scholarly journals Covid-19 Epidemic Dynamic Including Barriers of Circulation

2020 ◽  
Author(s):  
Sebasti o Gomes ◽  
Igor Monteiro
Keyword(s):  
Epidemic Dynamic

scholarly journals Evolutionary Dynamics of Stochastic SEIR Models with Migration and Human Awareness in Complex Networks

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yue Zhang ◽  
Yuxuan Li
Keyword(s):  
Complex Networks ◽  
Numerical Experiments ◽  
Evolutionary Dynamics ◽  
Sufficient Conditions ◽  
Deterministic System ◽  
Stochastic Solution ◽  
Epidemic Dynamic ◽  
Theoretical Results ◽  
Disease Persistence ◽  
Human Awareness

In this paper, a stochastic SEIR (Susceptible-Exposed-Infected-Removed) epidemic dynamic model with migration and human awareness in complex networks is constructed. The awareness is described by an exponential function. The existence of global positive solutions for the stochastic system in complex networks is obtained. The sufficient conditions are presented for the extinction and persistence of the disease. Under the conditions of disease persistence, the distance between the stochastic solution and the local disease equilibrium of the corresponding deterministic system is estimated in the time sense. Some numerical experiments are also presented to illustrate the theoretical results. Although the awareness introduced in the model cannot affect the extinction of the disease, the scale of the disease will eventually decrease as human awareness increases.

Threshold conditions for a family of epidemic dynamic models for malaria with distributed delays in a non-random environment

2018 ◽  
Vol 11 (06) ◽  
pp. 1850085 ◽  
Author(s):  
Divine Wanduku
Keyword(s):  
Incidence Rate ◽  
Dynamic Models ◽  
Family Type ◽  
Natural Immunity ◽  
Nonlinear Incidence Rate ◽  
Nonlinear Incidence ◽  
Reproduction Numbers ◽  
Threshold Conditions ◽  
Epidemic Dynamic ◽  
The Stability

A family of deterministic SEIRS epidemic dynamic models for malaria is presented. The family type is determined by a general functional response for the nonlinear incidence rate of the disease. Furthermore, the malaria models exhibit three random delays — the incubation periods of the plasmodium inside the female mosquito and human hosts, and also the period of effective acquired natural immunity against the disease. Insights about the effects of the delays and the nonlinear incidence rate of the disease on (1) eradication and (2) persistence of malaria in the human population are obtained via analyzing and interpreting the global asymptotic stability results of the disease-free and endemic equilibrium of the system. The basic reproduction numbers and other threshold values for malaria are calculated, and superior threshold conditions for the stability of the equilibria are found. Numerical simulation results are presented.

scholarly journals Information Agenda on Entertainment Radio Stations during the COVID19 Pandemic on the Example of “Radio Dacha”

2021 ◽  
Vol 20 (6) ◽  
pp. 192-199
Author(s):  
Yu. V. Nasonova
Keyword(s):  
Content Analysis ◽  
News Coverage ◽  
Radio Station ◽  
Radio Stations ◽  
News Program ◽  
Epidemic Dynamic ◽  
Russian Media ◽  
Maximum Quantity ◽  
Social News ◽  
Epidemiological Situation

The coronavirus pandemic has had a significant impact on the Russian media, which, regardless of their format, have been broadcasting news about the infection since the beginning of the outbreak on a regular basis. The main purpose of the research is to establish a connection between the epidemiological situation in Russia during the first wave and the nature of the change in the information agenda on the air of the entertainment “Radio Dacha”. To reach this goal the author, using the method of inclusive observation, analyzes 1 219 episodes of the news program, aired from January 2020, when radio hosts first mentioned the COVID-19, to July 2020, when the main restrictions were lifted in Russia. The article shows that depending on the epidemiological state, the number of notes about the coronavirus increased. The maximum quantity of news about the disease was noted in April and May when the country had the highest amount of cases and announced a lockdown. Meanwhile, the content analysis indicated that there was direct and indirect news coverage of the coronavirus. Their ratio is 97 to 3 % in favor of direct news. It means that despite the format of the radio station, the radio hosts only talked about political and social news with little or no entertain ment content. Thus, the epidemic dynamic changed the information agenda, and the worst it was, the more news about the coronavirus went on the air. The news about the infection became the longest discussed subject on the air of “Radio Dacha”. 

scholarly journals Where to cut to delay a pandemic with minimum disruption? mathematical analysis based on the SIS model

2021 ◽  
pp. 1-26
Author(s):  
Paolo Bartesaghi ◽  
Ernesto Estrada
Keyword(s):  
Upper Bound ◽  
Time Delays ◽  
Transportation Network ◽  
Network Capacity ◽  
Sis Model ◽  
Transportation Capacity ◽  
Epidemic Dynamic ◽  
Dynamic Relations ◽  
The Uk ◽  
Communicability Function

