Evidence map›Paper›PMID 39962562›Full record

ArticleBMC research notes2025

Nationwide spatial epidemiological dataset of over 100,000 influenza-like illness notifications in Iran by county (2015-2019).

Atieh Sedghian, Shahab MohammadEbrahimi, Benn Sartorius, Behzad Kiani

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC research notes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Atieh SedghianDepartment of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. Atieh.sedghian1@gmail.com.ORCID http://orcid.org/0000-0002-0473-2183
Shahab MohammadEbrahimiDepartment of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Benn SartoriusUQ Centre for Clinical Research (UQCCR), Faculty of Health, Medicine, and Behavioural Sciences, University of Queensland, Brisbane, Australia.
Behzad KianiUQ Centre for Clinical Research (UQCCR), Faculty of Health, Medicine, and Behavioural Sciences, University of Queensland, Brisbane, Australia.

Funding

Mashhad University of Medical Sciences 4001855
6 · The paper itself

Abstract

objectivesThis data note documents influenza-like illness (ILI) notifications in Iran by county from 2015 to 2019 as a pre-COVID-19 dataset, providing individual and spatial data for further comprehensive spatiotemporal analysis. Due to the high contagion rate of ILI and global health impact, precise geographic mapping serves as a critical tool for public health officials and researchers to monitor, mitigate, and predict epidemics. By utilizing advanced spatial-temporal epidemiological analysis to study disease occurrence patterns, this geodatabase can enable a better understanding and more effective management of ILIs in the future. DATA DESCRIPTION: This is the most comprehensive dataset of all individual ILI notifications in Iran between 2015 and 2019 by date of notification and county (398 counties). The database includes two data files, a help file, and a data usage agreement: Data File 1 is an Excel (.xlsx) file detailing demographic and clinical information from 109,919 ILI notifications nationwide, covering county and date of notification, patient demographics, admission details, sample types, differential diagnosis, medical history, mortality details, test results, and symptoms. Data File 2 contains spatiotemporal information in polygon shapefiles (.shp), mapping ILI notification locations by county with data on case counts for each year, total population, gender distribution, and geographic coordinates.

Indexed as

Influenza, HumanAdolescentAdultAgedChildChild, PreschoolCOVID-19Databases, FactualDisease NotificationFemaleHumansInfantIranMaleMiddle AgedSpatio-Temporal AnalysisBig dataInfluenza-like illnessIranPublic healthSpace-timeSpatiotemporal

Identifiers

PMID39962562
PMCPMC11834186

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

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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.