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SUMMARY:Individually based stochastic model of influenza: an analysis of s
chool closure
DTSTART;VALUE=DATE-TIME:20180709T060000Z
DTEND;VALUE=DATE-TIME:20180709T062000Z
DTSTAMP;VALUE=DATE-TIME:20241109T185204Z
UID:indico-contribution-320@conferences.maths.unsw.edu.au
DESCRIPTION:Speakers: Masayuki Kakehashi (Hiroshima University)\nIn this r
esearch\, we proposed an infectious disease spread model of influenza whic
h was individually based and stochastic. We first described the method to
build a realistic model\, or to estimate realistic parameter values\, base
d on observed data. An appropriate model has to be individually based and
stochastic if we take advantage of small unit data (in this case\, every d
ay class unit data). We also analysed the effect of different strategies o
f school closure\, e.g.\, the criteria for implementing school closure and
the duration of continuous school closure. \n\nThe data we used were the
daily reported data of the numbers of cases of swine flu and the dates of
school/class closure in each class of schools collected from September 20
09 to March 2010 in a city in Japan. Because the data were collected in ea
ch class\, transmission rates could be estimated separately for within cla
ss\, within-school and inter-school rates. Totally 21\,253 cases were repo
rted out of 51\,871 students in 134 schools (elementary schools\, junior h
igh schools\, high schools and kindergartens). To construct accurate model
\, infected numbers must be estimated from case report data taking latent
period into account\, which is deterministically impossible. To resolve th
is difficulty\, we stochastically estimated and obtained data of infected
numbers by ‘Monte Carlo back calculation’ and used in the analysis. Th
e analysis was mainly carried out using data during September up to Decemb
er to avoid the influence of vacations. The influence of humidity was also
analysed using daily meteorological data of the area where data were coll
ected. The analysis of total population using deterministic model was also
carried out to obtain the overview of the flu spread. \n\nThe transmissio
n rates of different levels were estimated by maximum likelihood method us
ing detailed data reconstructed by Monte Carlo back calculation method. Th
e rate within class was much larger (approximately 15 times larger) than w
ithin school rate. The transition rate between schools was much smaller th
an between classes of the same school. Stochastic variations of estimated
parameters were also analysed. Optimal strategy of school closure was anal
ysed in relation to the characteristics of flu. \n\nBy the analysis based
on stochastic infectious disease spread model\, we could have presented po
ssible variations of total number of cases and the size and timing of the
epidemic peak. ‘Monte Carlo back calculation’ approach was concluded t
o be useful in the analysis of effective preventive strategy against influ
enza based on individually based stochastic model.\n\nhttps://conferences.
maths.unsw.edu.au/event/2/contributions/320/
LOCATION:University of Sydney New Law School/--020
URL:https://conferences.maths.unsw.edu.au/event/2/contributions/320/
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