This is a table of type trigram and their frequencies. Use it to search & browse the list to learn more about your study carrel.
trigram | frequency |
---|---|
the number of | 318 |
the spread of | 188 |
in order to | 125 |
of the covid | 122 |
of the disease | 121 |
the dynamics of | 115 |
basic reproduction number | 109 |
of the epidemic | 107 |
in this paper | 100 |
based on the | 100 |
the impact of | 94 |
spread of the | 93 |
of the model | 92 |
the basic reproduction | 91 |
spread of covid | 91 |
the effect of | 85 |
due to the | 84 |
number of infected | 81 |
as well as | 76 |
it can be | 75 |
dynamics of the | 75 |
of novel coronavirus | 74 |
total number of | 73 |
of the virus | 70 |
the novel coronavirus | 67 |
the rate of | 67 |
the proposed model | 61 |
is given by | 59 |
of infectious diseases | 59 |
one of the | 58 |
solitons fractals doi | 58 |
chaos solitons fractals | 58 |
analysis of the | 58 |
the evolution of | 57 |
the sir model | 57 |
number of infections | 56 |
the total number | 56 |
on the other | 55 |
the other hand | 54 |
in terms of | 53 |
the value of | 52 |
transmission dynamics of | 52 |
in this section | 51 |
a mathematical model | 51 |
the existence of | 50 |
dynamics of covid | 49 |
to predict the | 49 |
the transmission dynamics | 46 |
the case of | 45 |
reproduction number r | 45 |
number of cases | 44 |
with respect to | 44 |
number of confirmed | 44 |
estimation of the | 44 |
in the population | 44 |
evolution of the | 44 |
the model is | 43 |
the end of | 43 |
there is no | 43 |
can be seen | 43 |
of the system | 43 |
shown in fig | 43 |
there is a | 42 |
fractional differential equations | 42 |
of the novel | 42 |
of confirmed cases | 42 |
of infected individuals | 41 |
model for the | 41 |
of the infected | 41 |
world health organization | 41 |
in this work | 40 |
in this study | 40 |
the authors declare | 39 |
in this case | 39 |
locally asymptotically stable | 38 |
number of deaths | 38 |
to study the | 38 |
of coronavirus disease | 38 |
the total population | 38 |
of the population | 38 |
epidemic model with | 38 |
we assume that | 37 |
according to the | 37 |
that they have | 36 |
the beginning of | 36 |
shown in figure | 36 |
as shown in | 36 |
authors declare that | 36 |
of the outbreak | 35 |
they have no | 35 |
solution of the | 35 |
the use of | 35 |
in the following | 34 |
the optimal control | 34 |
related to the | 34 |
in the number | 34 |
acute respiratory syndrome | 34 |
of the number | 34 |
we consider the | 33 |
is locally asymptotically | 33 |
in cryptocurrency markets | 33 |
declare that they | 33 |
value of the | 33 |
of new cases | 33 |
of the infection | 33 |
the transmission of | 32 |
severe acute respiratory | 32 |
of the pandemic | 32 |
by using the | 32 |
of the proposed | 32 |
we have the | 31 |
that could have | 31 |
increase in the | 31 |
to reduce the | 31 |
and control of | 31 |
reported in this | 31 |
the epidemic spreading | 31 |
the outbreak of | 31 |
of fractional order | 30 |
the fractional order | 30 |
ordinary differential equations | 30 |
relationships that could | 30 |
are given in | 29 |
such as the | 29 |
virus in the | 29 |
appeared to influence | 29 |
personal relationships that | 29 |
the rest of | 29 |
could have appeared | 29 |
given by the | 29 |
have appeared to | 29 |
or personal relationships | 29 |
influence the work | 29 |
interests or personal | 29 |
to influence the | 29 |
in the case | 29 |
financial interests or | 29 |
competing financial interests | 29 |
the role of | 28 |
known competing financial | 28 |
globally asymptotically stable | 28 |
in the model | 28 |
work reported in | 28 |
shows that the | 28 |
the work reported | 28 |
no known competing | 28 |
have no known | 28 |
is shown in | 28 |
mathematical model for | 28 |
the influence of | 27 |
be used to | 27 |
rate of new | 27 |
of infected people | 27 |
the fact that | 27 |
the model parameters | 27 |
most of the | 27 |
the effectiveness of | 27 |
the endemic equilibrium | 27 |
in stock markets | 27 |
the susceptible population | 27 |
show that the | 26 |
models have been | 26 |
assume that the | 26 |
model can be | 26 |
to model the | 26 |
the effects of | 26 |
the epidemic peak | 26 |
the risk of | 26 |
growth rate of | 26 |
number of new | 26 |
in the environment | 26 |
numerical solution of | 26 |
of this paper | 26 |
is given as | 26 |
to control the | 25 |
that there is | 25 |
the coronavirus disease | 25 |
of the coronavirus | 25 |
transmission of the | 25 |
it should be | 25 |
large number of | 25 |
have the following | 25 |
optimal control problem | 25 |
cumulative number of | 25 |
which can be | 25 |
a novel coronavirus | 24 |
on the dynamics | 24 |
of the spread | 24 |
the solution of | 24 |
with the help | 24 |
the help of | 24 |
to find the | 24 |
the basis of | 24 |
to understand the | 24 |
the infected population | 24 |
in which the | 24 |
beginning of the | 24 |
well as the | 24 |
we use the | 24 |
the peak of | 24 |
the presence of | 24 |
markets during pandemic | 24 |
can be used | 24 |
it has been | 24 |
is globally asymptotically | 24 |
individuals in the | 24 |
markets before pandemic | 24 |
a case study | 23 |
the analysis of | 23 |
fractional optimal control | 23 |
the development of | 23 |
the probability of | 23 |
of the parameters | 23 |
differential equations with | 23 |
prediction of the | 23 |
the seir model | 22 |
cases of covid | 22 |
on the basis | 22 |
of the total | 22 |
compared to the | 22 |
during the pandemic | 22 |
optimal control of | 22 |
sir epidemic model | 22 |
control of covid | 22 |
the state of | 22 |
is given in | 22 |
depends on the | 22 |
a large number | 22 |
of the basic | 22 |
at time t | 22 |
around the world | 22 |
transmission of covid | 22 |
parameters of the | 21 |
vaccine failure rate | 21 |
associated with the | 21 |
the absence of | 21 |
of the fractional | 21 |
next generation matrix | 21 |
of disease transmission | 21 |
in the world | 21 |
public health interventions | 21 |
mathematical theory of | 21 |
depending on the | 21 |
model of covid | 21 |
a modelling study | 21 |
stability of the | 21 |
daily new cases | 21 |
is based on | 21 |
is defined as | 21 |
be seen that | 21 |
of susceptible individuals | 20 |
the mathematical theory | 20 |
at the beginning | 20 |
is used to | 20 |
respiratory syndrome coronavirus | 20 |
the proof of | 20 |
in the system | 20 |
by the following | 20 |
to estimate the | 20 |
to analyze the | 20 |
used in the | 20 |
the next generation | 20 |
rest of the | 20 |
at a rate | 20 |
are shown in | 20 |
different values of | 20 |
of the country | 20 |
period of time | 20 |
that the model | 20 |
assumed to be | 20 |
to minimize the | 19 |
impact of the | 19 |
of this virus | 19 |
the numerical solution | 19 |
in the host | 19 |
on the spread | 19 |
as a result | 19 |
around the globe | 19 |
the incubation period | 19 |
rate of infection | 19 |
in the first | 19 |
number of susceptible | 19 |
we propose a | 19 |
model for covid | 19 |
strict social distancing | 19 |
behavior of the | 19 |
disease free equilibrium | 18 |
given in table | 18 |
the virus in | 18 |
in the early | 18 |
fractional white noise | 18 |
and it is | 18 |
be noted that | 18 |
a function of | 18 |
