Department of Geography College of Earth and Mineral Sciences

Department ofGeography

College of Earth and Mineral

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Identifying the Spatially Dynamic Variables Affecting the Distribution of West Nile Virus in Pennsylvania

GEOG – 596A, Summer 2013Mark Brady

Advisor: Dr. Justine Blanford



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Acknowledge

Project Outline

BackgroundOrigin in North AmericaHealth EffectsEnzootic CycleEnvironmental Variables

MethodsGeographically Weighted Regression

Expected outcomesIdentification of Explanatory VariablesPredictive Model of WNV Distribution

Timeline

What is West Nile Virus ?

WNV was first isolated in Uganda in 1937

Appeared on the North AmericanContinent in 1999 (New York, isolated from a Flamingo in the Bronx Zoo)

WNV had spread to the west coast within 4 years

Since 1999 WNV has been detected in all of the Lower 48 States



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Typical WNVTransmission

Cycle

Avian Host

Avian Host

WNV Vector

Incidental Hosts

What is West Nile Virus?



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1999 2000

2001 2002

2003 2004

Why is West Nile Virus a Problem ?

Human infection with WNV may result in serious illness and in extreme cases, death

WNV is an invasive exotic species in North America

50% reduction in bird populations, particularly among Corvids (Crows and Jays)



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West Nile Virus Infection - Symptoms and Prognosis

+/- 80% of people infected with WNV will develop no symptoms.

Symptoms include: fever with other symptoms such as headache, body aches, joint pains, vomiting, diarrhea, or rash, with fatigue and weakness that may last for weeks or months

< 1% of human infections are fatal (e.g. neurologic illness such as encephalitis or meningitis) and can lead to death



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WNV Impacts on Human HealthDepartment ofGeography


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1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 20120

100020003000400050006000700080009000

10000

62 21 66

4156

9862

25393000

42693630

1356720 1021 712

5674

Human WNV Infections (1999 - 2012)Nationwide

19992000

20012002

20032004

20052006

20072008

20092010

20112012

050

100150200250300

7 2 10

284264

100 119

177

124

44 3257 43

286

Human Deaths from WNV (1999 – 2012)

Nationwide

Total Infected: 37,088

Total Deaths: 1,549

Anthropogenic and Environmental Factors Affecting WNV



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Kilpatrick (2011). Globalization, Land Use, and the Invasion of West Nile Virus, Sciences



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Factors Affecting WNV

Source : Reisen et al. 2006 J Med Entomol 43:309-317

Source : Blanford et al. 2012, Submitted

Temperature

Precipitation



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Anthropogenic and Environmental Factors Affecting WNV - Landuse

Kilpatrick (2011).

Climate Landuse Vector Biology Host InteractionAllen et al (2009) Allen et al (2009) Andrade et al (2011) Apperson et al (2004)Andrade et al (2011) Burkett-Cadena et al (2013) Andreadis et al (2004) Boos (2009)Chaves et al (2011) Chaves et al (2011) Apperson et al (2004) Burkett-Cadena et al (2013)DeGroot et al (2008) Dale et al (2008) Blanford et al (2013) Cummins et al (2012)Deichmeister et al (2011) DeGroot et al (2008) Boos (2009) DeGroot et al (2008)Gardner et al (2012) Deichmeister et al (2011) Brinton (2002) Ghosh (2009)

Gibbs et al (2006) Ezenwa et al (2007) Burkett-Cadena et al (2013) Landesman et al (2007)

Gong et al (2011) Gibbs et al (2006) Crans (2004) Messina et al (2011)Kilpatrick et al (2006) Kilpatrick et al (2011) Chaves et al (2011) Rochlin et al (2011)Kilpatrick et al (2008) Rochlin et al (2011) Dale et al (2008) Sugumaran et al (2009)Keonraadt et al (2008) Gardner et al (2012) Weaver et al (2004)Landesman et al (2007) Hamer et al (2008)Reisen et al (2006) Kilpatrick et al (2010)Reisen et al (2010) Kilpatrick et al (2008)Ruiz et al (2010) Kwan et al (2012)Ruiz et al (2004) Reisen et al (2006)Thompson (2004) Reisen et al (2010)Trawinski et al (2008) Ruiz et al (2010)

Weaver et al (2004)

Literature Review



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Factors affecting WNV

Spatial and temporal effects - Modelling at weekly/monthly/bimonthly etc. to best capture population dynamics

Land use – Urban vs. Rural

Temperature – affects virus transmission and population abundance

Rainfall – affects population abundance and availability of breeding sites

Vector species and composition (Culex species: Cx tarsalis, Cx pipiens, Cx restuans, Cx salinarius)

Challenges Modeling WNV

Environmental parameters are not stationary, they vary spatially in occurrence and intensity

The relationship between parameters influencing WNV occurrence vary spatially

The competence and abundance of vectors vary spatially

Host abundance varies spatially



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Question remains… What key factors are important for predicting WNV?

