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

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 infect...

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Main Authors: Aida Perramon-Malavez (Author), Mario Bravo (Author), Víctor López de Rioja (Author), Martí Català (Author), Sergio Alonso (Author), Enrique Álvarez-Lacalle (Author), Daniel López (Author), Antoni Soriano-Arandes (Author), Clara Prats (Author)
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Published: Frontiers Media S.A., 2024-01-01T00:00:00Z.
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100 1 0 |a Aida Perramon-Malavez  |e author 
700 1 0 |a Mario Bravo  |e author 
700 1 0 |a Víctor López de Rioja  |e author 
700 1 0 |a Martí Català  |e author 
700 1 0 |a Sergio Alonso  |e author 
700 1 0 |a Enrique Álvarez-Lacalle  |e author 
700 1 0 |a Daniel López  |e author 
700 1 0 |a Antoni Soriano-Arandes  |e author 
700 1 0 |a Antoni Soriano-Arandes  |e author 
700 1 0 |a Clara Prats  |e author 
245 0 0 |a A semi-empirical risk panel to monitor epidemics: multi-faceted tool to assist healthcare and public health professionals 
260 |b Frontiers Media S.A.,   |c 2024-01-01T00:00:00Z. 
500 |a 2296-2565 
500 |a 10.3389/fpubh.2023.1307425 
520 |a 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. 
546 |a EN 
690 |a respiratory infections 
690 |a epidemic 
690 |a levels 
690 |a threshold 
690 |a effective potential growth 
690 |a epidemic indicators 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n Frontiers in Public Health, Vol 11 (2024) 
787 0 |n https://www.frontiersin.org/articles/10.3389/fpubh.2023.1307425/full 
787 0 |n https://doaj.org/toc/2296-2565 
856 4 1 |u https://doaj.org/article/e94dca24ff6a4fa3ad19e8983fe02c4b  |z Connect to this object online.