to be the | 18 |
the fraction of | 18 |
this paper is | 18 |
the cumulative number | 18 |
model has been | 18 |
dynamics of transmission | 18 |
we obtain the | 18 |
are presented in | 18 |
and forecasting the | 18 |
of the transmission | 18 |
to describe the | 18 |
the spreading of | 18 |
to assess the | 18 |
reduction in the | 18 |
results of the | 18 |
the onset of | 18 |
we observe that | 18 |
number of covid | 18 |
in the same | 18 |
end of the | 18 |
a number of | 17 |
in the absence | 17 |
has a unique | 17 |
to determine the | 17 |
described by the | 17 |
in the country | 17 |
free equilibrium is | 17 |
have been proposed | 17 |
theory of epidemics | 17 |
we have that | 17 |
of this study | 17 |
dynamics of novel | 17 |
control of the | 17 |
analysis of a | 17 |
that can be | 17 |
the level of | 17 |
to the mathematical | 17 |
on the number | 17 |
the implementation of | 17 |
the infected individuals | 17 |
asymptotically stable if | 17 |
the context of | 17 |
caputo fractional derivative | 17 |
the world health | 17 |
of the sars | 17 |
the values of | 17 |
mathematical model of | 17 |
of differential equations | 16 |
stock markets before | 16 |
in addition to | 16 |
the early phase | 16 |
the behavior of | 16 |
to account for | 16 |
the amount of | 16 |
each of the | 16 |
to evaluate the | 16 |
we can obtain | 16 |
there are no | 16 |
international spread of | 16 |
of the sir | 16 |
an epidemic model | 16 |
it follows that | 16 |
a mathematical modelling | 16 |
of an epidemic | 16 |
solutions of the | 16 |
an introduction to | 16 |
infection in the | 16 |
impact on the | 16 |
and the number | 16 |
be considered as | 16 |
size of the | 16 |
the nature of | 16 |
in the future | 16 |
be seen in | 16 |
model based on | 16 |
in case of | 16 |
of transmission and | 16 |
to fit the | 16 |
of the most | 16 |
when r b | 16 |
sir model is | 16 |
of epidemic spreading | 16 |
the recovery rate | 16 |
study of the | 15 |
of transmission of | 15 |
the transmission rate | 15 |
peak of the | 15 |
can be described | 15 |
of the world | 15 |
be applied to | 15 |
the appearance of | 15 |
and international spread | 15 |
early dynamics of | 15 |
is less than | 15 |
based on a | 15 |
shown that the | 15 |
the ministry of | 15 |
to solve the | 15 |
is assumed to | 15 |
the real data | 15 |
ncov outbreak originating | 15 |
in the next | 15 |
potential domestic and | 15 |
fractional derivative order | 15 |
strategies for covid | 15 |
originating in wuhan | 15 |
the topic of | 15 |
with fractional derivative | 15 |
for the covid | 15 |
assumed that the | 15 |
at the end | 15 |
to investigate the | 15 |
a backward bifurcation | 15 |
nature of the | 15 |
the high risk | 15 |
the third equation | 15 |
mathematical modeling of | 15 |
in the table | 15 |
completes the proof | 15 |
domestic and international | 15 |
for the spread | 15 |
respect to the | 15 |
which is a | 15 |
in the context | 15 |
the potential domestic | 15 |
the city of | 15 |
cryptocurrency markets before | 15 |
study on the | 15 |
reproduction number of | 15 |
the caputo fractional | 15 |
is one of | 15 |
shown in table | 15 |
of the data | 15 |
existence of the | 15 |
early phase of | 15 |
has been used | 15 |
forecasting the potential | 15 |
the control measures | 15 |
of infected population | 15 |
nowcasting and forecasting | 15 |
outbreak originating in | 15 |
values of the | 15 |
the parameters of | 14 |
as a function | 14 |
are used to | 14 |
is organized as | 14 |
the disease is | 14 |
the disease free | 14 |
confirmed cases of | 14 |
asymptotic stability of | 14 |
the mitigation strategies | 14 |
organized as follows | 14 |
phase of the | 14 |
stock markets during | 14 |
should be noted | 14 |
for the numerical | 14 |
data from the | 14 |
growth of the | 14 |
of asymptomatic infectives | 14 |
the possibility of | 14 |
this study is | 14 |
this completes the | 14 |
global stability of | 14 |
daily growth rate | 14 |
of individuals in | 14 |
for different values | 14 |
epidemic spreading and | 14 |
the results of | 14 |
international stock markets | 14 |
in heilongjiang province | 14 |
fractional order differential | 14 |
effect of the | 14 |
total population of | 14 |
the reproduction number | 14 |
has not been | 14 |
the system is | 14 |
the daily growth | 14 |
of a novel | 14 |
conflict of interest | 14 |
into account the | 14 |
is the most | 14 |
the disease in | 14 |
of the new | 14 |
people in the | 14 |
case of covid | 14 |
is divided into | 14 |
numerical solutions of | 14 |
number of active | 14 |
in the susceptible | 14 |
function of time | 14 |
high risk group | 14 |
two types of | 14 |
the second equation | 14 |
can be written | 14 |
the initial conditions | 14 |
cryptocurrency markets during | 14 |
the disease to | 14 |
effectiveness of the | 14 |
to obtain the | 14 |
it is assumed | 14 |
the whole population | 14 |
is that the | 14 |
of fractional derivative | 14 |
of the quarantine | 14 |
the virus and | 14 |
some of the | 14 |
used in this | 14 |
stable if r | 14 |
modeling the dynamics | 14 |
mathematical modelling study | 14 |
that there are | 14 |
transmission and control | 14 |
can be obtained | 14 |
and recovered cases | 14 |
in the form | 14 |
consider the following | 14 |
the low risk | 13 |
of social distancing | 13 |
a fractional order | 13 |
the reproductive number | 13 |
seen that the | 13 |
asymptotically infected people | 13 |
is applied to | 13 |
to prevent the | 13 |
the stability of | 13 |
to forecast the | 13 |
the data from | 13 |
is the average | 13 |
dynamics and control | 13 |
the united states | 13 |
if r b | 13 |
is assumed that | 13 |
order differential equations | 13 |
which may be | 13 |
see that the | 13 |
asymptomatic infectious individuals | 13 |
we take the | 13 |
mitigation strategies for | 13 |
the jacobian matrix | 13 |
of infectious disease | 13 |
to the model | 13 |
duration of the | 13 |
and so on | 13 |
of fractional differential | 13 |
to get the | 13 |
an infectious disease | 13 |
from the first | 13 |
sir model with | 13 |
of the asymptomatic | 13 |
global sensitivity analysis | 13 |
can be found | 13 |
it is a | 13 |
apen variance in | 13 |
for the fractional | 13 |
the disease and | 13 |
the growth rate | 13 |
by the government | 13 |
variance in cryptocurrency | 13 |
is defined by | 13 |
note that the | 13 |
part of the | 13 |
than that of | 13 |
in the time | 13 |
characteristics of the | 13 |
number of days | 13 |
of the mitigation | 13 |
low risk group | 13 |
the epidemic threshold | 13 |
that it is | 13 |
second wave of | 13 |
may be considered | 13 |
impact of non | 13 |
it is observed | 13 |
incubation period of | 13 |
estimated to be | 13 |
the susceptible individuals | 13 |
less than unity | 13 |
no conflict of | 13 |
which is the | 13 |
of cases and | 13 |
ministry of health | 13 |
has become a | 13 |
we set the | 12 |
due to covid | 12 |
sensitivity analysis of | 12 |
to deal with | 12 |
epidemic in china | 12 |
the most important | 12 |
rate of the | 12 |
case study of | 12 |
figure shows the | 12 |
we can see | 12 |
are given by | 12 |
in the second | 12 |
web of science | 12 |
from the environment | 12 |
and in the | 12 |
of the current | 12 |
applied to the | 12 |
