1 of 1

Acknowledgments

Temporal and Spatial Understanding of Culex Restuans and C. Pipiens in Fairfax County, Virginia

Discussion

James Dunbar

Department of Geography and the Environment, Villanova University

Research Mentors: Dr. Nathaniel Weston

Fairfax County Methodology

• Mosquitos Culex Restuans and C. Pipiens are abundant in northern Virginia. Combined species into Culex Spp
• C. Spp have different seasonal presence and vector development, but are not biologically different enough to identify
• Transport vector borne diseases like West Nile Virus (WNV)
• Habitat includes stagnant water bodies, anthropogenic containers, any water quality, with incubation periods of at least 4 days (Crans 2014)
• This project Identified predictors for species volume and positive WNV pools during an epiweek over the mosquito season
• Female gravid mosquitos were targeted over six years through the usage of fermented water and catching traps
• Analyzed over 24,000 collection points to understand the population across six years of weather and land use data
• See if there are trends that can influence the Health Department’s work on where and when they do surveillance testing

Figure 2. Total of positive Culex pools per epiweek across the respective collection sites each year. Positive mosquitos appear being around beginning of July and tail off around October.

Figure 6. Shows the comparison of total annual collection of Culex and positive pools. There appears to be very little correlation and one can not predict the other. R²=0.039

Table 1. Shows the equations derived from a regression analysis for significance of temperature and precipitation.

^A Cumulative precipitation (in) 6 weeks prior to sampling

^B Averaged temperature (C) during sampling week and week prior

^C Developed Open Space % of total ½ mile buffer on sites

^D Developed Low-Intensity % of total ½ mile buffer on sites

^E Developed Medium-Intensity % of total ½ mile buffer on sites

^F Culex collected at a respective site

I want to thank the Fairfax County Health Department, particularly Joshua Smith, Lauren Lochstampfor, and Rachel Kemf for their assistance with project development, data sharing, and industry insight. I want to thank Dr. Weston for his invaluable mentorship experience and assistance with this project.

• Utilization of Reiter-Cummings Modified Gravid Trap
• Activating the trap and collecting the trap pods 24 hours later
• Pods are placed into a deep freezer until ready to be sorted
• Catch sorted and C. Spp. summed into groups of 5-50
• Groupings are recorded, placed into testing tubes, and placed back into freezer until they are sent off to be PCR tested for WNV
• Data was recorded on a standardized calendar system of epiweeks

• ”Freedom of Information Act” the Fairfax County Health Department for the last 6 years of their gravid trap collecting Culex data and WNV
• When trapping locations were moved, I averaged the GPS coordinates for the new location, as seen in figures 4 and 5
• Accessed USGS weather data at the Vienna Station, assuming the precipitation and temperature data to be representative of all testing locations
• Used National Land Coverage Data to identify 15 types of usage
• Trap sites were set with a ½ mile buffer to identify land usage
• Temporal regression analysis at 2-8 weeks, using average temperature and cumulative precipitation
• Trial and error to isolate the most predictive variation of timescales for precipitation and temperature
• Used SSPS (IBM) to find the most significant land usage for predicting Culex and WNV.

​

​

My Methodology

Figure 4. Shows spatial distribution of Culex across Fairfax County. There is heavy presence in developed open and low intensity land usage, and along the border of Washington D.C.

Figure 5. Shows spatial distribution of positive WNV pools across Fairfax County. There is heavy presence in developed low- and medium-intensity land usage.

Table 2. shows the equations derived from a regression analysis for significance of land usage and Culex population.

Figure 1. Total of collected Culex per epiweek across the respective collection sites each year. Trapping has the most volume seen during the summer months, with volume peaks again in late September and October.

Crans, Wayne. “Culex Restuans Theobald.” Mosquito Biology: Rutgers Center for Vector Biology, 2014,

https://vectorbio.rutgers.edu/outreach/species/rest.htm. 

Giordano, Bryan V., et al. “West Nile Virus in Ontario, Canada: A Twelve-Year Analysis of Human Case

Prevalence, Mosquito Surveillance, and Climate Data.” PLOS ONE, 2017, Public Library of Science,

https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0183568.

Ruiz, Marilyn O, et al. “Local Impact of Temperature and Precipitation on West Nile Virus Infection in

Culex Species Mosquitoes in Northeast Illinois, USA.” Parasites & Vectors, BioMed Central, 19 Mar.

2010, https://parasitesandvectors.biomedcentral.com/articles/10.1186/1756-3305-3-19. 

​

​

• I found Culex and WNV was higher during times with increased temperature and precipitation, and in areas characterized by developed land use.
• Need to assume some uncertainty by using only one weather station and it not being reflective of local weather conditions.
• Positive Culex Spp. collected are the strongest predictor of seeing WNV present in human (Giordano 2017)
• One of the largest WNV peaks was around epiweek 33. This is similar to an Ontario study that found an epidemic peak in cases at epiweek 34 (Giordano 2017).
• Temperature was more predictive in Culex compared to precipitation data. This is supported through another study where they found temperature able to predict about 80% of species population (Ruiz et al, 2010).
• There should be further studies to look at more localized environmental trends, and to compare both temporal and spatial data together

• There are seasonal trends of the Culex population and associated West Nile Virus in Fairfax County
• There is no direct relationship between Culex species presence and WNV positivity detection
• There are other factors that can influence these variables:
• Cumulative precipitation and average temperature are significant predictors of Culex and WNV
• Significant precipitation was 6 weeks stretch before trapping
• Significant temperature was the week of trapping and (n-1)
• Land development significantly affects both variables as well
• Developed open and low-intensity land coverages were the most significant land types for predicting Culex
• Developed low- and medium-intensity, along the with Culex population, were the most significant with predicting WNV

​