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Sensitivity is defined as the proportion of true positives correctly predicted (e.g., the percentage of locations where mosquito presence is correctly predicted), whereas specificity is the proportion of true negatives correctly predicted (e.g., the percentage of locations where mosquito absence is correctly predicted) (Fielding and Bell 1997, Phillips et al. 2006, Phillips and Dudik 2008). A model with perfect discrimination between presence and absence will have an AUC of 1.0. As a general rule, an AUC between 0.5 and 0.7 indicates a poor discriminative capacity; 0.7-0.9 indicates a reasonable capacity; and > 0.9 indicates a very good capacity (Brooker et al. 2001, Phillips et al. 2006, Phillips and Dudik 2008). The distribution map resulting from the “best model” (highest AUC) represents the best approximation of the species‟ realized niche, as a function of the given environmental variables of the study area. This map was subsequently exported to ArcGIS 9.2 for use in the development of a Virginia RVF risk map. 3.7 VIRGINIA RIFT VALLEY FEVER RISK MAP DEVELOPMENT A weighted suitability model was developed using the ArcGIS Spatial Analyst extension to create risk maps that visually represent the variation in risk of RVF virus establishment across Virginia and risk of RVF transmission to humans in Virginia. RVF virus establishment and transmission to humans is likely to occur where competent mosquito vectors are present near host populations. Therefore, the model included the MaxEnt Mosquito Habitat Suitability model as the layer representing competent vector mosquito distribution in Virginia and three layers representing competent host (domestic animal, wildlife, and human) density in Virginia. The domestic animal layer, created using the Map 79
Algebra tool in the ArcGIS Spatial Analyst extension, included county level combined numbers of cattle, sheep and goat per square mile (Figure 3.10). Figure 3.10. Domestic Animal Density in Virginia. The map shows the density of domestic animals (cattle, sheep, and goats) in Virginia as the number of animals per square mile by county. The data is categorized and displayed in 8 quantiles. Density data for Maryland and the District of Columbia is also included. In the weighted suitability model, each data layer was first reclassified on a relative scale (0-9 scale) in order to allow comparison between the variables. Each reclassified layer was then multiplied by a weight that indicates its estimated relative importance in RVF virus establishment or RVF virus transmission to humans. The weights summed to 1.0 so that the weight of a layer was equivalent to the percentage importance of each category in the final model. This process was somewhat subjective, based on a review of RVF literature related to 80
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Using Remote Sensing, Ecological Ni
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DEDICATION This is dedicated to my
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Lastly, I would like to thank all o
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CHAPTER 4: RESULTS ................
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LIST OF FIGURES Figures Page 2.1 Kn
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AUC - Area Under the Curve LIST OF
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ABSTRACT USING REMOTE SENSING, ECOL
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Keywords Rift Valley fever, risk as
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systematically inventory and monito
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populations), human demographics an
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The geographic distribution of pote
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human and animal health, economic l
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1.8 ORGANIZATION OF DISSERTATION Th
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(e.g., ether, chloroform), detergen
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(Imam et al. 1979, Davies and Marti
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have demonstrated that wild ruminan
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flooding of grassland depressions c
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and created mosquito breeding habit
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may transmit the RVF virus mechanic
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virus during inter-epizootic period
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grown by nearly 9% per year (Tatem
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Page 45 and 46: sufficient and continued contact be
Page 47 and 48: Environmental factors are directly
Page 49 and 50: animals could arrive in an uninfect
Page 51 and 52: GIS technology and RS data has been
Page 53 and 54: NDVI is calculated as a normalized
Page 55 and 56: In September 2006, the RVF forecast
Page 57 and 58: In the U.S. RVF is not present and
Page 59 and 60: changes in mosquito populations in
Page 61 and 62: hosts that are widely dispersed thr
Page 63 and 64: mountain range of the Appalachian M
Page 65 and 66: The land area of Hampton Roads incl
Page 67 and 68: 52 Table 3.1. Primary data sets and
Page 69 and 70: Table 3.2. Sources of Virginia mosq
Page 71 and 72: Figure 3.3. Cattle Density in Virgi
Page 73 and 74: Figure 3.6. 2006 Deer Abundance Est
Page 75 and 76: Land-Cover Global land-cover data a
Page 77 and 78: Figure 3.8. Virginia Land-cover Nor
Page 79 and 80: Figure 3.9. June 2006 Normalized Di
Page 81 and 82: Table 3.4. Worldclim interpolated c
Page 83 and 84: 3.2.5 DATA PROCESSING All data sets
Page 85 and 86: normalize differences among surveil
Page 87 and 88: for three regions of Virginia - Nor
Page 89 and 90: Correlation analyses The Pearson‟
Page 91 and 92: of maximum entropy (i.e., that is m
Page 93: When test data are available, MaxEn
Page 97 and 98: CHAPTER 4. RESULTS 4.1 POTENTIAL RV
Page 99 and 100: 1. If a native U.S. vector can tran
Page 101 and 102: Bioecology of Species Selected for
Page 103 and 104: ditches, animal waste lagoons, and
Page 105 and 106: 90 Mosquito Species Typical Habitat
Page 107 and 108: The majority of mosquitoes were col
Page 109 and 110: Table 4.5. Virginia competent vecto
Page 115 and 116: 4.3 MOSQUITO DENSITY CORRELATIONS W
Page 117 and 118: 102 Table 4.8. Mean and range of ea
Page 119 and 120: Regional graphical analyses In Figu
Page 121 and 122: Population Density (mean daily trap
Page 125 and 126: Competent vector species were plott
Page 129 and 130: Predictor correlation analyses Whil
Page 131 and 132: temperature of the coldest month (b
Page 133 and 134: data. Mosquito populations tend to
Page 135 and 136: 120 Predictor Variable Northern Vir
Page 137 and 138: 122 was 0.003. At this threshold, t
Page 139 and 140: 124 The Jackknife test of variable
Page 141 and 142: 126 4.5 RISK OF RVF ESTABLISHMENT A
Page 143 and 144: 128 The weighted suitability modeli
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CHAPTER 5. DISCUSSION 5.1 ENVIRONME
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heavily on rainfall as do the predo
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5.2 ENVIRONMENTAL-CLIMATIC VARIABLE
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study; predicted suitable habitat w
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state. The high risk in this region
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The results of this study indicate
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It is recommended that species dive
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individually and over smaller time
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146 APPENDIX A: RVF COMPETENT VECTO
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148 Figure A.3. Ae. sollicitans dis
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150 Figure A.5. Ae. triseriatus dis
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152 Figure A.7. Cx. pipiens distrib
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154 Figure A.9. Cx. salinarius dist
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Desiccation - drying. Diapause - ph
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Larva - immature form of certain or
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Vector competence - the vector comp
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REFERENCES Ackerman GA, Giroux J. A
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Brown H, Duik-Wasser M, Andreadis T
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Diallo M, Nabeth P, Ba K, Sall AA,
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Glass GE, Cheek JE, Patz JA, Shield
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Komar O, Robbins MB, Klenk K, Blitv
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NASA Earth Observatory (EO) Measuri
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Phillips SJ, Dudík M, Schapire RE.
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Tatem AJ, Hay SI, Rogers DJ. Global
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WHO Disease Outbreak News [Internet
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