Rapid invasion and expansion of the Asian longhorned tick (Haemaphysalis longicornis) into a new area on Long Island, New York, USA

Since its discovery in the United States in 2017, the Asian longhorned tick (Haemaphysalis longicornis) has been detected in most eastern states between Rhode Island and Georgia. Long Island, east of New York City, a recognized high-risk area for tick-borne diseases, is geographically close to New Jersey and New York sites where H. longicornis was originally found. However, extensive tick surveys conducted in 2018 did not identify H. longicornis on Long Island. In stark contrast, our 2022 tick survey suggests that H. longicornis has rapidly invaded and expanded in multiple surveying sites on Long Island (12 out of 17 sites). Overall, the relative abundance of H. longicornis was similar to that of lone star ticks, Amblyomma americanum, a previously recognized tick species abundantly present on Long Island. Interestingly, our survey suggests that H. longicornis has expanded within the Appalachian forest ecological zone of Long Island's north shore compared to the Pine Barrens located on the south shore of Long Island. The rapid invasion and expansion of H. longicornis into an insular environment are different from the historical invasion and expansion of two native tick species, Ixodes scapularis (blacklegged tick or deer tick) and A. americanum, in Long Island. The implications of H. longicornis transmitting or introducing tick-borne pathogens of public health importance remain unknown.

Origin of 3 Rabid Terrestrial Animals in Raccoon Rabies Virus-Free Zone, Long Island, New York, USA, 2016-2017

During 2016–2017, three rabid terrestrial animals were discovered in the raccoon rabies virus–free zone of Long Island, New York, USA. Whole-genome sequencing and phylogenetic analyses revealed the likely origins of the viruses, enabling the rabies outbreak response (often costly and time-consuming) to be done less expensively and more efficiently.

Infection with New York Orthohantavirus and Associated Respiratory Failure and Multiple Cerebral Complications

We report a case of infection with New York orthohantavirus in a woman who showed renal impairment and hemorrhage, complicated by hydrocephalus, in Long Island, New York, USA. Phylogenetic analysis showed that this virus was genetically similar to a New York orthohantavirus isolated in the same region during 1993.

Spatiotemporal modeling of ecological and sociological predictors of West Nile virus in Suffolk County, NY, mosquitoes

Suffolk County, New York, is a locus for West Nile virus (WNV) infection in the American northeast that includes the majority of Long Island to the east of New York City. The county has a system of light and gravid traps used for mosquito collection and disease monitoring. In order to identify predictors of WNV incidence in mosquitoes and predict future occurrence of WNV, we have developed a spatiotemporal Bayesian model, beginning with over 40 ecological, meteorological, and built-environment covariates. A mixed-effects model including spatially and temporally correlated errors was fit to WNV surveillance data from 2008 to 2014 using the R package “R-INLA,” which allows for Bayesian modeling using the stochastic partial differential equation (SPDE) approach. The integrated nested Laplace approximation (INLA) SPDE allows for simultaneous fitting of a temporal parameter and a spatial covariance, while incorporating a variety of likelihood functions and running in R statistical software on a home computer. We found that land cover classified as open water and woody wetlands had a negative association with WNV incidence in mosquitoes, and the count of septic systems was associated with an increase in WNV. Mean temperature at two-week lag was associated with a strong positive impact, while mean precipitation at no lag and one-week lag was associated with positive and negative impacts on WNV, respectively. Incorporation of spatiotemporal factors resulted in a marked increase in model goodness-of-fit. The predictive power of the model was evaluated on 2015 surveillance results, where the best model achieved a sensitivity of 80.9% and a specificity of 77.0%. The spatial covariate was mapped across the county, identifying a gradient of WNV prevalence increasing from east to west. The Bayesian spatiotemporal model improves upon previous approaches, and we recommend the INLA SPDE methodology as an efficient way to develop robust models from surveillance data to develop and enhance monitoring and control programs. Our study confirms previously found associations between weather conditions and WNV and suggests that wetland cover has a mitigating effect on WNV infection in mosquitoes, while high septic system density is associated with an increase in WNV infection.

