Early Detection of SARS-CoV-2 Epidemic Waves: Lessons from the Syndromic Surveillance in Lombardy, Italy

Giorgio Bagarella, Mauro Maistrello, Maddalena Minoja, Olivia Leoni, Francesco Bortolan, Danilo Cereda and Giovanni Corrao ()
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Giorgio Bagarella: Directorate General for Health, Lombardy Region, 20124 Milan, Italy
Mauro Maistrello: Directorate General for Health, Lombardy Region, 20124 Milan, Italy
Maddalena Minoja: Directorate General for Health, Lombardy Region, 20124 Milan, Italy
Olivia Leoni: Directorate General for Health, Lombardy Region, 20124 Milan, Italy
Francesco Bortolan: Directorate General for Health, Lombardy Region, 20124 Milan, Italy
Danilo Cereda: Directorate General for Health, Lombardy Region, 20124 Milan, Italy
Giovanni Corrao: Directorate General for Health, Lombardy Region, 20124 Milan, Italy

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

Abstract: We evaluated the performance of the exponentially weighted moving average (EWMA) model for comparing two families of predictors (i.e., structured and unstructured data from visits to the emergency department (ED)) for the early detection of SARS-CoV-2 epidemic waves. The study included data from 1,282,100 ED visits between 1 January 2011 and 9 December 2021 to a local health unit in Lombardy, Italy. A regression model with an autoregressive integrated moving average (ARIMA) error term was fitted. EWMA residual charts were then plotted to detect outliers in the frequency of the daily ED visits made due to the presence of a respiratory syndrome (based on coded diagnoses) or respiratory symptoms (based on free text data). Alarm signals were compared with the number of confirmed SARS-CoV-2 infections. Overall, 150,300 ED visits were encoded as relating to respiratory syndromes and 87,696 to respiratory symptoms. Four strong alarm signals were detected in March and November 2020 and 2021, coinciding with the onset of the pandemic waves. Alarm signals generated for the respiratory symptoms preceded the occurrence of the first and last pandemic waves. We concluded that the EWMA model is a promising tool for predicting pandemic wave onset.

Keywords: syndromic surveillance; SARS-CoV-2; early detection; emergency department; EWMA 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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