Data on major power outage events in the continental U.S.
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ABSTRACT:
SUBMITTER: Mukherjee S
PROVIDER: S-EPMC6141375 | biostudies-literature | 2018 Aug
REPOSITORIES: biostudies-literature
Publications
Data on major power outage events in the continental U.S.
Mukherjee Sayanti S Nateghi Roshanak R Hastak Makarand M
Data in brief 20180626
This paper presents the data that is used in the article entitled "A Multi-Hazard Approach to Assess Severe Weather-Induced Major Power Outage Risks in the U.S." (Mukherjee et al., 2018) [1]. The data described in this article pertains to the major outages witnessed by different states in the continental U.S. during January 2000-July 2016. As defined by the Department of Energy, the major outages refer to those that impacted atleast 50,000 customers or caused an unplanned firm load loss of atlea ...[more]
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Project description:BackgroundChronic obstructive pulmonary disease (COPD) is the third-leading cause of death worldwide with continuous rise. Limited studies indicate that COPD was associated with major storms and related power outages (PO). However, significant gaps remain in understanding what PO's role is on the pathway of major storms-COPD. This study aimed to examine how PO mediates the major storms-COPD associations.MethodsIn this time-series study, we extracted all hospital admissions with COPD as the principal diagnosis in New York, 2001-2013. Using distributed lag nonlinear models, the hospitalization rate during major storms and PO was compared to non-major storms and non-PO periods to determine the risk ratios (RRs) for COPD at each of 0-6 lag days respectively after controlling for time-varying confounders and concentration of fine particulate matter (PM2.5). We then used Granger mediation analysis for time series to assess the mediation effect of PO on the major storms-COPD associations.ResultsThe RRs of COPD hospitalization following major storms, which mainly included flooding, thunder, hurricane, snow, ice, and wind, were 1.23 to 1.49 across lag 0-6 days. The risk was strongest at lag3 and lasted significantly for 4 days. Compared with non-outage periods, the PO period was associated with 1.23 to 1.61 higher risk of COPD admissions across lag 0-6 days. The risk lasted significantly for 2 days and was strongest at lag2. Snow, hurricane and wind were the top three contributors of PO among the major storms. PO mediated as much as 49.6 to 65.0% of the major storms-COPD associations.ConclusionsBoth major storms and PO were associated with increased hospital admission of COPD. PO mediated almost half of the major storms-COPD hospitalization associations. Preparation of surrogate electric system before major storms is essential to reduce major storms-COPD hospitalization.
| S-EPMC8556928 | biostudies-literature
Project description:BackgroundCOPD is the third leading cause of death in the United States, with 16 million Americans currently experiencing difficulty with breathing. Power outages could be life-threatening for those relying on electricity. However, significant gaps remain in understanding the potential impact of power outages on COPD exacerbations.Research questionThe goal of this study was to determine how power outages affect COPD exacerbations.Study design and methodsUsing distributed lag nonlinear models controlling for time-varying confounders, the hospitalization rate during a power outage was compared vs non-outage periods to determine the rate ratio (RR) for COPD and its subtypes at each of 0 to 6 lag days in New York State from 2001 to 2013. Stratified analyses were conducted according to sociodemographic characteristics, season, and clinical severity; changes were investigated in numerous critical medical indicators, including length of stay, hospital cost, the number of comorbidities, and therapeutic procedures between the two periods.ResultsThe RR of COPD hospitalization following power outages ranged from 1.03 to 1.39 across lag days. The risk was strongest at lag0 and lag1 days and lasted significantly for 7 days. Associations were stronger for the subgroup with acute bronchitis (RR, 1.08-1.69) than for cases of acute exacerbation (RR, 1.03-1.40). Compared with non-outage periods, the outage period was observed to be $4.67 thousand greater in hospital cost and 1.38 greater in the number of comorbidities per case. The average cost (or number of comorbidities) was elevated in all groups stratified according to cost (or number of comorbidities). In contrast, changes in the average length of stay (-0.43 day) and the average number of therapeutic procedures (-0.09) were subtle.InterpretationPower outages were associated with a significantly elevated rate of COPD hospitalization, as well as greater costs and number of comorbidities. The average cost and number of comorbidities were elevated in all clinical severity groups.
