one possible model of prevention (one county in sw) chatham is...

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NW N SW C E 1996 124 2 579 9 243 1997 116 22 310 1 68 1998 181 34 758 33 154 1999 407 132 1603 102 314 2000 337 110 1120 50 292 2001 362 141 903 161 396 2002 795 345 887 534 925 2003 3017 1791 4789 3599 5451 Table 1: 1996 - 2003 Reported Flu Cases in Virginia regions: NW(1) = Northwest, N(2) = North, SW(3) = Southwest, C(4) = Central, E(5) = Eastern. Reaching the Community with Mathematical Biology Reaching the Community Reaching the Community with Mathematical Biology with Mathematical Biology Olgamary Rivera-Marrero [email protected] Purpose Purpose Students Learn how to apply basic mathematical concepts to model real-world situations. Teachers Acquire new ideas of integrating non-standard mathematics into the classroom. Abstract Algebra Abstract structures: inverses and identities Properties of operations: commutative, associative, distributive Finite fields: arithmetic and functions Software : Discrete Visualizer of Dynamics (DVD) Graph Theory Graphs: vertex , weighted Adjacency matrices Vertex coloring Paths and cycles: shortest, eulerian, hamiltonian Software : Mathematical Modeling: Using Graphs/Matrices (MM) Focus and Topics of the Workshop Focus and Topics of the Workshop To develop and implement a mathematics workshop for secondary mathematics teachers and high school students. The workshop was designed to introduce mathematical biology and to demonstrate innovative ways of teaching mathematics with graphical modeling software. Viral Epidemic Project Viral Epidemic Project Given data of the number of cases of influenza Find a model to predict a possible future epidemic. Find a model to prevent the spread of the infection. The teachers generated ideas to integrate standard mathematics and the topics of the workshop through interactions with the students and the other teachers. Solutions Solutions One possible model of prediction One possible model of prevention (one county in SW) This implies that the regions NW, SW, and C are likely to experience influenza at epidemic levels in the 2005/2006 flu season. A clinic will be constructed in the most central locality in the identified county. Dissemination of information by health specialists is one way to prevent spread of the flu. Graph 4: Hamiltonian circuit for one possible route for the specialists to visit each city in the county. The route starts and ends at the clinic. Conclusions Conclusions The students extended their problem solving and communication skills. The teachers explored ways to incorporate the concepts into their own classrooms. All participants established a connection among mathematics, biology, modeling, and technology. Brandilyn Stigler [email protected] All participants applied these concepts to an epidemiological problem. 1 5 2 3 4 1 2 1 2 3 4 1 3 4 1 5 3 4 5 4 1 5 1 ( ) ( 1) ( ) 0 ( ) 1 ( ) ( 1) 0 ( ) ( 1) ( ) 1 ( ) ( ) f x x x xx f xx f xx x f x x x x f x x x = + + + + + = + = + + + = + + + + + = + + + 5 2 Graph 1: Geographic relationships between regions. Variables = regions Graph 2: Evolution of flu epidemic behavior. 0 = no epidemic 1 = epidemic Year 2001 Predicted year 2005 NW N SW C E Graph 3: Vertex coloring of weighted graph for the county. Table 2: Shortest-path matrix for driving times between cities in the county. Letter = city Number = shortest driving time The minimum number of specialists needed are 3. Chatham is most central. Vertex-graph Hamilton circuit Color = specialist References References DVD: http://dvd.vbi.vt.edu MM: http://www.learninginmotion.com National Council for Teachers of Mathematics: http://www.nctm.org Graph theory lessons: http://www.utc.edu/Faculty/Christopher- Mawata/petersen/lesson12b.htm

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Page 1: One possible model of prevention (one county in SW) Chatham is …dimacs.rutgers.edu/Workshops/Biomath/slides/Rivera... · 2005-05-18 · Conclusions The students extended their problem

NW

NSW

CE

1996

124

257

99

243

1997

116

2231

01

6819

9818

134

758

3315

419

9940

713

216

0310

231

420

0033

711

011

2050

292

2001

362

141

903

161

396

2002

795

345

887

534

925

2003

3017

1791

4789

3599

5451

Tabl

e 1:

199

6 -2

003

Repo

rted

Flu

Cas

es in

Virg

inia

regi

ons:

N

W(1

) = N

orth

wes

t, N

(2) =

Nor

th, S

W(3

) = S

outh

wes

t, C

(4) =

Cen

tral,

E(5)

= E

aste

rn.

Rea

chin

g th

e C

omm

unit

yw

ith

Mat

hem

atic

al B

iolo

gyR

each

ing

the

Com

mun

ity

Rea

chin

g th

e C

omm

unit

yw

ith

Mat

hem

atic

al B

iolo

gyw

ith

Mat

hem

atic

al B

iolo

gyO

lgam

ary

Riv

era-

Mar

rero

or

iver

am@

mat

h.vt

.edu

Purp

ose

Purp

ose

Stud

ents

Lear

n ho

w to

app

ly b

asic

mat

hem

atic

al c

once

pts

to

mod

el re

al-w

orld

situ

atio

ns.

Teac

hers

Acq

uire

new

idea

s of

inte

grat

ing

non-

stan

dard

m

athe

mat

ics

into

the

clas

sroo

m.

