems Engineering, University of Washington, Seattle, Washington
| | - Judith N. Wasserheit
- Department of Global Health, University of Washington, Seattle, Washington
- Division of Allergy & Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington
| | - Jennifer M. Ross
- Division of Allergy & Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington
| | - Shi Chen
- Department of Information Systems and Operations Management, Foster School of Business, University of Washington, Seattle, Washington
| | - Shan Liu
- Department of Industrial & Systems Engineering, University of Washington, Seattle, Washington
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Wang K, Tseng CY, Li Z, White C, Wang B, Levine BL, Fesnak AD. A simulation-based comparison of centralized and point-of-care supply chain strategies for autologous cell therapy. Cytotherapy 2023; 25:1370-1379. [PMID: 37747394 DOI: 10.1016/j.jcyt.2023.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 08/16/2023] [Accepted: 08/17/2023] [Indexed: 09/26/2023]
Abstract
BACKGROUND AIMS The selection between centralized and point-of-care (POC) manufacturing supply-chain network design is a crucial consideration in the autologous cell therapy (AuCT) industry, as each approach offers its advantages and disadvantages. METHODS This study uses a simulation-based approach to compare and examine the two strategies using the supply chain for chimeric antigen receptor T-cell therapy manufacturing as an exemplar. When does it make sense to use one manufacturing strategy over another? Currently, major manufacturers in the AuCT industry use centralized supply-chain strategies predominantly in practice. The simulation results explain the reasons for this choice. To enhance the competitiveness of the POC strategy, two operation rules are proposed and tested with the simulation. The study uses key performance indicators such as cost, fulfillment time, service level, and resource utilization to provide generic guidelines based on the findings. RESULTS The results have revealed that (i) the centralized supply-chain strategy has a significant advantage at current demand levels of a few thousand products per year; (ii) "optimal capacity" exists for the POC strategy that minimizes the cost of goods and (iii) allowing part-time labor and order transshipment can significantly increase the competitiveness of the POC strategy. CONCLUSIONS This study may be useful in helping commercial manufacturers make informed decisions about their manufacturing approach to enhance their competitiveness in the market and to ensure a high level of patient benefit.
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Affiliation(s)
- Kan Wang
- Georgia Tech Manufacturing Institute, Georgia Institute of Technology, Atlanta, Georgia, USA.
| | - Chin-Yuan Tseng
- Georgia Tech Manufacturing Institute, Georgia Institute of Technology, Atlanta, Georgia, USA; School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
| | - Zhaowei Li
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Chip White
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Ben Wang
- Georgia Tech Manufacturing Institute, Georgia Institute of Technology, Atlanta, Georgia, USA; H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA; School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Bruce L Levine
- Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA; Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Andrew D Fesnak
- Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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He Y, Martinez L, Ge Y, Feng Y, Chen Y, Tan J, Westbrook A, Li C, Cheng W, Ling F, Cheng H, Wu S, Zhong W, Handel A, Huang H, Sun J, Shen Y. Social Mixing and Network Characteristics of COVID-19 Patients Before and After Widespread Interventions: A Population-based Study. Epidemiol Infect 2023; 151:1-38. [PMID: 37577939 PMCID: PMC10540215 DOI: 10.1017/s0950268823001292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 06/28/2023] [Accepted: 07/31/2023] [Indexed: 08/15/2023] Open
Abstract
SARS-CoV-2 rapidly spreads among humans via social networks, with social mixing and network characteristics potentially facilitating transmission. However, limited data on topological structural features has hindered in-depth studies. Existing research is based on snapshot analyses, preventing temporal investigations of network changes. Comparing network characteristics over time offers additional insights into transmission dynamics. We examined confirmed COVID-19 patients from an eastern Chinese province, analyzing social mixing and network characteristics using transmission network topology before and after widespread interventions. Between the two time periods, the percentage of singleton networks increased from 38.9 to 62.8 ; the average shortest path length decreased from 1.53 to 1.14 ; the average betweenness reduced from 0.65 to 0.11 ; the average cluster size dropped from 4.05 to 2.72 ; and the out-degree had a slight but nonsignificant decline from 0.75 to 0.63 Results show that nonpharmaceutical interventions effectively disrupted transmission networks, preventing further disease spread. Additionally, we found that the networks’ dynamic structure provided more information than solely examining infection curves after applying descriptive and agent-based modeling approaches. In summary, we investigated social mixing and network characteristics of COVID-19 patients during different pandemic stages, revealing transmission network heterogeneities.
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Affiliation(s)
- Yuncong He
- School of Mathematics, Sun Yat-sen University, Guangzhou, China
| | - Leonardo Martinez
- Department of Epidemiology, School of Public Health, Boston University, Boston, USA
| | - Yang Ge
- School of Health Professions, University of Southern Mississippi, Hattiesburg, USA
| | - Yan Feng
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Yewen Chen
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, USA
| | - Jianbin Tan
- School of Mathematics, Sun Yat-sen University, Guangzhou, China
| | - Adrianna Westbrook
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, USA
| | - Changwei Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, USA
| | - Wei Cheng
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Feng Ling
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Huimin Cheng
- Department of Statistics, University of Georgia, Athens, USA
| | - Shushan Wu
- Department of Statistics, University of Georgia, Athens, USA
| | - Wenxuan Zhong
- Department of Statistics, University of Georgia, Athens, USA
| | - Andreas Handel
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, USA
| | - Hui Huang
- Center for Applied Statistics and School of Statistics, Renmin University of China, Beijing, China
| | - Jimin Sun
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Ye Shen
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, USA
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He C, Jia G, McCabe B, Chen Y, Zhang P, Sun J. Psychological decision-making process of construction worker safety behavior: an agent-based simulation approach. Int J Occup Saf Ergon 2023; 29:141-153. [PMID: 34952562 DOI: 10.1080/10803548.2021.2022351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Objectives. Relationships between safety behavior and its antecedents have been widely studied. However, the psychological decision-making process of construction worker safety behavior (CWSB) is rarely examined from the systematic perspective. Thus, this study constructed the theoretical framework for the decision-making process of CWSB and systematically explored effects of individual factors (education, age and safety knowledge), organizational factors (safety climate and leader-member exchange [LMX]) and psychological factors (psychological capital [PsyCap] and communication competence [CommComp]) on the dynamic performance of CWSB. Methods. Data were collected from the literature and 536 construction workers in China. The theoretical model was tested with the agent-based simulation (ABS) technique. Results. High level of education, safety knowledge, safety climate, LMX, PsyCap and CommComp help to reduce unsafe behavior at the cut-off point. However, the age-safety relationship might present a U-shape, which denotes that reasonable age structure of construction worker groups may be an option for bettering safety performance. The results indicate that the psychological decision-making process of CWSB is not only the result of individual rational decision, but also the product of organizational and psychological impacts. Findings of this study shed lights on safety behavior management practices based on the psychological decision-making process of CWSB.
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Affiliation(s)
- Changquan He
- College of Civil Engineering, Shanghai Normal University, China
| | - Guangshe Jia
- Department of Construction Management and Real Estate, Tongji University, China
| | - Brenda McCabe
- Department of Civil Engineering, University of Toronto, Canada
| | - Yuting Chen
- Department of Engineering Technology and Construction Management, University of North Carolina at Charlotte, USA
| | - Puwei Zhang
- College of City Construction, Jiangxi Normal University, China
| | - Jide Sun
- Department of Construction Management and Real Estate, Tongji University, China
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Picardi S, Abrahms B, Gelzer E, Morrison TA, Verzuh T, Merkle JA. Defining null expectations for animal site fidelity. Ecol Lett 2023; 26:157-169. [PMID: 36453059 DOI: 10.1111/ele.14148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 10/31/2022] [Accepted: 11/02/2022] [Indexed: 12/03/2022]
Abstract
Site fidelity-the tendency to return to previously visited locations-is widespread across taxa. Returns may be driven by several mechanisms, including memory, habitat selection, or chance; however, pattern-based definitions group different generating mechanisms under the same label of 'site fidelity', often assuming memory as the main driver. We propose an operational definition of site fidelity as patterns of return that deviate from a null expectation derived from a memory-free movement model. First, using agent-based simulations, we show that without memory, intrinsic movement characteristics and extrinsic landscape characteristics are key determinants of return patterns and that even random movements may generate substantial probabilities of return. Second, we illustrate how to implement our framework empirically to establish ecologically meaningful, system-specific null expectations for site fidelity. Our approach provides a conceptual and operational framework to test hypotheses on site fidelity across systems and scales.