fabrizio fractional derivative | 12 |
a set of | 12 |
of an infectious | 12 |
conditions for the | 12 |
the mutation rate | 12 |
be written as | 12 |
considered as potential | 12 |
analysis of an | 12 |
is presented in | 12 |
slow down the | 12 |
number of novel | 12 |
the increase in | 12 |
it follows from | 12 |
is possible to | 12 |
of infected cases | 12 |
the epidemic dynamics | 12 |
from the disease | 12 |
the social distancing | 12 |
with recurrent mobility | 12 |
apen mean in | 12 |
that the covid | 12 |
obtained from the | 12 |
of the lockdown | 12 |
mean in cryptocurrency | 12 |
the application of | 12 |
the study of | 12 |
the fractional derivative | 12 |
fractional brownian motion | 12 |
the form of | 12 |
novel coronavirus in | 12 |
of being infected | 12 |
description of the | 12 |
and the uk | 12 |
prevention and control | 12 |
rate of detection | 12 |
observed that the | 12 |
time series forecasting | 12 |
would like to | 12 |
epidemic spreading in | 12 |
on the covid | 12 |
inter zone mobilization | 12 |
found that the | 12 |
mathematical models have | 12 |
the duration of | 12 |
the time interval | 12 |
development of the | 12 |
mathematical modelling of | 12 |
transmission dynamics in | 12 |
fractional order sidarthe | 12 |
model and the | 12 |
found to be | 12 |
lle variance in | 12 |
leads to the | 12 |
an outbreak of | 12 |
mean in stock | 12 |
a second wave | 12 |
of backward bifurcation | 12 |
we see that | 12 |
the isolation room | 12 |
the asymptomatic infectious | 12 |
that the number | 12 |
confirmed cases and | 12 |
the local stability | 12 |
move to the | 12 |
model of the | 12 |
proof of theorem | 12 |
to the following | 12 |
host and between | 12 |
cases and deaths | 12 |
to have a | 12 |
in other words | 12 |
the pandemic is | 12 |
it is not | 12 |
influence of the | 12 |
the characteristic equation | 12 |
the importance of | 12 |
it is clear | 12 |
in this way | 12 |
it is possible | 12 |
on the disease | 12 |
in the last | 12 |
application of the | 12 |
in the present | 12 |
second equation of | 12 |
variance in stock | 12 |
peak number of | 12 |
epidemic model for | 12 |
cases in the | 12 |
lle mean in | 12 |
to the best | 12 |
equation of system | 11 |
contribution to the | 11 |
the function f | 11 |
the eigenvalues of | 11 |
on the one | 11 |
in this model | 11 |
the sensitivity analysis | 11 |
across the globe | 11 |
in the field | 11 |
the lancet infectious | 11 |
disease information diffusion | 11 |
the course of | 11 |
been proposed to | 11 |
and then the | 11 |
proposed model is | 11 |
social distancing and | 11 |
confirmed cases in | 11 |
we present a | 11 |
recurrent mobility pattern | 11 |
distribution of the | 11 |
coronavirus disease in | 11 |
the time of | 11 |
the average number | 11 |
novel coronavirus outbreak | 11 |
less than one | 11 |
the time series | 11 |
li et al | 11 |
in a population | 11 |
of the time | 11 |
best of our | 11 |
in different countries | 11 |
data for the | 11 |
table and table | 11 |
a total of | 11 |
in the literature | 11 |
contact with the | 11 |
is carried out | 11 |
this can be | 11 |
time evolution of | 11 |
optimal control problems | 11 |
with the following | 11 |
of the season | 11 |
our model is | 11 |
stochastic differential equations | 11 |
the epidemic and | 11 |
state of the | 11 |
average number of | 11 |
is equal to | 11 |
control the spread | 11 |
the infection rate | 11 |
number of daily | 11 |
outbreak of covid | 11 |
paper is organized | 11 |
this paper we | 11 |
reported in the | 11 |
are based on | 11 |
reproduction number is | 11 |
is the rate | 11 |
so that the | 11 |
the diffusion of | 11 |
the daily new | 11 |
the paper is | 11 |
may not be | 11 |
classic sir model | 11 |
the solutions of | 11 |
for simulating the | 11 |
the data of | 11 |
of our knowledge | 11 |
taken into account | 11 |
is estimated to | 11 |
third equation of | 11 |
lancet infectious diseases | 11 |
and stock markets | 11 |
compared with the | 11 |
in the class | 11 |
the mean value | 11 |
caused by the | 11 |
changes in the | 11 |
to explore the | 11 |
the best of | 11 |
risk of the | 11 |
the same as | 11 |
we present the | 11 |
the recorded data | 11 |
dynamics of hiv | 11 |
the epidemic in | 11 |
can also be | 11 |
the classic sir | 11 |
a time series | 11 |
the time evolution | 11 |
the model to | 11 |
the disease information | 11 |
a model based | 11 |
it is also | 11 |
since the first | 11 |
p r a | 11 |
the following theorem | 11 |
the model and | 11 |
results show that | 11 |
the infectious disease | 11 |
states of india | 11 |
mean time between | 11 |
which means that | 11 |
in the usa | 11 |
using machine learning | 11 |
control measures v | 11 |
the set of | 11 |
the mean of | 11 |
this is not | 11 |
coupled slow system | 11 |
number of people | 10 |
structure of the | 10 |
was used to | 10 |
of the first | 10 |
the virus is | 10 |
been applied to | 10 |
and predict the | 10 |
time series data | 10 |
predict the covid | 10 |
q s q | 10 |
a new fractional | 10 |
cryptocurrency and stock | 10 |
we know that | 10 |
represents the number | 10 |
outbreak of the | 10 |
the population of | 10 |
will not be | 10 |
in this context | 10 |
infectious diseases of | 10 |
we study the | 10 |
such that the | 10 |
social distancing is | 10 |
during this period | 10 |
of the parameter | 10 |
model on the | 10 |
countries around the | 10 |
the parameter values | 10 |
data of the | 10 |
can be observed | 10 |
an increase in | 10 |
the state variables | 10 |
and prediction of | 10 |
the following result | 10 |
with fractional order | 10 |
financial interests personal | 10 |
the definition of | 10 |
endemic equilibrium point | 10 |
onset of symptoms | 10 |
without singular kernel | 10 |
that the disease | 10 |
of fractional calculus | 10 |
interests personal relationships | 10 |
model for simulating | 10 |
of the risk | 10 |
r in the | 10 |
sarii q s | 10 |
the pairwise approach | 10 |
is clear that | 10 |
the growth of | 10 |
means that the | 10 |
was carried out | 10 |
the following financial | 10 |
definition of fractional | 10 |
in the covid | 10 |
of pandemic covid | 10 |
spreading of the | 10 |
can be applied | 10 |
taking into account | 10 |
isolated slow system | 10 |
myopic update rule | 10 |
for the next | 10 |
asymptomatic infected individuals | 10 |
personal relationships which | 10 |
have been applied | 10 |
can be easily | 10 |
is related to | 10 |
following financial interests | 10 |
a result of | 10 |
is described by | 10 |
declare the following | 10 |
outbreak in china | 10 |
it is important | 10 |
we confirm that | 10 |
spreading in china | 10 |
this leads to | 10 |
the one hand | 10 |
this section we | 10 |
model based study | 10 |
relative cost of | 10 |
of health of | 10 |
contributions to the | 10 |
results in a | 10 |
that the virus | 10 |
analysis and forecast | 10 |
the population is | 10 |
stability analysis of | 10 |
of public health | 10 |
time of the | 10 |
is expected to | 10 |
relationships which may | 10 |
take into account | 10 |
is considered as | 10 |
transmission risk of | 10 |
follows from the | 10 |
and forecast of | 10 |
the infected people | 10 |
the existence and | 10 |
each of these | 10 |
