Using Geographic Information Systems for Exposure Assessment in Environmental Epidemiology Studies

Geographic information systems (GIS) are being used with increasing frequency in environmental epidemiology studies. Reported applications include locating the study population by geocoding addresses (assigning mapping coordinates), using proximity analysis of contaminant source as a surrogate for exposure, and integrating environmental monitoring data into the analysis of the health outcomes. Although most of these studies have been ecologic in design, some have used GIS in estimating environmental levels of a contaminant at the individual level and to design exposure metrics for use in epidemiologic studies. In this article we discuss fundamentals of three scientific disciplines instrumental to using GIS in exposure assessment for epidemiologic studies: geospatial science, environmental science, and epidemiology. We also explore how a GIS can be used to accomplish several steps in the exposure assessment process. These steps include defining the study population, identifying source and potential routes of exposure, estimating environmental levels of target contaminants, and estimating personal exposures. We present and discuss examples for the first three steps. We discuss potential use of GIS and global positioning systems (GPS) in the last step. On the basis of our findings, we conclude that the use of GIS in exposure assessment for environmental epidemiology studies is not only feasible but can enhance the understanding of the association between contaminants in our environment and disease

Roles of tetrahydrobiopterin in promoting tumor angiogenesis.

Nitric oxide (NO), which is derived from endothelial NO synthase (eNOS), provides crucial signals for angiogenesis in the tumor microenvironment. Tetrahydrobiopterin (BH4) is an absolute requirement for eNOS activity. In this study, we investigated whether this activation is both maintained by a wild-type Ras/phosphatidylinositol 3-kinase (PI3K)/Akt-positive feedback loop in endothelial cells and affects tumor angiogenesis. We found that supplementation of BH4 (via the pterin salvage pathway with Sep) increased Akt/eNOS phosphorylation in both human eNOS-transfected COS-7 cells and endothelial cells concomitant with increases in NO production, cell proliferation, migration, and tube formation. This augmentation was abrogated by a PI3K inhibitor. Sepiapterin (Sep) also increased GTP-bound wild-type Ras and PI3K/Akt/eNOS activation, which was prevented by the eNOS inhibitor, Nω-Nitro-L-arginine methyl ester (L-NAME). Furthermore, expression of GTP cyclohydrolase I (the rate-limiting enzyme in de novo BH4 synthesis) under doxycycline control potentiated in vivo tumorigenesis, tumor cell proliferation, as well as angiogenesis. Conversely, both switching off GTP cyclohydrolase I expression as well as inhibiting its enzymatic activity significantly decreased eNOS expression and tumor vascularization. This study demonstrates an important role for BH4 synthesis in angiogenesis by the activation of eNOS for NO production, which is maintained by a PI3K/Akt-positive feedback loop through effects on wild-type Ras in endothelial cells. Our findings suggest that BH4 synthesis may be a rational target for antiangiogenesis therapy for tumors

Evaluation of cost-effective strategies for rabies post-exposure vaccination in low-income countries

<b>Background:</b> Prompt post-exposure prophylaxis (PEP) is essential in preventing the fatal onset of disease in persons exposed to rabies. Unfortunately, life-saving rabies vaccines and biologicals are often neither accessible nor affordable, particularly to the poorest sectors of society who are most at risk and upon whom the largest burden of rabies falls. Increasing accessibility, reducing costs and preventing delays in delivery of PEP should therefore be prioritized.<p></p> <b>Methodology/Principal Findings:</b> We analyzed different PEP vaccination regimens and evaluated their relative costs and benefits to bite victims and healthcare providers. We found PEP vaccination to be an extremely cost-effective intervention (from $200 to less than$60/death averted). Switching from intramuscular (IM) administration of PEP to equally efficacious intradermal (ID) regimens was shown to result in significant savings in the volume of vaccine required to treat the same number of patients, which could mitigate vaccine shortages, and would dramatically reduce the costs of implementing PEP. We present financing mechanisms that would make PEP more affordable and accessible, could help subsidize the cost for those most in need, and could even support new and existing rabies control and prevention programs.<p></p> <b>Conclusions/Significance:</b> We conclude that a universal switch to ID delivery would improve the affordability and accessibility of PEP for bite victims, leading to a likely reduction in human rabies deaths, as well as being economical for healthcare providers.<p></p&gt

Costs analysis of a population level rabies control programme in Tamil Nadu, India

