Targeted COVID-19 Vaccination (TAV-COVID) Considering Limited Vaccination Capacities-An Agent-Based Modeling Evaluation

(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

Calibration of an Agent-based Influenza Model

Zusammenfassung in englischer SpracheAbweichender Titel nach Übersetzung der Verfasserin/des VerfassersAgentenbasierte Modellierung wird in der Modellbildung und Simulation immer öfter verwendet. Demzufolge ist es wichtig, die üblichen Methoden zur Qualitätsüberprüfung eines Modells auf ihre Anwendbarkeit auf agentenbasierte Modelle zu überprüfen. Diese Arbeit beschäftigt sich mit der Kalibrierung eines agentenbasierten Modells. Dabei wird zuerst auf allgemeine Probleme eingegangen, die bei dieser Aufgabestellung auftreten. Es werden zwei Kalibrierungsalgorithmen vorgestellt, die zur Kalibrierung herangezogen werden können: das Simulated Annealing und ein evolutionärer Algorithmus. Bei beiden werden verschiedene Varianten und Konfigurationen besprochen und, soweit dies bekannt ist, auf das Konvergenzverhalten eingegangen. Die Leistung der beiden Algorithmen wird an kleinen Beispielmodellen getestet. Es handelt sich dabei um ein SIR- und um ein SIRS-Modell, die den Verlauf einer infektiösen Krankheit simulieren. Bei diesen Tests wird versucht eine geeignete Konfiguration der Kalibrierungsalgorithmen zu bestimmen. Es zeigt sich, dass die beiden Kalibrierungsalgorithmen nur bei einem der beiden Beispielmodelle vergleichbar gute Resultate liefern. Bei dem zweiten Modell werden nur beim evolutionären Algorithmus gute Ergebnisse erzielt. Ein Problem, das bei allen Kalibrierungsdurchläufen auftaucht, stellt die lange Rechenzeit dar. Deswegen wird eine mögliche Methode zur Reduzierung der Laufzeit vorgestellt. Sie besteht darin, die Anzahl der in der Simulation benutzten Agenten während der Kalibrierung zu verändern. Anfangs wird nur eine geringe Agentenanzahl benutzt um in kurzer Zeit mehrere Simulationen durchführen zu können. Die Simulationen mit einer geringen Agentenanzahl weisen jedoch eine größere Varianz auf, sodass die Resultate mit Unsicherheiten behaftet sind. Während der Kalibrierung wird die Agentenzahl progressiv auf ein gewünschtes Maß erhöht, um die Unsicherheit der Resultate zu verringern. Verschiedene Konfigurationen dieser Vorgehensweise werden ebenfalls an den Beispielmodellen getestet und ausgewertet. Auch bei dieser Methode ist der evolutionäre Algorithmus erfolgreicher und es ist möglich die benötigte Laufzeit um etwa die Hälfte zu reduzieren. Die erhaltenen Erkenntnisse werden schlussendlich benutzt, um ein komplexeres agentenbasiertes Modell zu kalibrieren. Hierbei handelt es sich um ein Influenzamodell, das die Ausbreitung der Grippe innerhalb der österreichischen Bevölkerung simuliert. Es wurden mehrere erfolgreiche Kalibrierungen mittels evolutionärem Algorithmus durchgeführt. Hierbei konnte zudem festgestellt werden, dass die berechneten Parameterwerte sehr unterschiedlich sind und demnach mehrere gleichwertige, lokale Minima existieren.Agent-based modelling has experienced increasing application in several fields since it offers many benefits over other modelling methods. Therefore it is important to verifiy whether quality assessment methods can be applied on agent-based models. This master's thesis discusses the problem of calibrating such models. Two algorithms which can be used to perform this task are presented: simulated annealing and an evolutionary algorithm. For each algorithm, different versions and configurations, as well as the convergence behaviour, are discussed. The performance of these algorithms is tested on different example models: an SIR and an SIRS model. These models are used to describe the spreading of an infectious disease. It can be observed that simulated annealing produces good results only on one of the example models, while the evolutionary algorithm performs successfull calibrations for all of them. Unfortunately, all calibrations require a lot of computing time. A possible solution to this problem is presented. It consists of varying the number of agents used in the simulation during the calibration. At the beginning, only a small amout of agents is used in order to perform many simulation runs in a short period of time. However, if a low agent count is used, the simulations exhibit a greater variability. During the course of the calibration, the agent count is progressively increased until it reaches the targeted amount. This way, the variability of the results occuring when a low agent count is used, is being reduced. Different configurations of this method are beeing tested on the example model. It shows that the evolutionary algorithm provides a better performance than simulated annealing and it is possible to cut the computing time in half. Ultimately, the findings are used to calibrate a more complex agent-based model simulating an influenza epidemic in the Austrian population. Several successful calibrations have been performed using the evolutionary algorithm. The calculated parameter sets turned out to be very diverse. Therefore it is plausible that several comparable local minima exist.6

Reproduction of patterns in melanocytic proliferations by agent-based simulation and geometric modeling.

Spatio-temporal patterns of melanocytic proliferations observed in vivo are important for diagnosis but the mechanisms that produce them are poorly understood. Here we present an agent-based model for simulating the emergence of the main biologic patterns found in melanocytic proliferations. Our model portrays the extracellular matrix of the dermo-epidermal junction as a two-dimensional manifold and we simulate cellular migration in terms of geometric translations driven by adhesive, repulsive and random forces. Abstracted cellular functions and melanocyte-matrix interactions are modeled as stochastic events. For identification and validation we use visual renderings of simulated cell populations in a horizontal perspective that reproduce growth patterns observed in vivo by sequential dermatoscopy and corresponding vertical views that reproduce the arrangement of melanocytes observed in histopathologic sections. Our results show that a balanced interplay of proliferation and migration produces the typical reticular pattern of nevi, whereas the globular pattern involves additional cellular mechanisms. We further demonstrate that slight variations in the three basic cellular properties proliferation, migration, and adhesion are sufficient to produce a large variety of morphological appearances of nevi. We anticipate our model to be a starting point for the reproduction of more complex scenarios that will help to establish functional connections between abstracted microscopic behavior and macroscopic patterns in all types of melanocytic proliferations including melanoma

Methods for integrated simulation: 10 concepts to integrate

This note summarises the current status of the work of EUROSIMs ans ASIMs Technical Committees "Data Driven System Simulation" - with main emphasis on Big Data integration in simulation. This overview suggests ten developed concepts and methods which should be considered, implemented and documented in modern simulation studies with Big Data

Targeted COVID-19 Vaccination (TAV-COVID) Considering Limited Vaccination Capacities—An Agent-Based Modeling Evaluation

(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