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Kai Nagel

Publications and source records attributed to Kai Nagel.

At least 19 recordsLinked to original sources

Mechanics of Pandemics

COVID-19 and previous pandemics have shown how diseases can disrupt, threaten, and transform daily life. Since pathogens and societies are continuously evolving, every pandemic is different. However, certain fundamental principles of disease transmission appear to hold true across different outbreaks. These ``mechanisms'' are grounded in natural laws or the very structure of our biology and societies. This paper compiles ten fundamental mechanisms, curated by a multidisciplinary team with backgrounds spanning public health, medicine, epidemiology, political science, mathematics, physics, and psychology. These mechanisms, although perhaps underappreciated, substantially shape how pandemics unfold and are controlled. The better we succeed in understanding these mechanisms and establishing this knowledge in our societies, the better we will be able to prepare for future pandemics and respond appropriately when they occur.

q-bio.PE

Inferring Mobility Reductions from COVID-19 Disease Spread along the Urban-Rural Gradient

The COVID-19 pandemic reshaped human mobility through policy interventions and voluntary behavioral changes. Mobility adaptions helped mitigate pandemic spread, however our knowledge which environmental, social, and demographic factors helped mobility reduction and pandemic mitigation is patchy. We introduce a Bayesian hierarchical model to quantify heterogeneity in mobility responses across time and space in Germany's 400 districts using anonymized mobile phone data. Decomposing mobility into a disease-responsive component and disease-independent factors (temperature, school vacations, public holidays) allows us to quantify the impact of each factor. We find significant differences in reaction to disease spread along the urban-rural gradient, with large cities reducing mobility most strongly. Employment sectors further help explain variance in reaction strength during the first wave, while political variables gain significance during the second wave. However, reduced mobility only partially translates to lower peak incidence, indicating the influence of other hidden factors. Our results identify key drivers of mobility reductions and demonstrate that mobility behavior can serve as an operational proxy for population response.

stat.AP

Interplay between risk perception, behaviour, and COVID-19 spread

Pharmaceutical and non-pharmaceutical interventions (NPIs) have been crucial for controlling COVID-19. They are complemented by voluntary health-protective behaviour, building a complex interplay between risk perception, behaviour, and disease spread. We studied how voluntary health-protective behaviour and vaccination willingness impact the long-term dynamics. We analysed how different levels of mandatory NPIs determine how individuals use their leeway for voluntary actions. If mandatory NPIs are too weak, COVID-19 incidence will surge, implying high morbidity and mortality before individuals react; if they are too strong, one expects a rebound wave once restrictions are lifted, challenging the transition to endemicity. Conversely, moderate mandatory NPIs give individuals time and room to adapt their level of caution, mitigating disease spread effectively. When complemented with high vaccination rates, this also offers a robust way to limit the impacts of the Omicron variant of concern. Altogether, our work highlights the importance of appropriate mandatory NPIs to maximise the impact of individual voluntary actions in pandemic control.

q-bio.PE

Nachhaltige Strategien gegen die COVID-19-Pandemie in Deutschland im Winter 2021/2022

In this position paper, a large group of interdisciplinary experts outlines response strategies against the spread of SARS-CoV-2 in the winter of 2021/2022 in Germany. We review the current state of the COVID-19 pandemic, from incidence and vaccination efficacy to hospital capacity. Building on this situation assessment, we illustrate various possible scenarios for the winter, and detail the mechanisms and effectiveness of the non-pharmaceutical interventions, vaccination, and booster. With this assessment, we want to provide orientation for decision makers about the progress and mitigation of COVID-19.

q-bio.OT

The winter dilemma

With winter coming in the northern hemisphere, disadvantageous seasonality of SARS-CoV-2 requires high immunity levels in the population or increasing non-pharmaceutical interventions (NPIs), compared to summer. Otherwise intensive care units (ICUs) might fill up. However, compliance with mandatory NPIs, vaccine uptake, and individual protective measures depend on individuals' opinions and behavior. Opinions, in turn, depend on information, e.g., about vaccine safety or current infection levels. Therefore, understanding how information about the pandemic affects its spread through the modulation of voluntary protection-seeking behaviors is crucial for better preparedness this winter and for future crises.

q-bio.PE

A realistic agent-based simulation model for COVID-19 based on a traffic simulation and mobile phone data

