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Assess Hurricane Sandy’s impact on primary care providers’ services in the Rockaways.
Methods
In-person surveys were conducted in 2014. A list of 46 health care sites in the area of interest was compiled and each site was called to offer participation in our survey. Respondents included physicians and practice administrators who remained familiar with Sandy-related operational challenges.
Results
Of the 40 sites that opted in, most had been in their current location for more than 10 years (73%) and were a small practice (1 or 2 physicians) before Hurricane Sandy (75%). All but 2 (95%) had to temporarily close or relocate. All sites experienced electrical problems that impacted landline, fax, and Internet. Less than one-quarter (n = 9) reported having a plan for continuity of services before Hurricane Sandy, and 43% reported having a plan poststorm. The majority (80%) did not report coordinating with other primary care stakeholders or receiving support from government agencies during the Sandy response.
Conclusions
Hurricane Sandy significantly disrupted access to primary care in the Rockaways. Severe impact to site operations and infrastructure forced many practices to relocate. Greater emergency response and recovery planning is needed, including with government agencies, to minimize disruptions of access to primary care during disaster recovery. (Disaster Med Public Health Preparedness. 2016;10:492–495)
Hurricane 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.
Methods
Using 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.
Results
The 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.
Conclusions
An 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)
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