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Affiliation(s)
- Simona Picardi
- Department of Wildland Resources, Jack H. Berryman Institute, Utah State University, Logan, Utah, USA
| | - Briana Abrahms
- Center for Ecosystem Sentinels, Department of Biology, University of Washington, Seattle, Washington, USA
| | - Emily Gelzer
- Department of Zoology and Physiology, University of Wyoming, Laramie, Wyoming, USA
| | - Thomas A Morrison
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, UK
| | - Tana Verzuh
- Department of Zoology and Physiology, University of Wyoming, Laramie, Wyoming, USA
| | - Jerod A Merkle
- Department of Zoology and Physiology, University of Wyoming, Laramie, Wyoming, USA
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Harweg T, Wagner M, Weichert F. Agent-Based Simulation for Infectious Disease Modelling over a Period of Multiple Days, with Application to an Airport Scenario. Int J Environ Res Public Health 2022; 20:545. [PMID: 36612868 PMCID: PMC9819456 DOI: 10.3390/ijerph20010545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 12/16/2022] [Accepted: 12/20/2022] [Indexed: 06/17/2023]
Abstract
With the COVID-19 pandemic, the role of infectious disease spreading in public places has been brought into focus more than ever. Places that are of particular interest regarding the spread of infectious diseases are international airport terminals, not only for the protection of staff and ground crew members but also to help minimize the risk of the spread of infectious entities such as COVID-19 around the globe. Computational modelling and simulation can help in understanding and predicting the spreading of infectious diseases in any such scenario. In this paper, we propose a model, which combines a simulation of high geometric detail regarding virus spreading with an account of the temporal progress of infection dynamics. We, thus, introduce an agent-based social force model for tracking the spread of infectious diseases by modelling aerosol traces and concentration of virus load in the air. We complement this agent-based model to have consistency over a period of several days. We then apply this model to investigate simulations in a realistic airport setting with multiple virus variants of varying contagiousness. According to our experiments, a virus variant has to be at least twelve times more contagious than the respective control to result in a level of infection of more than 30%. Combinations of agent-based models with temporal components can be valuable tools in an attempt to assess the risk of infection attributable to a particular virus and its variants.
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Affiliation(s)
- Thomas Harweg
- Department of Computer Science, TU Dortmund University, Otto-Hahn-Str. 16, 44227 Dortmund, North Rhine-Westphalia, Germany
| | - Mathias Wagner
- Department of Pathology, University of Saarland Medical School, Homburg Saar Campus, Kirrberger Strasse 100, 66424 Homburg Saar, Saarland, Germany
| | - Frank Weichert
- Department of Computer Science, TU Dortmund University, Otto-Hahn-Str. 16, 44227 Dortmund, North Rhine-Westphalia, Germany
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Young E, Allen RJ. Lineage dynamics in growing biofilms: Spatial patterns of standing vs. de novo diversity. Front Microbiol 2022; 13:915095. [PMID: 35966660 PMCID: PMC9363821 DOI: 10.3389/fmicb.2022.915095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 06/30/2022] [Indexed: 11/13/2022] Open
Abstract
Microbial biofilms show high phenotypic and genetic diversity, yet the mechanisms underlying diversity generation and maintenance remain unclear. Here, we investigate how spatial patterns of growth activity within a biofilm lead to spatial patterns of genetic diversity. Using individual-based computer simulations, we show that the active layer of growing cells at the biofilm interface controls the distribution of lineages within the biofilm, and therefore the patterns of standing and de novo diversity. Comparing biofilms of equal size, those with a thick active layer retain more standing diversity, while de novo diversity is more evenly distributed within the biofilm. In contrast, equal-sized biofilms with a thin active layer retain less standing diversity, and their de novo diversity is concentrated at the top of the biofilm, and in fewer lineages. In the context of antimicrobial resistance, biofilms with a thin active layer may be more prone to generate lineages with multiple resistance mutations, and to seed new resistant biofilms via sloughing of resistant cells from the upper layers. Our study reveals fundamental "baseline" mechanisms underlying the patterning of diversity within biofilms.
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Affiliation(s)
- Ellen Young
- School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom
| | - Rosalind J. Allen
- School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom
- Theoretical Microbial Ecology, Institute of Microbiology, Faculty of Biological Sciences, Friedrich Schiller University Jena, Jena, Germany
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9
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Wang Z, Li Y, Jain A, Pierce NE. Agent-based models reveal limits of mark-release-recapture estimates for the rare butterfly, Bhutanitis thaidina (Lepidoptera: Papilionidae). Insect Sci 2022; 29:550-566. [PMID: 34263543 DOI: 10.1111/1744-7917.12949] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 06/15/2021] [Accepted: 06/16/2021] [Indexed: 06/13/2023]
Abstract
Insect diversity and abundance are in drastic decline worldwide, but quantifying insect populations to better conserve them is a difficult task. Mark-release-recapture (MRR) is widely used as an ecological indicator for insect populations, but the accuracy of MRR estimates can vary with factors such as spatial scale, sampling effort and models of inference. We conducted a 3-year MRR study of B. thaidina in Yanzigou valley, Mt. Gongga but failed to obtain sufficient data for a robust population estimate. This prompted us to integrate B. thaidina life history information to parameterize agent-based models and evaluate the conditions under which successful MRR studies could be conducted. We evaluated: (1) the performance of MRR models under different landscape types, and (2) the influence of experimental design on the accuracy and variance of MRR-based estimates. Our simulations revealed systematic underestimates of true population parameters by MRR models when sampling effort was insufficient. In a total of 2772 simulations, subjective decisions in sampling protocol (e.g., frequency, number of sampling locations, use of spatially explicit models, type of estimands) accounted for nearly half of the variation in estimates. We conclude that MRR-based estimates could be improved with the addition of more field-specific parameters.
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Affiliation(s)
- Zhengyang Wang
- Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
| | - Yuanheng Li
- Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
| | - Anuj Jain
- Nature Society (Singapore), Singapore, Singapore
| | - Naomi E Pierce
- Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
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Renda F, Miles C, Tikhonenko I, Fisher R, Carlini L, Kapoor TM, Mogilner A, Khodjakov A. Non-centrosomal microtubules at kinetochores promote rapid chromosome biorientation during mitosis in human cells. Curr Biol 2022; 32:1049-1063.e4. [PMID: 35108523 PMCID: PMC8930511 DOI: 10.1016/j.cub.2022.01.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 11/23/2021] [Accepted: 01/06/2022] [Indexed: 12/18/2022]
Abstract
Proper segregation of chromosomes during mitosis depends on "amphitelic attachments"-load-bearing connections of sister kinetochores to the opposite spindle poles via bundles of microtubules, termed as the "K-fibers." Current models of spindle assembly assume that K-fibers arise largely from stochastic capture of microtubules, which occurs at random times and locations and independently at sister kinetochores. We test this assumption by following the movements of all kinetochores in human cells and determine that most amphitelic attachments form synchronously at a specific stage of spindle assembly and within a spatially distinct domain. This biorientation domain is enriched in bundles of antiparallel microtubules, and perturbation of microtubule bundling changes the temporal and spatial dynamics of amphitelic attachment formation. Structural analyses indicate that interactions of kinetochores with microtubule bundles are mediated by non-centrosomal short microtubules that emanate from most kinetochores during early prometaphase. Computational analyses suggest that momentous molecular motor-driven interactions with antiparallel bundles rapidly convert these short microtubules into nascent K-fibers. Thus, load-bearing connections to the opposite spindle poles form simultaneously on sister kinetochores. In contrast to the uncoordinated sequential attachments of sister kinetochores expected in stochastic models of spindle assembly, our model envisions the formation of amphitelic attachments as a deterministic process in which the chromosomes connect with the spindle poles synchronously at a specific stage of spindle assembly and at a defined location determined by the spindle architecture. Experimental analyses of changes in the kinetochore behavior in cells with perturbed activity of molecular motors CenpE and dynein confirm the predictive power of the model.
