Modeling the COVID-19 epidemic in Croatia: a comparison of three analytic approaches.

AIM: To facilitate the development of a COVID-19 predictive model in Croatia by analyzing three different methodological approaches. METHOD: We used the historical data to explore the fit of the extended SEIRD compartmental model, the Heidler function, an exponential approximation in analyzing electromagnetic phenomena related to lightning strikes, and the Holt-Winters smoothing (HWS) for short-term epidemic predictions. We also compared various methods for the estimation of R0. RESULTS: The R0 estimates for Croatia varied from 2.09 (95% CI 1.77-2.40) obtained by using an empirical post-hoc method to 2.28 (95% CI 2.27-2.28) when we assumed an exponential outbreak at the very beginning of the COVID-19 epidemic in Croatia. Although the SEIRD model provided a good fit for the early epidemic stages, it was outperformed by the Heidler function fit. HWS achieved accurate short-term predictions and depended the least on model entry parameters. Neither model performed well across the entire observed period, which was characterized by multiple wave-form events, influenced by the re-opening for the tourist season during the summer, mandatory masks use in closed spaces, and numerous measures introduced in retail stores and public places. However, an extension of the Heidler function achieved the best overall fit. CONCLUSIONS: Predicting future epidemic events remains difficult because modeling relies on the accuracy of the information on population structure and micro-environmental exposures, constant changes of the input parameters, varying societal adherence to anti-epidemic measures, and changes in the biological interactions of the virus and hosts.

Machine learning-assisted antenna modelling for realistic assessment of incident power density on non-planar surfaces above 6 GHz.

In this paper, the analysis of exposure reference levels is performed for the case of a half-wavelength dipole antenna positioned in the immediate vicinity of non-planar body parts. The incident power density (IPD) spatially averaged over the spherical and cylindrical surface is computed at the 6-90 GHz range, and subsequently placed in the context of the current international guidelines and standards for limiting exposure to electromagnetic (EM) fields which are defined considering planar computational tissue models. As numerical errors are ubiquitous at such high frequencies, the spatial resolution of EM models needs to be increased which in turn results in increased computational complexity and memory requirements. To alleviate this issue, we hybridise machine learning and traditional scientific computing approaches through differentiable programming paradigm. Findings demonstrate a strong positive effect the curvature of non-planar models has on the spatially averaged IPD with up to 15% larger values compared to the corresponding planar model in considered exposure scenarios.

Assessment of absorbed power density in multilayer planar model of human tissue.

The paper deals with the determination of the absorbed power density (Sab) in a planar multilayer model of a tissue exposed to the radiation of a dipole antenna, based on the analytical/numerical approach. A derivation of Sab from the differential form of Poynting theorem is presented. The two-layer and three-layer tissue models are used. Illustrative analytical/numerical results for electric and magnetic fields and Sab induced at the tissue surface for various antenna lengths, operating frequencies and antenna-interface distances are presented in the paper. Exposure scenarios of interest pertain to frequencies above 6GHz pertaining to 5G mobile systems.

Analysis of Transcranial Magnetic Stimulation Based on the Surface Integral Equation Formulation.

GOAL: The aim of this paper is to provide a rigorous model and, hence, a more accurate description of the transcranial magnetic stimulation (TMS) induced fields and currents, respectively, by taking into account the inductive and capacitive effects, as well as the propagation effects, often being neglected when using quasi-static approximation. METHODS: The formulation is based on the surface integral equation (SIE) approach. The model of a lossy homogeneous brain has been derived from the equivalence theorem and using the appropriate boundary conditions for the electric field. The numerical solution of the SIE has been carried out using the method of moments. RESULTS: Numerical results for the induced electric field, electric current density, and the magnetic flux density distribution inside the human brain, presented for three typical TMS coils, are in a good agreement with some previous analysis as well as to the results obtained by analytical approach. CONCLUSION: The future work should be related to the development of a more detailed geometrical model of the human brain that will take into account complex cortical columnar structures, as well as some additional brain tissues. SIGNIFICANCE: To the best of authors knowledge, similar approach in modeling TMS has not been previously reported, albeit integral equation methods are seeing a revival in computational electromagnetics community.