Modifiable Areal Unit Problems for Infectious Disease Cases Described in Medicare and Medicaid Claims, 2016-2019

Introduction: Modifiable Areal Unit Problems are a major source of spatial uncertainty, but their impact on infectious diseases and epidemic detection is unknown

Bibliographische Detailangaben
Veröffentlicht in:Journal of bacteriology & parasitology. - 2011. - 15(2024), Suppl 27 vom: 23.
1. Verfasser: Williams, Nick (VerfasserIn)
Format: Aufsatz
Sprache:English
Veröffentlicht: 2024
Zugriff auf das übergeordnete Werk:Journal of bacteriology & parasitology
Schlagworte:Journal Article
Beschreibung
Zusammenfassung:Introduction: Modifiable Areal Unit Problems are a major source of spatial uncertainty, but their impact on infectious diseases and epidemic detection is unknown
Methods: CMS claims (2016-2019) which included infectious disease codes learned through Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) were extracted and analysed at two different units of geography; states and 'home to work commute extent' mega regions. Analysis was per member per month. Rolling average above the series median within geography and agent of infection was used to assess peak detection. Spatial random forest was used to assess region segmentation by agent of infection
Results: Mega-regions produced better peak discovery for most, but not all agents of infection. Variable importance and Gini measures from spatial random forest show agent-location discrimination between states and regions
Conclusion: Researchers should defend their geographic unit of report used in peer review studies on an agent by-agent basis
Beschreibung:Date Revised 04.01.2025
published: Print-Electronic
Citation Status PubMed-not-MEDLINE
ISSN:2155-9597