Software Practice and Experience,
Год журнала:
2021,
Номер
52(4), С. 824 - 840
Опубликована: Апрель 1, 2021
Abstract
The
Covid‐19
pandemic
has
emerged
as
one
of
the
most
disquieting
worldwide
public
health
emergencies
21st
century
and
thrown
into
sharp
relief,
among
other
factors,
dire
need
for
robust
forecasting
techniques
disease
detection,
alleviation
well
prevention.
Forecasting
been
powerful
statistical
methods
employed
world
over
in
various
disciplines
detecting
analyzing
trends
predicting
future
outcomes
based
on
which
timely
mitigating
actions
can
be
undertaken.
To
that
end,
several
machine
learning
have
harnessed
depending
upon
analysis
desired
availability
data.
Historically
speaking,
predictions
thus
arrived
at
short
term
country‐specific
nature.
In
this
work,
multimodel
technique
is
called
EAMA
related
parameters
long‐term
both
within
India
a
global
scale
proposed.
This
proposed
hybrid
model
well‐suited
to
past
present
For
study,
two
datasets
from
Ministry
Health
&
Family
Welfare
Worldometers,
respectively,
exploited.
Using
these
datasets,
data
outlined,
observed
predicted
being
very
similar
real‐time
values.
experiment
also
conducted
statewise
countrywise
across
it
included
Appendix.
Equilibrium Quarterly Journal of Economics and Economic Policy,
Год журнала:
2020,
Номер
15(2), С. 181 - 204
Опубликована: Июнь 24, 2020
Research
background:
On
11
March
2020,
the
Covid-19
epidemic
was
identified
by
World
Health
Organization
(WHO)
as
a
global
pandemic.
The
rapid
increase
in
scale
of
has
led
to
introduction
non-pharmaceutical
countermeasures.
Forecast
prevalence
is
an
essential
element
actions
undertaken
authorities.
Purpose
article:
article
aims
assess
usefulness
Auto-regressive
Integrated
Moving
Average
(ARIMA)
model
for
predicting
dynamics
incidence
at
different
stages
epidemic,
from
first
phase
growth,
maximum
daily
incidence,
until
epidemic's
extinction.
Methods:
ARIMA(p,d,q)
models
are
used
predict
virus
distribution
many
diseases.
Model
estimates,
forecasts,
and
accuracy
forecasts
presented
this
paper.
Findings
&
Value
added:
Using
ARIMA(1,2,0)
forecasting
cases
each
stage
way
evaluating
implemented
countermeasures
on
epidemic.
Software Practice and Experience,
Год журнала:
2021,
Номер
52(4), С. 841 - 867
Опубликована: Май 18, 2021
Abstract
The
COVID‐19
pandemic
has
emerged
as
a
highly
transmissible
disease
which
caused
disastrous
impact
worldwide
by
adversely
affecting
the
global
economy,
health,
and
human
lives.
This
sudden
explosion
uncontrolled
spread
of
revealed
limitations
existing
healthcare
systems
regarding
handling
public
health
emergencies.
As
governments
seek
to
effectively
re‐establish
their
economies,
open
workplaces,
ensure
safe
travels
progressively
return
normal
life,
there
is
an
urgent
need
for
technologies
that
may
alleviate
severity
losses.
article
explores
promising
solution
secure
Digital
Health
Certificate,
called
NovidChain,
Blockchain‐based
privacy‐preserving
platform
test/vaccine
certificates
issuing
verifying.
More
precisely,
NovidChain
incorporates
several
emergent
concepts:
(i)
Blockchain
technology
data
integrity
immutability,
(ii)
self‐sovereign
identity
allow
users
have
complete
control
over
data,
(iii)
encryption
Personally
Identifiable
Information
enhance
privacy,
(iv)
W3C
verifiable
credentials
standard
facilitate
instant
verification
proof,
(v)
selective
disclosure
concept
permit
user
share
selected
pieces
information
with
trusted
parties.
Therefore,
designed
meet
high
level
protection
personal
in
compliant
GDPR
KYC
requirements,
guarantees
user's
self‐sovereignty,
while
ensuring
both
safety
populations
right
privacy.
To
prove
security
efficiency
proposed
platform,
this
also
provides
detailed
technical
description,
proof‐of‐concept
implementation,
different
experiments,
comparative
evaluation.
evaluation
shows
better
financial
cost
scalability
results
compared
other
solutions.
we
note
difference
time
between
operations
(i.e.,
46%
56%).
Furthermore,
confirms
ensures
properties,
particularly
integrity,
forge,
binding,
uniqueness,
peer‐indistinguishability,
revocation.
Software Practice and Experience,
Год журнала:
2021,
Номер
52(4), С. 824 - 840
Опубликована: Апрель 1, 2021
Abstract
The
Covid‐19
pandemic
has
emerged
as
one
of
the
most
disquieting
worldwide
public
health
emergencies
21st
century
and
thrown
into
sharp
relief,
among
other
factors,
dire
need
for
robust
forecasting
techniques
disease
detection,
alleviation
well
prevention.
Forecasting
been
powerful
statistical
methods
employed
world
over
in
various
disciplines
detecting
analyzing
trends
predicting
future
outcomes
based
on
which
timely
mitigating
actions
can
be
undertaken.
To
that
end,
several
machine
learning
have
harnessed
depending
upon
analysis
desired
availability
data.
Historically
speaking,
predictions
thus
arrived
at
short
term
country‐specific
nature.
In
this
work,
multimodel
technique
is
called
EAMA
related
parameters
long‐term
both
within
India
a
global
scale
proposed.
This
proposed
hybrid
model
well‐suited
to
past
present
For
study,
two
datasets
from
Ministry
Health
&
Family
Welfare
Worldometers,
respectively,
exploited.
Using
these
datasets,
data
outlined,
observed
predicted
being
very
similar
real‐time
values.
experiment
also
conducted
statewise
countrywise
across
it
included
Appendix.
