GIS and its applications in GIS and its applications in HealthHealth
دانشکده بهداشت دانشگاه علوم پزشکی تهراندانشکده بهداشت دانشگاه علوم پزشکی تهران13841384آذر ماه آذر ماه
اکبر حقدوست اکبر حقدوستييارايه دهنده: علارايه دهنده: عل
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Definition
Lilienfeld 1976 in “Fundamental epidemiology”
EpidemiologyEpidemiology: study of distribution of disease, or pathological condition in human populations and factors that influence this distribution
What does mean “distribution” in above definition?
We should explore the distribution in timetime and spacespace
John Snow project
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
�Example
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Poisson DistributionPoisson Distribution
k!
eλk)P(x
λk
Assumptions:Assumptions:
1.1.Constant proportion in areaConstant proportion in area
2.2.Independent distributionIndependent distribution
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Flying bombs strikes, south London
آيا بمبهاي آلمان در جنگ جهاني دوم آن گونه كه ادعا مي نمود قدرت تفكيك باال در هدف قرار
دادن مواضع را داشت؟
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Flying bombs strikes, south London
Number of bombs in cells
# of cells 0 1 2 3 4 5 Total
observed 229 211 93 35 7 1 576
expected 227.5 211.3 98.2 30.4 7.1 1.54 576
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Flying bombs strikes, south London
How can we test if the distribution of bombs was random?
x
Sm
x
xxobs
dfmwithondistributifollowsmx
S
x
SModelPoissonIn
xm
i
i
i
ii
x
x
2
1
222
22
2
)1()(
exp
)exp(
)1()1(
1:
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
This method is robust even for small sample numbers
You can estimate variance even based on the group data
Limitation
It does not taking into account distances between events
Flying bombs strikes, south London
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
A
Nearest neighbor method
Minimum distance between observation I and (n-1)
Checks the distances between events
a b
cd
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Exponential (e)
nx
n
n
xe
ne
)1lim(
)1
1lim(
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Exponential (e)
nqnnn en
nqqp )1()1(
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
R
r
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
A
r 2
1
Probability that a random point within the boundaries of the large circle falls within the boundaries of the small circle
Probability that a random point within the boundaries of the large circle does not fall within the boundaries of the small circle
A
r 2
Probability that n random points within the boundaries of the large circle does not fall within the boundaries of the small circle
An
rn
eA
r2
)1(2
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Probability that at least one of n random points within the boundaries of the large circle falls
within the boundaries of the small circle
A
rn
e
2
1
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Expected median, mean and variance based on these explanations (nearest neighbor analysis)
2068.0)var(5.0)(
)2log(47.047.0)(
n
Arwith
n
Armean
n
Armedian
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
example
دارد؟ وجود ارتباطي هيچ شكل اين نقاط بين آيا
0
5
10
15
0 5 10 15
x
y
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
نقاط ضعف روش نزديكترين گزينه
Very large and small area (A) may reduce the significance
0
5
10
15
20
25
30
35
40
45
50
0 5 10 15 20 25 30 35 40 45 50
x
y
0
5
10
0 5 10
x
y
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
BoundaryBoundary influenceinfluence
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Transformed map
Uniform distribution is violated in nearly all situations.
Redraw a map so that the density of the individuals at risk is equalized over the area under study, called a cartogram
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Original map
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Cartogram
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Limitations in using cartogram
1. We need to have an accurate map to illustrate the population density
2. The population at risk is not usually distributed exactly the same as the whole population
3. It needs power full computer to generate a cartogram
GIS workshop in TUMSGIS workshop in TUMS A.A. HaghdoostA.A. Haghdoost
Alternative method
Case control approach
It means we can compare the spatial distribution of cases versus controls using Poisson models
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