health of morocco | 10 |
we found that | 10 |
there will be | 10 |
number of the | 10 |
in a given | 10 |
w is locally | 10 |
number of swabs | 10 |
fractional order model | 10 |
forecasts of the | 10 |
to characterize the | 10 |
all over the | 10 |
the epidemic is | 10 |
mathematical analysis of | 10 |
of infected players | 10 |
the dynamics and | 10 |
in the state | 10 |
spread of infectious | 10 |
and of the | 10 |
we want to | 10 |
operational matrix of | 10 |
is able to | 10 |
of the three | 10 |
in the current | 10 |
hiv aids epidemic | 10 |
the propagation of | 10 |
assessment of the | 10 |
for public health | 10 |
models of disease | 10 |
equations of the | 10 |
the published data | 10 |
leads to a | 10 |
during the covid | 10 |
the disease transmission | 10 |
corresponds to the | 10 |
indicates that the | 10 |
is important to | 10 |
model to the | 10 |
at the same | 10 |
new infection cases | 10 |
tests per day | 9 |
dynamics in wuhan | 9 |
to that of | 9 |
the transmission risk | 9 |
the probability that | 9 |
the characteristics of | 9 |
that number of | 9 |
infected and recovered | 9 |
depend on the | 9 |
trend of covid | 9 |
female sex workers | 9 |
the same way | 9 |
number of recovered | 9 |
during the outbreak | 9 |
princess cruise ship | 9 |
risk assessment of | 9 |
the mild cases | 9 |
sei i r | 9 |
authors declare the | 9 |
this is the | 9 |
of control strategies | 9 |
for the same | 9 |
as potential competing | 9 |
the same time | 9 |
been used to | 9 |
optimal control is | 9 |
basic reproductive number | 9 |
outbreak in wuhan | 9 |
is the time | 9 |
the mathematics of | 9 |
a long time | 9 |
the diamond princess | 9 |
equilibrium w is | 9 |
to the disease | 9 |
the trend of | 9 |
is a constant | 9 |
of the infectious | 9 |
when compared to | 9 |
by the end | 9 |
integrated moving average | 9 |
early detection of | 9 |
autoregressive integrated moving | 9 |
we consider a | 9 |
we show the | 9 |
cost of vaccination | 9 |
is not the | 9 |
shown in the | 9 |
and information diffusion | 9 |
the latent period | 9 |
over the world | 9 |
rate at which | 9 |
the spectral radius | 9 |
local and global | 9 |
there exists a | 9 |
has been considered | 9 |
the sensitivity of | 9 |
and the initial | 9 |
we have considered | 9 |
we have used | 9 |
of virus in | 9 |
number of individuals | 9 |
number of tests | 9 |
the length of | 9 |
assessment of novel | 9 |
for the disease | 9 |
is the same | 9 |
the infected density | 9 |
is depicted in | 9 |
the mean time | 9 |
study is to | 9 |
controlling the spread | 9 |
of social media | 9 |
for the transmission | 9 |
for each country | 9 |
of the state | 9 |
given in fig | 9 |
number r b | 9 |
existence and uniqueness | 9 |
to the number | 9 |
we do not | 9 |
natural death rate | 9 |
the infected person | 9 |
model with a | 9 |
the epidemic topic | 9 |
see for example | 9 |
has been shown | 9 |
cases and the | 9 |
the infection is | 9 |
the data and | 9 |
seir model with | 9 |
the sum of | 9 |
forecast of covid | 9 |
as soon as | 9 |
of the epidemics | 9 |
optimal control strategies | 9 |
the control of | 9 |
an infected person | 9 |
middle east respiratory | 9 |
and uniqueness of | 9 |
analysis in the | 9 |
to identify the | 9 |
the prediction of | 9 |
is said to | 9 |
case of the | 9 |
is easy to | 9 |
local stability of | 9 |
reduce the number | 9 |
more than one | 9 |
obtain the following | 9 |
ncov and its | 9 |
due to a | 9 |
has been proposed | 9 |
with novel coronavirus | 9 |
of the paper | 9 |
likely due to | 9 |
needs to be | 9 |
point of view | 9 |
potential competing interests | 9 |
by solving the | 9 |
attention to the | 9 |
disease in the | 9 |
corona virus disease | 9 |
the simulation results | 9 |
the initial condition | 9 |
with a case | 9 |
at any time | 9 |
matrix of fractional | 9 |
implication for public | 9 |
existence of a | 9 |
is necessary to | 9 |
of infection is | 9 |
convolutional neural network | 9 |
to tackle the | 9 |
can be defined | 9 |
we investigate the | 9 |
the first equation | 9 |
for the model | 9 |
many of the | 9 |
in controlling the | 9 |
data becomes available | 9 |
the arima model | 9 |
been carried out | 9 |
for the infected | 9 |
the class of | 9 |
presented in section | 9 |
its implication for | 9 |
parameter values are | 9 |
r a ft | 9 |
the basic reproductive | 9 |
the disease spread | 9 |
at the point | 9 |
the final size | 9 |
the average time | 9 |
ml and ai | 9 |
it is worth | 9 |
with saturated incidence | 9 |
mathematics of infectious | 9 |
model with the | 9 |
given in the | 9 |
transmission dynamics with | 9 |
this shows that | 9 |
is observed that | 9 |
and optimal control | 9 |
that of the | 9 |
mobility and contact | 9 |
and its implication | 9 |
the following form | 9 |
and disease information | 9 |
values of fractional | 9 |
networked population with | 9 |
maximum number of | 9 |
of the optimal | 9 |
for the first | 9 |
novel corona virus | 9 |
expected number of | 9 |
on epidemic spreading | 9 |
with each other | 9 |
at the rate | 9 |
pharmaceutical interventions on | 9 |
to show that | 9 |
spreading and information | 9 |
for the number | 9 |
the purpose of | 9 |
we note that | 9 |
prediction of covid | 9 |
infected with novel | 9 |
and the existence | 9 |
fact that the | 9 |
of the exposed | 9 |
covidmaroc the ministry | 9 |
free equilibrium point | 9 |
new fractional derivative | 9 |
it is shown | 9 |
s q model | 9 |
of the control | 9 |
detected infected population | 9 |
start of the | 9 |
with a large | 9 |
observe that the | 9 |
of confirmed covid | 9 |
east respiratory syndrome | 9 |
insights into the | 9 |
from january to | 9 |
amount of virus | 9 |
higher than the | 8 |
the lockdown rate | 8 |
mathematical model to | 8 |
virus infection in | 8 |
the model can | 8 |
it is easy | 8 |
forecasting of the | 8 |
in the community | 8 |
it is necessary | 8 |
and forecasting of | 8 |
understanding of the | 8 |
of our model | 8 |
clinical characteristics of | 8 |
is greater than | 8 |
study the dynamics | 8 |
for more details | 8 |
at the dfe | 8 |
the contribution of | 8 |
performance of the | 8 |
the world and | 8 |
infectious diseases in | 8 |
similar to the | 8 |
have been infected | 8 |
for all t | 8 |
because of the | 8 |
kermack and mckendrick | 8 |
first of all | 8 |
the proposed fractional | 8 |
model to study | 8 |
of control measures | 8 |
method for the | 8 |
we analyze the | 8 |
that the epidemic | 8 |
are reported in | 8 |
to mitigate the | 8 |
the field of | 8 |
model parameters are | 8 |
the social distance | 8 |
condition for the | 8 |
was used for | 8 |
by means of | 8 |
the inflection point | 8 |
the size of | 8 |
sir model can | 8 |
estimate of the | 8 |
it is found | 8 |
the fractional optimal | 8 |
in the initial | 8 |
this implies that | 8 |
which implies that | 8 |
allows us to | 8 |
d is the | 8 |
this means that | 8 |
first equation of | 8 |
system of differential | 8 |
by the same | 8 |
to the data | 8 |
time forecasts and | 8 |
of hiv aids | 8 |
diamond princess cruise | 8 |
to show the | 8 |
we conclude that | 8 |
infected population and | 8 |
by the time | 8 |
the global stability | 8 |
for compartmental models | 8 |
and social distancing | 8 |
time a new | 8 |
