Risk of Exposure to Eastern Equine Encephalomyelitis Virus Increases with the Density of Northern Cardinals

<div><p>For a variety of infectious diseases, the richness of the community of potential host species has emerged as an important factor in pathogen transmission, whereby a higher richness of host species is associated with a lowered disease risk. The proposed mechanism driving this pattern is an increased likelihood in species-rich communities that infectious individuals will encounter dead-end hosts. Mosquito-borne pathogen systems potentially are exceptions to such “dilution effects” because mosquitoes vary their rates of use of vertebrate host species as bloodmeal sources relative to host availabilities. Such preferences may violate basic assumptions underlying the hypothesis of a dilution effect in pathogen systems. Here, we describe development of a model to predict exposure risk of sentinel chickens to eastern equine encephalitis virus (EEEV) in Walton County, Florida between 2009 and 2010 using avian species richness as well as densities of individual host species potentially important to EEEV transmission as candidate predictor variables. We found the highest support for the model that included the density of northern cardinals, a highly preferred host of mosquito vectors of EEEV, as a predictor variable. The highest-ranking model also included <i>Culiseta melanura</i> abundance as a predictor variable. These results suggest that mosquito preferences for vertebrate hosts influence pathogen transmission.</p> </div

Association between EEEV exposure and <i>Cs. melanura</i> abundance.

<p>Added-variable plot showing the relationship between EEEV exposure risk in chickens during 2009 and 2010 and <i>Culiseta melanura</i> abundance at 24 sentinel sites in Walton County, Florida. The estimate for the slope of EEEV exposure risk regressed on <i>Cs. melanura</i> was 0.0028 with a 95% UCI of (−0.0012, 0.0058). <i>Cs. melanura</i> abundance residuals = residuals from regression of northern cardinal density on <i>Cs. melanura</i> abundance, EEEV exposure risk residuals = residuals from regression of EEEV exposure risk residuals on <i>Cs. melanura</i> abundance. The best-fit line from simple linear regression of EEEV exposure risk residuals on northern cardinal density residuals are overlaid, with the solid line fit to the full dataset, and the dashed line fit to the dataset that excluded the influential observation shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057879#pone-0057879-g003" target="_blank">Figure 3</a>.</p

Walton County, Florida.

<p>Circles represent sentinel traps locations, where turquoise represents sites where EEEV exposure risk in sentinel chickens ≤0.010 seroconversions/chicken-week (median seroconversion incidence rate) and pink represents sites where EEEV exposure risk >0.010 seroconversions/chicken-week. Yellow star shows location of DeFuniak Springs, the Walton County seat. Subsetted image shows the location of Walton County within the state of Florida.</p

Importance weights and results of model averaging for predictor variables in spatial modeling of EEEV exposure risk in sentinel chickens in Walton County, Florida in 2009 and 2010.

<p>Results below the dotted line are based on the development of models using the dataset that excluded an influential observation.</p><p>Variable names: mel = Culiseta melanura abundance, avian = avian species richness, EUST = European starling density, NOCA = northern cardinal density.</p

Association between annual <i>Culiseta melanura</i> abundances.

<p>Scatterplot showing the relationship between <i>Cs. melanura</i> abundance from April to October 2009 at 24 sentinel sites in Walton County, Florida with <i>Cs. melanura</i> abundance from the same sentinel sites and the same sampling period during 2010. Abundances from the two years are highly correlated (Spearman Rank Test, r_S = 0.63, p = 0.001). The best-fit line from simple linear regression is overlaid.</p

Association between EEEV exposure and northern cardinal density.

<p>Scatterplot showing the relationship between EEEV exposure risk in chickens during 2009 and 2010 and northern cardinal density at 24 sentinel sites in Walton County, Florida. The estimate for the slope of exposure risk regressed on northern cardinal density was 0.006 with a 95% UCI of [0.0025, 0.0107]. This estimated slope, when an influential observation (indicated by the arrow) was removed from the dataset, was 0.004 [−0.001, 0.009]. The best-fit line from simple linear regression of exposure risk residuals on northern cardinal density are overlaid, with the solid line fit to the full dataset, and the dashed line fit to the dataset that excluded the influential observation.</p