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Affiliation(s)
- Fioranna Renda
- Wadsworth Center, New York State Department of Health, Albany, NY, USA
| | - Christopher Miles
- Courant Institute and Department of Biology, New York University, New York, NY, USA; Department of Mathematics and the NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine, Irvine, CA, USA
| | - Irina Tikhonenko
- Wadsworth Center, New York State Department of Health, Albany, NY, USA
| | - Rebecca Fisher
- Wadsworth Center, New York State Department of Health, Albany, NY, USA
| | - Lina Carlini
- Laboratory of Chemistry and Cell Biology, Rockefeller University, New York, NY, USA
| | - Tarun M Kapoor
- Laboratory of Chemistry and Cell Biology, Rockefeller University, New York, NY, USA
| | - Alex Mogilner
- Courant Institute and Department of Biology, New York University, New York, NY, USA.
| | - Alexey Khodjakov
- Wadsworth Center, New York State Department of Health, Albany, NY, USA; Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY, USA.
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11
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Bai Y, He C, Chu P, Long J, Li X, Fu X. Spatial modulation of individual behaviors enables an ordered structure of diverse phenotypes during bacterial group migration. eLife 2021; 10:67316. [PMID: 34726151 PMCID: PMC8563000 DOI: 10.7554/elife.67316] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 09/16/2021] [Indexed: 11/22/2022] Open
Abstract
Coordination of diverse individuals often requires sophisticated communications and high-order computational abilities. Microbial populations can exhibit diverse individualistic behaviors, and yet can engage in collective migratory patterns with a spatially sorted arrangement of phenotypes. However, it is unclear how such spatially sorted patterns emerge from diverse individuals without complex computational abilities. Here, by investigating the single-cell trajectories during group migration, we discovered that, despite the constant migrating speed of a group, the drift velocities of individual bacteria decrease from the back to the front. With a Langevin-type modeling framework, we showed that this decreasing profile of drift velocities implies the spatial modulation of individual run-and-tumble random motions, and enables the bacterial population to migrate as a pushed wave front. Theoretical analysis and stochastic simulations further predicted that the pushed wave front can help a diverse population to stay in a tight group, while diverse individuals perform the same type of mean reverting processes around centers orderly aligned by their chemotactic abilities. This mechanism about the emergence of orderly collective migration from diverse individuals is experimentally demonstrated by titration of bacterial chemoreceptor abundance. These results reveal a simple computational principle for emergent ordered behaviors from heterogeneous individuals. Organisms living in large groups often have to move together in order to navigate, forage for food, and increase their roaming range. Such groups are often made up of distinct individuals that must integrate their different behaviors in order to migrate in the same direction at a similar pace. For instance, for the bacteria Escherichia coli to travel as a condensed group, they must coordinate their response to a set of chemical signals called chemoattractants that tell them where to go. The chemoattractants surrounding the bacteria are unequally distributed so that there is more of them at the front than the back of the group. During migration, each bacterium moves towards this concentration gradient in a distinct way, spontaneously rotating its direction in a ‘run-and-tumble’ motion that guides it towards areas where there are high levels of these chemical signals. In addition to this variability, how well individual bacteria are able to swim up the gradient also differs within the population. Bacteria that are better at sensing the chemoattractant gradient are placed at the front of the group, while those that are worst are shifted towards the back. This spatial arrangement is thought to help the bacteria migrate together. But how E. coli organize themselves in to this pattern is unclear, especially as they cannot communicate directly with one another and display such diverse, randomized behaviors. To help answer this question, Bai, He et al. discovered a general principle that describes how single bacterial cells move within a group. The results showed that E. coli alter their run-and-tumble motion depending on where they reside within the population: individuals at the rear drift faster so they can catch up with the group, while those leading the group drift slower to draw themselves back. This ‘reversion behavior’ allows the migrating bacteria to travel at a constant speed around a mean position relative to the group. A cell’s drifting speed is determined by how well it moves towards the chemoattractant and its response to the concentration gradient. As a result, the mean position around which the bacterium accelerates or deaccelerates will vary depending on how sensitive it is to the chemoattractant gradient. The E. coli therefore spatially arrange themselves so that the more sensitive bacteria are located at the front of the group where the gradient is shallower; and cells that are less sensitive are located towards the back where the gradient is steeper. These findings suggest a general principle for how bacteria form ordered patterns whilst migrating as a collective group. This behavior could also apply to other populations of distinct individuals, such as ants following a trail or flocks of birds migrating in between seasons.
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Affiliation(s)
- Yang Bai
- CAS Key Laboratory for Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Caiyun He
- CAS Key Laboratory for Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Pan Chu
- CAS Key Laboratory for Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Junjiajia Long
- Yale University, Department of Physics, New Haven, United States
| | - Xuefei Li
- CAS Key Laboratory for Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Xiongfei Fu
- CAS Key Laboratory for Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.,University of Chinese Academy of Sciences, Beijing, China
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12
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Lőrincz L. Do Co-Worker Networks Increase or Decrease Productivity Differences? Entropy (Basel) 2021; 23:e23111451. [PMID: 34828149 PMCID: PMC8621545 DOI: 10.3390/e23111451] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 10/19/2021] [Accepted: 10/26/2021] [Indexed: 12/02/2022]
Abstract
Do labor mobility and co-worker networks contribute to convergence or divergence between regions? Based on the previous literature, labor mobility contributes to knowledge transfer between firms. Therefore, mobility may contribute to decreasing productivity differences, while limited mobility sustains higher differences. The effect of co-worker networks, however, can be two-fold in this process; they transmit information about potential jobs, which may enhance the mobility of workers—even between regions—and this enhanced mobility may contribute to levelling of differences. However, if mobility between regions involves movement costs, co-worker networks may concentrate locally—possibly contributing to the persistence of regional differences. In this paper, we build an agent-based model of labor mobility across firms and regions with knowledge spillovers that reflects key empirical observations on labor markets. We analyze the impact of network information provided about potential employers in this model and find that it contributes to increasing inter-regional mobility, and subsequently, to decreasing regional differences. We also find that both the density of coworker networks, as well as their regional concentrations, decrease if network information is available.
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Affiliation(s)
- László Lőrincz
- NETI Lab, Corvinus Institute for Advanced Studies, Corvinus University of Budapest, 1093 Budapest, Hungary;
- ANet Lab, Institute of Economics, Centre for Economic and Regional Studies, 1097 Budapest, Hungary
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13
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Kyvik Nordås H, Klügl F. Drivers of Automation and Consequences for Jobs in Engineering Services: An Agent-Based Modelling Approach. Front Robot AI 2021; 8:637125. [PMID: 34041273 PMCID: PMC8141855 DOI: 10.3389/frobt.2021.637125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 04/21/2021] [Indexed: 11/14/2022] Open
Abstract
New technology is of little use if it is not adopted, and surveys show that less than 10% of firms use Artificial Intelligence. This paper studies the uptake of AI-driven automation and its impact on employment, using a dynamic agent-based model (ABM). It simulates the adoption of automation software as well as job destruction and job creation in its wake. There are two types of agents: manufacturing firms and engineering services firms. The agents choose between two business models: consulting or automated software. From the engineering firms’ point of view, the model exhibits static economies of scale in the software model and dynamic (learning by doing) economies of scale in the consultancy model. From the manufacturing firms’ point of view, switching to the software model requires restructuring of production and there are network effects in switching. The ABM matches engineering and manufacturing agents and derives employment of engineers and the tasks they perform, i.e. consultancy, software development, software maintenance, or employment in manufacturing. We find that the uptake of software is gradual; slow in the first few years and then accelerates. Software is fully adopted after about 18 years in the base line run. Employment of engineers shifts from consultancy to software development and to new jobs in manufacturing. Spells of unemployment may occur if skilled jobs creation in manufacturing is slow. Finally, the model generates boom and bust cycles in the software sector.
