Evidence map›Paper›PMID 31409397›Full record

ArticleBMC public health2019

Assessment of two complementary influenza surveillance systems: sentinel primary care influenza-like illness versus severe hospitalized laboratory-confirmed influenza using the moving epidemic method.

Núria Torner, Luca Basile, Ana Martínez, Cristina Rius, Pere Godoy, Mireia Jané, Ángela Domínguez, Working Group on PIDIRAC Sentinel Surveillance of Catalonia

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.1field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 17 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Núria TornerDepartment of Health, Public Health Agency of Catalonia, Generalitat of Catalonia, Salvany Building, Roc Boronat 81-95, 08005, Barcelona, Catalonia, Spain. nuria.torner@gencat.cat.ORCID http://orcid.org/0000-0003-0143-5295
Luca BasileDepartment of Health, Public Health Agency of Catalonia, Generalitat of Catalonia, Salvany Building, Roc Boronat 81-95, 08005, Barcelona, Catalonia, Spain.
Ana MartínezDepartment of Health, Public Health Agency of Catalonia, Generalitat of Catalonia, Salvany Building, Roc Boronat 81-95, 08005, Barcelona, Catalonia, Spain.
Cristina RiusCIBER Epidemiología y Salud Pública (CIBERESP) Institute Carlos III, Madrid, Spain.
Pere GodoyDepartment of Health, Public Health Agency of Catalonia, Generalitat of Catalonia, Salvany Building, Roc Boronat 81-95, 08005, Barcelona, Catalonia, Spain.
Mireia JanéDepartment of Health, Public Health Agency of Catalonia, Generalitat of Catalonia, Salvany Building, Roc Boronat 81-95, 08005, Barcelona, Catalonia, Spain.
Ángela DomínguezCIBER Epidemiología y Salud Pública (CIBERESP) Institute Carlos III, Madrid, Spain.
Working Group on PIDIRAC Sentinel Surveillance of Catalonia
Generalitat de Catalunya · ESInstituto de Salud Carlos III · ES

Funding

CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III Prevention and Control of Transmissible Diseases (PREVICET)Grants for University Research (AGAUR) 2017/SGR 1342
6 · The paper itself

Abstract

backgroundMonitoring seasonal influenza epidemics is the corner stone to epidemiological surveillance of acute respiratory virus infections worldwide. This work aims to compare two sentinel surveillance systems within the Daily Acute Respiratory Infection Information System of Catalonia (PIDIRAC), the primary care ILI and Influenza confirmed samples from primary care (PIDIRAC-ILI and PIDIRAC-FLU) and the severe hospitalized laboratory confirmed influenza system (SHLCI), in regard to how they behave in the forecasting of epidemic onset and severity allowing for healthcare preparedness.

methodsEpidemiological study carried out during seven influenza seasons (2010-2017) in Catalonia, with data from influenza sentinel surveillance of primary care physicians reporting ILI along with laboratory confirmation of influenza from systematic sampling of ILI cases and 12 hospitals that provided data on severe hospitalized cases with laboratory-confirmed influenza (SHLCI-FLU). Epidemic thresholds for ILI and SHLCI-FLU (overall) as well as influenza A (SHLCI-FLUA) and influenza B (SHLCI-FLUB) incidence rates were assessed by the Moving Epidemics Method.

resultsEpidemic thresholds for primary care sentinel surveillance influenza-like illness (PIDIRAC-ILI) incidence rates ranged from 83.65 to 503.92 per 100.000 h. Paired incidence rate curves for SHLCI -FLU / PIDIRAC-ILI and SHLCI-FLUA/ PIDIRAC-FLUA showed best correlation index' (0.805 and 0.724 respectively). Assessing delay in reaching epidemic level, PIDIRAC-ILI source forecasts an average of 1.6 weeks before the rest of sources paired. Differences are higher when SHLCI cases are paired to PIDIRAC-ILI and PIDIRAC-FLUB although statistical significance was observed only for SHLCI-FLU/PIDIRAC-ILI (p-value Wilcoxon test = 0.039).

conclusionsThe combined ILI and confirmed influenza from primary care along with the severe hospitalized laboratory confirmed influenza data from PIDIRAC sentinel surveillance system provides timely and accurate syndromic and virological surveillance of influenza from the community level to hospitalization of severe cases.

Indexed as

EpidemicsPrimary Health CareSentinel SurveillanceHospitalizationHumansInfluenza A virusInfluenza B virusInfluenza, HumanLaboratories, HospitalReproducibility of ResultsSeasonsSeverity of Illness IndexSpainEpidemicHospitalizationInfluenzaInfluenza like illnessPrimary health careSentinel surveillanceThreshold

Identifiers

PMID31409397
PMCPMC6691547
OpenAlexW2967333973

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.