REMOTELY SENSED INDICATORS OF MICRO-CLIMATE IN PREDICTING NEW AREAS OF HUMAN RISK OF LYME DISEASE USING

SPATIAL STATISTICS AND ARTIFICIAL NEURAL NETWORKS

A PRESENTATION TO THE SUMMER COLLOQUIUM ON CLIMATE AND HEALTH

JULY 26, 2004, NCAR, BOULDER COLORADO

RUSSELL BARBOUR PH.D.

VECTOR ECOLOGY LABORATORY

YALE SCHOOL OF MEDICINE

NEW HAVEN CT.

PROBLEM STATEMENT

• HUMAN CASE DATA HAS BEEN PROVEN AN UNRELIABLE INDICATOR OF LYME DISEASE RISK

• UNDER REPORTING, MIS-DIAGNOSES, AND OVER REPORTING DISTORT HUMAN CASE DISTRIBUTION

• COLLECTION AND TESTING OF INFECTED NYMPHS COSTLY

PROBLEMS CONTINUED

• Ixodes scapularis TICKS HAVE NOT EXPANDED INTO ALL AREAS OF SUITABLE HABITAT

• INVADING TICKS ARE NOT NECESSARILY INFECTED WITH Borrelia burgdorferei ( BACTERIAL AGENT OF LYME DISEASE)

• ONLY INFECTED NYMPHAL TICKS POSE A THREAT TO HUMANS

NEW APPROACH TO RISK ESTIMATION AND PREDICTION

• INTEGRATE HUMAN CASE DATA WITH LANDSCAPE INDICATORS OF THE NIDALITY (FOCI) OF INFECTION OF Borrelia burgdorferi

• BUILD DATA LAYERS FROM REMOTELY SENSED MICRO-CLIMATE INDICATORS, PUBLISHED CANINE SEROPREVALENCE AND PREVIOUS HUMAN CASE DATA

• DERIVE PROBABILITY OF INCREASING RISK THROUGH MARKOV-BAYES MONTE CARLO SIMULATIONS

KRIGING VERSUS MARKOV-BAYES MONTE CARLO CHAIN (MMCC)

SIMULATION

• KRIGING GIVES THE MOST LIKELY EVENT AT ALL LOCATIONS.. THE TOP OF A PROBABILITY DENSITY CURVE

• KRIGING IS BASED ON JUST ONE “ ITERATION OF POSSIBLE REALITY”

• KRIGING DISHONORS THE ORIGINAL DATA …“ EVENTS MORE PROBABLE THAN REALITY”

• MMCC GIVES OTHER PROBABILITIES AT EACH LOCATION

• MMCC HONORS THE ORIGINAL DATA

• MMCC IS BASED ON METROPOLIS-HASTINGS RANDOM WALK (ALGORITHM USED TO DEVELOP H-BOMB). THE NEXT STATE IS ONLY DERIVED FROM THE CURRENT STATE