Spatiotemporal modeling of ecological and sociological predictors of West Nile virus in Suffolk County, NY, mosquitoes

Suffolk County, New York, is a locus for West Nile virus (WNV) infection in the American northeast that includes the majority of Long Island to the east of New York City. The county has a system of light and gravid traps used for mosquito collection and disease monitoring. In order to identify predictors of WNV incidence in mosquitoes and predict future occurrence of WNV, we have developed a spatiotemporal Bayesian model, beginning with over 40 ecological, meteorological, and built-environment covariates. A mixed-effects model including spatially and temporally correlated errors was fit to WNV surveillance data from 2008 to 2014 using the R package "R-INLA," which allows for Bayesian modeling using the stochastic partial differential equation (SPDE) approach. The integrated nested Laplace approximation (INLA) SPDE allows for simultaneous fitting of a temporal parameter and a spatial covariance, while incorporating a variety of likelihood functions and running in R statistical software on a home computer. We found that land cover classified as open water and woody wetlands had a negative association with WNV incidence in mosquitoes, and the count of septic systems was associated with an increase in WNV. Mean temperature at two-week lag was associated with a strong positive impact, while mean precipitation at no lag and one-week lag was associated with positive and negative impacts on WNV, respectively. Incorporation of spatiotemporal factors resulted in a marked increase in model goodness-of-fit. The predictive power of the model was evaluated on 2015 surveillance results, where the best model achieved a sensitivity of 80.9% and a specificity of 77.0%. The spatial covariate was mapped across the county, identifying a gradient of WNV prevalence increasing from east to west. The Bayesian spatiotemporal model improves upon previous approaches, and we recommend the INLA SPDE methodology as an efficient way to develop robust models from surveillance data to develop and enhance monitoring and control programs. Our study confirms previously found associations between weather conditions and WNV and suggests that wetland cover has a mitigating effect on WNV infection in mosquitoes, while high septic system density is associated with an increase in WNV infection.

Superstorm Sandy marine debris wash-ups on Long Island - What happened to them?

Superstorm Sandy generated huge quantities of debris in the Long Island, NY coastal zone. However, little appears to have been washed offshore to eventually be returned to Long Island's beaches as marine debris wash-ups. Information for our analysis includes debris collection statistics, very high resolution satellite images, along with wind and sea level data. Rigorous debris collection efforts along with meteorological conditions following the storm appear to have reduced the likelihood of debris wash-ups.

PAH-DNA adducts, cigarette smoking, GST polymorphisms, and breast cancer risk

BACKGROUND

Polycyclic aromatic hydrocarbons (PAHs) may increase breast cancer risk, and the association may be modified by inherited differences in deactivation of PAH intermediates by glutathione S-transferases (GSTs). Few breast cancer studies have investigated the joint effects of multiple GSTs and a PAH biomarker.

OBJECTIVE

We estimated the breast cancer risk associated with multiple polymorphisms in the GST gene (GSTA1, GSTM1, GSTP1, and GSTT1) and the interaction with PAH-DNA adducts and cigarette smoking.

METHODS

We conducted unconditional logistic regression using data from a population-based sample of women (cases/controls, respectively): GST polymorphisms were genotyped using polymerase chain reaction and matrix-assisted laser desorption/ionization time-of-flight assays (n = 926 of 916), PAH-DNA adduct blood levels were measured by competitive enzyme-linked immunosorbent assay (n = 873 of 941), and smoking status was assessed by in-person questionnaires (n = 943 of 973).

RESULTS

Odds ratios for joint effects on breast cancer risk among women with at least three variant alleles were 1.56 [95% confidence interval (CI), 1.13-2.16] for detectable PAH-DNA adducts and 0.93 (95% CI, 0.56-1.56) for no detectable adducts; corresponding odds ratios for three or more variants were 1.18 (95% CI, 0.82-1.69) for ever smokers and 1.44 (95% CI, 0.97-2.14) for never smokers. Neither interaction was statistically significant (p = 0.43 and 0.62, respectively).

CONCLUSION

We found little statistical evidence that PAHs interacted with GSTT1, GSTM1, GSTP1, and GSTA1 polymorphisms to further increase breast cancer risk.

Reponse to Freeman: the Stony Brook perspective

It has been my attitude up until this point to discuss only those medical aspects of the case which were required by legal proceedings. I have considered this essentially a private matter for the parents. However, there is some additional information that I would now like to bring to light, because some of the things that Dr. Freeman has said reflect certain inaccuracies which undoubtedly are present because he did not have access to all of the information. I would like to bring forth some additional facts, not only about the medical aspects, but also about the manner in which this case was handled. My hope is that I can convince Dr. Freeman that, in fact, the process that was undertaken in this case was a correct one.