ArticleJournal of urban health : bulletin of the New York Academy of Medicine2026
Estimating Spatial and Temporal Patterns of Residential Power Outages in Massachusetts from 2013 to 2022 Using Public Records.
Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Power outages are a growing threat to human health. Extreme weather events and strains on the electrical grid can cut off access to critical health-supporting medical equipment. However, the full scope of health impacts related to power outages has not been quantified, in large part because outage data with high spatial and temporal resolution are not widely available. In this work, we present a methodological framework for constructing a longitudinal, high spatial and temporal resolution dataset of power outages using public records. We apply this method to the Commonwealth of Massachusetts, extracting and synthesizing data from daily town-level reports submitted by electricity providers to the Massachusetts Department of Public Utilities from 2013 to 2022. For reference, towns in Massachusetts (N = 351) are smaller than counties (N = 14). For each town and day, we calculated the fraction of electrical circuits experiencing a power outage and classified this into a tertile categorical variable: mild, moderate, or severe. Across the state, the median and inter-quartile range (IQR) of outages per town was 7.3 power outages per year of any type [IQR: 4.3, 11.4], with substantial heterogeneity across months. Mild outages were most associated with equipment failure or planned maintenance, whereas moderate and severe outages were associated with tree interference (35.6% and 50.9% of outages, respectively). Developing suburbs and rural towns experienced the highest frequency of severe outages, while towns with a high density of Environmental Justice populations experienced more frequent mild outages. Our dataset reinforces substantial spatial and temporal heterogeneity in power outages, and our methods provide a framework for building similar datasets for future analyses of population vulnerability and health impacts associated with power outages in other states where curated datasets are not available.
Indexed as
Identifiers
42632856What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.