Applying the moving epidemic method to determine influenza epidemic and intensity thresholds using influenza‐like illness surveillance data 2009‐2018 in Tunisia. Issue 5 (10th May 2020)

• Record Type: Journal Article
• Authors: Bouguerra, Hind; Boutouria, Elyes; Zorraga, Mokhtar; Cherif, Amal; Yazidi, Rihab; Abdeddaiem, Naima; Maazaoui, Latifa; ElMoussi, Awatef; Abid, Salma; Amine, Slim; Bouabid, Leila; Bougatef, Souha; Kouni Chahed, Mohamed; Ben Salah, Afif; Bettaieb, Jihene; Bouafif Ben Alaya, Nissaf
• Is Part Of: Influenza and other respiratory viruses. Volume 14:Issue 5(2020)
• Page Start: 507
• Page End: 514
• Publication Date: 2020-05-10
• Subjects: epidemic threshold -- ILI surveillance -- influenza -- moving epidemic method; Influenza -- Periodicals; Respiratory infections -- Periodicals; Virus diseases -- Periodicals; Influenza, Human -- Periodicals; Respiratory Tract Diseases -- Periodicals; Virus Diseases -- Periodicals; Grippe -- Périodiques; Appareil respiratoire -- Infections -- Périodiques; Maladies à virus -- Périodiques; 616.203
• DOI: 10.1111/irv.12748
• Languages: English
• ISSNs: 1750-2640

Abstract

Abstract: Background: Defining the start and assessing the intensity of influenza seasons are essential to ensure timely preventive and control measures and to contribute to the pandemic preparedness. The present study aimed to determine the epidemic and intensity thresholds of influenza season in Tunisia using the moving epidemic method. Methods: We applied the moving epidemic method (MEM) using the R Language implementation (package "mem"). We have calculated the epidemic and the different intensity thresholds from historical data of the past nine influenza seasons (2009‐2010 to 2017‐2018) and assessed the impact of the 2009‐2010 pandemic year. Data used were the weekly influenza‐like illness (ILI) proportions compared with all outpatient acute consultations. The goodness of the model was assessed using a cross validation procedure. Results: The average duration of influenza epidemic during a typical season was 20 weeks and ranged from 11 weeks (2009‐2010 season) to 23 weeks (2015‐2016 season). The epidemic threshold with the exclusion of the pandemic season was 6.25%. It had a very high sensitivity of 85% and a high specificity of 69%. The different levels of intensity were established as follows: low, if ILI proportion is below 9.74%, medium below 12.05%; high below 13.27%; and very high above this last rate. Conclusions: This is the first mathematically based study of seasonal threshold of influenza in Tunisia. As in other studies in different countries, the model has shown both good specificity and sensitivity, which allows timely and accurate detection of the start of influenza seasons. The findings will contribute to the development of more efficient measures for influenza prevention and control.