Review
Journal
Name of Jornal
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BMC Infection
Diseases
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Title of Journal
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Accounting
for behavioral responses during a flu epidemic using home television viewing
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Date of Journal
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2015
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Methods
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Use
data on variation in home television viewing
as a proxy for variation in time
spent in the home
and, by extension, contact. This behavioral proxy is imperfect but appealing since information on a rich and representative sample is collected using consistent techniques
across time and most major
cities. Study in April-May 2009
outbreak of A/H1N1
in Central Mexico and examine the dynamic behavioral response in
aggregate and contrast the observed patterns of various demographic
subgroups. Develop and calibrate a dynamic behavioral model of disease transmission
informed by the proxy data on daily variation in contact rates and compare it
to a standard (non-adaptive) model and a fixed effects model that crudely
captures behavior.
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The Main
Discussion
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Individual
behavioral responses impact the spread of flu-like illnesses, but this has
been difficult to empirically characterize. Social distancing is an important
component of behavioral response, though analyses have been limited by a lack
of behavioral data. Our objective is to use media data to characterize social
distancing behavior in order to empirically inform explanatory and predictive
epidemiological models.
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Summary
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Results
from both behavioral models (FE and DB) suggested that
social distancing was a key
factor in constraining the initial
wave of A/H1N1 in Central Mexico. In the absence
of a behavioral response,
the estimated counterfactual path of new cases escalated rapidly in initial
weeks rather than stabilizing and eventu- ally falling as was
observed. The assumption of fixed be- havior in the
standard (SD) model led to shortcomings in estimation and prediction.
Estimates of the baseline
rate of transmission systematically shifted over time. If the
baseline rate of transmission is interpreted as a measure
of biological infectivity in the standard model, this is likely to lead to an
underestimate of this
parameter, as in our setting, given confounding effects of behavioral
responses. This suggests that A/H1N1 had an innate transmission
potential much greater
than previously thought but
this was masked by behavioral responses.
This has implications for management advice including the
allocation of resources between
pharmaceutical and nonpharmaceutical interventions. Furthermore, the error in near term predictions of
new cases through
time was also
substantially greater under the
standard model compared to the behav- ioral models. This error was also
systematic. The standard model
consistently led to
over-prediction in the number of new
cases.
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Conclusion
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Results
suggest that A/H1N1 had an innate transmission potential greater than
previously thought but this was masked by behavioral responses. Observed
differences in behavioral response across demographic groups indicate a
potential benefit from targeting social distancing outreach efforts.
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Suggestion
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The
Reader suggest that use many media data to characterize social distancing
behavior in order to empirically inform explanatory and predictive
epidemiological models.
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Nama : Fajar Rahmana
Kelas : 4EB17
NPM : 22211643
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