Do these vary geographically?

West Nile Virus in Pennsylvania

WNV first detected in 2000

WNV PA has been collecting mosquitoes since 2000 Surveillance results used to guide mitigation efforts (larvicides, adulticides, breeding habitat removal)

Over 35,000 locations sampled statewide

Calculate MIR (Infection Rates: Proportion of mosquitoes +ve WNV of all mosquitoes collected.

Sampling sites are chosen based on nuisance complaints, past history, and staff experience

No environmental data has been collected



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Project Goals and ObjectivesDepartment of

Geography


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Spatial and temporal dynamics of WNV are not well described for PA since no detailed analysis of PA data has been conducted.

Explore complex interactions of a variety of factors that can influence disease dynamics.

Identify the variables that best explain the distribution and abundance of WNV in Pennsylvania using Geographically Weighted Regression (GWR)

Once identified, use the GWR model to estimate WNV distribution and intensity statewide (compared to historical, normal, and projected input criteria)



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19992000

20012002

20032004

20052006

20072008

20092010

20112012

Total

0

50

100

150

200

250

0 0 3

62

237

15 259 10 14 0

286

60

Human WNV Infections (1999 - 2012)Pennsylvania

2001

2002

2003

2005

1999

2007

1999

2006

2011

2010

20122008



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Culex pipiens – Primary vector of WNV to humans. Often associated with urban and suburban areas. Preferred hosts are birds, but will feed on mammals, snakes, and reptiles when avian hosts are unavailable. Larval habitats are stagnant pools, sewage plants, artificial containers (tires, buckets, etc.). Tolerant of polluted waterCulex restuans – Competent vector for WNV. Often associated with urban and suburban areas, but known to occur in diverse range of habitats. Preferred hosts are birds, but will feed on mammals, amphibians, and reptiles when avian hosts are unavailable. Larval habitats are similar to Cx. Pipiens, but less tolerant of polluted water. Abundant early in season and amplification of WNV.

Culex salinarius – An opportunistic feeder that will readily feed on birds or mammals, therefore may be an important bridge vector for WNV. Larval habitats include temporary grassy pools and artificial containers, though this species prefers natural habitats to artificial habitats.

Important WNV Vector Species in Pennsylvania

Identify the variables that most affect the abundance, competence, and distribution of WNV in PA

Overview of WNV in PA Analyze 6 years of data:

2003 and 2012 (high WNV incidence)2006 and 2007 (mid WNV incidence)2001 and 2011 (low WNV incidence)

Identify key WNV locations over the years

Identify temporal patterns of WNV (seasonality)

Describe vector populations (spatial, temporal, species)

Describe vector competence (spatial, temporal, species)Explore spatially varying relationships between WNV variables using GWR



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Proposed Methods



SciencesTemperature – Min, Max, Mean, Duration

Precipitation – Weekly/Monthly Sums and Means

Land Uses – Percentages by Spatial Units

Human Population Densities by Spatial Units

Vectors – Populations and Distributions by Temporal and Spatial Units

MIR – Mosquito Infection Rates

Potentially Significant Variables



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Data Sources

Landuse PopulationCadastral UnitsWatershed BoundariesHydrography

Precipitation Temperature Climate Normal SummariesClimate Forecasts

Vector ID Vector EnumerationsWNV Test ResultsHistorical/Future Treatments

Proposed Methodology:Geographically Weighted Regression (GWR)

Brunsdon, Fotheringham, and Charlton (1996)Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity

Spatial Autocorrelation

Tobler’s Law (1970)

Extension of multivariate regression that allows regression models to vary spatially

Allows the relationships between the independent variables to vary



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y = β +β x +ε 0 1 for i=1 … n



Sciences 𝑦𝑖 = 𝑏0 + 𝑏𝑗𝑚

𝑗=1 𝑥𝑖𝑗 + 𝜀𝑖

𝒚= 𝑿𝒃+ 𝒆

𝑦𝑖⋮𝑦𝑛൩ = 𝑥11 ⋯ 𝑥1𝑚⋮ ⋱ ⋮𝑥𝑛1 ⋯ 𝑥𝑛𝑚൩ 𝑏0⋮𝑏𝑚൩ + 𝜀1⋮𝜀𝑛൩

𝒃= ሺ𝑿𝑻𝑿ሻ –𝟏𝑿𝑻 𝒚 𝒃= ሺ𝑿𝑻𝑾𝑿ሻ –𝟏𝑾𝑿𝑻 𝒚


b = Regression Coefficientsy = Variable EstimatesW = Weighting Coefficients



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Kernel Function -Defines the shapeof the spatial weightingfunction (w)

W = 1

W = 0 D

*ArcMap uses a Gaussian function

Fixed Bandwidth

Adaptive Bandwidth



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Output feature class (estimates at regression points)

Model coefficient rasters for each variable

Diagnostic summary table

Prediction output feature class (estimates at locations other than regression points)



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Annual Land useTemperature (Mean)Population DensityWNV +ve mosquitoes

