Evidence map›Paper›PMID 32390333›Full record

ArticleInfluenza and other respiratory viruses2020

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

Hind Bouguerra, Elyes Boutouria, Mokhtar Zorraga, Amal Cherif, Rihab Yazidi, Naima Abdeddaiem, Latifa Maazaoui, Awatef ElMoussi, Salma Abid, Slim Amine and 6 more

Open access · goldAbstract read
In one paragraph

Article in Influenza and other respiratory viruses, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.7field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 8 citations in OpenAlex.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

16 authors at 4 institutions in 1 country.

Hind BouguerraNational Observatory of New and Emerging Diseases, Ministry of Health, Tunis, Tunisia.
Elyes BoutouriaNational Observatory of New and Emerging Diseases, Ministry of Health, Tunis, Tunisia.
Mokhtar ZorragaDirection of Primary Health Care, Tunis, Tunisia.
Amal CherifNational Observatory of New and Emerging Diseases, Ministry of Health, Tunis, Tunisia.
Rihab YazidiPasteur Institute of Tunis, Tunis, Tunisia.
Naima AbdeddaiemDirection of Primary Health Care, Tunis, Tunisia.
Latifa MaazaouiDirection of Primary Health Care, Tunis, Tunisia.
Awatef ElMoussiMicrobiology Laboratory, Virology Unit, Charles Nicolle Hospital, Tunis, Tunisia.
Salma AbidMicrobiology Laboratory, Virology Unit, Charles Nicolle Hospital, Tunis, Tunisia.
Slim AmineMicrobiology Laboratory, Virology Unit, Charles Nicolle Hospital, Tunis, Tunisia.
Leila BouabidNational Observatory of New and Emerging Diseases, Ministry of Health, Tunis, Tunisia.
Souha BougatefNational Observatory of New and Emerging Diseases, Ministry of Health, Tunis, Tunisia.
Mohamed Kouni ChahedFaculté de Médecine de Tunis, Université de Tunis El Manar, Tunis, Tunisia.
Afif Ben SalahPasteur Institute of Tunis, Tunis, Tunisia.
Jihene BettaiebPasteur Institute of Tunis, Tunis, Tunisia.
Nissaf Bouafif Ben AlayaNational Observatory of New and Emerging Diseases, Ministry of Health, Tunis, Tunisia.ORCID 0000-0002-3326-9861
National Institute of Meteorology · TNHôpital Charles-Nicolle · TNInstitut Pasteur de Tunis · TNTunis University · TN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDefining 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.

methodsWe 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.

resultsThe 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.

conclusionsThis 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.

Indexed as

Epidemiological MonitoringResearch DesignSeasonsAdolescentChildChild, PreschoolHumansInfantInfant, NewbornInfluenza, HumanMathematical ConceptsPandemicsSentinel SurveillanceTunisiaepidemic thresholdILI surveillanceinfluenzamoving epidemic method

Identifiers

PMID32390333
PMCPMC7431642
OpenAlexW3023269905

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.