ArticleInternational journal of health geographics2016
Spatial measurement errors in the field of spatial epidemiology.
Article in International journal of health geographics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Why it's so hard to match residence addresses to census blocks - and how to fix it.Transactions in GIS : TG · 2026Article
- Integrating genomic and spatial analyses to describe tuberculosis transmission: a scoping review.The Lancet. Microbe · 2025Article
- From infectious diseases to chronic diseases: the paradigm shift of spatial epidemiology in disease prevention and control.Frontiers in public health · 2025Review
- Comparing mapped park and greenspace boundaries in Philadelphia: implications for exposure assessment in health studies.International journal of health geographics · 2024Article
- Capturing emergency dispatch address points as geocoding candidates to quantify delimited confidence in residential geolocation.International journal of health geographics · 2023Article
- Human-BitingMicroorganisms · 2023Article
- Exploring agricultural land-use and childhood malaria associations in sub-Saharan Africa.Scientific reports · 2022Article
- Spatial Heterogeneity in Positional Errors: A Comparison of Two Residential Geocoding Efforts in the Agricultural Health Study.International journal of environmental research and public health · 2021Article
- Association of ambient air pollution with cardiovascular disease risks in people with type 2 diabetes: a Bayesian spatial survival analysis.Environmental health : a global access science source · 2020Article
- Geocoding Error, Spatial Uncertainty, and Implications for Exposure Assessment and Environmental Epidemiology.International journal of environmental research and public health · 2020Article
- Developing a surveillance system of sub-county data: Finding suitable population thresholds for geographic aggregations.Spatial and spatio-temporal epidemiology · 2020Article
- Spatial predictive properties of built environment characteristics assessed by drop-and-spin virtual neighborhood auditing.International journal of health geographics · 2020Article
- Association of neighbourhood migrant density and risk of non-affective psychosis: a national, longitudinal cohort study.The lancet. Psychiatry · 2020Article
- Modelling the impact of MAUP on environmental drivers for Schistosoma japonicum prevalence.Parasites & vectors · 2020Article
- Enhancing Models and Measurements of Traffic-Related Air Pollutants for Health Studies Using Dispersion Modeling and Bayesian Data Fusion.Research report (Health Effects Institute) · 2020Article
- Modeling Schistosoma japonicum Infection under Pure Specification Bias: Impact of Environmental Drivers of Infection.International journal of environmental research and public health · 2019Article
- Geographic Imputation of Missing Activity Space Data from Ecological Momentary Assessment (EMA) GPS Positions.International journal of environmental research and public health · 2018Article
- Modelling local areas of exposure to Schistosoma japonicum in a limited survey data environment.Parasites & vectors · 2018Article
- Evaluation of data accuracies within a comprehensive geospatial-health data surveillance platform: SOMAARTH Demographic Development and Environmental Surveillance Site, Palwal, Haryana, India.Global health, epidemiology and genomics · 2018Article
- Spatial clustering of childhood leukaemia with the integration of the Paediatric Environmental History.Environmental research · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundSpatial epidemiology has been aided by advances in geographic information systems, remote sensing, global positioning systems and the development of new statistical methodologies specifically designed for such data. Given the growing popularity of these studies, we sought to review and analyze the types of spatial measurement errors commonly encountered during spatial epidemiological analysis of spatial data.
methodsGoogle Scholar, Medline, and Scopus databases were searched using a broad set of terms for papers indexed by a term indicating location (space or geography or location or position) and measurement error (measurement error or measurement inaccuracy or misclassification or uncertainty): we reviewed all papers appearing before December 20, 2014. These papers and their citations were reviewed to identify the relevance to our review.
resultsWe were able to define and classify spatial measurement errors into four groups: (1) pure spatial location measurement errors, including both non-instrumental errors (multiple addresses, geocoding errors, outcome aggregations, and covariate aggregation) and instrumental errors; (2) location-based outcome measurement error (purely outcome measurement errors and missing outcome measurements); (3) location-based covariate measurement errors (address proxies); and (4) Covariate-Outcome spatial misaligned measurement errors. We propose how these four classes of errors can be unified within an integrated theoretical model and possible solutions were discussed.
conclusionSpatial measurement errors are ubiquitous threat to the validity of spatial epidemiological studies. We propose a systematic framework for understanding the various mechanisms which generate spatial measurement errors and present practical examples of such errors.
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