Adaptive Bandwidth

2003 Land useTemperature (Mean)Population DensityWNV +ve mosquitoes

Fixed Bandwidth

Exploratory Analysis and Results

Regression Coefficients



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Adaptive Bandwidth


Fixed Bandwidth


Estimate Standard Residuals



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Adaptive Bandwidth


Fixed Bandwidth


Estimate Residuals



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Adaptive Bandwidth


Fixed Bandwidth


Local R2 Statistic



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Annual LanduseTemperature (Mean)Population DensityWNV +ve mosquitoes

Adaptive Bandwidth

2003 LanduseTemperature (Mean)Population DensityWNV +ve mosquitoes

Fixed Bandwidth


Statistical Summary Tables



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Expected Results

A dataset of historical mosquito populations, competence, and species distribution merged with potentially relevant environmental data

Identify the environmental variables best suited to explain the historical distribution and intensity of WNV in PA

Develop a predictive GWR model using historical relationships between environmental variables and mosquito vectors, in order to estimate WNV response to future changes in climate, landuse, and human population dynamics



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Project Timeline

May2013

January2014

February2014

July2013

March2014

596 A Literature

review

596 B Complete

Data Analysis

596 A Peer Review

Cloud Server Class

Conference Presentation



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Selected References Blanford, J. I., Blanford, S., Crane, R. G., Mann, M. E., Paaijmans, K. P., Schreiber, K. V., et al. (2013). Implications of temperature variation for malaria parasite development across Africa. Scientific Reports , 3 (1300).

Brunsdon, C., Fotheringham, A. S., & Charlton, M. (1999). Some notes on parametric significance tests for geographically weighted regression. Journal of Regional Science , 39 (3), 497-524.

Brunsdon, C., Fotheringham, A. S., & Charlton, M. E. (1996). Geographically weighted regression: a method for exploring spatial nonstationarity. Geographical Analysis , 28 (4), 281-298.

Brunsdon, C., McClatchey, J., & Unwin, D. J. (2001). Spatial variation in the average rainfall - altitude relationship in Great Britain: an approach using geographically weighted regression. International Journal of Climatology , 21, 455-456.

Charlton, M., & Fotheringham, A. S. (2009). Geographically Weighted Regression (White Paper). National University of Ireland Maynooth. Maynooth, Ireland: National Center for Geocomputation.

PAWNVCP. (2013). Pennsylvania's West Nile Virus Control Program. Retrieved May 18, 2013, from http://www.westnile.state.pa.us/index.html

Reisen, W. K., Fang, Y., & Martinez, V. M. (2006). Effects of temperature on the transmission of West Nile virus by Culex tarsalis (Diptera:Culicidae). Journal of Medical Entomology , 43 (2), 309-317.

http://www.westnile.state.pa.us/index.html



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Selected References Reisen, W. K., Thiemann, T., Barker, C. M., Lu, H., Carroll, B., Fang, Y., et al. (2010). Effects of warm winter temperature on the abundance and gonotrophic activity of Culex (Diptera:Culicidae) in California. Journal of Medical Entomology , 47 (2), 230-237.

Ruiz, M. O., Tedesco, C., McTighe, T. J., Austin, C., & Kitron, U. (2004). Environmental and social determinants of human risk during a West Nile virus outbreak in the greater Chicago area, 2002. International Journal of Health Geographics , 3 (8).

Kilpatrick, A. M. (2011). Globalization, Land Use, and the Invasion of West Nile Virus. Science , 334, 323-327.Kilpatrick, A. M., Daszak, P., Jones, M. J., Peter, P. M., & Kramer, L. D. (2006). Host heterogeneity dominates West Nile virus transmission. Proc Biol Sci , 273, 2327-2333.

Kilpatrick, A. M., Fornseca, D. M., Ebel, G. D., Reddy, M. R., & Kramer, L. D. (2010). Spatial and temporal variation in vector competence of Culex pipiens and Culex restuans mosquitoes for West Nile virus. Am J Trop Med Hyg , 83 (3), 607-613.

Kilpatrick, A. M., Meola, M. A., Robin, M. M., & Kramer, L. D. (2008). Temperature, viral genetics, and the transmission of West Nile virus by Culex pipiens mosquitoes. Plos Pathogens , 4 (6).

Chaves, L. F., Hamer, G. L., Walker, E. D., Brown, W. M., Ruiz, M. O., & Kitron, U. D. (2011). Climatic variability and landscape heterogeneity impact urban mosquito diversity and vector abundance and infection. Ecosphere , 2 (6).



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Acknowledgements Dr. Justine Blanford

Michael Hutchinson - PA West Nile Virus Control Program

Andrew Kyle - PA West Nile Virus Control Program

James Haefner - PA West Nile Virus Control Program

Matt Helwig - PA West Nile Virus Control Program

Dr. Doug Miller

Beth King



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Questions

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Department of Geography College of Earth and Mineral Sciences