A Statistical Framework for Evaluating the Effectiveness of Vegetation Management in Reducing Power Outages Caused during Storms in Distribution Networks

This paper develops a statistical framework to analyze the effectiveness of vegetation management at reducing power outages during storms of varying severity levels. The framework was applied on the Eversource Energy distribution grid in Connecticut, USA based on 173 rain and wind events from 2005–2020, including Hurricane Irene, Hurricane Sandy, and Tropical Storm Isaias. The data were binned by storm severity (high/low) and vegetation management levels, where a maximum applicable length of vegetation management for each circuit was determined, and the data were divided into four bins based on the actual length of vegetation management performed divided by the maximum applicable value (0–25%, 25–50%, 50–75%, and 75–100%). Then, weather and overhead line length normalized outage statistics were taken for each group. The statistics were used to determine the effectiveness of vegetation management and its dependence on storm severity. The results demonstrate a higher reduction in damages for lower-severity storms, with a reduction in normalized outages between 45.8% and 63.8%. For high-severity events, there is a large increase in effectiveness between the highest level of vegetation management and the two lower levels, with 75–100% vegetation management leading to a 37.3% reduction in trouble spots. Yet, when evaluating system reliability, it is important to look at all storms combined, and the results of this study provide useful information on total annual trouble spots and allow for analysis of how various vegetation management scenarios would impact trouble spots in the electric grid. This framework can also be used to better understand how more rigorous vegetation management standards (applying ETT) help reduce outages at an individual event level. In future work, a similar framework may be used to evaluate other resilience improvements.

Registered nurses: can our supply meet the demand during a disaster?

Background Death and destructions are often reported during natural disasters; yet little is known about how hospitals operate during disasters and if there are sufficient resources available for hospitals to provide ongoing care during these catastrophic events. The purpose of this study was to determine if the State of New Jersey had a supply of registered nurses (RNs) that was sufficient to meet the needs of hospitalized patients during a natural disaster – Hurricane Sandy. Methods Secondary data were used to forecast the demand and supply of New Jersey RNs during Hurricane Sandy. Data sources from November 2011 and 2012 included the State Inpatient Databases (SID), American Hospital Association (AHA) Annual Survey on hospital characteristics and staffing data from New Jersey Department of Health. Three models were used to estimate the RN shortage for each hospital, which was the difference between the demand and supply of RN full-time equivalents. Results Data were available on 66 New Jersey hospitals, more than half of which experienced a shortage of RNs during Hurricane Sandy. For hospitals with a RN shortage in ICUs, a 20% increase in observed RN supply was needed to meet the demand; and a 10% increase in observed RN supply was necessary to meet the demand for hospitals with a RN shortage in non-ICUs. Conclusion Findings from this study suggest that many hospitals in New Jersey had a shortage of RNs during Hurricane Sandy. Efforts are needed to improve the availability of nurse resources during a natural disaster.

Peritraumatic Stress From a Disaster Increases Risk for Onset of Chronic Diseases Among Older Adults

Background and Objectives Our understanding of the impact of disaster exposure on the physical health of older adults is largely based on hospital admissions for acute illnesses in the weeks following a disaster. Studies of longer-term outcomes have centered primarily on mental health. Missing have been studies examining whether exposure to disaster increases the risk for the onset of chronic diseases. We examined the extent to which 2 indicators of disaster exposure (geographic exposure and peritraumatic stress) were associated with new onset of cardiovascular disease, diabetes, arthritis, and lung disease to improve our understanding of the long-term physical health consequences of disaster exposure. Research Design and Methods We linked self-reported data collected prior to and following Hurricane Sandy from a longitudinal panel study with Medicare data to assess time to new onset of chronic diseases in the 4 years after the hurricane. Results We found that older adults who reported high levels of peritraumatic stress from Hurricane Sandy had more than twice the risk of experiencing a new diagnosis of lung disease, diabetes, and arthritis in the 4 years after the hurricane compared to older adults who did not experience high levels of peritraumatic stress. Geographic proximity to the hurricane was not associated with these outcomes. Analyses controlled for known risk factors for the onset of chronic diseases, including demographic, psychosocial, and health risks. Discussion and Implications Findings reveal that physical health effects of disaster-related peritraumatic stress extend beyond the weeks and months after a disaster and include new onset of chronic diseases that are associated with loss of functioning and early mortality.

