arXiv subjects

Joel Wagner

Publications and source records attributed to Joel Wagner.

6 recordsLinked to original sources

arXiv2026

Household size can explain 40% of the variance in cumulative COVID-19 incidence across Europe

Household size impacts the spread of respiratory infectious diseases: Larger households tend to boost transmission by acquiring external infections more frequently and subsequently transmitting them back into the community. Furthermore, mandatory interventions primarily modulate contagion between households rather than within them. We developed an approach to quantify the role of household size in epidemics by separating within-household from out-household transmission, and found that household size explains 41% of the variability in cumulative COVID-19 incidence across 34 European countries (95% confidence interval: [15%, 46%]). The contribution of households to the overall dynamics can be quantified by a boost factor that increases with the effective household size, implying that countries with larger households require more stringent interventions to achieve the same levels of containment. This suggests that households constitute a structural (dis-)advantage that must be considered when designing and evaluating mitigation strategies.

q-bio.PE↗

arXiv2025

On the Statistical Physics of Wealth Distribution

Asset exchange models (AEMs) provide a physics-inspired framework for studying wealth formation. These models capture wealth distribution dynamics via pairwise money exchanges, yielding steady-state distributions from exponential to heavy-tailed power laws. However, empirical validation remains limited due to scarce real-world transaction data. Here, we bridge this gap by analyzing spectral properties of Markov transition matrices from both AEMs and Ethereum blockchain data, enabling quantitative comparison of model and empirical exchange dynamics. We assess thermodynamic equilibrium in exchange processes - specifically, detailed balance - and derive steady-state wealth distributions from transition matrices. We find that equilibrium systems' spectra contain only real eigenvalues and link Ethereum price changes to spectral shifts. We also investigate external factors (e.g., taxes), showing that advantages for richer individuals make wealth evolution path-dependent on initial distributions. Our work establishes a quantitative framework for validating AEMs with real data, advancing economic modeling and understanding of wealth formation.

physics.soc-ph↗

arXiv2025

Societal self-regulation induces complex infection dynamics and chaos

Classically, endemic infectious diseases are expected to display relatively stable, predictable infection dynamics. Accordingly, basic disease models such as the susceptible-infected-recovered-susceptible model display stable endemic states or recurrent seasonal waves. However, if the human population reacts to high infection numbers by mitigating the spread of the disease, then this delayed behavioral feedback loop can generate infection waves itself, driven by periodic mitigation and subsequent relaxation. We show that such behavioral reactions, together with a seasonal effect of comparable impact, can cause complex and unpredictable infection dynamics, including Arnold tongues, coexisting attractors, and chaos. Importantly, these arise in epidemiologically relevant parameter regions where the costs associated to infections and mitigation are jointly minimized. By comparing our model to data, we find signs that COVID-19 was mitigated in a way that favored complex infection dynamics. Our results challenge the intuition that endemic disease dynamics necessarily implies predictability and seasonal waves and show the emergence of complex infection dynamics when humans optimize their reaction to increasing infection numbers.

physics.soc-ph↗

arXiv2023

Model-based assessment of sampling protocols for infectious disease genomic surveillance

Genomic surveillance of infectious diseases allows monitoring circulating and emerging variants and quantifying their epidemic potential. However, due to the high costs associated with genomic sequencing, only a limited number of samples can be analysed. Thus, it is critical to understand how sampling impacts the information generated. Here, we combine a compartmental model for the spread of COVID-19 (distinguishing several SARS-CoV-2 variants) with different sampling strategies to assess their impact on genomic surveillance. In particular, we compare adaptive sampling, i.e., dynamically reallocating resources between screening at points of entry and inside communities, and constant sampling, i.e., assigning fixed resources to the two locations. We show that adaptive sampling uncovers new variants up to five weeks earlier than constant sampling, significantly reducing detection delays and estimation errors. This advantage is most prominent at low sequencing rates. Although increasing the sequencing rate has a similar effect, the marginal benefits of doing so may not always justify the associated costs. Consequently, it is convenient for countries with comparatively few resources to operate at lower sequencing rates, thereby profiting the most from adaptive sampling. Finally, our methodology can be readily adapted to study undersampling in other dynamical systems.

q-bio.PE↗

arXiv2022

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↗

arXiv2021

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↗