The study aimed to determine costs to the state government of implementing different interventions for controlling rabies among the entire human and animal populations of Tamil Nadu. This built upon an earlier assessment of Tamil Nadu’s efforts to control rabies. Anti-rabies vaccines were made available at all health facilities. Costs were estimated for five different combinations of animal and human interventions using an activity-based costing approach from the provider perspective. Disease and population data were sourced from the state surveillance data, human census and livestock census. Program costs were extrapolated from official documents. All capital costs were depreciated to estimate annualized costs. All costs were inflated to 2012 Rupees. Sensitivity analysis was conducted across all major cost centres to assess their relative impact on program costs. It was found that the annual costs of providing Anti-rabies vaccine alone and in combination with Immunoglobulins was \$0.7 million (Rs 36 million) and \$2.2 million (Rs 119 million), respectively. For animal sector interventions, the annualised costs of rolling out surgical sterilisation-immunization, injectable immunization and oral immunizations were estimated to be \$ 44 million (Rs 2,350 million), \$23 million (Rs 1,230 million) and \$ 11 million (Rs 590 million), respectively. Dog bite incidence, health systems coverage and cost of rabies biologicals were found to be important drivers of costs for human interventions. For the animal sector interventions, the size of dog catching team, dog population and vaccine costs were found to be driving the costs. Rabies control in Tamil Nadu seems a costly proposition the way it is currently structured. Policy makers in Tamil Nadu and other similar settings should consider the long-term financial sustainability before embarking upon a state or nation-wide rabies control programme

The air quality impacts of road closures associated with the 2004 Democratic National Convention in Boston

BACKGROUND: The Democratic National Convention (DNC) in Boston, Massachusetts in 2004 provided an opportunity to evaluate the impacts of a localized and short-term but potentially significant change in traffic patterns on air quality, and to determine the optimal monitoring approach to address events of this nature. It was anticipated that the road closures associated with the DNC would both influence the overall air pollution level and the distribution of concentrations across the city, through shifts in traffic patterns. METHODS: To capture these effects, we placed passive nitrogen dioxide badges at 40 sites around metropolitan Boston before, during, and after the DNC, with the goal of capturing the array of hypothesized impacts. In addition, we continuously measured elemental carbon at three sites, and gathered continuous air pollution data from US EPA fixed-site monitors and traffic count data from the Massachusetts Highway Department. RESULTS: There were significant reductions in traffic volume on the highway with closures north of Boston, with relatively little change along other highways, indicating a more isolated traffic reduction rather than an across-the-board decrease. For our nitrogen dioxide samples, while there was a relatively small change in mean concentrations, there was significant heterogeneity across sites, which corresponded with our a priori classifications of road segments. The median ratio of nitrogen dioxide concentrations during the DNC relative to non-DNC sampling periods was 0.58 at sites with hypothesized traffic reductions, versus 0.88 for sites with no changes hypothesized and 1.15 for sites with hypothesized traffic increases. Continuous monitors measured slightly lower concentrations of elemental carbon and nitrogen dioxide during road closure periods at monitors proximate to closed highway segments, but not for PM(2.5 )or further from major highways. CONCLUSION: We conclude that there was a small but measurable influence of DNC-related road closures on air quality patterns in the Boston area, and that a low-cost monitoring study combining passive badges for spatial heterogeneity and continuous monitors for temporal heterogeneity can provide useful insight for community air quality assessments

Use of Advanced Flexible Modeling Approaches for Survival Extrapolation from Early Follow-up Data in two Nivolumab Trials in Advanced NSCLC with Extended Follow-up

Objectives: Immuno-oncology (IO) therapies are often associated with delayed responses that are deep and durable, manifesting as long-term survival benefits in patients with metastatic cancer. Complex hazard functions arising from IO treatments may limit the accuracy of extrapolations from standard parametric models (SPMs). We evaluated the ability of flexible parametric models (FPMs) to improve survival extrapolations using data from 2 trials involving patients with non–small-cell lung cancer (NSCLC). Methods: Our analyses used consecutive database locks (DBLs) at 2-, 3-, and 5-y minimum follow-up from trials evaluating nivolumab versus docetaxel in patients with pretreated metastatic squamous (CheckMate-017) and nonsquamous (CheckMate-057) NSCLC. For each DBL, SPMs, as well as 3 FPMs—landmark response models (LRMs), mixture cure models (MCMs), and Bayesian multiparameter evidence synthesis (B-MPES)—were estimated on nivolumab overall survival (OS). The performance of each parametric model was assessed by comparing milestone restricted mean survival times (RMSTs) and survival probabilities with results obtained from externally validated SPMs. Results: For the 2- and 3-y DBLs of both trials, all models tended to underestimate 5-y OS. Predictions from nonvalidated SPMs fitted to the 2-y DBLs were highly unreliable, whereas extrapolations from FPMs were much more consistent between models fitted to successive DBLs. For CheckMate-017, in which an apparent survival plateau emerges in the 3-y DBL, MCMs fitted to this DBL estimated 5-y OS most accurately (11.6% v. 12.3% observed), and long-term predictions were similar to those from the 5-y validated SPM (20-y RMST: 30.2 v. 30.5 mo). For CheckMate-057, where there is no clear evidence of a survival plateau in the early DBLs, only B-MPES was able to accurately predict 5-y OS (14.1% v. 14.0% observed [3-y DBL]). Conclusions: We demonstrate that the use of FPMs for modeling OS in NSCLC patients from early follow-up data can yield accurate estimates for RMST observed with longer follow-up and provide similar long-term extrapolations to externally validated SPMs based on later data cuts. B-MPES generated reasonable predictions even when fitted to the 2-y DBLs of the studies, whereas MCMs were more reliant on longer-term data to estimate a plateau and therefore performed better from 3 y. Generally, LRM extrapolations were less reliable than those from alternative FPMs and validated SPMs but remained superior to nonvalidated SPMs. Our work demonstrates the potential benefits of using advanced parametric models that incorporate external data sources, such as B-MPES and MCMs, to allow for accurate evaluation of treatment clinical and cost-effectiveness from trial data with limited follow-up. Flexible advanced parametric modeling methods can provide improved survival extrapolations for immuno-oncology cost-effectiveness in health technology assessments from early clinical trial data that better anticipate extended follow-up. Advantages include leveraging additional observable trial data, the systematic integration of external data, and more detailed modeling of underlying processes. Bayesian multiparameter evidence synthesis performed particularly well, with well-matched external data. Mixture cure models also performed well but may require relatively longer follow-up to identify an emergent plateau, depending on the specific setting. Landmark response models offered marginal benefits in this scenario and may require greater numbers in each response group and/or increased follow-up to support improved extrapolation within each subgroup