detected and quarantined | 8 |
is the first | 8 |
based transmissibility of | 8 |
of vaccination c | 8 |
the infected and | 8 |
epidemic models with | 8 |
a unique solution | 8 |
this virus is | 8 |
the following system | 8 |
day of the | 8 |
be found in | 8 |
time markov chain | 8 |
infected cases and | 8 |
the structure of | 8 |
a recovered person | 8 |
asymptotically stable when | 8 |
to the covid | 8 |
analysis of covid | 8 |
of new infection | 8 |
models for the | 8 |
determined by the | 8 |
of the dynamics | 8 |
the performance of | 8 |
infection from the | 8 |
from the third | 8 |
to prove the | 8 |
new infected cases | 8 |
compartmental models of | 8 |
describe the dynamics | 8 |
effective reproduction number | 8 |
the estimated parameters | 8 |
signifies the rate | 8 |
the new fractional | 8 |
can be explained | 8 |
mutation rate is | 8 |
of asymptomatic infected | 8 |
and analysis of | 8 |
early transmission dynamics | 8 |
in more detail | 8 |
health care facilities | 8 |
rate due to | 8 |
the peak number | 8 |
the vaccine failure | 8 |
the nucleotide mutation | 8 |
against the covid | 8 |
to the fact | 8 |
a and b | 8 |
respect to time | 8 |
function of the | 8 |
initial conditions are | 8 |
endemic equilibria for | 8 |
equation in the | 8 |
the contact rate | 8 |
in such a | 8 |
prediction and control | 8 |
the pandemic period | 8 |
social distancing measures | 8 |
seen in fig | 8 |
of the network | 8 |
equilibria for compartmental | 8 |
reproduction numbers and | 8 |
the results are | 8 |
of active cases | 8 |
the coupled slow | 8 |
in view of | 8 |
of new infections | 8 |
considered to be | 8 |
at the time | 8 |
transmissibility of a | 8 |
of patients infected | 8 |
in the dynamics | 8 |
we discuss the | 8 |
to calculate the | 8 |
time between infections | 8 |
population due to | 8 |
each time step | 8 |
the numerical simulation | 8 |
soon as possible | 8 |
have been used | 8 |
that the total | 8 |
of all the | 8 |
of the next | 8 |
which leads to | 8 |
deep convolutional neural | 8 |
a deep learning | 8 |
in each of | 8 |
of the cumulative | 8 |
forecasts and risk | 8 |
spread of disease | 8 |
the turning point | 8 |
supplementary material fig | 8 |
order sidarthe model | 8 |
global asymptotic stability | 8 |
the containment rate | 8 |
a susceptible individual | 8 |
by applying the | 8 |
the model was | 8 |
for fractional order | 8 |
with different fractional | 8 |
diseases of humans | 8 |
corresponding to the | 8 |
depicted in figure | 8 |
have not been | 8 |
of days between | 8 |
the control strategies | 8 |
for the sir | 8 |
and dynamics of | 8 |
the system of | 8 |
have been reported | 8 |
is close to | 8 |
in the figure | 8 |
of fractional differentiation | 8 |
the infection and | 8 |
equilibrium is globally | 8 |
approach for the | 8 |
mean square error | 8 |
numerical simulation of | 8 |
mean value function | 8 |
the disease burden | 8 |
of the hiv | 8 |
the proposed hybrid | 8 |
model to predict | 8 |
we can observe | 8 |
together with the | 8 |
with real data | 8 |
the above equation | 8 |
t is the | 8 |
subject to the | 8 |
rate of recovery | 8 |
has also been | 8 |
the start of | 8 |
has been observed | 8 |
be defined as | 8 |
a machine learning | 8 |
on the data | 8 |
wave of infection | 8 |
due to its | 8 |
it could be | 8 |
different types of | 8 |
across the world | 8 |
in this article | 8 |
the equilibrium points | 8 |
and can be | 8 |
a contribution to | 8 |
will have a | 8 |
a numerical scheme | 8 |
in the appendix | 8 |
at least one | 8 |
the brownian motion | 8 |
dynamics of a | 8 |
be able to | 8 |
which in turn | 8 |
control of a | 8 |
individuals and the | 8 |
driven adaptive process | 8 |
the proposed method | 8 |
coronavirus in wuhan | 8 |
the pandemic in | 8 |
isolation of cases | 8 |
the control u | 8 |
spreading of pandemic | 8 |
across the country | 8 |
preliminary estimation of | 8 |
an infected individual | 8 |
a class of | 8 |
infected population due | 8 |
modeling of the | 8 |
infected individuals and | 8 |
population with recurrent | 8 |
the numerical results | 8 |
at which the | 8 |
equilibrium point is | 8 |
necessary conditions for | 8 |
a lot of | 8 |
sir model and | 8 |
is the number | 8 |
number of secondary | 8 |
presented in the | 8 |
the sirsi model | 7 |
concluded that the | 7 |
it difficult to | 7 |
the present study | 7 |
risk of transmission | 7 |
and move to | 7 |
and found that | 7 |
for the seir | 7 |
trend of the | 7 |
the epidemic prevalence | 7 |
of susceptible people | 7 |
is independent of | 7 |
fractional order derivative | 7 |
we give a | 7 |
following system of | 7 |
the ongoing covid | 7 |
the outbreak is | 7 |
necessary optimality conditions | 7 |
given in section | 7 |
as compared to | 7 |
before the pandemic | 7 |
the recovered individuals | 7 |
to the reported | 7 |
the epidemic will | 7 |
of ordinary differential | 7 |
be described by | 7 |
of the models | 7 |
with pneumonia in | 7 |
supported by the | 7 |
all individuals are | 7 |
case projection using | 7 |
in supplementary material | 7 |
is to say | 7 |
the most effective | 7 |
of the theorem | 7 |
has been developed | 7 |
sir model in | 7 |
and during the | 7 |
and contact tracing | 7 |
affected by the | 7 |
surges in the | 7 |
and the control | 7 |
and control the | 7 |
the epidemic spread | 7 |
science foundation of | 7 |
that when the | 7 |
the final state | 7 |
that is to | 7 |
is the total | 7 |
with optimal control | 7 |
disease caused by | 7 |
at each time | 7 |
in this manuscript | 7 |
the model in | 7 |
the success of | 7 |
the asymptomatic class | 7 |
the process of | 7 |
infected individual is | 7 |
of this epidemic | 7 |
the exposed individuals | 7 |
the other countries | 7 |
as a pandemic | 7 |
infections generated by | 7 |
agreement with the | 7 |
if it is | 7 |
on the epidemic | 7 |
order model for | 7 |
the state and | 7 |
in the hospital | 7 |
of the following | 7 |
the relative cost | 7 |
the aim of | 7 |
patients with pneumonia | 7 |
we have seen | 7 |
number of asymptomatic | 7 |
deal with the | 7 |
person to be | 7 |
fractional derivative without | 7 |
the new coronavirus | 7 |
are listed in | 7 |
exposed to the | 7 |
of the function | 7 |
we define the | 7 |
is no conflict | 7 |
the range of | 7 |
that our model | 7 |
applied over the | 7 |
we compute the | 7 |
accumulated number of | 7 |
case of a | 7 |
to be a | 7 |
r epidemic model | 7 |
been shown in | 7 |
a given time | 7 |
the maximum number | 7 |
there has been | 7 |
of hiv infection | 7 |
outbreaks by isolation | 7 |
the interplay between | 7 |
caputo fractional derivatives | 7 |
nucleotide mutation rate | 7 |
definition of the | 7 |
presented in figure | 7 |
differential equations and | 7 |
patients infected with | 7 |
science and engineering | 7 |
about of the | 7 |
the assumption that | 7 |
of the solution | 7 |
that the spread | 7 |
to the new | 7 |
a total population | 7 |
spread the disease | 7 |
the proposed approach | 7 |
in china and | 7 |
we derive the | 7 |
is determined by | 7 |
of the above | 7 |
an updated estimation | 7 |
and the epidemic | 7 |
natural science foundation | 7 |
appearance of symptoms | 7 |
is to be | 7 |
we need to | 7 |
as we can | 7 |
the infected individual | 7 |
