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See detailStages of COVID-19 pandemic and paths to herd immunity by vaccination: dynamical model comparing Austria, Luxembourg and Sweden
Kemp, Francoise UL; Proverbio, Daniele UL; Aalto, Atte UL et al

E-print/Working paper (2021)

Background. Worldwide more than 72 million people have been infected and 1.6 million died with SARS-CoV-2 by 15th December 2020. Non-pharmaceutical interventions which decrease social interaction have ... [more ▼]

Background. Worldwide more than 72 million people have been infected and 1.6 million died with SARS-CoV-2 by 15th December 2020. Non-pharmaceutical interventions which decrease social interaction have been implemented to reduce the spread of SARS-CoV-2 and to mitigate stress on healthcare systems and prevent deaths. The pandemic has been tackled with disparate strategies by distinct countries resulting in different epidemic dynamics. However, with vaccines now becoming available, the current urgent open question is how the interplay between vaccination strategies and social interaction will shape the pandemic in the next months. Methods. To address this question, we developed an extended Susceptible-Exposed-Infectious-Removed (SEIR) model including social interaction, undetected cases and the progression of patients trough hospitals, intensive care units (ICUs) and death. We calibrated our model to data of Luxembourg, Austria and Sweden, until 15th December 2020. We incorporated the effect of vaccination to investigate under which conditions herd immunity would be achievable in 2021. Results. The model reveals that Sweden has the highest fraction of undetected cases, Luxembourg displays the highest fraction of infected population, and all three countries are far from herd immunity as of December 2020. The model quantifies the level of social interactions, and allows to assess the level which would keep Reff(t) below 1. In December 2020, this level is around 1/3 of what it was before the pandemic for all the three countries. The model allows to estimate the vaccination rate needed for herd immunity and shows that 2700 vaccinations/day are needed in Luxembourg to reach it by mid of April and 45,000 for Austria and Sweden. The model estimates that vaccinating the whole country’s population within 1 year could lead to herd immunity by July in Luxembourg and by August in Austria and Sweden. Conclusion. The model allows to shed light on the dynamics of the epidemics in different waves and countries. Our results emphasize that vaccination will help considerably but not immediately and therefore social measures will remain important for several months before they can be fully alleviated. [less ▲]

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See detailFastField: An Open-Source Toolbox for Efficient Approximation of Deep Brain Stimulation Electric Fields
Baniasadi, Mehri UL; Proverbio, Daniele UL; Goncalves, Jorge UL et al

in NeuroImage (2020)

Deep brain stimulation (DBS) is a surgical therapy to alleviate symptoms of certain brain disorders by electrically modulating neural tissues. Computational models predicting electric fields and volumes ... [more ▼]

Deep brain stimulation (DBS) is a surgical therapy to alleviate symptoms of certain brain disorders by electrically modulating neural tissues. Computational models predicting electric fields and volumes of tissue activated are key for efficient parameter tuning and network analysis. Currently, we lack efficient and flexible software implementations supporting complex electrode geometries and stimulation settings. Available tools are either too slow (e.g. finite element method–FEM), or too simple, with limited applicability to basic use-cases. This paper introduces FastField, an efficient open-source toolbox for DBS electric field and VTA approximations. It computes scalable e-field approximations based on the principle of superposition, and VTA activation models from pulse width and axon diameter. In benchmarks and case studies, FastField is solved in about 0.2s, ~ 1000 times faster than using FEM. Moreover, it is almost as accurate as using FEM: average Dice overlap of 92%, which is around typical noise levels found in clinical data. Hence, FastField has the potential to foster efficient optimization studies and to support clinical applications [less ▲]

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See detailAssessing suppression strategies against epidemicoutbreaks like COVID-19: the SPQEIR model
Proverbio, Daniele UL; Kemp, Francoise UL; Magni, Stefano UL et al

E-print/Working paper (2020)

The current COVID-19 outbreak represents a most serious challenge for societies worldwide. It isendangering the health of millions of people, and resulting in severe socioeconomic challenges dueto lock ... [more ▼]

The current COVID-19 outbreak represents a most serious challenge for societies worldwide. It isendangering the health of millions of people, and resulting in severe socioeconomic challenges dueto lock-down measures. Governments worldwide aim to devise exit strategies to revive the economywhile keeping the pandemic under control. The problem is that the effects of distinct measures arenot well quantified. This paper compares several suppression approaches and potential exit strategiesusing a new extended epidemic SEIR model. It concludes that while rapid and strong lock-down isan effective pandemic suppression measure, a combination of other strategies such as social distanc-ing, active protection and removal can achieve similar suppression synergistically. This quantitativeunderstanding will support the establishment of mid- and long-term interventions. Finally, the paperprovides an online tool that allows researchers and decision makers to interactively simulate diversescenarios with our model. [less ▲]

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See detailCOVID-19 Crisis Management in Luxembourg: Insights from an Epidemionomic Approach
burzynski, Michal; Machado, Joel; Aalto, Atte UL et al

E-print/Working paper (2020)

We develop an epidemionomic model that jointly analyzes the health and economic responses to the COVID-19 crisis and to the related containment and public health policy measures implemented in Luxembourg ... [more ▼]

