Predictive Modeling of West Nile Virus

Outbreaks Using Remotely-Sensed

Data

Dr. Michael Ward

Professor of Epidemiology

College of Veterinary Medicine

Texas A&M University

James Steele Conference on Diseases in Nature Transmissible to Man, Austin, 11 June 2007

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James SchuermannZoonosis Control GroupTexas Department of State Health Services,

Austin TX

Linda HighfieldDepartment of Veterinary Integrative

BiosciencesTexas A&M University, College Station TX

partial funding provided by theTexas Equine Research Advisory

Committee

3

Outline

1. Background2. Methods3. Results4. Discussion5. Conclusions

1. Background

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West Nile Virusfamily Flaviviridae genus FlavivirusJapanese Encephalitis serocomplex, includes:

Japanese encephalitisMurray Valley encephalitisSt. Louis encephalitisKunjin

antigenically, all closely related

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WNV Historyfirst occurrence in U.S.: 1999 ( Bronx Zoo, New York )by 2001: extension of range to include Florida2002: large equine epidemicby 2003: 46 states, 7 Canadian provinces, 5 Mexican statesonly states WNV not detected: Alaska, Hawaii

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WNV Life Cycle

Vector

Mosquito

Reservoir

Wild birds

Dead end host

Horses and humans

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WNV Mosquito Vectorsbiological and mechanical vectors

14 species identified

Culex spp. most likely in the U.S.breed in standing water

Cx. pipiens, quiquefasciatus, tarsalis

Aedes spp. may spread disease to horsesbreed in locations where water will be present

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WNV Avian Reservoirs

responsible for distribution

>110 species of birds

most susceptible species include American crows, fish jays, blue jays

game species (wild ducks, geese, pheasants, turkeys, pigeons, doves)

raptors (owls, hawks, eagles)

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Indicator % countiesdead bird 62equine case 29human case 4infected mosquito pool 3sentinel bird seroconversion

0.8

seropositive wild-caught bird

0.2

First indicators of WNV activity

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WNV Surveillance Programs

avian mortality surveillance tracking system

mosquito trapping and testing

testing wild birds, sentinel chickens,

horses and humans with neurologic disease

forecasting systems: environmental variables

temperature

precipitation

remotely-sensed data

2. Methods

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reported cases of equine WNV

encephalomyelitis: 2002, 2003 and 2004

time series of case reports, 2-week window

image data: 2-week 1km2 resolution rasters

of the Normalized Difference Vegetation

Index (NDVI)

mean NDVI for each 2-week period

periods with versus without reported cases

autoregressive model: NDVI as a predictor of

equine WNV cases (scaled, transform)

0

10

20

30

40

50

60

13-J

un

27-J

un

11-J

ul

25-J

ul

8-A

ug

22-A

ug

5-S

ep

19-S

ep

3-O

ct

17-O

ct

31-O

ct

14-N

ov

28-N

ov

12-D

ec

No.

cas

es

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What is the NDVI?

Advanced Very High Resolution

Radiometer (AVHRR) sensor,

NOAA polar-orbiting satellite

Normalized Difference Vegetation Index:

visible and near-infrared data

daily observations biweekly 1km2 resolution raster based

on daily maximum observed NDVI value

resulting 1x1 km pixel represents maximum scaled NDVI

value during each 2 weeks of the study period

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tx02_011024m

Value

High : 0.830000

Low : -0.430000

3. Results

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0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

Jan-02 May-02 Oct-02 Mar-03 Jul-03 Dec-03 May-04 Sep-04

Rep

orte

d ca

ses

0.0

0.1

0.2

0.3

0.4

0.5

0.6

ND

VI

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2-week periods N mean (95% CI)

WNV cases reported 45 0.4390 (0.4219, 0.4561)

WNV cases not reported 33 0.3962 (0.3730, 0.4193)

(P<0.001)

correlation, number of cases reported versus NDVI: 45%

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cases = – 0.9102 + 8.5762 (casesweeks 1–2) – 5.6137 (casesweeks 3–4)

+ 0.9262 (NDVIweeks 1–2) – 0.2661 (NDVIweeks 3–4)

no. observed versus predicted cases highly correlated (rSP 83%,

P<0.001)

-2

-1

0

1

2

3

4

5

6

7

0.0 2.0 4.0 6.0 8.0

observed

predicted

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mean difference, observed versus predicted cases, P= 0.973

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0Ja

n-02

Mar

-02

May

-02

Jul-0

2

Sep

-02

Nov

-02

Jan-

03

Mar

-03

May

-03

Jul-0

3

Sep

-03

Nov

-03

Jan-

04

Mar

-04

May

-04

Jul-0

4

Sep

-04

Nov

-04

Observed

Predicted

4. Discussion

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Prevention and Control

reduce exposure

indoor housing, repellants?

mosquito control

larvicides, adulticides, environment

vaccination

killed or recombinant canarypox-vectored

2 doses, 3-6 weeks apart; annual booster

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Forecasting Systems

anticipate increases in risk

optimize control strategies

increased awareness

identify “hotspots”

sentinel warning for zoonotic disease

5. Conclusion

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remotely-sensed data:availabilitylow-costcoverage

could be used to:enhanced WNV surveillanceprovide early warning of increased riskidentify hotspotswarn of potential zoonotic transmission of WNV