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Affiliation(s)
- Hildegunn Kyvik Nordås
- Economics and Statistics, School of Business, Örebro University, Örebro, Sweden.,Council on Economic Policies (CEP), Zürich, Switzerland
| | - Franziska Klügl
- Machine Perception and Interaction Lab, AASS, School of Science and Technology, Örebro University, Örebro, Sweden
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14
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Jahn B, Sroczynski G, Bicher M, Rippinger C, Mühlberger N, Santamaria J, Urach C, Schomaker M, Stojkov I, Schmid D, Weiss G, Wiedermann U, Redlberger-Fritz M, Druml C, Kretzschmar M, Paulke-Korinek M, Ostermann H, Czasch C, Endel G, Bock W, Popper N, Siebert U. Targeted COVID-19 Vaccination (TAV-COVID) Considering Limited Vaccination Capacities-An Agent-Based Modeling Evaluation. Vaccines (Basel) 2021; 9:434. [PMID: 33925650 PMCID: PMC8145290 DOI: 10.3390/vaccines9050434] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 04/21/2021] [Accepted: 04/22/2021] [Indexed: 12/21/2022] Open
Abstract
(1) Background: The Austrian supply of COVID-19 vaccine is limited for now. We aim to provide evidence-based guidance to the authorities in order to minimize COVID-19-related hospitalizations and deaths in Austria. (2) Methods: We used a dynamic agent-based population model to compare different vaccination strategies targeted to the elderly (65 ≥ years), middle aged (45-64 years), younger (15-44 years), vulnerable (risk of severe disease due to comorbidities), and healthcare workers (HCW). First, outcomes were optimized for an initially available vaccine batch for 200,000 individuals. Second, stepwise optimization was performed deriving a prioritization sequence for 2.45 million individuals, maximizing the reduction in total hospitalizations and deaths compared to no vaccination. We considered sterilizing and non-sterilizing immunity, assuming a 70% effectiveness. (3) Results: Maximum reduction of hospitalizations and deaths was achieved by starting vaccination with the elderly and vulnerable followed by middle-aged, HCW, and younger individuals. Optimizations for vaccinating 2.45 million individuals yielded the same prioritization and avoided approximately one third of deaths and hospitalizations. Starting vaccination with HCW leads to slightly smaller reductions but maximizes occupational safety. (4) Conclusion: To minimize COVID-19-related hospitalizations and deaths, our study shows that elderly and vulnerable persons should be prioritized for vaccination until further vaccines are available.
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Affiliation(s)
- Beate Jahn
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT—University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060 Hall in Tirol, Austria; (B.J.); (G.S.); (N.M.); (J.S.); (M.S.); (I.S.)
| | - Gaby Sroczynski
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT—University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060 Hall in Tirol, Austria; (B.J.); (G.S.); (N.M.); (J.S.); (M.S.); (I.S.)
| | - Martin Bicher
- dwh GmbH, dwh Simulation Services, Neustiftgasse 57–59, A-1070 Vienna, Austria; (M.B.); (C.R.); (C.U.); (N.P.)
- Institute of Information Systems Engineering, TU Wien, Favoritenstraße 11, A-1050 Vienna, Austria
| | - Claire Rippinger
- dwh GmbH, dwh Simulation Services, Neustiftgasse 57–59, A-1070 Vienna, Austria; (M.B.); (C.R.); (C.U.); (N.P.)
| | - Nikolai Mühlberger
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT—University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060 Hall in Tirol, Austria; (B.J.); (G.S.); (N.M.); (J.S.); (M.S.); (I.S.)
| | - Júlia Santamaria
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT—University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060 Hall in Tirol, Austria; (B.J.); (G.S.); (N.M.); (J.S.); (M.S.); (I.S.)
| | - Christoph Urach
- dwh GmbH, dwh Simulation Services, Neustiftgasse 57–59, A-1070 Vienna, Austria; (M.B.); (C.R.); (C.U.); (N.P.)
| | - Michael Schomaker
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT—University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060 Hall in Tirol, Austria; (B.J.); (G.S.); (N.M.); (J.S.); (M.S.); (I.S.)
- Center for Infectious Disease Epidemiology and Research, University of Cape Town, Barnard Fuller Building, Anzio Rd, Observatory, Cape Town 7935, South Africa
| | - Igor Stojkov
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT—University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060 Hall in Tirol, Austria; (B.J.); (G.S.); (N.M.); (J.S.); (M.S.); (I.S.)
| | - Daniela Schmid
- Division for Quantitative Methods in Public Health and Health Services Research, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT—University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060 Hall in Tirol, Austria;
| | - Günter Weiss
- Department of Internal Medicine II, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria;
| | - Ursula Wiedermann
- Center of Pathophysiology, Infectiology & Immunology (OEL), Institute of Specific Prophylaxis and Tropical Medicine, Medical University of Vienna, Kinderspitalgasse 15, 1090 Vienna, Austria;
| | - Monika Redlberger-Fritz
- Center of Virology, Medical University of Vienna, Kinderspitalgasse 15, 1090 Vienna, Austria;
| | - Christiane Druml
- UNESCO Chair on Bioethics, Medical University of Vienna, Waehringerstrasse 25, 1090 Vienna, Austria;
| | - Mirjam Kretzschmar
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX Utrecht, The Netherlands;
| | - Maria Paulke-Korinek
- Ministry of Social Affairs, Health, Care and Consumer Protection, Stubenring 1, 1010 Vienna, Austria;
| | - Herwig Ostermann
- Austrian National Public Health Institute/Gesundheit Österreich GmbH, Stubenring 6, 1010 Vienna, Austria; (H.O.); (C.C.)
| | - Caroline Czasch
- Austrian National Public Health Institute/Gesundheit Österreich GmbH, Stubenring 6, 1010 Vienna, Austria; (H.O.); (C.C.)
| | - Gottfried Endel
- Austrian Federation of Social Insurances, Kundmanngasse 21, 1030 Vienna, Austria;
| | - Wolfgang Bock
- Department of Mathematics, TU Kaiserslautern, Gottlieb-Daimler-Straße 48, 67663 Kaiserslautern, Germany;
| | - Nikolas Popper
- dwh GmbH, dwh Simulation Services, Neustiftgasse 57–59, A-1070 Vienna, Austria; (M.B.); (C.R.); (C.U.); (N.P.)
- Institute of Information Systems Engineering, TU Wien, Favoritenstraße 11, A-1050 Vienna, Austria
- Association for Decision Support for Health Policy and Planning, DEXHELPP, Neustiftgasse 57–59, A-1070 Vienna, Austria
| | - Uwe Siebert
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT—University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060 Hall in Tirol, Austria; (B.J.); (G.S.); (N.M.); (J.S.); (M.S.); (I.S.)
- Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 101 Merrimac St., Boston, MA 02114, USA
- Center for Health Decision Science, Departments of Epidemiology and Health Policy & Management, Harvard T.H. Chan School of Public Health, 718 Huntington Avenue, Boston, MA 02115, USA
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15
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Lee S, Zabinsky ZB, Wasserheit JN, Kofsky SM, Liu S. COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society. Med Decis Making 2021; 41:419-429. [PMID: 33733933 DOI: 10.1177/0272989x211003081] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021.
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Affiliation(s)
- Serin Lee
- Department of Industrial & Systems Engineering, University of Washington, Seattle, WA, USA
| | - Zelda B Zabinsky
- Department of Industrial & Systems Engineering, University of Washington, Seattle, WA, USA
| | - Judith N Wasserheit
- Department of Global Health, Department of Allergy and Infectious Diseases, University of Washington, Seattle, WA, USA
| | | | - Shan Liu
- Department of Industrial & Systems Engineering, University of Washington, Seattle, WA, USA
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16
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Carramiñana D, Campaña I, Bergesio L, Bernardos AM, Besada JA. Sensors and Communication Simulation for Unmanned Traffic Management. Sensors (Basel) 2021; 21:s21030927. [PMID: 33573192 PMCID: PMC7866552 DOI: 10.3390/s21030927] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 01/19/2021] [Accepted: 01/25/2021] [Indexed: 11/16/2022]
Abstract
Unmanned traffic management (UTM) systems will become a key enabler to the future drone market ecosystem, enabling the safe concurrent operation of both manned and unmanned aircrafts. Currently, these systems are usually tested by performing real scenarios that are costly, limited, hardly scalable, and poorly repeatable. As a solution, in this paper we propose an agent-based simulation platform, implemented through a micro service architecture, which may simulate UTM information sources, such as flight plans, telemetry messages, or tracks from a surveillance network. The final objective of this simulator is to use these information streams to perform a system-level evaluation of UTM systems both in the pre-flight and in-flight stages. The proposed platform, with a focus on simulation of communications and sensors, allows to model UTM actors' behaviors and their interactions. In addition, it also considers the manual definition of events to simulate unexpected behaviors/events (contingencies), such as communications failures or pilots' actions. In order to validate our architecture, we implemented a simulator that considers the following actors: drones, pilots, ground control stations, surveillance networks, and communications networks. This platform enables the simulation of the drone trajectory and control, the C2 (command and control) link, drone detection by surveillance sensors, and the communication of all agents by means of a mobile communications network. Our results show that it is possible to truthfully recreate complex scenarios using this simulator, mitigating the disadvantages of real testbeds.