We consider the problem of modifying a network topology in such a way as to delay the propagation of a disease with minimal disruption of the network capacity to reroute goods/items/passengers. We find an approximate solution to the Susceptible-Infected-Susceptible (SIS) model, which constitutes an upper bound to its exact solution. This upper bound allows direct structure-epidemic dynamic relations via the total communicability function. Using this approach we propose a strategy to remove edges in a network that significantly delays the propagation of a disease across the network with minimal disruption of its capacity to deliver goods/items/passengers. We apply this strategy to the analysis of the UK airport transportation network weighted by the number of passengers transported in 2003. We find that the removal of all flights connecting four origin-destination pairs in the UK delays the propagation of a disease by more than 300%, with a minimal deterioration of the transportation capacity of this network. These time delays in the propagation of a disease represent an important non-pharmaceutical intervention to confront an epidemic, allowing for better preparations of the health systems, while keeping the economy moving with minimal disruptions.

scholarly journals The effect of population size for pathogen transmission on prediction of COVID-19 spread

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xuqi Zhang ◽  
Haiqi Liu ◽  
Hanning Tang ◽  
Mei Zhang ◽  
Xuedong Yuan ◽  
...  
Keyword(s):  
Public Health ◽  
Dynamic System ◽  
Population Size ◽  
Nonlinear Filtering ◽  
Hidden Markov ◽  
Pathogen Transmission ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Stochastic Epidemic ◽  
Epidemic Dynamic

AbstractExtreme public health interventions play a critical role in mitigating the local and global prevalence and pandemic potential. Here, we use population size for pathogen transmission to measure the intensity of public health interventions, which is a key characteristic variable for nowcasting and forecasting of COVID-19. By formulating a hidden Markov dynamic system and using nonlinear filtering theory, we have developed a stochastic epidemic dynamic model under public health interventions. The model parameters and states are estimated in time from internationally available public data by combining an unscented filter and an interacting multiple model filter. Moreover, we consider the computability of the population size and provide its selection criterion. With applications to COVID-19, we estimate the mean of the effective reproductive number of China and the rest of the globe except China (GEC) to be 2.4626 (95% CI: 2.4142–2.5111) and 3.0979 (95% CI: 3.0968–3.0990), respectively. The prediction results show the effectiveness of the stochastic epidemic dynamic model with nonlinear filtering. The hidden Markov dynamic system with nonlinear filtering can be used to make analysis, nowcasting and forecasting for other contagious diseases in the future since it helps to understand the mechanism of disease transmission and to estimate the population size for pathogen transmission and the number of hidden infections, which is a valid tool for decision-making by policy makers for epidemic control.

scholarly journals Performance Analysis of DTN Using Level Signal Priority Epidemic Routing Protocol

2016 ◽  
Vol 3 (2) ◽  
Author(s):  
Ahmad Zainudin ◽  
Amang Sudarsono ◽  
Kevin Prima Pambudi
Keyword(s):  
Routing Protocol ◽  
Network Architecture ◽  
Dynamic Routing ◽  
Delay Tolerant Network ◽  
Test Bed ◽  
Measurement Results ◽  
Epidemic Routing ◽  
Epidemic Dynamic ◽  
Performance System ◽  
Delay Tolerant

A DTN architecture consists of several nodes that are connected with high dynamic topology. The routing protocol is an important part which determine the DTN performance system. Although DTN is addressed to be tolerant of delay, a routing protocol with better performance will maximizing packet delivery rate and minimizing the delivery latency. This paper evaluate a level signal priority epidemic routing protocol for delay tolerant network architecture. Our system adopts DTN2 framework using classic epidemic and priority epidemic dynamic routing protocols. The performance of both dynamic routing is observed and compared based on throughput and delay of transmitted data. The measurement results show that the classic epidemic use more bandwith due to sending the same messages many times. The delay transmission using a level signal priority epidemic routing is smaller than classic epidemic routing protocol in all hops of the test-bed. Epidemic based on signal level routing could make traffic of network more efficient than classic Epidemic routing because of filtering system in node before sending bundle to neighbor node.Keywords: DTN, dynamic routing, level signal priority

scholarly journals Application of Big Data Technology in the Fight Against New Coronary Pneumonia Epidemic in China

2021 ◽  
Author(s):  
Xie Yan
Keyword(s):  
Big Data ◽  
Policy Implementation ◽  
Prevention And Control ◽  
Control Period ◽  
Vital Role ◽  
Great Success ◽  
Dynamic Information ◽  
Epidemic Dynamic ◽  
And Control ◽  
Big Data Technology

In the fight against New Coronary Pneumonia Epidemic, Chinese Ministry of Health put forward the inevitable requirements of precise policy implementation and scientific epidemic prevention. Accordingly, the big data technology has been applied in the analysis of epidemic dynamic, information inquiry, disease prevention and treatment, and prediction of epidemic trend. And, great success has been achieved in the fight, where the big data technology has played a vital role. This article outlines the main applications of big data technology in the prevention and control of New Coronary Pneumonia Epidemic, and proposes suggestions based on the problems in the application of big data during the epidemic prevention and control period. In the later stage, the integration of big data technology in various fields should be accelerated, information should be further shared and the utility value of data should be maximized.

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