in the presence | 7 |
machine learning approach | 7 |
of the impact | 7 |
the variance of | 7 |
cases of the | 7 |
feasibility of controlling | 7 |
of time series | 7 |
measures such as | 7 |
cases and contacts | 7 |
that the mean | 7 |
model with saturated | 7 |
epidemic in india | 7 |
in recent years | 7 |
in the network | 7 |
the formulation of | 7 |
onset of the | 7 |
can be reduced | 7 |
the lockdown period | 7 |
in a similar | 7 |
stochastic epidemic model | 7 |
to capture the | 7 |
within the population | 7 |
individuals who have | 7 |
in this regard | 7 |
of the mild | 7 |
and machine learning | 7 |
models can be | 7 |
we can write | 7 |
spread in the | 7 |
city of wuhan | 7 |
a variety of | 7 |
equal to zero | 7 |
the observed daily | 7 |
unique solution of | 7 |
of the daily | 7 |
two positive equilibria | 7 |
detection of covid | 7 |
characteristic equation of | 7 |
the system has | 7 |
of these models | 7 |
into the environment | 7 |
is obvious that | 7 |
governed by the | 7 |
cases in china | 7 |
the necessary conditions | 7 |
have also been | 7 |
the estimated value | 7 |
infected with covid | 7 |
was supported by | 7 |
we apply the | 7 |
let us consider | 7 |
prediction for the | 7 |
where is the | 7 |
the infectious rate | 7 |
course of the | 7 |
control strategies to | 7 |
model that can | 7 |
the increase of | 7 |
in the sir | 7 |
fractional derivative is | 7 |
mutation rate of | 7 |
the environment by | 7 |
unique endemic equilibrium | 7 |
there are many | 7 |
confirmed infected cases | 7 |
the control is | 7 |
has a disease | 7 |
has been carried | 7 |
i and j | 7 |
city of jakarta | 7 |
lower than the | 7 |
the need to | 7 |
it is obvious | 7 |
as in the | 7 |
and more than | 7 |
reproductive number of | 7 |
the first case | 7 |
of daily new | 7 |
the best fit | 7 |
of a large | 7 |
is an important | 7 |
the first days | 7 |
in the sense | 7 |
stereographic projection coordinates | 7 |
a period of | 7 |
state of texas | 7 |
epidemic in wuhan | 7 |
given in figure | 7 |
can observe that | 7 |
and inter zone | 7 |
of vaccinated individuals | 7 |
and the state | 7 |
considered as a | 7 |
the rate at | 7 |
basis of the | 7 |
clinical features of | 7 |
are depicted in | 7 |
cumulative confirmed cases | 7 |
i r epidemic | 7 |
decrease in the | 7 |
approach based on | 7 |
in the previous | 7 |
is lower than | 7 |
all of the | 7 |
case fatality rate | 7 |
asymptotically stable whenever | 7 |
seir epidemic model | 7 |
on the topic | 7 |
data up to | 7 |
infected individuals from | 7 |
novel coronavirus from | 7 |
a unique positive | 7 |
number of patients | 7 |
then the system | 7 |
the real world | 7 |
lead to a | 7 |
transition rate from | 7 |
it is expected | 7 |
of stability in | 7 |
before and during | 7 |
view of the | 7 |
and implementation of | 7 |
to become cure | 7 |
infected people increases | 7 |
for the country | 7 |
used for the | 7 |
that the peak | 7 |
is higher than | 7 |
intra and inter | 7 |
among the population | 7 |
implementation of population | 7 |
decay of the | 7 |
based study on | 7 |
deep transfer learning | 7 |
government of india | 7 |
partial rank correlation | 7 |
fractional differential equation | 7 |
to the spread | 7 |
spread of coronavirus | 7 |
the first day | 7 |
epidemic and implementation | 7 |
then we have | 7 |
sensitivity analysis is | 7 |
the mortality rate | 7 |
parts of the | 7 |
brownian motion on | 7 |
the following equation | 7 |
the infection rates | 7 |
and control measures | 7 |
for a long | 7 |
presence of a | 7 |
derivative without singular | 7 |
host dynamics in | 7 |
system of ordinary | 7 |
used to model | 7 |
r b and | 7 |
the model with | 7 |
driven analysis in | 7 |
from the model | 7 |
the efficiency of | 7 |
of this pandemic | 7 |
can see that | 7 |
for the rest | 7 |
fx t dg | 7 |
conflicts of interest | 7 |
and effectiveness of | 7 |
estimated value of | 7 |
an overview of | 7 |
by isolation of | 7 |
the observed data | 7 |
in the city | 7 |
updated estimation of | 7 |
spread of hiv | 7 |
the total cumulative | 7 |
the sign of | 7 |
time series analysis | 7 |
smaller than the | 7 |
epidemiology of infectious | 7 |
proof of the | 7 |
total population n | 7 |
of cd t | 7 |
estimated from the | 7 |
the distribution of | 7 |
is associated with | 7 |
as it can | 7 |
to do this | 7 |
for the optimal | 7 |
as far as | 7 |
with a total | 7 |
and using the | 7 |
using lstm networks | 7 |
population in the | 7 |
of asymptomatic patients | 7 |
illustrated in fig | 7 |
a reduction in | 7 |
is denoted by | 7 |
values for the | 7 |
sensitive to the | 7 |
of the work | 7 |
w is unstable | 7 |
free and endemic | 7 |
the effective reproduction | 7 |
the delay between | 7 |
the unique solution | 7 |
reproduction number and | 7 |
the case fatality | 7 |
global financial crisis | 7 |
has been a | 7 |
simulating the phase | 7 |
n is the | 7 |
which makes it | 7 |
features of patients | 7 |
parameters and the | 7 |
and risk assessment | 7 |
confirm that the | 7 |
of the isolation | 7 |
predictions of the | 7 |
the model from | 7 |
the present paper | 7 |
of a stochastic | 7 |
who do not | 7 |
be described as | 7 |
given time t | 7 |
the population and | 7 |
between individuals and | 7 |
novel coronavirus disease | 7 |
the initial value | 7 |
in our model | 7 |
between infection and | 6 |
province in china | 6 |
it does not | 6 |
of caputo fractional | 6 |
the epidemic of | 6 |
that the data | 6 |
the coronavirus outbreak | 6 |
a major role | 6 |
at the disease | 6 |
they can be | 6 |
of both the | 6 |
to the system | 6 |
existence of equilibria | 6 |
epidemic in italy | 6 |
in mainland china | 6 |
the positive equilibrium | 6 |
from the data | 6 |
the normalized forward | 6 |
no more than | 6 |
infected individuals in | 6 |
model using the | 6 |
a stochastic epidemic | 6 |
dynamics of epidemic | 6 |
pandemic in the | 6 |
cases for the | 6 |
the severe acute | 6 |
in networked population | 6 |
zhang et al | 6 |
country or region | 6 |
to stop the | 6 |
stable when r | 6 |
interventions on the | 6 |
but it is | 6 |
given by where | 6 |
the following results | 6 |
with a new | 6 |
to the asymptomatic | 6 |
fractional order derivatives | 6 |
new cases is | 6 |
more than countries | 6 |
incubation period and | 6 |
to compare the | 6 |
what are the | 6 |
control the disease | 6 |
that have been | 6 |
the government to | 6 |
equilibrium of system | 6 |
that we have | 6 |
and forecast the | 6 |
adjusted estimation of | 6 |
always has a | 6 |
days since the | 6 |
baleanu fractional derivative | 6 |
support vector regression | 6 |
model to analyze | 6 |
as one of | 6 |
similar to that | 6 |
the numerical solutions | 6 |
a report of | 6 |
in the transmission | 6 |
a boundary arc | 6 |
model with fractional | 6 |
find out the | 6 |
different fractional derivative | 6 |
and is the | 6 |
is considered to | 6 |
consistent with the | 6 |
that the system | 6 |
known as the | 6 |
from the above | 6 |
infection of the | 6 |
the novel covid | 6 |
a constant rate | 6 |
is smaller than | 6 |
to improve the | 6 |
the strength of | 6 |
is plotted in | 6 |
for infectious diseases | 6 |
more than of | 6 |
due to spreading | 6 |
period of the | 6 |
the following fractional | 6 |