On the probability of cost-effectiveness using data from randomized clinical trials

BACKGROUND: Acceptability curves have been proposed for quantifying the probability that a treatment under investigation in a clinical trial is cost-effective. Various definitions and estimation methods have been proposed. Loosely speaking, all the definitions, Bayesian or otherwise, relate to the probability that the treatment under consideration is cost-effective as a function of the value placed on a unit of effectiveness. These definitions are, in fact, expressions of the certainty with which the current evidence would lead us to believe that the treatment under consideration is cost-effective, and are dependent on the amount of evidence (i.e. sample size). METHODS: An alternative for quantifying the probability that the treatment under consideration is cost-effective, which is independent of sample size, is proposed. RESULTS: Non-parametric methods are given for point and interval estimation. In addition, these methods provide a non-parametric estimator and confidence interval for the incremental cost-effectiveness ratio. An example is provided. CONCLUSIONS: The proposed parameter for quantifying the probability that a new therapy is cost-effective is superior to the acceptability curve because it is not sample size dependent and because it can be interpreted as the proportion of patients who would benefit if given the new therapy. Non-parametric methods are used to estimate the parameter and its variance, providing the appropriate confidence intervals and test of hypothesis

Cryo Electron Tomography of Native HIV-1 Budding Sites

The structure of immature and mature HIV-1 particles has been analyzed in detail by cryo electron microscopy, while no such studies have been reported for cellular HIV-1 budding sites. Here, we established a system for studying HIV-1 virus-like particle assembly and release by cryo electron tomography of intact human cells. The lattice of the structural Gag protein in budding sites was indistinguishable from that of the released immature virion, suggesting that its organization is determined at the assembly site without major subsequent rearrangements. Besides the immature lattice, a previously not described Gag lattice was detected in some budding sites and released particles; this lattice was found at high frequencies in a subset of infected T-cells. It displays the same hexagonal symmetry and spacing in the MA-CA layer as the immature lattice, but lacks density corresponding to NC-RNA-p6. Buds and released particles carrying this lattice consistently lacked the viral ribonucleoprotein complex, suggesting that they correspond to aberrant products due to premature proteolytic activation. We hypothesize that cellular and/or viral factors normally control the onset of proteolytic maturation during assembly and release, and that this control has been lost in a subset of infected T-cells leading to formation of aberrant particles

Spatial Epidemiology: Current Approaches and Future Challenges

Spatial epidemiology is the description and analysis of geographic variations in disease with respect to demographic, environmental, behavioral, socioeconomic, genetic, and infectious risk factors. We focus on small-area analyses, encompassing disease mapping, geographic correlation studies, disease clusters, and clustering. Advances in geographic information systems, statistical methodology, and availability of high-resolution, geographically referenced health and environmental quality data have created unprecedented new opportunities to investigate environmental and other factors in explaining local geographic variations in disease. They also present new challenges. Problems include the large random component that may predominate disease rates across small areas. Though this can be dealt with appropriately using Bayesian statistics to provide smooth estimates of disease risks, sensitivity to detect areas at high risk is limited when expected numbers of cases are small. Potential biases and confounding, particularly due to socioeconomic factors, and a detailed understanding of data quality are important. Data errors can result in large apparent disease excess in a locality. Disease cluster reports often arise nonsystematically because of media, physician, or public concern. One ready means of investigating such concerns is the replication of analyses in different areas based on routine data, as is done in the United Kingdom through the Small Area Health Statistics Unit (and increasingly in other European countries, e.g., through the European Health and Environment Information System collaboration). In the future, developments in exposure modeling and mapping, enhanced study designs, and new methods of surveillance of large health databases promise to improve our ability to understand the complex relationships of environment to health