Pearson correlations (r) for fixed effect variables used in our modeling exercises.

<p>First, we examined if the detection of <i>Trueperella pyogenes</i> on one mucosal layer was associated with higher chance of detecting it at other mucosal layers. White-tailed deer were sampled along the forehead, nose, and tongue for presence of <i>T</i>. <i>pyogenes</i>. The prevalence of <i>T</i>. <i>pyogenes</i> on these mucosal layers across deer sampled at each site was used as predictor variables in subsequent modeling exercises to determine if associations with increased risk of cranial abscess disease at the site level. We then ensured no collinearity between the age and gender. No variables were significantly correlated enough to be excluded from being in the same model (cutoff of r = ± 0.70).</p

Location of 29 sites and the number of hunter-harvested adult (≥1.5 years old) male white-tailed deer testing positive for cranial abscess disease and the number examined for the presence of the cranial abscess disease in Georgia, USA during Fall 2011 and 2012.

<p>Location of 29 sites and the number of hunter-harvested adult (≥1.5 years old) male white-tailed deer testing positive for cranial abscess disease and the number examined for the presence of the cranial abscess disease in Georgia, USA during Fall 2011 and 2012.</p

Akaike information criteria with small sample bias adjustment (AICc); number of parameters (K), ΔAICc, Akaike weights (<i>w</i>) for candidate models (<i>i</i>) relating prevalence of detecting <i>Trueperella pyogenes</i> on the mucosal surfaces of deer to the occurrence of cranial abscess disease at 29 sites across Georgia, USA in 2011–2012.

<p>^a Models correspond to prevalence of <i>T</i>. <i>pyogenes</i> on: O = overall (i.e., detection at any of the three dermal linings sampled), H = Forehead, N = Nasal, T = Tongue.</p><p>^bNumber of estimating parameters in approximating model.</p><p>^c Models with ΔAICc ≤ 2 were considered good candidates for explaining patterns in field data, models with ΔAICc 2–7 had little support, and models with ΔAICc > 10 had relatively no support.</p><p>^dAkaike weight.</p><p>The detection of <i>T</i>. <i>pyogenes</i> on any mucosal surface (overall detection) has the lowest AICc score.</p

Epethelial Presence of <i>Trueperella pyogenes</i> Predicts Site-Level Presence of Cranial Abscess Disease in White-Tailed Deer (<i>Odocoileus virginianus</i>)

<div><p>Cranial/intracranial abscess disease is an emerging source of significant mortality for male white-tailed deer (<i>Odocoileus virginianus</i>). Most cases of cranial/intracranial abscess disease are associated with infection by the opportunistic pathogen <i>Trueperella pyogenes</i> although the relationship between the prevalence of the bacteria and occurrence of disease is speculative. We examined 5,612 hunter-harvested deer from 29 sites across all physiographic provinces in Georgia for evidence of cranial abscess disease and sampled the forehead, lingual, and nasal surfaces from 692 deer. We used polymerase chain reaction (PCR) to determine presence of <i>T</i>. <i>pyogenes</i> from these samples. We found <i>T</i>. <i>pyogenes</i> prevalence at a site was a predictor for the occurrence of cranial abscess disease. Prevalence of <i>T</i>. <i>pyogenes</i> did not differ between samples from the nose or tongue although prevalence along the forehead was greater for males than females (p = 0.04), particularly at sites with high occurrence of this disease. Socio-sexual behaviors, bacterial prevalence, or physiological characteristics may predispose male deer to intracranial/cranial abscess disease. Determination of factors that affect <i>T</i>. <i>pyogenes</i> prevalence among sites may help explain the occurrence of this disease among populations.</p></div

Parameter estimates (logit scale) for a model of the risk of an individual white-tailed deer testing positive for <i>Trueperella pyogenes</i> on A) overall (detection at any of the three dermal linings sampled), B) head, C) nose, and D) tongue.

<p>¹ Site was considered a random effect in the model. Thus, it is a variance estimate.</p><p>Standard errors (SE), z values, and probabilities that a coefficient differs from 0 are also presented. Age and gender data was available for 527 deer across 26 sites. Residual degrees of freedom was 522 for all models.</p

Girls for Sale? Child Sex Ratio and Girls Trafficking in India

Illegal trafficking of women is a result of their disadvantageous position in the society that is often reflected in increasing preference for son and neglect for daughters. Multiple reports point to India as country confronted with both higher levels of illegal trafficking of girls and abnormal child sex ratios in favor of boys. In this paper we examine if a skewed sex ratio and shortage of girls is associated with their illegal trafficking in India. Using panel data of 29 Indian states from 1980-2011, we find that 100 unit increase in child sex ratio is associated with 0.635% increase in illegal trafficking of girls. We find the association to be heterogeneous by female empowerment, crime against women and party rule in the state. We find that association between child sex ratio and illegal trafficking of girls is stronger and larger in magnitude in states with greater female empowerment. Overall, it appears that the results are driven by both greater reporting and greater incidence of illegal girls trafficking. Contrary to popular belief, the results do not vary differentially by states with larger share of schedule tribe population or states bordering Nepal and Bangladesh. Our results survive variety of robustness checks