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Project description:Major power outages have risen over the last two decades, largely due to more extreme weather conditions. However, there is a lack of knowledge on the distribution of power outages and its relationship to social vulnerability and co-occurring hazards. We examined the associations between localized outages and social vulnerability factors (demographic characteristics), controlling for environmental factors (weather), in Washington State between 2018-2021. We additionally analyzed the validity of PowerOutage.us data compared to federal datasets. The population included 27 counties served by 14 electric utilities. We developed a continuous measure of daily outage burden using PowerOutage.us data and operationalized social vulnerability using four factors: poverty level, unemployment, disability, and limited English proficiency. We applied zero-altered lognormal generalized additive mixed-effects models to characterize the relationship between social vulnerability and daily power outage burden, controlling for daily minimum temperature, maximum wind speed, and precipitation, from 2018 to 2021 in Washington State. We found that social vulnerability factors have non-linear relationships with outages. Wind and precipitation are consistent drivers of outage occurrence and duration. There are seasonal effects that vary by county-utility area. Both PowerOutage.us and federal datasets have missing and inaccurate outage data. This is the first study evaluating differential exposure to localized outages as related to social vulnerability that has accounted for weather and temporal correlation. There is a lack of transparency into power outage distribution for those most vulnerable to climate impacts, despite known contributions by electric utilities to climate change. For effective public health surveillance of power outages and transparency, outage data should be made available at finer spatial resolution and temporal scales and/or utilities should be required to report differential exposure to power outages for socially vulnerable populations.
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Project description:ImportanceExposure to hurricanes is associated with increased mortality and morbidity in nursing home (NH) residents, but the factors contributing to these outcomes are less understood. One hypothesized pathway could be power outages from hurricanes that expose NH residents to excess ambient heat.ObjectiveTo determine the association of power loss from Hurricane Irma with hospitalization and mortality in NH residents in Florida.Design setting and participantsThis retrospective cohort study of NH residents residing in Florida when Hurricane Irma landed on September 10, 2017, assessed mortality at 7 and 30 days after the storm and hospitalization at 30 days after the storm. The analysis was conducted from May 2, 2021, to June 28, 2021. All NH residents residing in Florida at landfall were eligible (N = 67 273). We excluded those younger than 65 years, missing power status information, or who were evacuated (13 178 [19.6%]).ExposureWe used state-administered surveys to determine NH power outage status. Exposed residents experienced a power outage poststorm, whereas unexposed residents did not experience a power outage poststorm.Main outcomes and measuresWe used Medicare claims to assess mortality and hospitalization after Hurricane Irma landfall using generalized linear models with robust standard errors.ResultsIn the aftermath of Hurricane Irma, 27 892 residents (18 510 women [66.4%]; 3906 [14.0%] Black, 1651 [5.9%] Hispanic, and 21 756 [78.0%] White individuals) in 299 NHs were exposed to power loss and 26 203 residents (17 620 women [67.2%]; 4175 [15.9%] Black, 1030 [3.9%] Hispanic, and 20 477 [78.1%] White individuals) in 292 NHs were unexposed. Nursing homes that lost power were similar in size, quality star rating, and type of ownership compared with NHs that did not lose power. Power loss was associated with an increased adjusted odds of mortality among all residents within 7 days (odds ratio [OR],1.25; 95% CI,1.05-1.48) and 30 days (OR, 1.12; 95% CI,1.02-1.23) poststorm and hospitalization within 30 days, although only among residents aged 65 to 74 years (OR, 1.16; 95% CI, 1.03-1.33).Conclusions and relevanceIn this cohort study, power loss was associated with higher odds of mortality in all affected NH residents and hospitalization in some residents. The benefits and costs of policies that require NHs to have emergency alternate power sources should be assessed.
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