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17
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Jisun Lee, Hyunsoo Lee, Mardelle McCuskey Shepley. Exploring the spatial arrangement of patient rooms for minimum nurse travel in hospital nursing units in Korea. Frontiers of Architectural Research 2020; 9. [ DOI: 10.1016/j.foar.2020.06.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2020] [Revised: 06/15/2020] [Accepted: 06/16/2020] [Indexed: 08/13/2023]
Abstract
With increasing demands on medical care services, one of the trends is the mixed patient room arrangement of single/double-bed and multi-bed rooms in a nursing unit on the same floor. This influences nurse-to-patient assignment and often causes an unbalanced workload and longer travel distances for nurses. The objective of this study was to investigate how floor configuration and room density influence nurse travel in the hospital's medical surgical units in Korea. This study presented a novel approach to measure nurse travel distances in eight existing nursing units. The agent-based simulation was conducted to model nurses' walking trails, and the distance of one nurse travel to assigned patient rooms was measured for each nurse. With revisions in the spatial arrangement of patient rooms, locating multi-bed rooms near the nurse station, symmetric room layout centering the nurse station, and planning both single/double-bed and multi-bed rooms on one side of corridors, nurse travel distance decreased more than 15%. This study contributed to the knowledge of agent-based simulation as an evaluation framework for spatial analysis. Apart from application to Korea, these results are particularly of interest in countries where private patient rooms are not commonly economically feasible.
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18
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Nishi A, Dewey G, Endo A, Neman S, Iwamoto SK, Ni MY, Tsugawa Y, Iosifidis G, Smith JD, Young SD. Network interventions for managing the COVID-19 pandemic and sustaining economy. Proc Natl Acad Sci U S A 2020; 117:30285-30294. [PMID: 33177237 PMCID: PMC7720236 DOI: 10.1073/pnas.2014297117] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Sustaining economic activities while curbing the number of new coronavirus disease 2019 (COVID-19) cases until effective vaccines or treatments become available is a major public health and policy challenge. In this paper, we use agent-based simulations of a network-based susceptible-exposed-infectious-recovered (SEIR) model to investigate two network intervention strategies for mitigating the spread of transmission while maintaining economic activities. In the simulations, we assume that people engage in group activities in multiple sectors (e.g., going to work, going to a local grocery store), where they interact with others in the same group and potentially become infected. In the first strategy, each group is divided into two subgroups (e.g., a group of customers can only go to the grocery store in the morning, while another separate group of customers can only go in the afternoon). In the second strategy, we balance the number of group members across different groups within the same sector (e.g., every grocery store has the same number of customers). The simulation results show that the dividing groups strategy substantially reduces transmission, and the joint implementation of the two strategies could effectively bring the spread of transmission under control (i.e., effective reproduction number ≈ 1.0).
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Affiliation(s)
- Akihiro Nishi
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095;
- California Center for Population Research, University of California, Los Angeles, CA 90095
- Bedari Kindness Institute, University of California, Los Angeles, CA 90095
| | - George Dewey
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095
| | - Akira Endo
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, WC1E 7HT London, United Kingdom
- The Alan Turing Institute, NW1 2DB London, United Kingdom
| | - Sophia Neman
- School of Medicine, Medical College of Wisconsin, Wauwatosa, WI 53213
| | - Sage K Iwamoto
- College of Letters & Science, University of California, Berkeley, CA 94720
| | - Michael Y Ni
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 999077, Hong Kong Special Administrative Region, China
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, 999077, Hong Kong Special Administrative Region, China
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, 999077, Hong Kong Special Administrative Region, China
| | - Yusuke Tsugawa
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, CA 90024
- Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles, CA 90095
| | - Georgios Iosifidis
- School of Computer Science and Statistics, Trinity College Dublin, Dublin 2, Ireland
| | - Justin D Smith
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT 84108
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611
- Department of Pediatrics, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611
| | - Sean D Young
- University of California Institute for Prediction Technology, Department of Informatics, University of California, Irvine, CA 92617
- Department of Emergency Medicine, University of California, Irvine, CA 92868
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19
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Asgary A, Najafabadi MM, Karsseboom R, Wu J. A Drive-through Simulation Tool for Mass Vaccination during COVID-19 Pandemic. Healthcare (Basel) 2020; 8:E469. [PMID: 33182336 PMCID: PMC7711491 DOI: 10.3390/healthcare8040469] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 10/29/2020] [Accepted: 11/02/2020] [Indexed: 12/24/2022] Open
Abstract
Several research and development teams around the world are working towards COVID-19 vaccines. As vaccines are expected to be developed and produced, preparedness and planning for mass vaccination and immunization will become an important aspect of the pandemic management. Mass vaccination has been used by public health agencies in the past and is being proposed as a viable option for COVID-19 immunization. To be able to rapidly and safely immunize a large number of people against SARS-CoV-2, different mass vaccination options are available. Drive-through facilities have been successfully used in the past for immunization against other diseases and for testing during COVID-19. In this paper we introduce a drive-through vaccination simulation tool that can be used to enhance the planning, design, operation, and feasibility and effectiveness assessment of such facilities. The simulation tool is a hybrid model that integrates discrete event and agent-based modeling techniques. The simulation outputs visually and numerically show the average processing and waiting times and the number of cars and people that can be served (throughput values) under different numbers of staff, service lanes, screening, registration, immunization, and recovery times.
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Affiliation(s)
- Ali Asgary
- Disaster & Emergency Management, School of Administrative Studies and Advanced Disaster, Emergency and Rapid Response Simulation (ADERSIM), York University, Toronto, ON M3J 1P3, Canada
| | - Mahdi M. Najafabadi
- Advanced Disaster, Emergency and Rapid Response Simulation (ADERSIM), York University, Toronto, ON M3J 1P3, Canada;
| | - Richard Karsseboom
- Duty Officer, Departmental Emergency Operations Centre, Community and Health Services, The Regional Municipality of York, Newmarket, ON L3Y 4W5, Canada;
| | - Jianhong Wu
- Department of Mathematics and Statistics and Laboratory for Industrial and Applied Mathematics, York University, Toronto, ON M3J 1P3, Canada;
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20
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Luo Z, Zhang Y, Li L, He B, Li C, Zhu H, Wang W, Ying S, Xi Y. A Hybrid Method for Predicting Traffic Congestion during Peak Hours in the Subway System of Shenzhen. Sensors (Basel) 2019; 20:E150. [PMID: 31881726 DOI: 10.3390/s20010150] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 12/22/2019] [Accepted: 12/23/2019] [Indexed: 11/26/2022]
Abstract
Traffic congestion, especially during peak hours, has become a challenge for transportation systems in many metropolitan areas, and such congestion causes delays and negative effects for passengers. Many studies have examined the prediction of congestion; however, these studies focus mainly on road traffic, and subway transit, which is the main form of transportation in densely populated cities, such as Tokyo, Paris, and Beijing and Shenzhen in China, has seldom been examined. This study takes Shenzhen as a case study for predicting congestion in a subway system during peak hours and proposes a hybrid method that combines a static traffic assignment model with an agent-based dynamic traffic simulation model to estimate recurrent congestion in this subway system. The homes and work places of the residents in this city are collected and taken to represent the traffic demand for the subway system of Shenzhen. An origin-destination (OD) matrix derived from the data is used as an input in this method of predicting traffic, and the traffic congestion is presented in simulations. To evaluate the predictions, data on the congestion condition of subway segments that are released daily by the Shenzhen metro operation microblog are used as a reference, and a comparative analysis indicates the appropriateness of the proposed method. This study could be taken as an example for similar studies that model subway traffic in other cities.
