Geocoding cryptosporidiosis cases in Ireland (2008–2017)—development of a reliable, reproducible, multiphase geocoding methodology
Autor: | Jean O'Dwyer, P McKeown, Paul Hynds, Patricia Garvey, Howard Johnson, Lisa Domegan, Coilín ÓhAiseadha |
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Rok vydání: | 2021 |
Předmět: |
Matching (statistics)
Geospatial analysis Epidemiology 030231 tropical medicine Cryptosporidiosis Geographic Mapping Data validation computer.software_genre 03 medical and health sciences 0302 clinical medicine Medicine and Health Sciences Humans Medicine 030212 general & internal medicine Spatial analysis Protocol (science) Geocoding Surveillance Application programming interface business.industry Data quality Geospatial Censuses General Medicine Geographic Information Systems Original Article Data mining business Ireland computer |
Zdroj: | Articles Irish Journal of Medical Science |
ISSN: | 1863-4362 0021-1265 |
DOI: | 10.1007/s11845-020-02468-0 |
Popis: | Background Geocoding (the process of converting a text address into spatial data) quality may affect geospatial epidemiological study findings. No national standards for best geocoding practice exist in Ireland. Irish postcodes (Eircodes) are not routinely recorded for infectious disease notifications and > 35% of dwellings have non-unique addresses. This may result in incomplete geocoding and introduce systematic errors into studies. Aims This study aimed to develop a reliable and reproducible methodology to geocode cryptosporidiosis notifications to fine-resolution spatial units (Census 2016 Small Areas), to enhance data validity and completeness, thus improving geospatial epidemiological studies. Methods A protocol was devised to utilise geocoding tools developed by the Health Service Executive’s Health Intelligence Unit. Geocoding employed finite-string automated and manual matching, undertaken sequentially in three additive phases. The protocol was applied to a cryptosporidiosis notification dataset (2008–2017) from Ireland’s Computerised Infectious Disease Reporting System. Outputs were validated against devised criteria. Results Overall, 92.1% (4266/4633) of cases were successfully geocoded to one Small Area, and 95.5% (n = 4425) to larger spatial units. The proportion of records geocoded increased by 14% using the multiphase approach, with 5% of records re-assigned to a different spatial unit. Conclusions The developed multiphase protocol improved the completeness and validity of geocoding, thus increasing the power of subsequent studies. The authors recommend capturing Eircodes ideally using application programming interface for infectious disease or other health-related datasets, for more efficient and reliable geocoding. Where Eircodes are not recorded/available, for best geocoding practice, we recommend this (or a similar) quality driven protocol. |
Databáze: | OpenAIRE |
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