Using GIS: to analyze vector borne disease. David Attaway Esri

Transcription

1 Using GIS: to analyze vector borne disease David Attaway Esri

2 Why do I care?

3 Example: YELP Most of us have used it Most of us let it help guide our decisions Most see it helpful But. How does this relate to Medical Geography?

4 When we search for Restaurants. Behind the scenes: All locations are being RANKED

5 When we search for Pizza. Behind the scenes: All locations are being RANKED

6 How about we do this with GIS?

7 Similarity Search identifies which candidate features are most similar or most dissimilar to one or more input features based on feature attributes

8 potential store locations

9 potential store locations high performing store

10 LocID PopDensity AvIncome DistToCompetition Rank by how similar they are to based on: LocID PopDensity AvIncome DistToCompetition

11 LocID PopDensity AvIncome DistToCompetition Rank by how similar they are to based on: PopDensity AvIncome DistToCompetition LocID PopDensity AvIncome DistToCompetition

12

13

14 Methodology Similarity Search Model - Dengue Utilize Similarity Search: Elevation Population density Bioclimatic variables Standardize variables Run model in ArcGIS (1) (2) Layer ALT BIO1 BIO2 BIO4 BIO5 BIO6 BIO9 BIO10 * BIO12 BIO13 BIO14 BIO15 BIO19 LNDSCN_POP Description Elevation data Annual mean temperature Mean diurnal range (mean of monthly (max temp - min temp)) Temperature seasonality (standard deviation *100) Max temperature of warmest month Min temperature of coldest month Mean temperature of driest quarter Mean temperature of warmest quarter Annual precipitation Precipitation of wettest month Precipitation of driest month Precipitation seasonality (coefficient of variation) Precipitation of coldest quarter 2011 Landscan population density data

15 Mosquito Locations (365 Survey sites 167 cells) Dengue Outbreaks ( ) (4 Locations 120 Cells) Elevation Data Similarity Search Tool Population Density Bioclimatic Layers Similarity Search based on averages of 287 points Similarity Search based on 287 individual iterations Similarity Search Averages Map Comparison Discussion and Results Similarity Search 287 Iterations Combined Map

16 Factor Parameters Count Total UNIVARIATE MODELS Percentage Included Elevation ALT 1800 (meters) % Minimum Temperature MinTemp 100 (10 C) % Human Population Density* POP > % Land Cover (2009) GLC 11 (Irrigated Crops) AND GLC 190 (Artificial areas) % Maximum Temperature MaxTemp 300 (30 C) % Max Precipitation Average BIO13 > 0, BIO16> 0, AND BIO (55mm) % Distance from Water** WBD 200km % Min Precipitation Average BIO14 > 20 (.2mm) AND BIO17 > % BIVARIATE MODELS Elevation AND Min Temp ALT 1800 (meters) AND MinTemp 10 C % Min Temp AND Population* MinTemp 10 C AND POP > % Elevation AND Max Temp ALT 1800 (meters) AND MaxTemp 30 C % Land Cover AND Population* GLC 11 (Irrigated Crops) AND GLC 190 (Artificial areas) AND POP > % Max Temp AND Human Population Density* MaxTemp 30 C AND POP > % Land Cover AND Min Temp GLC 11 (Irrigated Crops) AND GLC 190 (Artificial areas) AND MinTemp 10 C % Elevation AND Population* ALT 1800 (meters) AND POP > % Land Cover AND Max Temp GLC 11 (Irrigated Crops) AND GLC 190 (Artificial areas) AND Max Temp 300 (30 C) % Elevation AND Max Precipitation ALT 1800 (meters) AND MaxPrecip Avg Parameters % Min Temp AND Max Precip MinTemp 10 C AND MaxPrecip Avg Parameters % Elevation AND Precip (Max OR Min) ALT 1800 (meters) AND MaxPrecip Avg Parameters OR MinPrecip Avg Parameters % Land Cover AND Max Precipitation GLC 11 (Irrigated Crops) AND GLC 190 (Artificial areas) AND MaxPrecip % Max Temp AND Max Precip MaxTemp 30 C AND MaxPrecip Avg Parameters % MinTemp AND MinPrecip MinTemp 10 C AND MinPrecip Avg Parameters % Land Cover AND Min Precipitation GLC 11 (Irrigated Crops) AND GLC 190 (Artificial areas) AND MinPrecip Avg Parameters %

17 Results 195,573, ,442 Points Points (! Mosquito and Outbreak Reference Points SIMRANK High : 100% Low : 0% _^( _^ Capital Major Towns Major Roads Waterbodies Countries

18 Predictive Analysis

19 ArcGIS Predictive Analysis Tools Add-In Capabilities Predictive Analysis Tools Predict suitable locations, and travel routes Extremely fast to accommodate iterative analysis Auto-generate analysis based on historic data Repeatable and shareable workflows Easy to use

20 Versatility Predictive Analysis Tools

21

22

23

24 Results: Africa PA Tools Analysis Allowed determination in Africa for: High suitable Somewhat suitable Limited suitability Highly unsuitable Not suitable Increased efficiency Provided localized analysis (1km x 1km) Model can easily be modified as conditions change

25 Comparison QFIT vs. Query Editor Expression Models Human population density Localized analysis (1km x 1km) Model easily modified Red - Limited the spatial bias Red - Captured 67% of reported dengue data Red - Captured 83% of reported dengue data w/ 3km buffer Blue - Captured 86% of reported dengue data

26 Method that draws on temperature, precipitation, elevation, land cover, and population density variables to identify locations suitable for mosquito activity year-round.

27