Geocoding health data with Geographic Information Systems: a pilot study in northeast Italy for developing a standardized data-acquiring format


Environment and Public Health
Geographic Information Systems
Data matching



Introduction: Geographic Information Systems (GIS) have become an innovative and even more crucial tool for analyzing relationships between public health data and environment. This study, though focusing on a Local Health Unit of northeastern Italy, could be taken as a benchmark for developing a standardized national data acquiring format.

Methods: Geocoding analysis was carried out on a health database comprising 268,517 records of the Local Health Unit of Rovigo in the Veneto region, covering a period of 10 years, starting from 2001 up to 2010. The Map Service provided by the Environmental Research System Institute (ESRI, Redlands, CA), and ArcMap 10.0 by ESRI® were, respectively, the reference data and the GIS software, employed in the geocoding process.

Results: The first attempt of geocoding produced a poor quality result, having about 40% of the addresses matched. A procedure of manual standardization was performed in order to enhance the quality of the results, consequently a set of guiding principle were expounded which should be pursued for geocoding health data. High-level geocoding detail will provide a more precise geographic representation of health related events.

Conclusions: The main achievement of this study was to outline some of the difficulties encountered during the geocoding of health data and to put forward a set of guidelines, which could be useful to facilitate the process and enhance the quality of the results. Public health informatics represents an emerging specialty that highlights on the application of information science and technology to public health practice and research. Therefore, this study could draw the attention of the National Health Service to the underestimated problem of geocoding accuracy in health related data for environmental risk assessment.


Longley PA, Goodchild MF, Maguire DJ. Geographic Information Systems and Science. Second Edition. England: John Wiley & Sons Ltd; 2005. [Google Scholar]

Goldberg DW, Jacquez GM. Advances in geocoding for the health sciences.. Spat Spatiotemporal Epidemiol 2012;3(1):1-5. Available from: PubMed PMID: 22469486. doi: 10.1016/j.sste.2012.02.001. [Google Scholar]

Musa GJ, Chiang P, Sylk T, Bavley R, Keating W, Lakew B, et al. Use of GIS Mapping as a Public Health Tool-From Cholera to Cancer.. Health Serv Insights 2013 Nov;6:111-116. Available from: PubMed PMID: 25114567. doi: 10.4137/HSI.S10471. [Google Scholar]

Miranda ML, Casper M, Tootoo J, Schieb L. Putting chronic disease on the map: building GIS capacity in state and local health departments. . doi: 10.5888/pcd10.120321. [Google Scholar]

Carroll LN, Au AP, Detwiler LT, et al. Visualization and analytics tools for infectious disease epidemiology: a systematic review. J Biomed Inform 2014;51:287-298. Available from: PubMed PMID: 24747356. doi: 10.1016/j.jbi.2014.04.006. [Google Scholar]

Xie Y, Chen T, Lei M, Yang J, Guo Q, Song B, et al. Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: accuracy and uncertainty analysis.. Chemosphere 2011;82(3):468-476. Available from: PubMed PMID: 20970158. doi: 10.1016/j.chemosphere.2010.09.053. [Google Scholar]

Wang W, Ying Y, Wu Q, Zhang H, Ma D, Xiao W. A GIS-based spatial correlation analysis for ambient air pollution and AECOPD hospitalizations in Jinan, China. Respir Med 2015;109(3):372-378. Available from: PubMed PMID: 25682544. doi: 10.1016/j.rmed.2015.01.006. [Google Scholar]

Dangendorf F, Herbst S, Reintjes R, Kistemann T. Spatial patterns of diarrhoeal illnesses with regard to water supply structures--a GIS analysis.. Int J Hyg Environ Health 2002;205(3):183-191. Available from: PubMed PMID: 12040916. doi: 10.1078/1438-4639-00151. [Google Scholar]

Nas B, Berktay A. Groundwater quality mapping in urban groundwater using GIS. Environ Monit Assess 2010;160(1-4):215-227. Available from: PubMed PMID: 19096909. doi: 10.1007/s10661-008-0689-4. [Google Scholar]

Dijkstra A, Hak E, Janssen F. A systematic review of the application of spatial analysis in pharmacoepidemiologic research. Ann Epidemiol 2013;23(8):504-514. Available from: PubMed PMID: 23830932. doi: 10.1016/j.annepidem.2013.05.015. [Google Scholar]

Zandbergen PA. A comparison of address point, parcel and street geocoding techniques. Computers, Environment and Urban Systems 2008;32(3):214-232. Available from: doi: 10.1016/j.compenvurbsys.2007.11.006. [Google Scholar]

Kistemann T, Dangendorf F, Schweikart J. New perspectives on the use of Geographical Information Systems (GIS) in environmental health sciences. Int J Hyg Environ Health 2002;205(3):169-181. Available from: PubMed PMID: 12040915. doi: 10.1078/1438-4639-00145. [Google Scholar]

Usps 2. Postal Addressing Standards. Unites States Postal, Service. Publication 28. Updated April 2010;Available from. Available from: [Google Scholar]

Dearwent SM, Jacobs RR, Halbert JB. Locational uncertainty in georeferencing public health datasets. J Expo Anal Environ Epidemiol 2001;11(4):329-334. Available from: PubMed PMID: 11571612. doi: 10.1038/sj.jea.7500173. [Google Scholar]

Zhan FB, Brender JD, De_Lima I. Match rate and positional accuracy of two geocoding methods for epidemiologic research. Ann Epidemiol. Ann Epidemiol 2006;16(11):842-849. Available from: PubMed PMID: 17027286. doi: 10.1016/j.annepidem.2006.08.001. [Google Scholar]

Jacquez GM. A research agenda: does geocoding positional error matter in health GIS studies?. Spat Spatiotemporal Epidemiol 2012;3(1):7-16. Available from: PubMed PMID: 22469487. doi: 10.1016/j.sste.2012.02.002. [Google Scholar]

Bonner MR, Han D, Nie J. Positional accuracy of geocoded addresses in epidemiologic research. Epidemiology. Epidemiology 2003;14(4):408-412. Available from: PubMed PMID: 12843763. doi: 10.1097/01.EDE.0000073121.63254.c5. [Google Scholar]

Zandbergen PA, Hart TC, Lenzer KE. Error propagation models to examine the effects of geocoding quality on spatial analysis of individual-level datasets. Spat Spatiotemporal Epidemiol. Spat Spatiotemporal Epidemiol 2012;3(1):69-82. Available from: PubMed PMID: 22469492. doi: 10.1016/j.sste.2012.02.007. [Google Scholar]

Girardi P, Marcon A, Rava M, Pironi V, Ricci P, de Marco R. Spatial analysis of binary health indicators with local smoothing techniques The Viadana study.. Sci Total Environ 2012;414:380-386. Available from: PubMed PMID: 22100254. doi: 10.1016/j.scitotenv.2011.10.020. [Google Scholar]

Nuvolone D, Della Maggiore R, Maio S, Fresco R, Baldacci S, Carrozzi L, et al. Geographical information system and environmental epidemiology: a cross-sectional spatial analysis of the effects of traffic-related air pollution on population respiratory health. Environ Health 2011;10(1):12. Available from: PubMed PMID: 21362158. doi: 10.1186/1476-069X-10-12. [Google Scholar]