Geographic distribution and molecular diversity of Bartonella infections in moose, Alces alces, in Finland.

Moose, Alces alces (Artiodactyla: Cervidae) in Finland are heavily infested with deer keds, Lipoptena cervi (Diptera: Hippoboschidae). The deer ked, which carries species of the genus Bartonella, has been proposed as a vector for the transmission of bartonellae to animals and humans. Previously, bartonella DNA was found in deer keds as well as in moose blood collected in Finland. We investigated the prevalence and molecular diversity of Bartonella spp. infection from blood samples collected from free-ranging moose. Given that the deer ked is not present in northernmost Finland, we also investigated whether there were geographic differences in the prevalence of bartonella infection in moose. The overall prevalence of bartonella infection was 72.9% (108/148). Geographically, the prevalence was highest in the south (90.6%) and lowest in the north (55.9%). At least two species of bartonellae were identified by multilocus sequence analysis. Based on logistic regression analysis, there was no significant association between bartonella infection and either age or sex; however, moose from outside the deer ked zone were significantly less likely to be infected (P<0.015) than were moose hunted within the deer ked zone.

Toxics Release Inventory facilities and childhood cancer: Geographic information systems based approach

Purpose. To examine the association between living in proximity to Toxics Release Inventory (TRI) facilities and the incidence of childhood cancer in the State of Texas. ^ Design. This is a secondary data analysis utilizing the publicly available Toxics release inventory (TRI), maintained by the U.S. Environmental protection agency that lists the facilities that release any of the 650 TRI chemicals. Total childhood cancer cases and childhood cancer rate (age 0-14 years) by county, for the years 1995-2003 were used from the Texas cancer registry, available at the Texas department of State Health Services website. Setting: This study was limited to the children population of the State of Texas. ^ Method. Analysis was done using Stata version 9 and SPSS version 15.0. Satscan was used for geographical spatial clustering of childhood cancer cases based on county centroids using the Poisson clustering algorithm which adjusts for population density. Pictorial maps were created using MapInfo professional version 8.0. ^ Results. One hundred and twenty five counties had no TRI facilities in their region, while 129 facilities had at least one TRI facility. An increasing trend for number of facilities and total disposal was observed except for the highest category based on cancer rate quartiles. Linear regression analysis using log transformation for number of facilities and total disposal in predicting cancer rates was computed, however both these variables were not found to be significant predictors. Seven significant geographical spatial clusters of counties for high childhood cancer rates (p<0.05) were indicated. Binomial logistic regression by categorizing the cancer rate in to two groups (<=150 and >150) indicated an odds ratio of 1.58 (CI 1.127, 2.222) for the natural log of number of facilities. ^ Conclusion. We have used a unique methodology by combining GIS and spatial clustering techniques with existing statistical approaches in examining the association between living in proximity to TRI facilities and the incidence of childhood cancer in the State of Texas. Although a concrete association was not indicated, further studies are required examining specific TRI chemicals. Use of this information can enable the researchers and public to identify potential concerns, gain a better understanding of potential risks, and work with industry and government to reduce toxic chemical use, disposal or other releases and the risks associated with them. TRI data, in conjunction with other information, can be used as a starting point in evaluating exposures and risks. ^

Geographic variation in the utilization and survival associated with oxaliplatin chemotherapy in patients with stage III colon cancer