We develop an epidemionomic model that jointly analyzes the health and economic responses to the COVID-19 crisis and to the related containment and public health policy measures implemented in Luxembourg and in the Greater Region. The model has a weekly structure and covers the whole year 2020. With a limited number of parameters, the model is calibrated to depict the pre-crisis evolution of the Luxembourg economy, and to match post-lockdown leading economic indicators and industry-specific infection curves. The nowcasting part of our analysis reveals that each week of lockdown reduces national output by about 28% (and annual GDP by 0.54%). A first peak of the infection curve was observed at the very beginning of April. If the lockdown measures had been permanent, annual GDP would have decreased by 22% in 2020, the number of COVID-19 cases would have reached zero around mid-June, and the proportion of recovered people would have reached 1.4% of the population. In an economy heavily relying on skill-intensive services, we show that the role of teleworking has been instrumental to limiting the weekly economic output loss (almost by one half) and the propagation of the virus. In the forecasting part of the analysis, we quantify the epidemiological and economic responses to gradual deconfinement measures under various public health scenarios. If the post-lockdown transmission rates could be kept constant throughout the deconfinement period, restarting all sectors would have huge effects on the economy (limiting the annual GDP loss to about 7%) and no effect on the aggregate infection curve. While it is a good time for lifting containment measures, there is also a risk that increasing the density of employees at the workplace and resuming social activities would induce a rebound in the infection curve. Preventing such a relapse is possible with PCR testing of both national and cross-border workers, and with accompanying measures such as (i) maintaining teleworking practices, (ii) reopening hotels, restaurants and cafes at half of their full capacity or with equivalent physical distancing measures and last but not least, (iii) sustaining distancing measures in social activities. Overall, in our worst-case scenario, combining bi-monthly testing with contact tracing and quarantining measures appear to be a suficient (perhaps not necessary) policy option in the aftermath of the deconfinement plan. [less ▲]

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See detailA Multi-agent approach for in silico simulations of micro-biological systems
Proverbio, Daniele UL; Gallo, Luca; Passalacqua, Barbara et al

E-print/Working paper (2019)

A Multi-agent approach forin silicosimulations ofmicro-biological systemsProverbio D., Gallo L., Passalacqua B., Pellegrino J., Maggiora M.AbstractUsing a Multi-agent systems paradigm, the present project ... [more ▼]

A Multi-agent approach forin silicosimulations ofmicro-biological systemsProverbio D., Gallo L., Passalacqua B., Pellegrino J., Maggiora M.AbstractUsing a Multi-agent systems paradigm, the present project develops, validates and exploits a computa-tionaltestbedthat simulates micro-biological complex systems, namely the aggregation patterns of thesocial amoebaDyctiostelium discoideum. We propose a new design and implementation for managingdiscrete simulations with autonomous agents on a microscopic scale, thus focusing on their social be-havior and mutual interactions. Then, the dependence on the main physical variables is tested, namelydensity and number of amoebas; in addition, we analyze the robustness of the dynamics against var-ious noise sources. Along with these results, we suggest a methodology for further studies that makeuse of our validated model. [less ▲]

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See detailApproXON: Heuristic Approximation to the E-Field-Threshold for Deep Brain Stimulation Volume-of-Tissue-Activated Estimation
Proverbio, Daniele UL; Husch, Andreas UL

E-print/Working paper (2019)

This paper introduces a heuristic approximation of the e-field threshold used for volume-of-tissue activated computation in deep brain stimulation. Pulse width and axon diameter are used as predictors. An ... [more ▼]

This paper introduces a heuristic approximation of the e-field threshold used for volume-of-tissue activated computation in deep brain stimulation. Pulse width and axon diameter are used as predictors. An open source implementation in MATLAB is provided together with an integration in the open LeadDBS deep brain stimulation research toolbox. [less ▲]

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See detailDynamical strategies for obstacle avoidance during Dictyostelium discoideum aggregation: a Multi-agent system model
Proverbio, Daniele UL; Maggiora, Marco

E-print/Working paper (2019)

Chemotaxis, the movement of an organism in response to a chemical stimulus, is a typical feature of many microbiological systems. In particular, the social amoeba Disctyostelium discoideum is widely used ... [more ▼]

Chemotaxis, the movement of an organism in response to a chemical stimulus, is a typical feature of many microbiological systems. In particular, the social amoeba Disctyostelium discoideum is widely used as a model organism, but it is not still clear how it behaves in heterogeneous environments. A few models focused on mechanical features have already addressed the question; however, we propose that phenomenological models focusing on the dynamics may provide new meaningful data. Consequently, by means of a specific Multi-agent system model, we studied the dynamical features emerging from complex social interactions among individuals belonging to amoeboids colonies. After defining an appropriate metric to perform meaningful measurements, we found that: a) obstacles play the role of local topological perturbation, as they alter the flux of chemical signals; b) that obstacle that physically block the cellular motion as well as the chemicals elicit dynamical evolutions that are not statistically distinguishable from the case where obstacles that do not interfere physically with said motion; c) that fluctuations of the dynamics can lead to better exploration of the physical space, thus preventing multiple stable aggregates. From previous results, we may speculate about the fact that chemotactic cells, in many cases, can avoid obstacles by simply following the altered chemical gradient: social interactions seem to be sufficient to guarantee the aggregation of the whole colony past numerous obstacles. It is then unlikely that cells have developed special mechanisms to cope with the presence of topological perturbation sources. Nevertheless, we suggest that further studies can provide better understanding and that, in order to gain deeper knowledge, mechanical models should be coupled with phenomenological, system-oriented ones. [less ▲]

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