Applying the moving epidemic method to determine influenza epidemic and intensity thresholds using influenza‐like illness surveillance data 2009‐2018 in Tunisia

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 usin...

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Veröffentlicht in:Influenza and other respiratory viruses 2020-09, Vol.14 (5), p.507-514
Hauptverfasser: 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
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container_end_page 514
container_issue 5
container_start_page 507
container_title Influenza and other respiratory viruses
container_volume 14
creator 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
description 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.
doi_str_mv 10.1111/irv.12748
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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.</description><identifier>ISSN: 1750-2640</identifier><identifier>EISSN: 1750-2659</identifier><identifier>DOI: 10.1111/irv.12748</identifier><identifier>PMID: 32390333</identifier><language>eng</language><publisher>England: John Wiley &amp; Sons, Inc</publisher><subject>Analysis ; Confidence intervals ; epidemic threshold ; Epidemics ; Historical account ; ILI surveillance ; Illnesses ; Influenza ; Methods ; moving epidemic method ; Original ; Pandemics ; Prevention ; Primary care ; Respiratory diseases ; Seasons ; Sensitivity ; Thresholds ; Viruses</subject><ispartof>Influenza and other respiratory viruses, 2020-09, Vol.14 (5), p.507-514</ispartof><rights>2020 The Authors. Published by John Wiley &amp; Sons Ltd.</rights><rights>2020 The Authors. 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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. 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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.</abstract><cop>England</cop><pub>John Wiley &amp; Sons, Inc</pub><pmid>32390333</pmid><doi>10.1111/irv.12748</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-3326-9861</orcidid><oa>free_for_read</oa></addata></record>
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subjects Analysis
Confidence intervals
epidemic threshold
Epidemics
Historical account
ILI surveillance
Illnesses
Influenza
Methods
moving epidemic method
Original
Pandemics
Prevention
Primary care
Respiratory diseases
Seasons
Sensitivity
Thresholds
Viruses
title Applying the moving epidemic method to determine influenza epidemic and intensity thresholds using influenza‐like illness surveillance data 2009‐2018 in Tunisia
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