Background: Overall objectives of this dissertation are to examine the geographic variation and socio-demographic disparities (by age, race and gender) in the utilization and survival of newly FDA-approved chemotherapy agents (Oxaliplatin-containing regimens) as well as to determine the cost-effectiveness of Oxaliplatin in a large nationwide and population-based cohort of Medicare patients with resected stage-III colon cancer. Methods: A retrospective cohort of 7,654 Medicare patients was identified from the Surveillance, Epidemiology and End Results – Medicare linked database. Multiple logistic regression was performed to examine the relationship between receipt of Oxaliplatin-containing chemotherapy and geographic regions while adjusting for other patient characteristics. Cox proportional hazard model was used to estimate the effect of Oxaliplatin-containing chemotherapy on the survival variation across regions using 2004-2005 data. Propensity score adjustments were also made to control for potential bias related to non-random allocation of the treatment group. We used Kaplan-Meier sample average estimator to calculate the cost of disease after cancer-specific surgery to death, loss-to follow-up or censorship. Results: Only 51% of the stage-III patients received adjuvant chemotherapy within three to six months of colon-cancer specific surgery. Patients in the rural regions were approximately 30% less likely to receive Oxaliplatin chemotherapy than those residing in a big metro region (OR=0.69, p=0.033). The hazard ratio for patients residing in metro region was comparable to those residing in big metro region (HR: 1.05, 95% CI: 0.49-2.28). Patients who received Oxalipaltin chemotherapy were 33% less likely to die than those received 5-FU only chemotherapy (adjusted HR=0.67, 95% CI: 0.41-1.11). KMSA-adjusted mean payments were almost 2.5 times higher in the Oxaliplatin-containing group compared to 5-FU only group ($45,378 versus $17,856). When compared to no chemotherapy group, ICER of 5-FU based regimen was $12,767 per LYG, and ICER of Oxaliplatin-chemotherapy was $60,863 per LYG. Oxaliplatin was found economically dominated by 5-FU only chemotherapy in this study population. Conclusion: Chemotherapy use varies across geographic regions. We also observed considerable survival differences across geographic regions; the difference remained even after adjusting for socio-demographic characteristics. The cost-effectiveness of Oxaliplatin in Medicare patients may be over-estimated in the clinical trials. Our study found 5-FU only chemotherapy cost-effective in adjuvant settings in patients with stage-III colon cancer.^

Correlation of tuberculosis and human immunodeficiency virus in Harris County, Texas from 2009 through 2010 using Geographic Information Systems

A population based ecological study was conducted to identify areas with a high number of TB and HIV new diagnoses in Harris County, Texas from 2009 through 2010 by applying Geographic Information Systems to determine whether distinguished spatial patterns exist at the census tract level through the use of exploratory mapping. As of 2010, Texas has the fourth highest occurrence of new diagnoses of HIV/AIDS and TB.[31] The Texas Department of State Health Services (DSHS) has identified HIV infected persons as a high risk population for TB in Harris County.[29] In order to explore this relationship further, GIS was utilized to identify spatial trends. ^ The specific aims were to map TB and HIV new diagnoses rates and spatially identify hotspots and high value clusters at the census tract level. The potential association between HIV and TB was analyzed using spatial autocorrelation and linear regression analysis. The spatial statistics used were ArcGIS 9.3 Hotspot Analysis and Cluster and Outlier Analysis. Spatial autocorrelation was determined through Global Moran's I and linear regression analysis. ^ Hotspots and clusters of TB and HIV are located within the same spatial areas of Harris County. The areas with high value clusters and hotspots for each infection are located within the central downtown area of the city of Houston. There is an additional hotspot area of TB located directly north of I-10 and a hotspot area of HIV northeast of Interstate 610. ^ The Moran's I Index of 0.17 (Z score = 3.6 standard deviations, p-value = 0.01) suggests that TB is statistically clustered with a less than 1% chance that this pattern is due to random chance. However, there were a high number of features with no neighbors which may invalidate the statistical properties of the test. Linear regression analysis indicated that HIV new diagnoses rates (β=−0.006, SE=0.147, p=0.970) and census tracts (β=0.000, SE=0.000, p=0.866) were not significant predictors of TB new diagnoses rates. ^ Mapping products indicate that census tracts with overlapping hotspots and high value clusters of TB and HIV should be a targeted focus for prevention efforts, most particularly within central Harris County. While the statistical association was not confirmed, evidence suggests that there is a relationship between HIV and TB within this two year period.^

