Urbanization, Land Cover, Weather, and Incidence Rates of Neuroinvasive West Nile Virus Infections In Illinois

Transcription

1 Urbanization, Land Cover, Weather, and Incidence Rates of Neuroinvasive West Nile Virus Infections In Illinois JUNE 23, 2016 H ANNAH MATZ KE Background Uganda 1937 United States New York Quickly Spread Westward Illinois Cases, 64 Deaths Within Illinois: June-September Year to year variability Spatial variability 1 2 Transmission Cycle Vector-Mosquitoes Detected in 65 species Genus Culex Culex pipiens Culex restuans Reservoir-Birds Detected in over 300 species Birds from Order Passeriformes American Crows Blue Jays Photo Source: Yavapai County Department of Public Health Determinants of WNV Rates - Land Cover Some types of land cover are associated with higher Culex pipiens population density Wetlands (Medlock et al 2011, Johnson et al 2015) Forested Lands (Gardner et al 2014) Crops (Wimberly et al 2009, Rosà et al 2014) Elevation range (Liu et al 2008) Determinants of WNV Rates - Weather Temperature Increase season length of Culex pipiens mosquitoes (Rosà et al 2014) Decreased extrinsic incubation period (Riesen et al 2006) Warm winter (Wimberly et al 2014) Precipitation Increase in population density of Culex pipiens (Rosà et al 2014) Other Weather Wet spring & hot dry summer (Wimberly et al 2010, Midwest Regional Climate Center) Drought induced amplification (Johnson et al 2013) 5 6 1

2 Determinants of WNV Rates - Urbanization Create micro-environments ideal for Culex breeding Artificial Water Containers (Townroe et al 2014) Swimming Pools (Reisen et al 2009, Fischer et al 2010) Urban Nature (Quiroga et al 2013) Overwintering Habitats (Nasci et al 2001) Rural to Urban Continuum Code for Illinois Counties 7 8 Objectives Evaluate Effect of Land Cover on Incidence Rates of Neuroinvasive West Nile Virus Infections Evaluate Effect of Temperature on Incidence Rates of Neuroinvasive West Nile Virus Infections Evaluate Effect of Precipitation on Incidence Rates of Neuroinvasive West Nile Virus Infections Evaluate Effect of Urbanization on Incidence Rates of Neuroinvasive West Nile Virus Infections Are the observed associations different in rural versus urban counties? Data Sources Land Cover Illinois Geospatial Data Clearinghouse Elevation Illinois Geospatial Data Clearinghouse Weather Midwest Regional Climate Center National Oceanic and Atmospheric of Association Illinois West Nile Virus Surveillance Illinois Department of Public Health Data from Surveillance was de-identified and UIC IRB determined this is not human subject research Considerations Aggregation of spatial data -County Level Aggregation of temporal data -Annual Incidence Rates -Seasonal Weather No changes in land cover from Methods: Univariate and Bivariate Single Variable Mean, Median, Standard Deviation, Skewness, Kurtosis, and Missing Data Frequency Counts & Histograms Temperature Imputation Validation of imputation method Outcome and One Variable Land Cover & Urbanization: 12 year incidence rates Weather: Annual incidence rates Evaluate Collinearity

3 Mean Sumer Temperature (F) 7/11/2016 Methods: Model Building Regression Simultaneously models: rates and zeroes Pseudo-forward selection Goodness-of-fit Deviance Log Likelihood Stratified by Urbanization o Urban and Suburban Counties o Rural Counties Mean: 0.52 Variance 3.96 Results NWNV Surveillance Neuroinvasive West Nile Illinois Virus Cases N=1301 % (n) % Age <20 Years Old 3.9 % (51) 27.30% Years Old 28.8% (375) 41.50% >50 Years Old 67.3% (875) 31.30% Gender Female 49.4% (643) 51.00% Male 50.6% (658) 49.00% Status * Deceased 10.9% (134) Alive or Missing 90.8% (1090) * >5% missing or unknown values Results Land Cover Percent Wetland Population Density Results Land Cover Results Temperature Percent Surface Water Percent Forested Area 82 Mean Summer Temperature by Climate Division Image Source: Midwest Regional Climate Center Year