Epidemiological simulations as a method are used to better understand and predict the spreading of infectious diseases, for example of COVID-19. This paper presents an approach that combines person-centric data-driven human mobility modelling with a mechanistic infection model and a person-centric disease progression model. The model includes the consequences of disease import, of changed activity participation rates over time (coming from mobility data), of masks, of indoors vs.\ outdoors leisure activities, and of contact tracing. Results show that the model is able to credibly track the infection dynamics in Berlin (Germany). The model can be used to understand the contributions of different activity types to the infection dynamics over time. The model clearly shows the effects of contact reductions, school closures/vacations, or the effect of moving leisure activities from outdoors to indoors in fall. Sensitivity tests show that all ingredients of the model are necessary to track the current infection dynamics. One interesting result from the mobility data is that behavioral changes of the population mostly happened \textit{before} the government-initiated so-called contact ban came into effect. Similarly, people started drifting back to their normal activity patterns \emph{before} the government officially reduced the contact ban. Our work shows that is is possible to build detailed epidemiological simulations from microscopic mobility models relatively quickly. They can be used to investigate mechanical aspects of the dynamics, such as the transmission from political decisions via human behavior to infections, consequences of different lockdown measures, consequences of wearing masks in certain situations, or contact tracing.

physics.soc-ph

The Physics of Traffic and Regional Development

This contribution summarizes and explains various principles from physics which are used for the simulation of traffic flows in large street networks, the modeling of destination, transport mode, and route choice, or the simulation of urban growth and regional development. The methods stem from many-particle physics, from kinetic gas theory, or fluiddynamics. They involve energy and entropy considerations, transfer the law of gravity, apply cellular automata and require methods from evolutionary game theory. In this way, one can determine interaction forces among driver-vehicle units, reproduce breakdowns of traffic including features of synchronized congested flow, or understand changing usage patterns of alternative roads. One can also describe daily activity patterns based on decision models, simulate migration streams, and model urban growth as a particular kind of aggregation process.

physics.soc-ph

Probabilistic Traffic Flow Breakdown In Stochastic Car Following Models

There is discussion if traffic displays multiple phases (e.g. laminar, jammed, synchronized) or not. This paper presents evidence that a stochastic car following model, by changing one of its parameters, can be moved from showing two phases (laminar and jammed) to showing only one phase. Models with two phases show three states: two being homogeneous states corresponding to each phase, and a third state which consists of a mix between the two phases (phase coexistence). Although the gas-liquid analogy to traffic models has been widely discussed, no traffic-related model ever displayed a completely understood stochastic version of that transition. Having a stochastic model is however important to understand the potentially probabilistic nature of the transition. Most importantly, if indeed 2-phase models describe certain aspects correctly, then this leads to predictions for breakdown probabilities. Alternatively, if 1-phase models describe these aspects better, then there is no breakdown.Interestingly, such 1-phase models can still allow for jam formation on small scales, which may give the impression of having a 2-phase dynamics.

cond-mat.stat-mech

Breakdown and recovery in traffic flow models

Most car-following models show a transition from laminar to ``congested'' flow and vice versa. Deterministic models often have a density range where a disturbance needs a sufficiently large critical amplitude to move the flow from the laminar into the congested phase. In stochastic models, it may be assumed that the size of this amplitude gets translated into a waiting time, i.e.\ until fluctuations sufficiently add up to trigger the transition. A recently introduced model of traffic flow however does not show this behavior: in the density regime where the jam solution co-exists with the high-flow state, the intrinsic stochasticity of the model is not sufficient to cause a transition into the jammed regime, at least not within relevant time scales. In addition, models can be differentiated by the stability of the outflow interface. We demonstrate that this additional criterion is not related to the stability of the flow. The combination of these criteria makes it possible to characterize commonalities and differences between many existing models for traffic in a new way.

cond-mat.stat-mech

Parallel implementation of the TRANSIMS micro-simulation

This paper describes the parallel implementation of the TRANSIMS traffic micro-simulation. The parallelization method is domain decomposition, which means that each CPU of the parallel computer is responsible for a different geographical area of the simulated region. We describe how information between domains is exchanged, and how the transportation network graph is partitioned. An adaptive scheme is used to optimize load balancing. We then demonstrate how computing speeds of our parallel micro-simulations can be systematically predicted once the scenario and the computer architecture are known. This makes it possible, for example, to decide if a certain study is feasible with a certain computing budget, and how to invest that budget. The main ingredients of the prediction are knowledge about the parallel implementation of the micro-simulation, knowledge about the characteristics of the partitioning of the transportation network graph, and knowledge about the interaction of these quantities with the computer system. In particular, we investigate the differences between switched and non-switched topologies, and the effects of 10 Mbit, 100 Mbit, and Gbit Ethernet. keywords: Traffic simulation, parallel computing, transportation planning, TRANSIMS