Abs

trac

t Alg

ebra

Abs

trac

t str

uctu

res:

inve

rses

and

iden

titie

sPr

oper

ties o

f ope

ratio

ns: c

omm

utat

ive,

ass

ocia

tive,

di

stri

butiv

eFi

nite

fiel

ds: a

rith

met

ic a

nd fu

nctio

nsSo

ftw

are:

Disc

rete

Visu

aliz

erof

Dyn

amic

s(D

VD

)

Gra

ph T

heor

yG

raph

s: v

erte

x , w

eigh

ted

Adj

acen

cy m

atri

ces

Ver

tex

colo

ring

Path

s and

cyc

les:

shor

test

, eul

eria

n, h

amilt

onia

nSo

ftw

are:

Mat

hem

atic

al M

odeli

ng: U

sing

Gra

phs/

Mat

rices

(MM

)

Focu

s an

d To

pics

of t

he W

orks

hop

Focu

s an

d To

pics

of t

he W

orks

hop

To d

evel

op a

nd im

plem

ent a

mat

hem

atic

s w

orks

hop

for s

econ

dary

mat

hem

atic

s te

ache

rs a

nd h

igh

scho

ol

stud

ents

.

The

wor

ksho

p w

as d

esig

ned

to in

trod

uce

mat

hem

atic

al b

iolo

gy a

nd to

dem

onst

rate

inno

vativ

e w

ays

of te

achi

ng m

athe

mat

ics w

ith g

raph

ical

m

odel

ing

softw

are.

Vira

l Epi

dem

ic P

roje

ctVi

ral E

pide

mic

Pro

ject

Giv

en d

ata

of th

e nu

mbe

r of c

ases

of i

nflu

enza

Find

a m

odel

to p

redi

ct a

pos

sibl

e fu

ture

epi

dem

ic.

Find

a m

odel

to p

reve

nt th

e sp

read

of t

he in

fect

ion.

The

teac

hers

gen

erat

ed id

eas

to in

tegr

ate

stan

dard

mat

hem

atic

s an

d th

e to

pics

of t

he w

orks

hop

thro

ugh

inte

ract

ions

with

the

stud

ents

and

the

othe

r tea

cher

s.

Solu

tions

Solu

tions

One

pos

sibl

e m

odel

of p

redi

ctio

n

One

pos

sibl

e m

odel

of p

reve

ntio

n (o

ne c

ount

y in

SW

)

This

impl

ies

that

the

regi

ons N

W, S

W, a

nd C

are

like

ly to

ex

peri

ence

influ

enza

at e

pide

mic

leve

ls in

the

2005

/200

6 flu

seas

on.

A c

linic

will

be

cons

truc

ted

in th

e m

ost c

entr

al lo

calit

y in

the

iden

tifie

d co

unty

.

Dis

sem

inat

ion

of in

form

atio

n by

hea

lth s

peci

alis

ts is

one

w

ay to

pre

vent

spre

ad o

f the

flu. G

raph

4: H

amilt

onia

n ci

rcui

t for

one

pos

sible

ro

ute

for t

he s

peci

alist

s to

visit

eac

h ci

ty in

the

coun

ty.

The

rout

e st

arts

and

end

s at

the

clin

ic.

Con

clus

ions

Con

clus

ions

The

stud

ents

ext

ende

d th

eir p

robl

em s

olvi

ng a

nd

com

mun

icat

ion

skill

s.Th

e te

ache

rs e

xplo

red

way

s to

inco

rpor

ate

the

conc

epts

into

thei

r ow

n cl

assr

oom

s.A

ll pa

rtic

ipan

ts e

stab

lishe

d a

conn

ectio

n am

ong

mat

hem

atic

s, b

iolo

gy, m

odel

ing,

and

tech

nolo

gy.

Bra

ndil

yn S

tigl

erbs

tigl

er@

vbi.

vt.e

du

All

part

icip

ants

app

lied

thes

e co

ncep

ts to

an

epid

emio

logi

cal p

robl

em.

15

23

41

21

2

34

13

41

53

4

54

15

1

()

(1)

()

0

()

1

()

(1)

0(

)(

1)(

)

1(

)(

)

fx

xx

xx

fxx

fxx

xf

xx

xx

fx

xx

=+

++

++

=+

=+

++

=+

++

++

=+

++

5

2

Gra

ph 1

: Geo

grap

hic

rela

tions

hips

be

twee

n re

gion

s.

Varia

bles

= re

gion

s

Gra

ph 2

: Evo

lutio

n of

flu

epi

dem

ic

beha

vior

.

0 =

no e

pide

mic

1 =

epid

emic

Year

200

1

Pred

icte

d ye

ar

2005

NW

N S

W C

E

Gra

ph 3

: Ver

tex

colo

ring

of w

eigh

ted

grap

h fo

r the

cou

nty.

Tabl

e 2:

Sho

rtest

-pat

h m

atrix

for

driv

ing

times

bet

wee

n ci

ties

in th

e co

unty

.

Lette

r = c

ityN

umbe

r = s

horte

st d

rivin

g tim

e

The

min

imum

num

ber o

f sp

ecia

lists

nee

ded

are

3.

Cha

tham

is m

ost c

entr

al.

Ver

tex-

grap

hH

amilt

on c

ircui

t

Col

or =

spe

cial

ist

Refe

renc

esRe

fere

nces

DV

D: h

ttp:/

/dvd

.vbi

.vt.e

duM

M: h

ttp:/

/ww

w.le

arni

ngin

mot

ion.

com

Nat

iona

l Cou

ncil

for T

each

ers

of M

athe

mat

ics:

http

://w

ww

.nct

m.o

rgG

raph

theo

ry le

sson

s: ht

tp:/

/ww

w.u

tc.e

du/F

acul

ty/C

hris

toph

er-

Maw

ata/

pete

rsen

/les

son1

2b.h

tm