  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.