Inappropriate imaging utilization in Texas: Geographic variation and predictive factors

Objective::Describe and understand regional differences and associated multilevel factors (patient, provider and regional) to inappropriate utilization of advance imaging tests in the privately insured population of Texas. Methods: We analyzed Blue Cross Blue Shield of Texas claims dataset to study the advance imaging utilization during 2008-2010 in the PPO/PPO+ plans. We used three of CMS "Hospital Outpatient Quality Reporting" imaging efficiency measures. These included ordering MRI for low back pain without prior conservative management (OP-8) and utilization of combined with and without contrast abdominal CT (OP-10) and thorax CT (OP-11). Means and variation by hospital referral regions (HRR) in Texas were measured and a multilevel logistic regression for being a provider with high values for any the three OP measures was used in the analysis. We also analyzed OP-8 at the individual level. A multilevel logistic regression was used to identify predictive factors for having an inappropriate MRI for low back pain. Results: Mean OP-8 for Texas providers was 37.89%, OP-10 was 29.94% and OP-11 was 9.24%. Variation was higher for CT measure. And certain HRRs were consistently above the mean. Hospital providers had higher odds of high OP-8 values (OP-8: OR, 1.34; CI, 1.12-1.60) but had smaller odds of having high OP-10 and OP-11 values (OP-10: OR, 0.15; CI, 0.12-0.18; OP-11: OR, 0.43; CI, 0.34-0.53). Providers with the highest volume of imaging studies performed, were less likely to have high OP-8 measures (OP-8: OR, 0.58; CI, 0.48-0.70) but more likely to perform combined thoracic CT scans (OP-11: OR, 1.62; CI, 1.34-1.95). Males had higher odds of inappropriate MRI (OR, 1.21; CI, 1.16-1.26). Pattern of care in the six months prior to the MRI event was significantly associated with having an inappropriate MRI. Conclusion::We identified a significant variation in advance imaging utilization across Texas. Type of facility was associated with measure performance, but the associations differ according to the type of study. Last, certain individual characteristics such as gender, age and pattern of care were found to be predictors of inappropriate MRIs.^

Forecasting Helicoverpa populations in Australia: A comparison of regression based models and a bio-climatic based modeling approach

Long-term forecasts of pest pressure are central to the effective management of many agricultural insect pests. In the eastern cropping regions of Australia, serious infestations of Helicoverpa punctigera (Wallengren) and H. armigera (Hübner)(Lepidoptera: Noctuidae) are experienced annually. Regression analyses of a long series of light-trap catches of adult moths were used to describe the seasonal dynamics of both species. The size of the spring generation in eastern cropping zones could be related to rainfall in putative source areas in inland Australia. Subsequent generations could be related to the abundance of various crops in agricultural areas, rainfall and the magnitude of the spring population peak. As rainfall figured prominently as a predictor variable, and can itself be predicted using the Southern Oscillation Index (SOI), trap catches were also related to this variable. The geographic distribution of each species was modelled in relation to climate and CLIMEX was used to predict temporal variation in abundance at given putative source sites in inland Australia using historical meteorological data. These predictions were then correlated with subsequent pest abundance data in a major cropping region. The regression-based and bioclimatic-based approaches to predicting pest abundance are compared and their utility in predicting and interpreting pest dynamics are discussed.

GIS-integrated mathematical modeling of social phenomena at macro- and micro- levels—a multivariate geographically-weighted regression model for identifying locations vulnerable to hosting terrorist safe-houses: France as case study

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to terrorist locations such as safe-houses (rather than their targets or training sites) are rare and possibly nonexistent. At the time of this research, there were no publically available models designed to predict locations where violent extremists are likely to reside. This research uses France as a case study to present a complex systems model that incorporates multiple quantitative, qualitative and geospatial variables that differ in terms of scale, weight, and type. Though many of these variables are recognized by specialists in security studies, there remains controversy with respect to their relative importance, degree of interaction, and interdependence. Additionally, some of the variables proposed in this research are not generally recognized as drivers, yet they warrant examination based on their potential role within a complex system. This research tested multiple regression models and determined that geographically-weighted regression analysis produced the most accurate result to accommodate non-stationary coefficient behavior, demonstrating that geographic variables are critical to understanding and predicting the phenomenon of terrorism. This dissertation presents a flexible prototypical model that can be refined and applied to other regions to inform stakeholders such as policy-makers and law enforcement in their efforts to improve national security and enhance quality-of-life.

