Emergency Medical Services Calls Analysis for Trend Prediction during Epidemic Outbreaks: Interrupted Time Series Analysis on 2020–2021 COVID-19 Epidemic in Lazio, Italy

Antonio Vinci, Amina Pasquarella, Maria Paola Corradi, Pelagia Chatzichristou, Gianluca D’Agostino, Stefania Iannazzo, Nicoletta Trani, Maria Annunziata Parafati, Leonardo Palombi and Domenico Antonio Ientile
Additional contact information
Antonio Vinci: Local Health Authority “Roma 1”, 00193 Rome, Italy
Amina Pasquarella: Azienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy
Maria Paola Corradi: Azienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy
Pelagia Chatzichristou: Azienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy
Gianluca D’Agostino: Azienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy
Stefania Iannazzo: Azienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy
Nicoletta Trani: Azienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy
Maria Annunziata Parafati: Azienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy
Leonardo Palombi: Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, 00166 Rome, Italy
Domenico Antonio Ientile: Azienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy

IJERPH, 2022, vol. 19, issue 10, 1-15

Abstract: (1) Background: During the COVID-19 outbreak in the Lazio region, a surge in emergency medical service (EMS) calls has been observed. The objective of present study is to investigate if there is any correlation between the variation in numbers of daily EMS calls, and the short-term evolution of the epidemic wave. (2) Methods: Data from the COVID-19 outbreak has been retrieved in order to draw the epidemic curve in the Lazio region. Data from EMS calls has been used in order to determine Excess of Calls (ExCa) in the 2020–2021 years, compared to the year 2019 (baseline). Multiple linear regression models have been run between ExCa and the first-order derivative (D’) of the epidemic wave in time, each regression model anticipating the epidemic progression (up to 14 days), in order to probe a correlation between the variables. (3) Results: EMS calls variation from baseline is correlated with the slope of the curve of ICU admissions, with the most fitting value found at 7 days (R 2 0.33, p < 0.001). (4) Conclusions: EMS calls deviation from baseline allows public health services to predict short-term epidemic trends in COVID-19 outbreaks, and can be used as validation of current data, or as an independent estimator of future trends.

Keywords: COVID-19; time series analysis; emergency medical services; public health; prediction models (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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