ArticleEnvironmental science & technology2012
Integrating address geocoding, land use regression, and spatiotemporal geostatistical estimation for groundwater tetrachloroethylene.
Article in Environmental science & technology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Associations between Fecal Contamination of the Household Environment and Enteric Pathogen Detection in Children Living in Maputo, Mozambique.Environment & health (Washington, D.C.) · 2025Article
- A review of geospatial exposure models and approaches for health data integration.Journal of exposure science & environmental epidemiology · 2025Review
- Evaluation of Bayesian Maximum Entropy Data Fusion Approaches to Estimate Styrene, Benzene, Toluene, Ethylbenzene, and Xylenes and to Inform Epidemiological Analyses in the US Gulf States.Environmental science & technology · 2025Article
- Scalable Multipollutant Exposure Assessment Using Routine Mobile Monitoring Platforms.Research report (Health Effects Institute) · 2024Article
- Characterizing Spatial Information Loss for Wastewater Surveillance Using crAssphage: Effect of Decay, Temperature, and Population Mobility.Environmental science & technology · 2023Article
- A Bayesian maximum entropy model for predicting tsetse ecological distributions.International journal of health geographics · 2023Article
- The skin is no barrier to mixtures: Air pollutant mixtures and reported psoriasis or eczema in the Personalized Environment and Genes Study (PEGS).Journal of exposure science & environmental epidemiology · 2023Article
- The Utility of Machine Learning Models for Predicting Chemical Contaminants in Drinking Water: Promise, Challenges, and Opportunities.Current environmental health reports · 2023Review
- Progression of a large syphilis outbreak in rural North Carolina through space and time: Application of a Bayesian Maximum Entropy graphical user interface.PLOS global public health · 2023Article
- Scalable penalized spatiotemporal land-use regression for ground-level nitrogen dioxide.The annals of applied statistics · 2021Article
- Human fecal contamination of water, soil, and surfaces in households sharing poor-quality sanitation facilities in Maputo, Mozambique.International journal of hygiene and environmental health · 2020Article
- Modeling groundwater nitrate exposure in private wells of North Carolina for the Agricultural Health Study.The Science of the total environment · 2019Article
- Incorporating ToxCast and Tox21 datasets to rank biological activity of chemicals at Superfund sites in North Carolina.Environment international · 2017Article
- Bayesian Maximum Entropy space/time estimation of surface water chloride in Maryland using river distances.Environmental pollution (Barking, Essex : 1987) · 2016Article
- Nitrate variability in groundwater of North Carolina using monitoring and private well data models.Environmental science & technology · 2014Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
Abstract
Geographic information systems (GIS) based techniques are cost-effective and efficient methods used by state agencies and epidemiology researchers for estimating concentration and exposure. However, budget limitations have made statewide assessments of contamination difficult, especially in groundwater media. Many studies have implemented address geocoding, land use regression, and geostatistics independently, but this is the first to examine the benefits of integrating these GIS techniques to address the need of statewide exposure assessments. A novel framework for concentration exposure is introduced that integrates address geocoding, land use regression (LUR), below detect data modeling, and Bayesian Maximum Entropy (BME). A LUR model was developed for tetrachloroethylene that accounts for point sources and flow direction. We then integrate the LUR model into the BME method as a mean trend while also modeling below detects data as a truncated Gaussian probability distribution function. We increase available PCE data 4.7 times from previously available databases through multistage geocoding. The LUR model shows significant influence of dry cleaners at short ranges. The integration of the LUR model as mean trend in BME results in a 7.5% decrease in cross validation mean square error compared to BME with a constant mean trend.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.