Geographic Variation of Notified Ross River Virus Infections in Queensland, Australia, 1985-1996

The spatial and temporal variations of Ross River virus infections reported in Queensland, Australia, between 1985 and 1996 were studied by using the Geographic Information System. The notified cases of Ross River virus infection came from 489 localities between 1985 and 1988, 805 between 1989 and 1992, and 1,157 between 1993 and 1996 (chi2(df = 2) = 680.9; P < 0.001). There was a marked increase in the number of localities where the cases were reported by 65 percent for the period of 1989-1992 and 137 percent for 1993-1996, compared with that for 1985-1988. The geographic distribution of the notified Ross River virus cases has expanded in Queensland over recent years. As Ross River virus disease has impacted considerably on tourism and industry, as well as on residents of affected areas, more research is required to explore the causes of the geographic expansion of the notified Ross River virus infections.

Exploratory spatial analysis of social and environmental factors associated with the incidence of Ross River Virus in Brisbane, Australia

We used geographic information systems and a spatial analysis approach to explore the pattern of Ross River virus (RRV) incidence in Brisbane, Australia. Climate, vegetation and socioeconomic data in 2001 were obtained from the Australian Bureau of Meteorology, the Brisbane City Council and the Australian Bureau of Statistics, respectively. Information on the RRV cases was obtained from the Queensland Department of Health. Spatial and multiple negative binomial regression models were used to identify the socioeconomic and environmental determinants of RRV transmission. The results show that RRV activity was primarily concentrated in the northeastern, northwestern, and southeastern regions in Brisbane. Multiple negative binomial regression models showed that the spatial pattern of RRV disease in Brisbane seemed to be determined by a combination of local ecologic, socioeconomic, and environmental factors.

Residential sales by auction : a property type or geographic consideration

The sale of residential property by auction is a preferred sale method by real estate agents, but not always preferred by some vendors and most residential property buyers. In many residential property markets, the performance and measure of residential property market activity is based on the number of properties offered for sale by auction, auction clearance rates and the number of properties sold prior to auction. However, in many specific residential property markets, sale by auction may not be the preferred or supported method of sale. This paper will review the type of residential property sale within the Sydney residential property market and track the auction sales and clearance rates for Sydney over the past 5 months and compare these results in relation to clearance rates, passed in sales, and properties sold prior to auction This will provide a breakdown of real estate agency sale practice over a large metropolitan region to determine the impact of geographic location and socio-economic factors on the auction of residential property. In addition the paper will analyse the weekly auction sales in the Sydney residential property market to determine what areas of Sydney have the greatest number of house auctions and the performance of the auctions in relation location and socio economic factors.

Elicitator : an expert elicitation tool for regression in ecology

Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited, or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior model in Bayesian regression. Potential environmental domains for applying this elicitation tool include habitat modeling, assessing detectability or eradication, ecological condition assessments, risk analysis, and quantifying inputs to complex models of ecological processes. The tool has been developed to be user-friendly, extensible, and facilitate consistent and repeatable elicitation of expert knowledge across these various domains. We demonstrate its application to elicitation for logistic regression in a geographically based ecological context. The underlying statistical methodology is also novel, utilizing an indirect elicitation approach to target expert knowledge on a case-by-case basis. For several elicitation sites (or cases), experts are asked simply to quantify their estimated ecological response (e.g. probability of presence), and its range of plausible values, after inspecting (habitat) covariates via GIS.