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Numerical simulation of the novel coronavirus spreading.

ABSTRACT: The COVID-19 virus outbreak has affected most of the world in 2020. This paper deals with artificial intelligence (AI) methods that can address the problem of predicting scale, dynamics and sensitivity of the outbreak to preventive actions undertaken with a view to combatting the epidemic. In our study, we developed a cellular automata (CA) model for simulating the COVID-19 disease spreading. The enhanced infectious disease dynamics? SEIR (Susceptible, Exposed, Infectious, and Recovered) model was applied to estimate the epidemic trends in Poland, France, and Spain. We introduced new parameters into the simulation framework which reflect the statistically confirmed dependencies such as age-dependent death probability, a different definition of the contact rate and enhanced parameters reflecting population mobility. To estimate key epidemiological measures and to predict possible dynamics of the disease, we juxtaposed crucial CA framework parameters to the reported COVID-19 values, e.g. length of infection, mortality rates and the reproduction number. Moreover, we used real population density and age structures of the studied epidemic populations. The model presented allows for the examination of the effectiveness of preventive actions and their impact on the spreading rate and the duration of the disease. It also shows the influence of structure and behavior of the populations studied on key epidemic parameters, such as mortality and infection rates. Although our results are critically dependent on the assumptions underpinning our model and there is considerable uncertainty associated with the outbreaks at such an early epidemic stage, the obtained simulation results seem to be in general agreement with the observed behavior of the real COVID-19 disease, and our numerical framework can be effectively used to analyze the dynamics and efficacy of epidemic containment methods.

SUBMITTER: Medrek M

PROVIDER: S-EPMC7557303 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Numerical simulation of the novel coronavirus spreading.

Medrek M M Pastuszak Z Z

Expert systems with applications 20201015

The COVID-19 virus outbreak has affected most of the world in 2020. This paper deals with artificial intelligence (AI) methods that can address the problem of predicting scale, dynamics and sensitivity of the outbreak to preventive actions undertaken with a view to combatting the epidemic. In our study, we developed a cellular automata (CA) model for simulating the COVID-19 disease spreading. The enhanced infectious disease dynamics SEIR (Susceptible, Exposed, Infectious, and Recovered) model w ...[more]

PMID: 33078047

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Project description:BackgroundThe mortality of humans due to rabies in China has been declining in recent years, but it is still a significant public health problem. According to the global framework, China strives to achieve the goal of eliminating human rabies before 2030.MethodsWe reviewed the epidemiology of human deaths from rabies in mainland China from 2004 to 2018. We identified high risk regions, age and occupational groups, and used a continuous deterministic susceptibility-exposure-infection-recovery (SEIR) model with periodic transmission rate to explore seasonal rabies prevalence in different human populations. The SEIR model was used to simulate the data of human deaths from rabies reported by the Chinese Center for Disease Control and Prevention (China CDC). We calculated the relative transmission intensity of rabies from canines to different human groups, and they provided a reliable epidemiological basis for further control and prevention of human rabies.ResultsResults showed that human deaths from rabies exhibited regional differences and seasonal characteristics in mainland China. The annual human death from rabies in different regions, age groups and occupational groups decreased steadily across time. Nevertheless, the decreasing rates and the calculated R0s of canines of various human groups were different. The transmission intensity of rabies from canines to human populations was the highest in the central regions of China, in people over 45 years old, and in farmers.ConclusionsAlthough the annual cases of human deaths from rabies have decreased steadily since 2007, the proportion of human deaths from rabies varies with region, age, gender, and occupation. Further enhancement of public awareness and immunization status in high-risk population groups and blocking the transmission routes of rabies from canines to humans are necessary. The concept of One Health should be abided and human, animal, and environmental health should be considered simultaneously to achieve the goal of eradicating human rabies before 2030.

Project description:BackgroundCortical spreading depolarization (SD) is a propagating depolarization wave of neurons and glial cells in the cerebral gray matter. SD occurs in all forms of severe acute brain injury, as documented by using invasive detection methods. Based on many experimental studies of mechanical brain deformation and concussion, the occurrence of SDs in human concussion has often been hypothesized. However, this hypothesis cannot be confirmed in humans, as SDs can only be detected with invasive detection methods that would require either a craniotomy or a burr hole to be performed on athletes. Typical electroencephalography electrodes, placed on the scalp, can help detect the possible presence of SD but have not been able to accurately and reliably identify SDs.MethodsTo explore the possibility of a noninvasive method to resolve this hurdle, we developed a finite element numerical model that simulates scalp voltage changes that are induced by a brain surface SD. We then compared our simulation results with retrospectively evaluated data in patients with aneurysmal subarachnoid hemorrhage from Drenckhahn et al. (Brain 135:853, 2012).ResultsThe ratio of peak scalp to simulated peak cortical voltage, Vscalp/Vcortex, was 0.0735, whereas the ratio from the retrospectively evaluated data was 0.0316 (0.0221, 0.0527) (median [1st quartile, 3rd quartile], n = 161, p < 0.001, one sample Wilcoxon signed-rank test). These differing values provide validation because their differences can be attributed to differences in shape between concussive SDs and aneurysmal subarachnoid hemorrhage SDs, as well as the inherent limitations in human study voltage measurements. This simulated scalp surface potential was used to design a virtual scalp detection array. Error analysis and visual reconstruction showed that 1 cm is the optimal electrode spacing to visually identify the propagating scalp voltage from a cortical SD. Electrode spacings of 2 cm and above produce distorted images and high errors in the reconstructed image.ConclusionsOur analysis suggests that concussive (and other) SDs can be detected from the scalp, which could confirm SD occurrence in human concussion, provide concussion diagnosis on the basis of an underlying physiological mechanism, and lead to noninvasive SD detection in the setting of severe acute brain injury.

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Numerical simulation of the novel coronavirus spreading.

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Numerical simulation of the novel coronavirus spreading.

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