Artigo Acesso aberto Revisado por pares

Web-based surveillance of respiratory infection outbreaks: retrospective analysis of Italian COVID-19 epidemic waves using Google Trends

2023; Frontiers Media; Volume: 11; Linguagem: Inglês

10.3389/fpubh.2023.1141688

ISSN

2296-2565

Autores

Gloria Porcu, Yu Xi Chen, Andrea Stella Bonaugurio, Simone Villa, Leonardo Riva, Enza Messina, Giorgio Bagarella, Mauro Maistrello, Olivia Leoni, Danilo Cereda, Fulvio Matone, Andrea Gori, Giovanni Corrao,

Tópico(s)

COVID-19 epidemiological studies

Resumo

Introduction Large-scale diagnostic testing has been proven insufficient to promptly monitor the spread of the Coronavirus disease 2019. Electronic resources may provide better insight into the early detection of epidemics. We aimed to retrospectively explore whether the Google search volume has been useful in detecting Severe Acute Respiratory Syndrome Coronavirus outbreaks early compared to the swab-based surveillance system. Methods The Google Trends website was used by applying the research to three Italian regions (Lombardy, Marche, and Sicily), covering 16 million Italian citizens. An autoregressive-moving-average model was fitted, and residual charts were plotted to detect outliers in weekly searches of five keywords. Signals that occurred during periods labelled as free from epidemics were used to measure Positive Predictive Values and False Negative Rates in anticipating the epidemic wave occurrence. Results Signals from “fever,” “cough,” and “sore throat” showed better performance than those from “loss of smell” and “loss of taste.” More than 80% of true epidemic waves were detected early by the occurrence of at least an outlier signal in Lombardy, although this implies a 20% false alarm signals. Performance was poorer for Sicily and Marche. Conclusion Monitoring the volume of Google searches can be a valuable tool for early detection of respiratory infectious disease outbreaks, particularly in areas with high access to home internet. The inclusion of web-based syndromic keywords is promising as it could facilitate the containment of COVID-19 and perhaps other unknown infectious diseases in the future.

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