deep learning model | 6 |
is governed by | 6 |
will be used | 6 |
carried out to | 6 |
of the pathogen | 6 |
as of april | 6 |
the incubation time | 6 |
to real data | 6 |
all the eigenvalues | 6 |
driven receding horizon | 6 |
saturated incidence rate | 6 |
for the time | 6 |
the expectation of | 6 |
the second wave | 6 |
in modeling the | 6 |
and that the | 6 |
the objective functional | 6 |
a stochastic model | 6 |
this indicates that | 6 |
to contain the | 6 |
we observed that | 6 |
results in the | 6 |
and we have | 6 |
the myopic update | 6 |
of this disease | 6 |
it is evident | 6 |
model of hiv | 6 |
the following two | 6 |
the transition from | 6 |
to derive the | 6 |
parameter values and | 6 |
negative real parts | 6 |
the results found | 6 |
change of the | 6 |
is similar to | 6 |
model in the | 6 |
of chest ct | 6 |
in india is | 6 |
the raw data | 6 |
is known that | 6 |
the epidemic peaks | 6 |
been observed that | 6 |
the higher the | 6 |
the standard sir | 6 |
with applications to | 6 |
to spreading of | 6 |
of the main | 6 |
for the other | 6 |
the actual data | 6 |
free equilibrium w | 6 |
peaks of the | 6 |
of continuously evolving | 6 |
of a fractional | 6 |
a numerical solution | 6 |
the previous section | 6 |
is obtained as | 6 |
noted that the | 6 |
and r score | 6 |
isolation and quarantine | 6 |
the center manifold | 6 |
and deep learning | 6 |
symptomatic infectious individuals | 6 |
to the basic | 6 |
transmission dynamics and | 6 |
due to their | 6 |
and reported in | 6 |
to be used | 6 |
role in the | 6 |
we can say | 6 |
can be estimated | 6 |
the reduction of | 6 |
of hubei province | 6 |
has been performed | 6 |
is found that | 6 |
the overall number | 6 |
to the other | 6 |
the yule process | 6 |
spread of this | 6 |
a global pandemic | 6 |
topic discussion rate | 6 |
the exposed class | 6 |
the memory effect | 6 |
sk shahid nadim | 6 |
and global stability | 6 |
proposed fractional order | 6 |
the accumulated number | 6 |
to find out | 6 |
disease model with | 6 |
optimal control analysis | 6 |
the positivity and | 6 |
dynamics with a | 6 |
partial differential equations | 6 |
daily new covid | 6 |
implies that the | 6 |
data set is | 6 |
and application to | 6 |
on social media | 6 |
during pandemic apen | 6 |
the time window | 6 |
to be more | 6 |
and the effects | 6 |
this is a | 6 |
is in the | 6 |
model is the | 6 |
the information diffusion | 6 |
account for the | 6 |
caused by a | 6 |
a generalization of | 6 |
to be in | 6 |
national natural science | 6 |
and on the | 6 |
a ft t | 6 |
our proposed model | 6 |
before pandemic apen | 6 |
takes the form | 6 |
we give the | 6 |
from patients with | 6 |
the disease with | 6 |
symptoms of the | 6 |
infected population i | 6 |
final size and | 6 |
study of a | 6 |
for predicting the | 6 |
in this research | 6 |
the new data | 6 |
defined by the | 6 |
number of coronavirus | 6 |
on the time | 6 |
can say that | 6 |
the model predictions | 6 |
as seen in | 6 |
can be controlled | 6 |
the pandemic and | 6 |
we can get | 6 |
the acquired immunity | 6 |
the first time | 6 |
the relationship between | 6 |
of the class | 6 |
machine learning techniques | 6 |
an optimal control | 6 |
the asymptomatic duration | 6 |
a comparative study | 6 |
during a match | 6 |
boundedness of solutions | 6 |
the immune system | 6 |
the degree of | 6 |
fourth equation of | 6 |
projection using reduction | 6 |
a sir model | 6 |
stability of disease | 6 |
induced death rate | 6 |
addition to the | 6 |
to validate the | 6 |
to be zero | 6 |
the advantage of | 6 |
at least of | 6 |
have been taken | 6 |
deep learning techniques | 6 |
days from the | 6 |
the corresponding author | 6 |
point t n | 6 |
with the same | 6 |
of this work | 6 |
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pandemic in pakistan | 6 |
study on covid | 6 |
characteristics of coronavirus | 6 |
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dynamics of infectious | 6 |
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flattening the curve | 6 |
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deaths and recovered | 6 |
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the covid epidemic | 6 |
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we show that | 6 |
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normalized forward sensitivity | 6 |
disease transmission model | 6 |
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any time t | 6 |
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fractional order sei | 6 |
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deaths in the | 6 |
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infectious disease dynamics | 6 |
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pandemic lle variance | 6 |
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the confirmed cases | 6 |
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a new approach | 6 |
pure birth process | 6 |
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individual reaction and | 6 |
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model from scratch | 6 |
publicly available data | 6 |
when r w | 6 |
diagnosis of covid | 6 |
first day of | 6 |
endemic equilibrium is | 6 |
the epidemics trend | 6 |
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disease transmission rate | 6 |
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the null hypothesis | 6 |
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individuals can be | 6 |
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causal variables that | 6 |
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interventions in italy | 6 |
people increases with | 6 |
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birth and death | 6 |
properties of the | 6 |
forecasting of covid | 6 |
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the laplace transform | 6 |
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the disease can | 6 |
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behaviour of the | 6 |
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individuals who are | 6 |
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susceptible population s | 6 |
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overall number of | 6 |
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the magnitude of | 6 |
the severity of | 6 |
study of wuhan | 6 |
approximate solution of | 6 |
set is received | 6 |
and recovery rate | 6 |
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we calculate the | 6 |
epidemics trend of | 6 |
wide interventions in | 6 |
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network model for | 6 |
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the point t | 6 |
can be adjusted | 6 |
reaction and governmental | 6 |
weeks after the | 6 |
local asymptotic stability | 6 |
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severity of the | 6 |
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mortality rate of | 6 |
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showed that the | 6 |
integrating the second | 6 |
the early stage | 6 |
induced optimization problem | 6 |
the proportion of | 6 |
