Socioecology of Aedes Fever Virus Vectors Ari Whiteman & Tyler - - PowerPoint PPT Presentation
Socioecology of Aedes Fever Virus Vectors Ari Whiteman & Tyler Rapp Nature and Human Health: Vectors and Climate Change Monday, November 6, 2017 Background Mosquito-borne illnesses are increasing as a result of climate change,
Ari Whiteman & Tyler Rapp Nature and Human Health: Vectors and Climate Change Monday, November 6, 2017
Background
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Mosquito-borne illnesses are increasing as a result of climate change, urbanization, and globalization
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Charlotte has moderate to high potential for viral activity as a result of these three factors
Figure 1. Average temperature across the US Figure 2. Airport routes from Charlotte Douglas International Airport
Objectives
1)
Determine the fine-scale spatiotemporal hotspots of Aedes mosquito activity in Mecklenburg County
2)
Determine the effect of a socioeconomic variation on regional urban mosquito abundance
3)
Model habitat suitability that can be used to direct vector surveillance and control efforts
Figure 3. Examples of mosquito-breeding areas/containers
Socioeconomic Status & Mosquito Abundance?
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Previous studies1 have shown that:
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There is more urban decay in low-income areas
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Urban decay is linked with more unused containers à accumulate water when it rains à prime breeding spots
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There are less mosquito-borne illnesses in high- income regions
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Hypothesis:
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In low-income residential areas, the abundance
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This study is unique in its selection of sites in regards to strictly residential areas with similar population density and a large geographical range
Figure 4. Examples of mosquito- breeding containers
1Becker, Leisnham, LaDeau, 2014; LaDeau, et al., 2013; Dowling, et al., 2013 Methods: Site Selection
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Optimization procedure to select the census tracts
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Varying socioeconomic, infrastructure-based, and environmental variables
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One trap was placed in the center of each tract
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Two were placed in the nine tracts in the upper quartile of population density giving 90 traps total Figure 5. Residential units density map
Methods: Traps
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Gravid Aedes Traps
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Attract gravid (pregnant) container-breeding mosquitoes by:
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Hay-infused water
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Black color (more heat)
Figure 6. Gravid Aedes Trap
Methods: Sampling Scheme
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Traps were checked
May 26 - August 21
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Each mosquito specimen was identified to species and counted
Methods: Data Analysis
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Analyzing numerous socioeconomic, environmental, and land-cover based variables on the amount of mosquitoes caught at each site
Figure 7. Charlotte-Mecklenburg Rainfall Network map
Results
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Over 4,000 mosquitoes were caught during the study
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No Aedes aegypti were found
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86% caught were Aedes albopictus
100 200 300 400 500 600
Total Samples Collected Weeks
Figure 8. Mosquito samples collected
period (May 26 – August 21)
May June August July
Species Distribution
86.19%
4.82% 0.87% 0.81% 5.72% 0.87% 0.35% 0.35%
13.79%
Figure 9. Distribution of mosquito species caught over the entire study
Preliminary Models
Figure 10. Map of mean samples caught over a 12 week period (May 26 – August 21)
Preliminary Models
Figure 11. Regression of mean samples caught by SES percentile
5 10 15 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Mean Samples Caught Per Site Per Week SES Percentile
Regression of mean samples caught by SES percentile (R² = 0.065, p = 0.001, Coef. = -5.51)
Model(Mean)
Considerations
Sampling Design:
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Innovative – but not yet validated
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Higher margin of error due to lower density covered per “region”
Figure 12. Map of Mecklenburg County
Conclusion: Key Takeaways
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Aedes albopictus was nearly the sole mosquito caught
week study
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Varying geographic densities
throughout the county
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While currently weak, there is a statistically significant correlation between socioeconomic status and mosquito abundance
Conclusion: Next Steps
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Primary investigator is currently completing a comparative study in Panama City, Panama
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Further analyses (blood meal analysis, investigating more variables, etc.) upon his return
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Plan to release a full, comprehensive report to the Mecklenburg County Health Department by the end of spring
Acknowledgments
I would like to thank:
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Ari Whiteman, Primary Investigator
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Collection Volunteers
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Mecklenburg County Health Department
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Academy for Population Health Innovation (APHI)
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Smithsonian Institution
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The Levine Scholars Program at UNC Charlotte
*NOT in actual presentation – only for supplement
Aedes Genus
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Aedes albopictus: vector of dengue, yellow fever, and possibly Zika in the wild (more diseases under lab conditions)
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Aedes vexans: can transmit Eastern equine encephalitis (EEE), Western equine encephalitis (WEE), Saint Louis encephalitis (SLE), West Nile virus, and dog heartworm
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Aedes japonicus: can transmit West Nile virus
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Aedes triseriatus: can transmit LaCrosse strain of California encephalitis and more (such as yellow fever) under lab conditions
Culex Genus
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Culex pipiens: has been found naturally infected with Sindbis virus, WNV in Israel and Egypt, etc.
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Culex restuans: vector of SLE and WNV
Variables Used in Optimization Procedure
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Variables
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Home sale prices
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Percent of residents with a bachelor’s degree
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Household income
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Employment rate
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Tree canopy cover
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Violent crime rate
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Foreclosure rate
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Percent Hispanic and percent black
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Percent of land cover vacant
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Proximity to a park
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All variables were independent – not correlated
Additional Variables Being Studied Later
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Environmental Variables (about 100m around each trap):
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Type of land surrounding (satellite imagery)
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Amount of vegetation around
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Property occupancy
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Amount of trash present
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SES:
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Income
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Housing values (real estate data)
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Both environmental variables and SES variables will be in relation to the abundance of mosquitoes caught at each site