Impact of Hurricane Sandy on Hospital Admissions 2 Years Later

Disaster exposure is often followed by acute illness and injuries requiring hospital admission in the weeks after the disaster. It is not known whether disaster exposure is associated with hospitalization in the years after the disaster. We examined the extent to which disaster exposure is associated with hospitalization two years after Hurricane Sandy. The analyses fill a gap in our understanding of long-term physical health consequences of disaster exposure by identifying older adults at greatest risk for hospitalization two years after disaster exposure. Older adults (n=909) who participated in a longitudinal panel study provided data before and after Hurricane Sandy. These data were linked with Medicare inpatient files to assess the impact of Hurricane Sandy on hospital admissions after the post-hurricane interview. Those who reported experiencing a lot of fear and distress in the midst of Hurricane Sandy were at an increased risk of being hospitalized in the second or third years after the hurricane [Hazard Ratio=1.81 (1.15 – 2.85)]. Findings held after controlling for pre-hurricane demographics, social risks, chronic conditions, and decline in physical functioning after the hurricane. These findings are the first to show that disaster exposure increases risk for hospital admissions two years after a disaster, and that older adults’ appraisal of their emotional distress during the disaster has prognostic significance that is not explained by known risks for hospital admissions. The findings suggest that interventions during the storm and after the storm, may reduce long-term health consequences of disaster exposure among older adults.

Wave-like global economic ripple response to Hurricane Sandy

Tropical cyclones range among the costliest disasters on Earth. Their economic repercussions along the supply and trade network also affect remote economies that are not directly affected. We here simulate possible global repercussions on consumption for the example case of Hurricane Sandy in the US (2012) using the shock-propagation model Acclimate. The modeled shock yields a global three-phase ripple: an initial production demand reduction and associated consumption price decrease, followed by a supply shortage with increasing prices, and finally a recovery phase. Regions with strong trade relations to the US experience strong magnitudes of the ripple. A dominating demand reduction or supply shortage leads to overall consumption gains or losses of a region, respectively. While finding these repercussions in historic data is challenging due to strong volatility of economic interactions, numerical models like ours can help to identify them by approaching the problem from an exploratory angle, isolating the effect of interest. For this, our model simulates the economic interactions of over 7,000 regional economic sectors, interlinked through about 1.8 million trade relations. Under global warming, the wave-like structures of the economic response to major hurricanes like the one simulated here are likely to intensify and potentially overlap with other weather extremes.

Wind Speed Analysis of Hurricane Sandy

The database of the HWind project sponsored by the National Oceanic and Atmospheric Administration (NOAA) for hurricanes between 1994 and 2013 is analysed. This is the first objective of the current research. Among these hurricanes, Hurricane Sandy was selected for a detailed study due to the number of files available and its social relevance, with this being the second objective of this study. Robust wind speed statistics showed a sharp increase in wind speed, around 6 m s−1 at the initial stage as Category 1, and a linear progression of its interquartile range, which increased at a rate of 0.54 m s−1 per day. Wind speed distributions were initially right-skewed. However, they evolved to nearly symmetrical or even left-skewed distributions. Robust kurtosis was similar to that of the Gaussian distribution. Due to the noticeable fraction of wind speed intermediate values, the Laplace distribution was used, its scale parameter increasing slightly during the hurricane’s lifecycle. The key features of the current study were the surface and recirculation factor calculation. The surface area with a category equal to, or higher than, a tropical storm was calculated and assumed to be circular. Its radius increased linearly up to 600 km. Finally, parcel trajectories were spirals in the lower atmosphere but loops in the mid-troposphere due to wind translation and rotation. The recirculation factor varied, reaching values close to 0.9 and revealing atmospheric stratification.

Mental Health Effects of Hurricane Sandy on Older Adults

Objectives To examine whether hurricane exposure, lack of access to medical care (LAMC), and displacement during Hurricane Sandy were associated with PTSD and other mental health (MH) symptoms among older adult New York residents. Methods Participants ( N = 411) were ≥60 years old at the time of survey data collection (1–4 years post-Sandy). Outcomes included PTSD, depression, and anxiety symptoms and stress. Hurricane exposure, displacement, and LAMC were primary predictors. Results Older adults with greater hurricane exposure had increased PTSD, anxiety, and stress symptoms. LAMC had a strong association (ORadj = 4.11) with PTSD symptoms but was not associated with other MH symptoms. Displacement was not associated with MH outcomes. Discussion This is the first study to examine exposure, displacement, and LAMC together and to examine their varying impacts on different MH outcomes among older adults post-hurricane. Findings support the importance of disaster preparedness interventions tailored to the MH needs of community-dwelling older adults.

Ocean Affects from Severe Weather Systems in Coastal Areas

Severe weather systems can generate large waves and storm surges which can cause many fatalities in coastal areas. In extreme circumstances a single cyclone caused up to 500,000 fatalities in the Bay of Bengal in 1970. Adaption by authorities in that region from evacuations and construction of storm shelters have significantly reduced the number of such fatalities there. The effects of Hurricane Sandy in 2012 in New York City and surrounding areas is examined to show how ocean effects can cause many casualties. Scrutiny of a European storm shows how a slight error in analysis can fail to detect a deadly increase in intensity which caused many fatalities. World record wave height events are examined, and the historical Australian east coast events are investigated. The impacts from long period waves emanating from distant storms are shown to be a forecasting problem.