the infected class | 6 |
the current pandemic | 6 |
the estimated parameter | 6 |
to be determined | 6 |
various operating procedures | 6 |
available data from | 6 |
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purpose of this | 5 |
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consequence of the | 5 |
model to explore | 5 |
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asymptomatic infectious to | 5 |
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the idea of | 5 |
the actual number | 5 |
the fractional calculus | 5 |
while the other | 5 |
seir and ai | 5 |
it possible to | 5 |
global dynamics of | 5 |
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fractional order epidemic | 5 |
a fractional optimal | 5 |
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prompt isolation of | 5 |
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expression of the | 5 |
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short period of | 5 |
infection of cd | 5 |
segmented poisson model | 5 |
persists in the | 5 |
the problem of | 5 |
we get the | 5 |
the outbreaks of | 5 |
liouville fractional derivative | 5 |
beltrami operator of | 5 |
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responses are reported | 5 |
backward bifurcation phenomenon | 5 |
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us consider the | 5 |
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attack rate of | 5 |
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strategies to reduce | 5 |
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complexity of the | 5 |
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the model shows | 5 |
output of the | 5 |
masks in public | 5 |
study the transmission | 5 |
network in the | 5 |
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machine learning and | 5 |
endemic equilibrium w | 5 |
of the solutions | 5 |
of confirmed infected | 5 |
of isolated individuals | 5 |
population has been | 5 |
on the mathematical | 5 |
transmission of this | 5 |
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the virus has | 5 |
dynamic model of | 5 |
indicating that the | 5 |
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transition density function | 5 |
the public health | 5 |
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the per capita | 5 |
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and when r | 5 |
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differential equations in | 5 |
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a new study | 5 |
context of covid | 5 |
model to forecast | 5 |
to prove that | 5 |
distancing rule is | 5 |
coronavirus outbreak in | 5 |
the most influential | 5 |
the greatest potential | 5 |
results are shown | 5 |
higher compared to | 5 |
the epidemic starts | 5 |
using deep learning | 5 |
the initial phase | 5 |
techniques have been | 5 |
countries and territories | 5 |
of parameters in | 5 |
should be done | 5 |
longer period of | 5 |
sum of the | 5 |
overview of the | 5 |
free equilibrium e | 5 |
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this strategy is | 5 |
model is described | 5 |
day by day | 5 |
models in the | 5 |
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fractional differentiation on | 5 |
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pathogen from the | 5 |
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set to be | 5 |
effective way of | 5 |
the interaction radius | 5 |
when the value | 5 |
riesz wavelet systems | 5 |
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using the proposed | 5 |
only way to | 5 |
will eventually be | 5 |
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number of publications | 5 |
is a new | 5 |
during the first | 5 |
presence of the | 5 |
as there is | 5 |
the rapid dissemination | 5 |
vaccination and treatment | 5 |
this is an | 5 |
the lockdown effect | 5 |
a deterministic model | 5 |
can be achieved | 5 |
are displayed in | 5 |
fractional derivatives with | 5 |
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under public health | 5 |
editorial submission system | 5 |
developed a mathematical | 5 |
the informed individuals | 5 |
the jacobian of | 5 |
will reduce r | 5 |
the spreading dynamics | 5 |
comparison of the | 5 |
is obtained from | 5 |
probability of disease | 5 |
evolution of covid | 5 |
peak in the | 5 |
to reduce social | 5 |
was reported on | 5 |
pneumonia of unknown | 5 |
facilitates the rapid | 5 |
infected population is | 5 |
the genomic sequence | 5 |
using mathematical models | 5 |
differential equation model | 5 |
the incidence data | 5 |
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where the number | 5 |
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new cases of | 5 |
with that of | 5 |
reported in fig | 5 |
parameters for the | 5 |
sir model for | 5 |
wuhan novel coronavirus | 5 |
individuals which is | 5 |
obtain this way | 5 |
and capacity constraints | 5 |
of reported cases | 5 |
after implementing control | 5 |
and sensitivity analysis | 5 |
some of them | 5 |
stability results of | 5 |
the global asymptotic | 5 |
infectious diseases and | 5 |
with individual reaction | 5 |
number of infectious | 5 |
since there is | 5 |
of the slow | 5 |
that social distancing | 5 |
for the simulation | 5 |
infected country or | 5 |
on complex networks | 5 |
model is then | 5 |
a plethora of | 5 |
modelling the spread | 5 |
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wang et al | 5 |
this model can | 5 |
disease and to | 5 |
equation of the | 5 |
if and only | 5 |
of vaccine failure | 5 |
rise in the | 5 |
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manuscript has been | 5 |
the host will | 5 |
conclude that the | 5 |
unquarantined asymptomatic infectious | 5 |
or the other | 5 |
critical model parameters | 5 |
the mathematical modelling | 5 |
motion on s | 5 |
for the local | 5 |
and reduce the | 5 |
the treatment of | 5 |
information diffusion and | 5 |
in most of | 5 |
economic and social | 5 |
boundary value problem | 5 |
existence of backward | 5 |
of spread of | 5 |
social distancing in | 5 |
dynamics on the | 5 |
than one sentence | 5 |
it seems that | 5 |
if r c | 5 |
proposed sirsi model | 5 |
fractional derivative of | 5 |
covid epidemic in | 5 |
class of asymptomatic | 5 |
the vaccination behavior | 5 |
set of asymptomatic | 5 |
public health authorities | 5 |
mathematical models for | 5 |
been used in | 5 |
and has been | 5 |
infections and deaths | 5 |
control strategies for | 5 |
the epidemic duration | 5 |
cases generated by | 5 |
carried out by | 5 |
the manuscript has | 5 |
generation matrix method | 5 |
the disease dynamics | 5 |
solution to the | 5 |
for different countries | 5 |
mathematical model that | 5 |
epidemic spreading process | 5 |
this work is | 5 |
the health system | 5 |
likely to be | 5 |
of the endemic | 5 |
the virus will | 5 |
will lead to | 5 |
mean of apen | 5 |
system of the | 5 |
recovery rate of | 5 |
details of the | 5 |
clusters distributed as | 5 |
used for this | 5 |
the eigenvalues are | 5 |
exponential increase in | 5 |
convolutional neural networks | 5 |
with the lockdown | 5 |
of newly infected | 5 |