SEAHIR: A Specialized Compartmental Model for COVID-19.

The SEIR (Susceptible-Exposed-Infected-Removed) model is widely used in epidemiology to mathematically model the spread of infectious diseases with incubation periods. However, the SEIR model prototype is generic and not able to capture the unique nature of a novel viral pandemic such as SARS-CoV-2. We have developed and tested a specialized version of the SEIR model, called SEAHIR (Susceptible-Exposed-Asymptomatic-Hospitalized-Isolated-Removed) model. This proposed model is able to capture the unique dynamics of the COVID-19 outbreak including further dividing the Infected compartment into: (1) "Asymptomatic", (2) "Isolated" and (3) "Hospitalized" to delineate the transmission specifics of each compartment and forecast healthcare requirements. The model also takes into consideration the impact of non-pharmaceutical interventions such as physical distancing and different testing strategies on the number of confirmed cases. We used a publicly available dataset from the United Arab Emirates (UAE) as a case study to optimize the main parameters of the model and benchmarked it against the historical number of cases. The SEAHIR model was used by decision-makers in Dubai's COVID-19 Command and Control Center to make timely decisions on developing testing strategies, increasing healthcare capacity, and implementing interventions to contain the spread of the virus. The novel six-compartment SEAHIR model could be utilized by decision-makers and researchers in other countries for current or future pandemics.

Cyclic stroke mortality variations follow sunspot patterns.

BACKGROUND: Mapping time-structures is a burgeoning scientific field enriching the (P4) medicine models. Local evidence in Mediterranean populations is underinvestigated. METHODS: The Censused stroke-related death events (D) in the largest East-Mediterranean port (Piraeus), during (1985-1989), when local population had diet (low fat/sugar, proteins and vegetables/fruits daily, and pure olive oil almost exclusively) and genetic homogeneity-later interrupted by the immigration into Greece in 1990; and Sunspot numbers were indexed by Wolf numbers (Rz) (1944-2004), and evaluated using Fast Fourier Analysis and Singular Spectrum Analysis in MATLAB. RESULTS: D were turned with fluctuations >35% in Rz. A non-anthropogenic 6.8 days cycle was recognized. CONCLUSIONS: This study may be taken into consideration in future public health planning and chronotherapy evaluations.

An adaptive way for improving noise reduction using local geometric projection.

We propose an adaptive way to improve noise reduction by local geometric projection. From the neighborhood of each candidate point in phase space, we identify the best subspace that the point will be orthogonally projected to. The signal subspace is formed by the most significant eigendirections of the neighborhood, while the less significant ones define the noise subspace. We provide a simple criterion to separate the most significant eigendirections from the less significant ones. This criterion is based on the maximum logarithmic difference between the neighborhood eigendirection lengths, and the assumption that there is at least one eigendirection that corresponds to the noise subspace. In this way, we take into account the special characteristics of each neighborhood and introduce a more successful noise reduction technique. Results are presented for a chaotic time series of the Henon map and Ikeda map, as well as on the Nasdaq Composite index.