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Talk by Gabriela Gomes on the 1st Symposium of Big Data and Public Health, 2013
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Gabriela Gomes Instituto Gulbenkian de Ciência, Portugal
100 102
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0.6
0.8
1
transmission intensity, R0
prop
ortio
n in
fect
ed
A
Figure 1
105 10100
0.2
0.4
0.6
0.8
1
challenge dose, d
prop
ortio
n in
fect
ed
B
0 0.5 1susceptibility
dens
ity
€
Black (no intervention) :dSdt
= µ − λS − µS,
dIdt
= λS − µI, λ = βI.
Colored (intervention) :dsv (x)dt
= q(x)µ − xλsv (x),
div (x)dt
= xλsv (x) − µiv (x), λ = β iv01∫ (x)dx.
€
Black (no intervention) :
M =1− e−pd .
Colored (intervention) :
M =1− e−xpd01∫ q(x)dx.
Gomes et al 2013 PLOS Pathogens (in review).
€
di(x)dt
= β 1− i(x)[ ] − f (β,r)i(x),
where
f (β,r) =β
eβ r −1.
data from 90 communities
Smith et al 2005 Nature 438: 492.
Gomes et al 2012 Proc R Soc Lond B 279: 2473.
Cape Town
China
Taiwan India
Malawi
Rwanda Madras
Bangladesh
Spain Houston Denmark
Australia
Lombardy
US & Canada
data from 14 communities
Brazil Portugal
€
ILI(t) = p(t)I(t)
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