• RANDOM WALK CREATES A NUMBER OF ITERATIONS ALTHOUGH EVENTUALLY THEY WILL CONVERGE TO KRIGED VALUES

EVI AS A FACTOR IN ESTIMATING LYME DISEASE RISK

• MORE SENSITIVE TO PERIODS OF LIGHT VEGETATION , SPRING AND FALL WHEN NYMPHAL AND ADULT TICKS ARE ACTIVE

• DISTINGUISHES BETWEEN WOODED SUBURBS AND TRUE FORESTS DURING THIS TIME PERIOD

• IDENTIFIES DISCONTINUITY IN LANDSCAPES BETTER THAN NDVI

MODIS Products

MODIS

OceanLand

Atmosphere

Products:MOD36 Ocean ColorMOD28 SST…

Products:MOD36 Ocean ColorMOD28 SST…

Products:MOD04 AerosolsMOD05 Water VaporMOD06 CloudMOD35 Cloud Mas…

Products:MOD04 AerosolsMOD05 Water VaporMOD06 CloudMOD35 Cloud Mas…

Products:MOD09 ReflectanceMOD12 Snow CoverMOD13 VegetationMOD14 Thermal Anomaly

…

Products:MOD09 ReflectanceMOD12 Snow CoverMOD13 VegetationMOD14 Thermal Anomaly

…

SOURCE: http://modis.gsfc.nasa.gov/

MODIS Data products come in different

Spatial Resolution

250 m500 m1000 m4 km5 km5 min0.05 deg0.25 degEtc…

Temporal Resolution Versions

daily8-day composites16-day composites96-day compositesEtc…

Version3 v003Version4 v004

~But most products do NOT come with all these resolutions and versions~

RELATIONSHIP BY DATE BETWEEN HUMAN CASES AND EVI BY MOVING WINDOW ANALYSIS

HUMAN CASES

MODIS EVI DATES CORRELATION

1992 MAY25 2001

JULY 28 2001

.12

.01

1993 MAY 25 2001

JULY 28 2001

.11

.02

1994 MAY 25 2001

JULY 28 2001

.18

.06

1995 MAY 25 2001

JULY 28 2001

.14

.06

1996 MAY 25 2001

JULY 28 2001

.16

.06

1997 MAY 25 2001

JULY 28 2001

.14

.06

1999 MAY 25 2001

JULY 28 2001

.17

.06

2000 MAY 25 2001

JULY 28 2001

.20

.06

MATHEMATICAL DATA INTEGRATION MATHEMATICAL DATA INTEGRATION MATHEMATICAL DATA INTEGRATION MATHEMATICAL DATA INTEGRATION

NEW REMOTELY SENSEDVEGETATION INDEX

(EVI)PREVIOUS HABITAT SUITABILITY MODEL

CANINE SEROPREVALANCE

DATA POINTS

Most Abundant Data Most Abundant Data

ESTIMATED HUMAN CASES BY LOCATION

COMBINED BY ANNCOMBINED BY ANN

SPATIAL STATISTICS & MMCC SIMULATIONS

SPATIAL STATISTICS & MMCC SIMULATIONS

1992- 2000HUMAN CASE

DATA BY COUNTY

Sparse Data Sparse Data

PREDICTIVE VALUE OF 1995 MID-WESTERN CASE DATA WHEN INTEGRATED WITH PREVIOUS YEARS AND

LANDSCAPE INDICATORS OF INFECTION BY MULTILAYER ARTIFICIAL NEURAL NETWORKS

1995 0.99861996 0.90071997 0.84201998 0.88001999 0.87792000 0.8323

YEAR PREDICTIVE VALUE

PREDICTIVE VALUE OF 1998 MID-WESTERN CASE DATA WHEN INTEGRATED WITH PREVIOUS YEARS AND

LANDSCAPE INDICATORS OF INFECTION BY MULTILAYER ARTIFICIAL NEURAL NETWORKS

YEAR PREDICATIVE VALUE

1998 .99

1999 .99

2000 .91

URBAN AREASPROBABILITY

PROBABILITY OF HUMAN PREVALENCE HIGHER THAN 25/100,000 FROM 1992 HUMAN

CASE DATA AND LANDSCAPE INFECTION INDICATORS

PROBABILITY OF HUMAN PREVALENCE HIGHER THAN 25/100,000 FROM 2000 HUMAN

CASE DATA AND LANDSCAPE INFECTION INDICATORS

URBAN AREAS

PROBABILITY

1992 PROBABILITY OF HIGH PREVALENCE

2003 PROBABILITY OF HIGH PREVALENCE

URBAN AREAS

URBAN AREAS

PROBABILITY MAP

MODEL AGREEMENT WITH CASE DATA

• PREDICTED SPATIAL HUMAN LD PREVALENCE BY FROM LANDSCAPE AND PREVIOUS HUMAN CASE DATA AGREED WITH ACTUAL CASES BY 81%

WEAKNESS

• VEGETATION DATE TOO SPECIFIC

• LARGE AREAS OF UNCERTAINTY

• NO QUALITY CRITERIA FOR ORIGINAL CASE DATA

• “NOISE” STILL PRESENT

STRENGTHS

• HUMAN CASE DATA LINKED TO NIDALITY OF INFECTION

• REASONABLE PREDICTIONS OF HUMAN RISK POSSIBLE

• THREE YEAR ADVANCE OF INFECTION WALL APPEARS VISIBLE

WILDLIFE URBAN INTERFACE DATA

LOW DENSITY INTERFACE : AREAS WITH HOUSING DENSITY BETWEEN 6.2 AND 49.4 HOUSING UNITS PER KM 2 AND 50% VEGETATION COVER WITHIN ALL 2 KM AREAS WITH 75 % COVER

Source:SILVIS Lab Spatial Analysis For Conservation And SustainabilityForest Ecology & Management University Of Wisconsin - Madison

ASSOCIATED WITH HUMAN LD CASES In WI

SPATIAL STRUCTURE OF 2000 HUMAN CASE DATA IN WISCONSIN

CROSS VARIOGRAM2000 HUMAN CASES AND

LOW DENSITY WUI

CO-KRIGE OF 2000 HUMAN CASES AND LOW WUI % LAND COVER

SPREAD OF INFECTED NYMPHAL

Ixodes scapularis TICKS AS ESTIMATED

FROM HUMAN CASES

SPREAD OF INFECTED NYMPHAL

Ixodes scapularis TICKS AS ESTIMATED

FROM HUMAN CASES

FUTURE RESEARCH

• CUBIC SPLINE REGRESSION OF ALL HUMAN CASE DATA TO REMOVE NOISE

• ADDITION OF MODIS ATMOSPHERIC DATA TO CAPTURE HUMIDITY

• FILTER OF UNSUITABLE LANDSCAPES FARMLAND

• CALCULATION OF THE RATE OF INFECTION SPREAD, CURRENTLY ABOUT 6 KILOMETERS A YEAR, BASED ON MMCC PROBABILITY MODELS, NOT CASES