COVID-19 outbreak in Wuhan demonstrates the limitations of publicly available case numbers for epidemiological modeling

Raimúndez, Elba; Dudkin, Erika; Vanhoefer, Jakob; Alamoudi, Emad; Merkt, Simon; Fuhrmann, Lara; Bai, Fan; Hasenauer, Jan

doi:10.1016/j.epidem.2021.100439

Cited by 22 publications

(15 citation statements)

References 79 publications

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“…This is problematic for two reasons: Firstly, many parameters are region- and situation-specific and can thus lead to wrong estimates of inferred parameters. Secondly, estimates typically have large uncertainty intervals, as also seen in our study and by Raimúndez et al (2021). Fixing those to single values may lead to an underestimation of the uncertainty of inferred parameters.…”

Section: Discussionsupporting

confidence: 57%

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

Contento

Castelletti²,

Raimúndez

et al. 2021

Preprint

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Mathematical models have been widely used during the ongoing SARS-CoV-2 pandemic for data interpretation, forecasting, and policy making. However, most models are based on officially reported case numbers, which depend on test availability and test strategies. The time dependence of these factors renders interpretation difficult and might even result in estimation biases. Here, we present a computational modelling framework that allows for the integration of reported case numbers with seroprevalence estimates obtained from representative population cohorts. To account for the time dependence of infection and testing rates, we embed flexible splines in an epidemiological model. The parameters of these splines are estimated, along with the other parameters, from the available data using a Bayesian approach. The application of this approach to the official case numbers reported for Munich (Germany) and the seroprevalence reported by the prospective COVID-19 Cohort Munich (KoCo19) provides first estimates for the time dependence of the under-reporting factor. Furthermore, we estimate how the effectiveness of non-pharmaceutical interventions and of the testing strategy evolves over time. Overall, our results show that the integration of temporally highly resolved and representative data is beneficial for accurate epidemiological analyses.

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Section: Discussionsupporting

confidence: 57%

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

Contento

Castelletti²,

Raimúndez

et al. 2021

Preprint

Self Cite

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“…On the other hand, more general partial differential equations (PDEs) and systems can be considered, for example, system of coupled PDEs, nonlinear diffusion PDEs, and nonautonomous reaction diffusion PDEs. Those kinds of PDEs appear widely as epidemiological models to study and analyze the spread of diseases and pandemics [22][23][24][25].…”

Section: Discussionmentioning

confidence: 99%

“…These models describe the spatiotemporal prevalence of the viral pandemic and apprehend the dynamics depending on human habits and geographical features. The models estimate a qualitative harmony between the simulated prediction of the local spatiotemporal spread of a pan-demic and the epidemiological collected datum (see [22,23]). These data-driven emulations can essentially inform the respective authorities to purpose efficient pandemicarresting measures and foresee the geographical distribution of vital medical resources.…”

Section: Introductionmentioning

confidence: 92%

Generalized Laplace-Type Transform Method for Solving Multilayer Diffusion Problems

Akel

Elshehabey

Ahmed

2022

Journal of Function Spaces

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Multilayer diffusion problems have found significant importance that they arise in many medical, environmental, and industrial applications of heat and mass transfer. In this article, we study the solvability of a one-dimensional nonhomogeneous multilayer diffusion problem. A new generalized Laplace-type integral transform is used, namely, the M ρ , m -transform. First, we reduce the nonhomogeneous multilayer diffusion problem into a sequence of one-layer diffusion problems including time-varying given functions, followed by solving a general nonhomogeneous one-layer diffusion problem via the M ρ , m -transform. Hence, by means of general interface conditions, a renewal equations’ system is determined. Finally, the M ρ , m -transform and its analytic inverse are used to obtain an explicit solution to the renewal equations’ system. Our results are of general attractiveness and comprise a number of previous works as special cases.

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“…for example, system of coupled PDEs, nonlinear diffusion PDEs and non-autonomous reaction diffusion PDEs. Those kinds of PDEs appear widely as epidemiological models to study and analyze the spread of diseases and pandemics [12,15,29,36].…”

Section: Discussionmentioning

confidence: 99%

“…The models estimate a qualitative harmony between the simulated prediction of the local spatiotemporal spread of a pandemic and the epidemiological collected datum. See [29,36]. These data-driven emulations can essentially inform the respective authorities to purpose efficient pandemic-arresting measures and foresee the geographical distribution of vital medical resources.…”

Section: Introductionmentioning

confidence: 99%

Generalized integral transform method for solving multilayer diffusion problems

Akel,

Elshehabey,

Ahmed

2021

Preprint

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Multilayer diffusion problems have found significant important that they arise in many medical, environmental and industrial applications of heat and mass transfer. In this article, we study the solvability of one-dimensional nonhomogeneous multilayer diffusion problem. We use a new generalized integral transform, namely, M ρ,m −transform [Srivastava et al., https://doi.org/10.1016/S0252-9602(15)30061-8]. First, we reduce the nonhomogeneous multilayer diffusion problem into a sequence of one-layer diffusion problems including time-varying given functions, followed by solving a general nonhomogeneous one-layer diffusion problem via the M ρ,m −transform. Hence, by means of general interface conditions, a renewal equations' system is determined. Finally, the M ρ,m −transform and its analytic inverse are used to obtain an explicit solution to the renewal equations' system. Our results generalize those ones in [Rodrigo and Worthy,

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COVID-19 outbreak in Wuhan demonstrates the limitations of publicly available case numbers for epidemiological modeling

Cited by 22 publications

References 79 publications

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

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

Generalized Laplace-Type Transform Method for Solving Multilayer Diffusion Problems

Generalized integral transform method for solving multilayer diffusion problems

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