cs.CE

Spatial competition and price formation

We look at price formation in a retail setting, that is, companies set prices, and consumers either accept prices or go someplace else. In contrast to most other models in this context, we use a two-dimensional spatial structure for information transmission, that is, consumers can only learn from nearest neighbors. Many aspects of this can be understood in terms of generalized evolutionary dynamics. In consequence, we first look at spatial competition and cluster formation without price. This leads to establishement size distributions, which we compare to reality. After some theoretical considerations, which at least heuristically explain our simulation results, we finally return to price formation, where we demonstrate that our simple model with nearly no organized planning or rationality on the part of any of the agents indeed leads to an economically plausible price.

nlin.AO

The dynamics of iterated transportation simulations

Iterating between a router and a traffic micro-simulation is an increasibly accepted method for doing traffic assignment. This paper, after pointing out that the analytical theory of simulation-based assignment to-date is insufficient for some practical cases, presents results of simulation studies from a real world study. Specifically, we look into the issues of uniqueness, variability, and robustness and validation. Regarding uniqueness, despite some cautionary notes from a theoretical point of view, we find no indication of ``meta-stable'' states for the iterations. Variability however is considerable. By variability we mean the variation of the simulation of a given plan set by just changing the random seed. We show then results from three different micro-simulations under the same iteration scenario in order to test for the robustness of the results under different implementations. We find the results encouraging, also when comparing to reality and with a traditional assignment result. Keywords: dynamic traffic assignment (DTA); traffic micro-simulation; TRANSIMS; large-scale simulations; urban planning

nlin.AO

A Simplified Cellular Automaton Model for City Traffic

We systematically investigate the effect of blockage sites in a cellular automaton model for traffic flow. Different scheduling schemes for the blockage sites are considered. None of them returns a linear relationship between the fraction of ``green'' time and the throughput. We use this information for a fast implementation of traffic in Dallas.

cond-mat.stat-mech

Two-lane traffic rules for cellular automata: A systematic approach

Microscopic modeling of multi-lane traffic is usually done by applying heuristic lane changing rules, and often with unsatisfying results. Recently, a cellular automaton model for two-lane traffic was able to overcome some of these problems and to produce a correct density inversion at densities somewhat below the maximum flow density. In this paper, we summarize different approaches to lane changing and their results, and propose a general scheme, according to which realistic lane changing rules can be developed. We test this scheme by applying it to several different lane changing rules, which, in spite of their differences, generate similar and realistic results. We thus conclude that, for producing realistic results, the logical structure of the lane changing rules, as proposed here, is at least as important as the microscopic details of the rules.

cond-mat.stat-mech

Experiences with iterated traffic microsimulations in Dallas

This paper reports experiences with iterated traffic microsimulations in the context of a Dallas study. ``Iterated microsimulations'' here means that the information generated by a microsimulation is fed back into the route planner so that the simulated individuals can adjust their routes to circumvent congestion. This paper gives an overview over what has been done in the Dallas context to better understand the relaxation process, and how to judge the robustness of the results.

adap-org

TRANSIMS traffic flow characteristics

Knowledge of fundamental traffic flow characteristics of traffic simulation models is an essential requirement when using these models for the planning, design, and operation of transportation systems. In this paper we discuss the following: a description of how features relevant to traffic flow are currently under implementation in the TRANSIMS microsimulation, a proposition for standardized traffic flow tests for traffic simulation models, and the results of these tests for two different versions of the TRANSIMS microsimulation.

adap-org

Using microsimulation feedback for trip adaptation for realistic traffic in Dallas

This paper presents a day-to-day re-routing relaxation approach for traffic simulations. Starting from an initial planset for the routes, the route-based microsimulation is executed. The result of the microsimulation is fed into a re-router, which re-routes a certain percentage of all trips. This approach makes the traffic patterns in the microsimulation much more reasonable. Further, it is shown that the method described in this paper can lead to strong oscillations in the solutions.

adap-org

Experiences with a simplified microsimulation for the Dallas/Fort Worth area

We describe a simple framework for micro simulation of city traffic. A medium sized excerpt of Dallas was used to examine different levels of simulation fidelity of a cellular automaton method for the traffic flow simulation and a simple intersection model. We point out problems arising with the granular structure of the underlying rules of motion.

adap-org