310 research outputs found
The Economic Cybernetics Analysis and the Effects of the Occurrence of COVID-19 in Romania
From the perspectives of early warning and identification of risk, risk quantification and analysis, also as risk management, we propose recommendation, which includes analysis of citizen behavior in panic, cooperation of the institutions in Romania. The whole analysis will be performed from a perspective of the field of economic cybernetics. The 2019-nCoV coronavirus epidemic started in China's Wuhan city, which has spread throughout the country and subsequently, in a very short period of time, in several states, being viewed as a global contagion effect that causes great concern. As the virus gets closer to Romania, it becomes worrying and citizens are already panicking. Therefore, in this article we will analyze, according to public data, what is the current situation and how well Romania is prepared to manage the risks arising from the confirmation of COVID-19 in the country and how the behavior of citizens in a state of panic is influenced. In addition, we analysed the medical system from Romania from the point of view of the analysis of the management of the viable system, in the situation of pandemic crisis the medical system being one of the sensitive points of any system
Epidemic Modeling using Hybrid of Time-varying SIRD, Particle Swarm Optimization, and Deep Learning
Epidemiological models are best suitable to model an epidemic if the spread
pattern is stationary. To deal with non-stationary patterns and multiple waves
of an epidemic, we develop a hybrid model encompassing epidemic modeling,
particle swarm optimization, and deep learning. The model mainly caters to
three objectives for better prediction: 1. Periodic estimation of the model
parameters. 2. Incorporating impact of all the aspects using data fitting and
parameter optimization 3. Deep learning based prediction of the model
parameters. In our model, we use a system of ordinary differential equations
(ODEs) for Susceptible-Infected-Recovered-Dead (SIRD) epidemic modeling,
Particle Swarm Optimization (PSO) for model parameter optimization, and
stacked-LSTM for forecasting the model parameters. Initial or one time
estimation of model parameters is not able to model multiple waves of an
epidemic. So, we estimate the model parameters periodically (weekly). We use
PSO to identify the optimum values of the model parameters. We next train the
stacked-LSTM on the optimized parameters, and perform forecasting of the model
parameters for upcoming four weeks. Further, we fed the LSTM forecasted
parameters into the SIRD model to forecast the number of COVID-19 cases. We
evaluate the model for highly affected three countries namely; the USA, India,
and the UK. The proposed hybrid model is able to deal with multiple waves, and
has outperformed existing methods on all the three datasets.Comment: Accepted in ICCCNT 202
From Social Simulation to Integrative System Design
As the recent financial crisis showed, today there is a strong need to gain
"ecological perspective" of all relevant interactions in
socio-economic-techno-environmental systems. For this, we suggested to set-up a
network of Centers for integrative systems design, which shall be able to run
all potentially relevant scenarios, identify causality chains, explore feedback
and cascading effects for a number of model variants, and determine the
reliability of their implications (given the validity of the underlying
models). They will be able to detect possible negative side effect of policy
decisions, before they occur. The Centers belonging to this network of
Integrative Systems Design Centers would be focused on a particular field, but
they would be part of an attempt to eventually cover all relevant areas of
society and economy and integrate them within a "Living Earth Simulator". The
results of all research activities of such Centers would be turned into
informative input for political Decision Arenas. For example, Crisis
Observatories (for financial instabilities, shortages of resources,
environmental change, conflict, spreading of diseases, etc.) would be connected
with such Decision Arenas for the purpose of visualization, in order to make
complex interdependencies understandable to scientists, decision-makers, and
the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c
Control Strategies for COVID-19 Epidemic with Vaccination, Shield Immunity and Quarantine: A Metric Temporal Logic Approach
Ever since the outbreak of the COVID-19 epidemic, various public health
control strategies have been proposed and tested against the coronavirus
SARS-CoV-2. We study three specific COVID-19 epidemic control models: the
susceptible, exposed, infectious, recovered (SEIR) model with vaccination
control; the SEIR model with shield immunity control; and the susceptible,
un-quarantined infected, quarantined infected, confirmed infected (SUQC) model
with quarantine control. We express the control requirement in metric temporal
logic (MTL) formulas (a type of formal specification languages) which can
specify the expected control outcomes such as "the deaths from the infection
should never exceed one thousand per day within the next three months" or "the
population immune from the disease should eventually exceed 200 thousand within
the next 100 to 120 days". We then develop methods for synthesizing control
strategies with MTL specifications. To the best of our knowledge, this is the
first paper to systematically synthesize control strategies based on the
COVID-19 epidemic models with formal specifications. We provide simulation
results in three different case studies: vaccination control for the COVID-19
epidemic with model parameters estimated from data in Lombardy, Italy; shield
immunity control for the COVID-19 epidemic with model parameters estimated from
data in Lombardy, Italy; and quarantine control for the COVID-19 epidemic with
model parameters estimated from data in Wuhan, China. The results show that the
proposed synthesis approach can generate control inputs such that the
time-varying numbers of individuals in each category (e.g., infectious, immune)
satisfy the MTL specifications. The results also show that early intervention
is essential in mitigating the spread of COVID-19, and more control effort is
needed for more stringent MTL specifications
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