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Liang H, Lin KY, Zhang S. Understanding the Social Contagion Effect of Safety Violations within a Construction Crew: A Hybrid Approach Using System Dynamics and Agent-Based Modeling. Int J Environ Res Public Health 2018; 15:ijerph15122696. [PMID: 30501093 PMCID: PMC6313510 DOI: 10.3390/ijerph15122696] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2018] [Revised: 11/26/2018] [Accepted: 11/27/2018] [Indexed: 11/28/2022]
Abstract
Previous research has recognized the importance of eliminating safety violations in the context of a social group. However, the social contagion effect of safety violations within a construction crew has not been sufficiently understood. To address this deficiency, this research aims to develop a hybrid simulation approach to look into the cognitive, social, and organizational aspects that can determine the social contagion effect of safety violations within a construction crew. The hybrid approach integrates System Dynamics (SD) and Agent-based Modeling (ABM) to better represent the real world. Our findings show that different interventions should be employed for different work environments. Specifically, social interactions play a critical role at the modest hazard levels because workers in this situation may encounter more ambiguity or uncertainty. Interventions related to decreasing the contagion probability and the safety–productivity tradeoff should be given priority. For the low hazard situation, highly intensive management strategies are required before the occurrence of injuries or accidents. In contrast, for the high hazard situation, highly intensive proactive safety strategies should be supplemented by other interventions (e.g., a high safety goal) to further control safety violations. Therefore, this research provides a practical framework to examine how specific accident prevention measures, which interact with workers or environmental characteristics (i.e., the hazard level), can influence the social contagion effect of safety violations.
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Affiliation(s)
- Huakang Liang
- School of Management, Harbin Institute of Technology, Harbin 150001, China.
| | - Ken-Yu Lin
- Department of Construction Management, University of Washington, Seattle, WA 98195, USA.
| | - Shoujian Zhang
- School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China.
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García-Magariño I, Lacuesta R, Lloret J. ABS-SmartComAgri: An Agent-Based Simulator of Smart Communication Protocols in Wireless Sensor Networks for Debugging in Precision Agriculture. Sensors (Basel) 2018; 18:E998. [PMID: 29584703 DOI: 10.3390/s18040998] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Revised: 03/21/2018] [Accepted: 03/23/2018] [Indexed: 11/17/2022]
Abstract
Smart communication protocols are becoming a key mechanism for improving communication performance in networks such as wireless sensor networks. However, the literature lacks mechanisms for simulating smart communication protocols in precision agriculture for decreasing production costs. In this context, the current work presents an agent-based simulator of smart communication protocols for efficiently managing pesticides. The simulator considers the needs of electric power, crop health, percentage of alive bugs and pesticide consumption. The current approach is illustrated with three different communication protocols respectively called (a) broadcast, (b) neighbor and (c) low-cost neighbor. The low-cost neighbor protocol obtained a statistically-significant reduction in the need of electric power over the neighbor protocol, with a very large difference according to the common interpretations about the Cohen's d effect size. The presented simulator is called ABS-SmartComAgri and is freely distributed as open-source from a public research data repository. It ensures the reproducibility of experiments and allows other researchers to extend the current approach.
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García-Magariño I, Lacuesta R, Lloret J. ABS-FishCount: An Agent-Based Simulator of Underwater Sensors for Measuring the Amount of Fish. Sensors (Basel) 2017; 17:E2606. [PMID: 29137165 PMCID: PMC5713010 DOI: 10.3390/s17112606] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2017] [Revised: 11/08/2017] [Accepted: 11/09/2017] [Indexed: 11/16/2022]
Abstract
Underwater sensors provide one of the possibilities to explore oceans, seas, rivers, fish farms and dams, which all together cover most of our planet's area. Simulators can be helpful to test and discover some possible strategies before implementing these in real underwater sensors. This speeds up the development of research theories so that these can be implemented later. In this context, the current work presents an agent-based simulator for defining and testing strategies for measuring the amount of fish by means of underwater sensors. The current approach is illustrated with the definition and assessment of two strategies for measuring fish. One of these two corresponds to a simple control mechanism, while the other is an experimental strategy and includes an implicit coordination mechanism. The experimental strategy showed a statistically significant improvement over the control one in the reduction of errors with a large Cohen's d effect size of 2.55.
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Affiliation(s)
- Iván García-Magariño
- Department of Computer Science and Engineering of Systems, University of Zaragoza, 44003 Teruel, Spain.
- Instituto de Investigación Sanitaria Aragón, University of Zaragoza, 50009 Zaragoza, Spain.
| | - Raquel Lacuesta
- Department of Computer Science and Engineering of Systems, University of Zaragoza, 44003 Teruel, Spain.
- Instituto de Investigación Sanitaria Aragón, University of Zaragoza, 50009 Zaragoza, Spain.
| | - Jaime Lloret
- Integrated Management Coastal Research Institute, Universitat Politècnica de València, 46022 València, Spain.
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Stam S, Freedman SL, Banerjee S, Weirich KL, Dinner AR, Gardel ML. Filament rigidity and connectivity tune the deformation modes of active biopolymer networks. Proc Natl Acad Sci U S A 2017; 114:E10037-45. [PMID: 29114058 DOI: 10.1073/pnas.1708625114] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Molecular motors embedded within collections of actin and microtubule filaments underlie the dynamics of cytoskeletal assemblies. Understanding the physics of such motor-filament materials is critical to developing a physical model of the cytoskeleton and designing biomimetic active materials. Here, we demonstrate through experiments and simulations that the rigidity and connectivity of filaments in active biopolymer networks regulates the anisotropy and the length scale of the underlying deformations, yielding materials with variable contractility. We find that semiflexible filaments can be compressed and bent by motor stresses, yielding materials that undergo predominantly biaxial deformations. By contrast, rigid filament bundles slide without bending under motor stress, yielding materials that undergo predominantly uniaxial deformations. Networks dominated by biaxial deformations are robustly contractile over a wide range of connectivities, while networks dominated by uniaxial deformations can be tuned from extensile to contractile through cross-linking. These results identify physical parameters that control the forces generated within motor-filament arrays and provide insight into the self-organization and mechanics of cytoskeletal assemblies.
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Matyjaszkiewicz A, Fiore G, Annunziata F, Grierson CS, Savery NJ, Marucci L, di Bernardo M. BSim 2.0: An Advanced Agent-Based Cell Simulator. ACS Synth Biol 2017; 6:1969-1972. [PMID: 28585809 DOI: 10.1021/acssynbio.7b00121] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Agent-based models (ABMs) provide a number of advantages relative to traditional continuum modeling approaches, permitting incorporation of great detail and realism into simulations, allowing in silico tracking of single-cell behaviors and correlation of these with emergent effects at the macroscopic level. In this study we present BSim 2.0, a radically new version of BSim, a computational ABM framework for modeling dynamics of bacteria in typical experimental environments including microfluidic chemostats. This is facilitated through the implementation of new methods including cells with capsular geometry that are able to physically and chemically interact with one another, a realistic model of cellular growth, a delay differential equation solver, and realistic environmental geometries.
