Objectives: Influenza-like illness (ILI) refers to the set of symptoms associated with seasonal influenza infection. In Italy, the syndromic surveillance system RespiVirNet uses both epidemiological and virological data to monitor ILI incidence with a weekly cadence. To estimate ILI incidence in real time, several countries adopted surveil- lance systems which include data from the emergency-urgency (E-U) system. The aim of this study was to evaluate the relationship between the number of calls for respiratory symptoms to the E-U system and the regional incidence of ILI cases identified by the Italian syndromic surveillance system. Study design: Retrospective observational cohort study Methods: We analyzed data in the Lombardy region for the flu season from 2014 to 2024, excluding the COVID-19 pandemic period (from 2020 to 2022). We performed a linear regression analysis considering ILI incidence as the dependent variable and the percentage of respiratory calls to the E-U system as the independent variable. Results: Statistical analysis showed a positive correlation (r = 0.70), with a statistically significant coefficient of 1.34 (p-value <0.001) and R2 of 0.50. Conclusions: The observed correlation highlights the potential use of prehospital E-U system data in the sur- veillance systems of infectious diseases by using real-time data, encouraging future research to explore the limits and possibilities of an integrated surveillance system.

Telephone calls to emergency medical service as a tool to predict influenza-like illness: A 10-year study / R. Bonora, E.M. Ticozzi, F.E. Pregliasco, A. Pagliosa, A. Bodina, D. Cereda, G. Perotti, M. Lombardo, G. Stirparo. - In: PUBLIC HEALTH. - ISSN 0033-3506. - 238:(2025 Jan), pp. 239-244. [10.1016/j.puhe.2024.12.021]

Telephone calls to emergency medical service as a tool to predict influenza-like illness: A 10-year study

E.M. Ticozzi
Secondo
;
F.E. Pregliasco;A. Bodina;D. Cereda;G. Perotti;M. Lombardo
Penultimo
;
G. Stirparo
Ultimo
2025

Abstract

Objectives: Influenza-like illness (ILI) refers to the set of symptoms associated with seasonal influenza infection. In Italy, the syndromic surveillance system RespiVirNet uses both epidemiological and virological data to monitor ILI incidence with a weekly cadence. To estimate ILI incidence in real time, several countries adopted surveil- lance systems which include data from the emergency-urgency (E-U) system. The aim of this study was to evaluate the relationship between the number of calls for respiratory symptoms to the E-U system and the regional incidence of ILI cases identified by the Italian syndromic surveillance system. Study design: Retrospective observational cohort study Methods: We analyzed data in the Lombardy region for the flu season from 2014 to 2024, excluding the COVID-19 pandemic period (from 2020 to 2022). We performed a linear regression analysis considering ILI incidence as the dependent variable and the percentage of respiratory calls to the E-U system as the independent variable. Results: Statistical analysis showed a positive correlation (r = 0.70), with a statistically significant coefficient of 1.34 (p-value <0.001) and R2 of 0.50. Conclusions: The observed correlation highlights the potential use of prehospital E-U system data in the sur- veillance systems of infectious diseases by using real-time data, encouraging future research to explore the limits and possibilities of an integrated surveillance system.
Ambulances; Emergency medical services; Epidemics; Influenza; Public health surveillance
Settore MEDS-24/B - Igiene generale e applicata
gen-2025
17-dic-2024
Article (author)
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S0033350624005171-main.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Dimensione 2.67 MB
Formato Adobe PDF
2.67 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1125635
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact