Predicting Covid-19 EMS Incidents from Daily Hospitalization Trends

TL;DR

This study analyzes how Covid-19 affected EMS call patterns in Travis County and develops a forecasting model showing that daily Covid-19 hospitalizations strongly predict EMS incidents, aiding future pandemic response planning.

Contribution

The paper introduces a robust time series model that accurately forecasts Covid-19 EMS incidents based on hospitalization data, highlighting critical temporal changes during the pandemic.

Findings

Covid-19 caused significant shifts in EMS call distribution.

Hospitalization counts are strong predictors of EMS calls.

EMS demand for Covid-19 symptoms can be forecasted effectively.

Abstract

Introduction: The aim of our retrospective study was to quantify the impact of Covid-19 on the temporal distribution of Emergency Medical Services (EMS) demand in Travis County, Austin, Texas and propose a robust model to forecast Covid-19 EMS incidents. Methods: We analyzed the temporal distribution of EMS calls in the Austin-Travis County area between January 1st, 2019, and December 31st, 2020. Change point detection was performed to identify critical dates marking changes in EMS call distributions, and time series regression was applied for forecasting Covid-19 EMS incidents. Results: Two critical dates marked the impact of Covid-19 on the distribution of EMS calls: March 17th, when the daily number of non-pandemic EMS incidents dropped significantly, and May 13th, by which the daily number of EMS calls climbed back to 75% of the number in pre-Covid-19 time. The new daily count of the hospitalization of Covid-19 patients alone proves a powerful predictor of the number of pandemic EMS calls, with an r2 value equal to 0.85. In particular, for every 2.5 cases where EMS takes a Covid-19 patient to a hospital, one person is admitted. Conclusion: The mean daily number of non-pandemic EMS demand was significantly less than the period before Covid-19 pandemic. The number of EMS calls for Covid-19 symptoms can be predicted from the daily new hospitalization of Covid-19 patients. These findings may be of interest to EMS departments as they plan for future pandemics, including the ability to predict pandemic-related calls in an effort to adjust a targeted response.