Multi-regional COVID-19 epidemic forecast in Sweden

Public health system sustainability assessment by Gaidai hypersurface approach

BACKGROUND

to determine extreme cardiovascular and cancer diseases deathrate risks at any time in any region of interest.

DESIGN

Apply modern novel statistical methods to raw clinical surveillance data.

METHODS

multi-centre, population-based, medical survey data-based bio statistical approach. For this study, cardiovascular and cancer diseases annual recorded deaths numbers in all 195 world countries have been selected, constituting 390D (390-dimensional) biosystem. It is challenging to model such phenomena.

RESULTS

this paper describes a novel bio-system reliability approach, particularly suitable for multi-regional environmental and health systems, observed over a sufficient timelapse. Traditional statistical methods dealing with temporal observations of multi-regional processes do not have the advantage of dealing efficiently with extensive regional dimensionality. The suggested methodology coped with this challenge well.

CONCLUSIONS

the suggested methodology may be used in various public health applications, based on raw clinical survey data.

Gaidai reliability method for long-term coronavirus modelling

Background

Novel coronavirus disease has been recently a concern for worldwide public health. To determine epidemic rate probability at any time in any region of interest, one needs efficient bio-system reliability approach, particularly suitable for multi-regional environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of novel coronavirus infection rate. Traditional statistical methods dealing with temporal observations of multi-regional processes do not have the multi-dimensionality advantage, that suggested methodology offers, namely dealing efficiently with multiple regions at the same time and accounting for cross-correlations between different regional observations.

Methods

Modern multi-dimensional novel statistical method was directly applied to raw clinical data, able to deal with territorial mapping. Novel reliability method based on statistical extreme value theory has been suggested to deal with challenging epidemic forecast. Authors used MATLAB optimization software.

Results

This paper described a novel bio-system reliability approach, particularly suitable for multi-country environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of extreme novel coronavirus death rate probability. Namely, accurate maximum recorded patient numbers are predicted for the years to come for the analyzed provinces.

Conclusions

The suggested method performed well by supplying not only an estimate but 95% confidence interval as well. Note that suggested methodology is not limited to any specific epidemics or any specific terrain, namely its truly general. The only assumption and limitation is bio-system stationarity, alternatively trend analysis should be performed first. The suggested methodology can be used in various public health applications, based on their clinical survey data.

Carbon Storage Tanker Lifetime Assessment

CO₂ capture and storage (CCS) is an important strategy to reduce global CO₂ emissions. This work presents both cutting-edge carbon storage tanker design, as well as novel reliability method making possible to extract useful information about the lifespan distribution of carbon capture systems from their recorded time history. The method outlined may be applied on more complex sustainable systems that are exposed to environmental stresses throughout the whole period of their planned service life. The latter is of paramount importance at the design stage for complex engineering systems. Novel design for CCS system is discussed and accurate numerical simulation results are used to apply suggested novel reliability methodology. Furthermore, traditional reliability approaches that deal with complex energy systems are not well suited for handling high dimensionality and cross-correlation between various system components of innovative dynamic CO₂ storage subsea shuttle tanker. This study has two distinctive key features: the state of art CCS design concept, and the novel general purpose reliability method, recently developed by authors, and particularly suitable for operational safety study of complex energy systems.

A novel statistical method for long-term coronavirus modelling

Background: Novel coronavirus disease has been recently a concern for worldwide public health. To determine epidemic rate probability at any time in any region of interest, one needs efficient bio-system reliability approach, particularly suitable for multi-regional environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of novel coronavirus infection rate. Traditional statistical methods dealing with temporal observations of multi-regional processes do not have the multi-dimensionality advantage, that suggested methodology offers, namely dealing efficiently with multiple regions at the same time and accounting for cross-correlations between different regional observations. Methods: Modern multi-dimensional novel statistical method was directly applied to raw clinical data, able to deal with territorial mapping. Novel reliability method based on statistical extreme value theory has been suggested to deal with challenging epidemic forecast. Authors used MATLAB optimization software. Results: This paper described a novel bio-system reliability approach, particularly suitable for multi-country environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of extreme novel coronavirus death rate probability. Namely, accurate maximum recorded patient numbers are predicted for the years to come for the analyzed provinces. Conclusions: The suggested method performed well by supplying not only an estimate but 95% confidence interval as well. Note that suggested methodology is not limited to any specific epidemics or any specific terrain, namely its truly general. The only assumption and limitation is bio-system stationarity, alternatively trend analysis should be performed first. The suggested methodology can be used in various public health applications, based on their clinical survey data.