Policy-Relevant Indicators of Urban Emergency Medical Services COVID-19-Patient Encounters
Name
11524_2022_Article_672.pdf
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608.59 KB
Format
Adobe PDF
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053d234ff630e5139d88d00a3bf546f4
Author(s)
Brennan, Mark
Steil, Justin
Dyer, Sophia
Segal, Laura
Salvia, James
Serino, Erin
Date Issued
November 2, 2022
Publisher
Springer US
Citation
Brennan, Mark, Steil, Justin, Dyer, Sophia, Segal, Laura, Salvia, James et al. 2022. "Policy-Relevant Indicators of Urban Emergency Medical Services COVID-19-Patient Encounters."
Version
Final published version
Abstract
Abstract
In the first two years of the COVID-19 pandemic, members of Boston Emergency Medical Services, the City of Boston’s municipal ambulance service, had 7,689 encounters with confirmed-positive Boston residents. As COVID-19 virus strains continue to infect residents in Boston and across the country, understanding the correlation between population positivity, EMS encounters, and hospitalizations can inform healthcare response. This study examines urban virus-surveillance indicators that can serve as an early warning of the volume of Emergency Medical Services (EMS) encounters with COVID-19 positive patients and subsequently how EMS encounters with confirmed COVID-19 patients can serve as an early indicator of future hospital-demand surges. With daily data from Boston EMS and three other public agencies, we evaluate the relationship between five indicators and confirmed Boston EMS COVID-19 encounters by estimating separate Auto Regressive Integrated Moving Average models and cross-correlating their residuals. This study finds a significant and positive correlation between new COVID-19 cases citywide and EMS encounters 6 days later (p < 0.01), as well as between confirmed EMS encounters with COVID-19 patients and the number of intensive care unit beds occupied 7- and 18 -days later (p < 0.01). This study provides city health leadership needed clarity on the specific ordering and associated time lag in which infections in the population increase, EMS members encounter positive patients, and hospitals deliver care.
MIT Department
Massachusetts Institute of Technology. Center for Computational Science and Engineering
Massachusetts Institute of Technology. Department of Urban Studies and Planning
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1007/s11524-022-00672-0
