Literature DB >> 34656750

Uncertainty in geospatial health: challenges and opportunities ahead.

Eric M Delmelle1, Michael R Desjardins2, Paul Jung3, Claudio Owusu4, Yu Lan3, Alexander Hohl5, Coline Dony6.   

Abstract

PURPOSE: Uncertainty is not always well captured, understood, or modeled properly, and can bias the robustness of complex relationships, such as the association between the environment and public health through exposure, estimates of geographic accessibility and cluster detection, to name a few.
METHODS: We review current challenges and future opportunities as geospatial data and analyses are applied to the field of public health. We are particularly interested in the sources of uncertainty in geospatial data and how this uncertainty may propagate in spatial analysis.
RESULTS: We present opportunities to reduce the magnitude and impact of uncertainty. Specifically, we focus on (1) the use of multiple reference data sources to reduce geocoding errors, (2) the validity of online geocoders and how confidentiality (e.g., HIPAA) may be breached, (3) use of multiple reference data sources to reduce geocoding errors, (4) the impact of geoimputation techniques on travel estimates, (5) residential mobility and how it affects accessibility metrics and clustering, and (6) modeling errors in the American Community Survey. Our paper discusses how to communicate spatial and spatiotemporal uncertainty, and high-performance computing to conduct large amounts of simulations to ultimately increase statistical robustness for studies in public health.
CONCLUSIONS: Our paper contributes to recent efforts to fill in knowledge gaps at the intersection of spatial uncertainty and public health.
Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  American community survey; GIS; Geocoding; Geoimputation; High-performance computing; Residential Mobility Simulations; Uncertainty

Mesh:

Year:  2021        PMID: 34656750     DOI: 10.1016/j.annepidem.2021.10.002

Source DB:  PubMed          Journal:  Ann Epidemiol        ISSN: 1047-2797            Impact factor:   3.797


  3 in total

1.  Time-activity and daily mobility patterns during pregnancy and early postpartum - evidence from the MADRES cohort.

Authors:  Li Yi; Yan Xu; Sandrah P Eckel; Sydney O'Connor; Jane Cabison; Marisela Rosales; Daniel Chu; Thomas A Chavez; Mark Johnson; Tyler B Mason; Theresa M Bastain; Carrie V Breton; Genevieve F Dunton; John P Wilson; Rima Habre
Journal:  Spat Spatiotemporal Epidemiol       Date:  2022-03-24

2.  Geospatial Perspectives on the Intersection of Chronic Disease and COVID-19.

Authors:  Jeremy Mennis; Kevin A Matthews; Sara L Huston
Journal:  Prev Chronic Dis       Date:  2022-06-30       Impact factor: 4.354

3.  Utilizing prospective space-time scan statistics to discover the dynamics of coronavirus disease 2019 clusters in the State of São Paulo, Brazil.

Authors:  Ricardo Vicente Ferreira; Marcos Roberto Martines; Rogério Hartung Toppa; Luiza Maria de Assunção; Michael Richard Desjardins; Eric Delmelle
Journal:  Rev Soc Bras Med Trop       Date:  2022-08-05       Impact factor: 2.141

  3 in total

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