Frontiers in Public Health (Jan 2024)

A semi-empirical risk panel to monitor epidemics: multi-faceted tool to assist healthcare and public health professionals

  • Aida Perramon-Malavez,
  • Mario Bravo,
  • Víctor López de Rioja,
  • Martí Català,
  • Sergio Alonso,
  • Enrique Álvarez-Lacalle,
  • Daniel López,
  • Antoni Soriano-Arandes,
  • Antoni Soriano-Arandes,
  • Clara Prats

DOI
https://doi.org/10.3389/fpubh.2023.1307425
Journal volume & issue
Vol. 11

Abstract

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IntroductionBronchiolitis, mostly caused by Respiratory Syncytial Virus (RSV), and influenza among other respiratory infections, lead to seasonal saturation at healthcare centers in temperate areas. There is no gold standard to characterize the stages of epidemics, nor the risk of respiratory infections growing. We aimed to define a set of indicators to assess the risk level of respiratory viral epidemics, based on both incidence and their short-term dynamics, and considering epidemical thresholds.MethodsWe used publicly available data on daily cases of influenza for the whole population and bronchiolitis in children <2 years from the Information System for Infection Surveillance in Catalonia (SIVIC). We included a Moving Epidemic Method (MEM) variation to define epidemic threshold and levels. We pre-processed the data with two different nowcasting approaches and performed a 7-day moving average. Weekly incidences (cases per 105 population) were computed and the 5-day growth rate was defined to create the effective potential growth (EPG) indicator. We performed a correlation analysis to define the forecasting ability of this index.ResultsOur adaptation of the MEM method allowed us to define epidemic weekly incidence levels and epidemic thresholds for bronchiolitis and influenza. EPG was able to anticipate daily 7-day cumulative incidence by 4–5 (bronchiolitis) or 6–7 (influenza) days.DiscussionWe developed a semi-empirical risk panel incorporating the EPG index, which effectively anticipates surpassing epidemic thresholds for bronchiolitis and influenza. This panel could serve as a robust surveillance tool, applicable to respiratory infectious diseases characterized by seasonal epidemics, easy to handle for individuals lacking a mathematical background.

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