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Affiliation(s)
- Antoni Matyjaszkiewicz
- Department of Engineering
Mathematics, University of Bristol, Merchant Venturers’ Building,
Woodland Road, Bristol BS8 1UB, U.K
- BrisSynBio, Life Sciences Building, Tyndall
Avenue, Bristol BS8 1TQ, U.K
| | - Gianfranco Fiore
- Department of Engineering
Mathematics, University of Bristol, Merchant Venturers’ Building,
Woodland Road, Bristol BS8 1UB, U.K
- BrisSynBio, Life Sciences Building, Tyndall
Avenue, Bristol BS8 1TQ, U.K
| | - Fabio Annunziata
- BrisSynBio, Life Sciences Building, Tyndall
Avenue, Bristol BS8 1TQ, U.K
- School of Biochemistry, University of Bristol, Biomedical Sciences Building, University Walk, Bristol BS8 1TD, U.K
| | - Claire S. Grierson
- BrisSynBio, Life Sciences Building, Tyndall
Avenue, Bristol BS8 1TQ, U.K
- School of Biological Sciences, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol BS8 1TQ, U.K
| | - Nigel J. Savery
- BrisSynBio, Life Sciences Building, Tyndall
Avenue, Bristol BS8 1TQ, U.K
- School of Biochemistry, University of Bristol, Biomedical Sciences Building, University Walk, Bristol BS8 1TD, U.K
| | - Lucia Marucci
- Department of Engineering
Mathematics, University of Bristol, Merchant Venturers’ Building,
Woodland Road, Bristol BS8 1UB, U.K
- BrisSynBio, Life Sciences Building, Tyndall
Avenue, Bristol BS8 1TQ, U.K
| | - Mario di Bernardo
- Department of Engineering
Mathematics, University of Bristol, Merchant Venturers’ Building,
Woodland Road, Bristol BS8 1UB, U.K
- BrisSynBio, Life Sciences Building, Tyndall
Avenue, Bristol BS8 1TQ, U.K
- Department
of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy
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Read MN, Alden K, Rose LM, Timmis J. Automated multi-objective calibration of biological agent-based simulations. J R Soc Interface 2017; 13:rsif.2016.0543. [PMID: 27628175 DOI: 10.1098/rsif.2016.0543] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Accepted: 08/22/2016] [Indexed: 12/27/2022] Open
Abstract
Computational agent-based simulation (ABS) is increasingly used to complement laboratory techniques in advancing our understanding of biological systems. Calibration, the identification of parameter values that align simulation with biological behaviours, becomes challenging as increasingly complex biological domains are simulated. Complex domains cannot be characterized by single metrics alone, rendering simulation calibration a fundamentally multi-metric optimization problem that typical calibration techniques cannot handle. Yet calibration is an essential activity in simulation-based science; the baseline calibration forms a control for subsequent experimentation and hence is fundamental in the interpretation of results. Here, we develop and showcase a method, built around multi-objective optimization, for calibrating ABSs against complex target behaviours requiring several metrics (termed objectives) to characterize. Multi-objective calibration (MOC) delivers those sets of parameter values representing optimal trade-offs in simulation performance against each metric, in the form of a Pareto front. We use MOC to calibrate a well-understood immunological simulation against both established a priori and previously unestablished target behaviours. Furthermore, we show that simulation-borne conclusions are broadly, but not entirely, robust to adopting baseline parameter values from different extremes of the Pareto front, highlighting the importance of MOC's identification of numerous calibration solutions. We devise a method for detecting overfitting in a multi-objective context, not previously possible, used to save computational effort by terminating MOC when no improved solutions will be found. MOC can significantly impact biological simulation, adding rigour to and speeding up an otherwise time-consuming calibration process and highlighting inappropriate biological capture by simulations that cannot be well calibrated. As such, it produces more accurate simulations that generate more informative biological predictions.
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Affiliation(s)
- Mark N Read
- School of Life and Environmental Sciences, The University of Sydney, Camperdown, New South Wales, Australia Charles Perkins Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Kieran Alden
- Department of Electronics, University of York, York, UK
| | - Louis M Rose
- Department of Computer Science, University of York, York, UK
| | - Jon Timmis
- Department of Electronics, University of York, York, UK
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Cotter CR, Schüttler HB, Igoshin OA, Shimkets LJ. Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development. Proc Natl Acad Sci U S A 2017; 114:E4592-601. [PMID: 28533367 DOI: 10.1073/pnas.1620981114] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Collective cell movement is critical to the emergent properties of many multicellular systems, including microbial self-organization in biofilms, embryogenesis, wound healing, and cancer metastasis. However, even the best-studied systems lack a complete picture of how diverse physical and chemical cues act upon individual cells to ensure coordinated multicellular behavior. Known for its social developmental cycle, the bacterium Myxococcus xanthus uses coordinated movement to generate three-dimensional aggregates called fruiting bodies. Despite extensive progress in identifying genes controlling fruiting body development, cell behaviors and cell-cell communication mechanisms that mediate aggregation are largely unknown. We developed an approach to examine emergent behaviors that couples fluorescent cell tracking with data-driven models. A unique feature of this approach is the ability to identify cell behaviors affecting the observed aggregation dynamics without full knowledge of the underlying biological mechanisms. The fluorescent cell tracking revealed large deviations in the behavior of individual cells. Our modeling method indicated that decreased cell motility inside the aggregates, a biased walk toward aggregate centroids, and alignment among neighboring cells in a radial direction to the nearest aggregate are behaviors that enhance aggregation dynamics. Our modeling method also revealed that aggregation is generally robust to perturbations in these behaviors and identified possible compensatory mechanisms. The resulting approach of directly combining behavior quantification with data-driven simulations can be applied to more complex systems of collective cell movement without prior knowledge of the cellular machinery and behavioral cues.
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Abstract
Identifying the processes by which human cultures spread across different populations is one of the most topical objectives shared among different fields of study. Seminal works have analyzed a variety of data and attempted to determine whether empirically observed patterns are the result of demic and/or cultural diffusion. This special issue collects articles exploring several themes (from modes of cultural transmission to drivers of dispersal mechanisms) and contexts (from the Neolithic in Europe to the spread of computer programming languages), which offer new insights that will augment the theoretical and empirical basis for the study of demic and cultural diffusion. In this introduction we outline the state of art in the modeling of these processes, briefly discuss the pros and cons of two of the most commonly used frameworks (equation-based models and agent-based models), and summarize the significance of each article in this special issue.
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Affiliation(s)
- Joaquim Fort
- 1 Complex Systems Laboratory, Universitat de Girona, Department of Physics, Girona, Catalonia, Spain.,2 Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Catalonia, Spain
| | - Enrico R Crema
- 3 CaSEs - Complexity and Socio-Ecological Dynamics Research Group, Universitat Pompeu Fabra, Department of Humanities, Barcelona, Spain.,4 University College London Institute of Archaeology, London, United Kingdom
| | - Marco Madella
- 2 Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Catalonia, Spain.,3 CaSEs - Complexity and Socio-Ecological Dynamics Research Group, Universitat Pompeu Fabra, Department of Humanities, Barcelona, Spain.,5 Milà i Fontanals Institute, Spanish National Research Council (IMF-CSIC), Barcelona, Catalonia, Spain
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Abstract
We report a summary of our interdisciplinary research project "Evolutionary Perspective on Collective Decision Making" that was conducted through close collaboration between computational, organizational, and social scientists at Binghamton University. We redefined collective human decision making and creativity as evolution of ecologies of ideas, where populations of ideas evolve via continual applications of evolutionary operators such as reproduction, recombination, mutation, selection, and migration of ideas, each conducted by participating humans. Based on this evolutionary perspective, we generated hypotheses about collective human decision making, using agent-based computer simulations. The hypotheses were then tested through several experiments with real human subjects. Throughout this project, we utilized evolutionary computation (EC) in non-traditional ways-(1) as a theoretical framework for reinterpreting the dynamics of idea generation and selection, (2) as a computational simulation model of collective human decision-making processes, and (3) as a research tool for collecting high-resolution experimental data on actual collaborative design and decision making from human subjects. We believe our work demonstrates untapped potential of EC for interdisciplinary research involving human and social dynamics.
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Abstract
BACKGROUND Control of Clostridium difficile infection (CDI) is an increasingly difficult problem for health care institutions. There are commonly recommended strategies to combat CDI transmission, such as oral vancomycin for CDI treatment, increased hand hygiene with soap and water for health care workers, daily environmental disinfection of infected patient rooms, and contact isolation of diseased patients. However, the efficacy of these strategies, particularly for endemic CDI, has not been well studied. The objective of this research is to develop a valid, agent-based simulation model (ABM) to study C. difficile transmission and control in a midsized hospital. METHODS We develop an ABM of a midsized hospital with agents such as patients, health care workers, and visitors. We model the natural progression of CDI in a patient using a Markov chain and the transmission of CDI through agent and environmental interactions. We derive input parameters from aggregate patient data from the 2007-2010 Wisconsin Hospital Association and published medical literature. We define a calibration process, which we use to estimate transition probabilities of the Markov model by comparing simulation results to benchmark values found in published literature. RESULTS In a comparison of CDI control strategies implemented individually, routine bleach disinfection of CDI-positive patient rooms provides the largest reduction in nosocomial asymptomatic colonization (21.8%) and nosocomial CDIs (42.8%). Additionally, vancomycin treatment provides the largest reduction in relapse CDIs (41.9%), CDI-related mortalities (68.5%), and total patient length of stay (21.6%). CONCLUSION We develop a generalized ABM for CDI control that can be customized and further expanded to specific institutions and/or scenarios. Additionally, we estimate transition probabilities for a Markov model of natural CDI progression in a patient through calibration.