4 Total Summer Precipitation (Inches) 7/11/2016 Results - Precipitation Results - Single Association Total Summer Precipitation by Climate Division 12 YEAR RATE & LAND COVER ANNUAL RATE & WEATHER Series1 Series2 Low Intensity Developed Land Wooded Wetland (decrease) Total Fall Precipitation Mean Maximum Winter Temperature Mean Minimum Winter Temperature Series3 Series4 Series5 Series6 Series7 Herbaceous Wetland (decrease) All Developed Land Types Mean Winter Temperature Mean Maximum Spring Temperature Squared 100 Series8 Series9 All Wetland Types (decrease) Mean Minimum Spring Temperature 0 Mean Spring Temperature Year Mean Minimum Summer Temperature Squared Image Source: Midwest Regional Climate Center Mean Summer Temperature Squared Results Regression Variables Predicting Rates Urban counties - lower rates Counties with a higher percent of population over 50 - higher rates Years with warm winter - higher rates Years with warm summer- higher rates Results Stratified Urban and Suburban Counties Variables Predicting Rates Counties with a larger percent of population over 50 - higher rates Years with warm winter - higher rates Counties with a larger percent of cropland higher rates Counties with a larger percent of developed land higher rates Variables Predicting Zero Rates: Urban County, Percent of Population Over 50, Mean Minimum Winter Temperature, Mean Maximum Spring Temperature, Total Precipitation Preceding Fall Variables Predicting Zero Rates: Percent of Population Over 50, Population Density, Total Precipitation Preceding Fall, First Year Results Stratified Rural Counties Variables Predicting Rates Counties with a larger percent of developed land lower rates Sensitivity Analysis Final model results for whole state compared to dataset with: Excluded Imputed Temperatures Excluded Cases from 2002 Excluded Cases from Cook County No significant change in any results Variables Predicting Zero Rates: Percent Open Water, Percent Wetlands, Mean Winter Temperature, Minimum Spring Temperature, Minimum Spring Temperature Squared

5 Discussion Objective 1: Land Cover No significant associations Objective 2: Temperature Warm Winter Warm Summer Objective 3: Precipitation No significant association Objective 4 and Objective 5: Urbanization Developed Land Strengths and Limitations STRENGTHS Neuroinvasive infections are nearly 100% reported First study to look at factors associated with neuroinvasive WNV rates Consistency results for each sensitivity analysis LIMITATIONS Unknown location of viral transmission Counties with small population size Inflated Rates Ecological Fallacy Aggregation of time Aggregation to county Lack of data Built environment Mosquito abatement Bird surveillance Climate Change Climate change can effect West Nile Virus transmission Longer Seasons Wider Geographic Spread 2014 National Climate Assessment Warmer Temperatures Projected Temperature Change with Lowered Emission of Greenhouse Gases Prevention There is no human WNV vaccine Community Level Identify when risk is particularly high Annual West Nile Virus prevention plan Mosquito abatement Educate residents on risk and prevention Personal Level Bug spray Long sleeve shirts and Pants Dump containers holding standing water Photo Source: Other Mosquito Transmitted Viruses Results do not directly translate Research methods can be applied Different transmission dynamics Different Mosquitoes Different Reservoir Photo Source: West Nile vs. Zika Virus Same Family of Virus Flavivirus Different mosquito vector Aedes aegypti Different reservoir Primates Most asymptomatic infections Photo Source:

6 Acknowledgements There are no conflicts of interest to report. This work was conducted as part of the Building Resilience Against Climate Effects in Illinois (BRACE-IL) project This work was supported by the Cooperative Agreement Number, 5UE1EH , funded by the CDC. The University of Illinois at Chicago is agent for the Illinois Department of Public Health for the BRACE project. Thank You Special thank you to my committee members for assistance and guidance through the research process. Chair: Dr. Sam Dorevitch Committee: Dr. Mark Dworkin, Dr. Lee Friedman, & Dr. Jyotsna Jagai