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An Agent-Based Model for Addressing the Impact of a Disaster on Access to Primary Care Services

Authors :
Elizabeth Van Nostrand
Rishi K. Sood
Margaret A. Potter
Tina Batra Hershey
Mary G. Krauland
Angelica Bocour
Supriya Kumar
Hasan Guclu
David Galloway
Source :
Disaster Medicine and Public Health Preparedness. 10:386-393
Publication Year :
2016
Publisher :
Cambridge University Press (CUP), 2016.

Abstract

ObjectiveHurricane Sandy in the Rockaways, Queens, forced residents to evacuate and primary care providers to close or curtail operations. A large deficit in primary care access was apparent in the immediate aftermath of the storm. Our objective was to build a computational model to aid responders in planning to situate primary care services in a disaster-affected area.MethodsUsing an agent-based modeling platform, HAZEL, we simulated the Rockaways population, its evacuation behavior, and primary care providers’ availability in the aftermath of Hurricane Sandy. Data sources for this model included post-storm and community health surveys from New York City, a survey of the Rockaways primary care providers, and research literature. The model then tested geospatially specific interventions to address storm-related access deficits.ResultsThe model revealed that areas of high primary care access deficit were concentrated in the eastern part of the Rockaways. Placing mobile health clinics in the most populous census tracts reduced the access deficit significantly, whereas increasing providers’ capacity by 50% reduced the deficit to a lesser degree.ConclusionsAn agent-based model may be a useful tool to have in place so that policy makers can conduct scenario-based analyses to plan interventions optimally in the event of a disaster. (Disaster Med Public Health Preparedness. 2016;10:386–393)

Details

ISSN :
1938744X and 19357893
Volume :
10
Database :
OpenAIRE
Journal :
Disaster Medicine and Public Health Preparedness
Accession number :
edsair.doi.dedup.....30bcd8efccd7d17cc041aa04c62e48cc
Full Text :
https://doi.org/10.1017/dmp.2016.44