This study aims to assess the perception and attitude of emergency medical services (EMS) providers toward working during disease outbreaks, and the factors that may influence their decisions to ultimately work or not.

This is a cross-sectional study assessing the attitude of EMS providers to work during disease outbreaks. Descriptive statistics and regression analyses were performed to assess attitudes toward reporting for duty and factors that influence providers’ decisions.

Of the 500 surveys distributed, 466 (93.2%) were complete and included for analysis. The majority of participants (70.2%) are male with a mean age of 27 (SD 4.3) years. The study found that the majority (71.1%) of participants are willing to come to work during disease outbreaks. The study found 7 predictors of reporting for duty. Confidence that employer will provide adequate protective gear was the most significant predictor (odds ratio [OR], 3.95; 95% confidence interval [CI] = 2.31-5.42). Concern for family safety was the most important barrier against coming to work (OR, 0.40; 95% CI = 0.21-0.73).

Providing adequate supplies of protective gear along with knowledge and training for disease outbreak are the main factors that enhance providers to fulfill their work expectations.

This study empirically examines preparedness with a kit, medication, and a disaster plan on disaster outcomes including perceived recovery, property damage, and use of medical or mental health services.

Using a cross-sectional, retrospective study design, 1114 households in New York City were interviewed 21-34 months following Super Storm Sandy. Bivariate associations were examined and logistic regression models fit to predict the odds of disaster outcomes given the level of preparedness.

Respondents with an evacuation plan were more likely to report not being recovered (odds ratio [OR] = 2.4; 95% confidence interval [CI]: 1.5-3.8), property damage (OR = 1.4; 95% CI: 1.1-1.9), and use of medical services (OR = 2.3; 95% CI: 1.1-4.5). Respondents reporting a supply of prescription medication were more likely to report using mental health (OR = 3.5; 95% CI: 1.2-9.8) and medical services (OR = 2.3; 95% CI: 1.1-4.8)

Having a kit, plan, and medication did not reduce risk of adverse outcomes in Superstorm Sandy in this sample. Disaster managers should consider the lack of evidence for preparedness when making public education and resource allocation decisions. Additional research is needed to identify preparedness measures that lead to better outcomes for more efficient and effective response and recovery.

Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster.

We developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties.

The conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature.

The work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience. (Disaster Med Public Health Preparedness. 2018;12:127–137)