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Affiliation(s)
- James Codella
- Department of Industrial & Systems Engineering, University of Wisconsin-Madison, Madison, WI (JC, OA)
| | - Nasia Safdar
- Department of Medicine, University of Wisconsin Hospital and Clinics, Madison, WI and William S. Middleton Memorial Veterans Hospital, Madison, WI (NS)
| | - Rick Heffernan
- Bureau of Communicable Diseases and Emergency Response, Wisconsin Division of Public Health, Madison, WI (RH)
| | - Oguzhan Alagoz
- Department of Industrial & Systems Engineering, University of Wisconsin-Madison, Madison, WI (JC, OA)
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Abstract
In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analyzed. In particular, the generative power of ABM is found to have been underexploited, as the pressure for simple recipes has prevailed and shadowed the application of rich cognitive models. In the second part of the paper, the renewal of interest for Computational Social Science (CSS) is focused upon, and several of its variants, such as deductive, generative, and complex CSS, are identified and described. In the concluding remarks, an interdisciplinary variant, which takes after ABM, reconciling it with the quantitative one, is proposed as a fundamental requirement for a new program of the CSS.
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Affiliation(s)
| | - Mario Paolucci
- Laboratory of Agent Based Simulation, Institute of Cognitive Science and Technologies, CNRRome, Italy
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Figueredo GP, Joshi TV, Osborne JM, Byrne HM, Owen MR. On-lattice agent-based simulation of populations of cells within the open-source Chaste framework. Interface Focus 2014; 3:20120081. [PMID: 24427527 DOI: 10.1098/rsfs.2012.0081] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2012] [Accepted: 01/09/2013] [Indexed: 01/06/2023] Open
Abstract
Over the years, agent-based models have been developed that combine cell division and reinforced random walks of cells on a regular lattice, reaction-diffusion equations for nutrients and growth factors; and ordinary differential equations for the subcellular networks regulating the cell cycle. When linked to a vascular layer, this multiple scale model framework has been applied to tumour growth and therapy. Here, we report on the creation of an agent-based multi-scale environment amalgamating the characteristics of these models within a Virtual Physiological Human (VPH) Exemplar Project. This project enables reuse, integration, expansion and sharing of the model and relevant data. The agent-based and reaction-diffusion parts of the multi-scale model have been implemented and are available for download as part of the latest public release of Chaste (Cancer, Heart and Soft Tissue Environment; http://www.cs.ox.ac.uk/chaste/), part of the VPH Toolkit (http://toolkit.vph-noe.eu/). The environment functionalities are verified against the original models, in addition to extra validation of all aspects of the code. In this work, we present the details of the implementation of the agent-based environment, including the system description, the conceptual model, the development of the simulation model and the processes of verification and validation of the simulation results. We explore the potential use of the environment by presenting exemplar applications of the 'what if' scenarios that can easily be studied in the environment. These examples relate to tumour growth, cellular competition for resources and tumour responses to hypoxia (low oxygen levels). We conclude our work by summarizing the future steps for the expansion of the current system.
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Affiliation(s)
- Grazziela P Figueredo
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham NG7 2RD, UK
| | - Tanvi V Joshi
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham NG7 2RD, UK
| | - James M Osborne
- Oxford University Computing Laboratory, Department of Computer Science, University of Oxford, Wolfson Building, Oxford OX1 3QD, UK
| | - Helen M Byrne
- Oxford University Computing Laboratory, Department of Computer Science, University of Oxford, Wolfson Building, Oxford OX1 3QD, UK ; Oxford Centre for Collaborative Applied Mathematics, Oxford OX1 3LB, UK
| | - Markus R Owen
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham NG7 2RD, UK
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Abstract
The advent of farming around 12 millennia ago was a cultural as well as technological revolution, requiring a new system of property rights. Among mobile hunter-gatherers during the late Pleistocene, food was almost certainly widely shared as it was acquired. If a harvested crop or the meat of a domesticated animal were to have been distributed to other group members, a late Pleistocene would-be farmer would have had little incentive to engage in the required investments in clearing, cultivation, animal tending, and storage. However, the new property rights that farming required--secure individual claims to the products of one's labor--were infeasible because most of the mobile and dispersed resources of a forager economy could not cost-effectively be delimited and defended. The resulting chicken-and-egg puzzle might be resolved if farming had been much more productive than foraging, but initially it was not. Our model and simulations explain how, despite being an unlikely event, farming and a new system of farming-friendly property rights nonetheless jointly emerged when they did. This Holocene revolution was not sparked by a superior technology. It occurred because possession of the wealth of farmers--crops, dwellings, and animals--could be unambiguously demarcated and defended. This facilitated the spread of new property rights that were advantageous to the groups adopting them. Our results thus challenge unicausal models of historical dynamics driven by advances in technology, population pressure, or other exogenous changes. Our approach may be applied to other technological and institutional revolutions such as the 18th- and 19th-century industrial revolution and the information revolution today.
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Abstract
Humans are unique among primates in that women regularly outlive their reproductive period by decades. The grandmother hypothesis proposes that natural selection increased the length of the human post-menopausal period-and, thus, extended longevity-as a result of the inclusive fitness benefits of grandmothering. However, it has yet to be demonstrated that the inclusive fitness benefits associated with grandmothering are large enough to warrant this explanation. Here, we show that the inclusive fitness benefits are too small to affect the evolution of longevity under a wide range of conditions in simulated populations. This is due in large part to the relatively weak selection that applies to women near or beyond the end of their reproductive period. However, we find that grandmothers can facilitate the evolution of a shorter reproductive period when their help decreases the weaning age of their matrilineal grandchildren. Because selection favours a shorter reproductive period in the presence of shorter interbirth intervals, this finding holds true for any form of allocare that helps mothers resume cycling more quickly. We conclude that while grandmothering is unlikely to explain human-like longevity, allocare could have played an important role in shaping other unique aspects of human life history, such as a later age at first birth and a shorter female reproductive period.
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Affiliation(s)
- A Friederike Kachel
- Department of Human Evolution, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany.
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35
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Stevens JR, Volstorf J, Schooler LJ, Rieskamp J. Forgetting constrains the emergence of cooperative decision strategies. Front Psychol 2011; 1:235. [PMID: 21833289 PMCID: PMC3153839 DOI: 10.3389/fpsyg.2010.00235] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2010] [Accepted: 12/10/2010] [Indexed: 11/26/2022] Open
Abstract
Theoretical studies of cooperative behavior have focused on decision strategies that depend on a partner's last choices. The findings from this work assume that players accurately remember past actions. The kind of memory that these strategies employ, however, does not reflect what we know about memory. Here, we show that human memory may not meet the requirements needed to use these strategies. When asked to recall the previous behavior of simulated partners in a cooperative memory task, participants performed poorly, making errors in 10-24% of the trials. Participants made more errors when required to track more partners. We conducted agent-based simulations to evaluate how well cooperative strategies cope with error. These simulations suggest that, even with few errors, cooperation could not be maintained at the error rates demonstrated by our participants. Our results indicate that the strategies typically used in the study of cooperation likely do not reflect the underlying cognitive capacities used by humans and other animals in social interactions. By including unrealistic assumptions about cognition, theoretical models may have overestimated the robustness of the existing cooperative strategies. To remedy this, future models should incorporate what we know about cognition.
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Affiliation(s)
- Jeffrey R Stevens
- Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development Berlin, Germany
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36
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Abstract
Agent-based modeling is a technique currently used to simulate complex systems in computer science and social science. Here, we propose its application to the problem of molecular self-assembly. A system is allowed to evolve from a separated to an aggregated state following a combination of stochastic, deterministic, and adaptive rules. We consider the problem of packing rigid shapes on a lattice to verify that this algorithm produces more nearly optimal aggregates with less computational effort than comparable Monte Carlo simulations.
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Affiliation(s)
- Alessandro Troisi
- Dipartimento di Chimica "G. Ciamician," Università degli Studi di Bologna, Via F. Selmi 2, 40126 Bologna, Italy
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