Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infectious contacts

Contento, Lorenzo; Castelletti, Noemi; Raimúndez, Elba; R, Le Gleut; Schälte, Yannik; Stapor, Paul; Lc, Hinske; Höelscher, Michael; Radon, Katja; Fuchs, Christiane; Hasenauer, Jan

doi:10.1101/2021.10.01.21263052

Cited by 4 publications

(2 citation statements)

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“…To gain a comprehensive understanding of their dynamics, mathematical models have become an indispensable tool [3][4][5][6][7]. The global pandemic caused by the novel SARS-CoV-2 in 2020/21 prompted numerous modeling efforts, ranging from early situation assessments [8][9][10] to evaluating the effectiveness of non-pharmaceutical interventions [11][12][13], analyzing undetected cases [14,15] and employing agent-based model descriptions [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Non-Parametric Model-Based Estimation of the Effective Reproduction Number for SARS-CoV-2

Hermes,

Rosenblatt,

Tönsing

et al. 2023

Algorithms

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Describing viral outbreaks, such as the COVID-19 pandemic, often involves employing compartmental models composed of ordinary differential equation (ODE) systems. Estimating the parameter values for these ODE models is crucial and relies on accessible data. To accurately represent realistic pandemic scenarios with diverse situations, it is necessary to consider model parameters as time dependent. However, estimating such time-dependent parameters, like transition rates in compartmental models, is notoriously challenging due to the unknown function class of these parameters. In this study, we propose a novel approach by using an Augmented Kalman Smoother (AKS) combined with an Expectation-Maximization (EM) algorithm to simultaneously estimate all time-dependent parameters in an SIRD compartmental model. Our approach can be applied to general ODE systems with time-varying parameters, requiring no prior knowledge of model parameters or additional assumptions on the function class of the ODE time dependencies. A key advantage of our method compared to other methods is that it does not require assumptions about the parameterization of the serial interval distribution for estimating SIRD model parameters. Applying our approach to COVID-19 data in Germany, we adequately describe time-series data with strong fluctuations and multiple waves, obtaining non-parametric model-based time-course estimates for the effective reproduction number.

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Section: Introductionmentioning

confidence: 99%

Non-Parametric Model-Based Estimation of the Effective Reproduction Number for SARS-CoV-2

Hermes,

Rosenblatt,

Tönsing

et al. 2023

Algorithms

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show abstract

“…A good overview is given in [ 75 , 76 ]. A trade-off between simple ODE- and IDE-based models are delay-differential equations and linear chain trick [ 77 ] also recently used in [ 78 ]. The authors of [ 79 ] presented memory-equation-based spatial infection dynamics.…”

Section: Introductionmentioning

confidence: 99%

Regional opening strategies with commuter testing and containment of new SARS-CoV-2 variants in Germany

et al. 2022

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Background Despite the vaccination process in Germany, a large share of the population is still susceptible to SARS-CoV-2. In addition, we face the spread of novel variants. Until we overcome the pandemic, reasonable mitigation and opening strategies are crucial to balance public health and economic interests. Methods We model the spread of SARS-CoV-2 over the German counties by a graph-SIR-type, metapopulation model with particular focus on commuter testing. We account for political interventions by varying contact reduction values in private and public locations such as homes, schools, workplaces, and other. We consider different levels of lockdown strictness, commuter testing strategies, or the delay of intervention implementation. We conduct numerical simulations to assess the effectiveness of the different intervention strategies after one month. The virus dynamics in the regions (German counties) are initialized randomly with incidences between 75 and 150 weekly new cases per 100,000 inhabitants (red zones) or below (green zones) and consider 25 different initial scenarios of randomly distributed red zones (between 2 and 20% of all counties). To account for uncertainty, we consider an ensemble set of 500 Monte Carlo runs for each scenario. Results We find that the strength of the lockdown in regions with out of control virus dynamics is most important to avoid the spread into neighboring regions. With very strict lockdowns in red zones, commuter testing rates of twice a week can substantially contribute to the safety of adjacent regions. In contrast, the negative effect of less strict interventions can be overcome by high commuter testing rates. A further key contributor is the potential delay of the intervention implementation. In order to keep the spread of the virus under control, strict regional lockdowns with minimum delay and commuter testing of at least twice a week are advisable. If less strict interventions are in favor, substantially increased testing rates are needed to avoid overall higher infection dynamics. Conclusions Our results indicate that local containment of outbreaks and maintenance of low overall incidence is possible even in densely populated and highly connected regions such as Germany or Western Europe. While we demonstrate this on data from Germany, similar patterns of mobility likely exist in many countries and our results are, hence, generalizable to a certain extent.

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Non-parametric model-based estimation of the effective reproduction number for SARS-CoV-2

Hermes,

Rosenblatt,

Tönsing

et al. 2023

11th International Conference on Mathematical Modeling in Physical Sciences

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Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infectious contacts

Cited by 4 publications

References 46 publications

Non-Parametric Model-Based Estimation of the Effective Reproduction Number for SARS-CoV-2

Non-Parametric Model-Based Estimation of the Effective Reproduction Number for SARS-CoV-2

Regional opening strategies with commuter testing and containment of new SARS-CoV-2 variants in Germany

Non-parametric model-based estimation of the effective reproduction number for SARS-CoV-2

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