Evidence map›Paper›PMID 40038819›Full record

ArticleBMC research notes2025

Real-time epidemiological surveillance data: tracking the occurrences of avian influenza outbreaks around the world.

Francesco Branda, Ranjan K Mohapatra, Lawrence Sena Tuglo, Massimo Ciccozzi, Fabio Scarpa

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. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
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

5 authors.

Francesco BrandaUnit of Medical Statistics and Molecular Epidemiology, University Campus Bio-Medico of Rome, Rome, Italy. f.branda@unicampus.it.
Ranjan K MohapatraDepartment of Chemistry, Government College of Engineering, Keonjhar, 758 002, Odisha, India.ORCID http://orcid.org/0000-0001-7623-3343
Lawrence Sena TugloDepartment of Nutrition and Dietetics, School of Allied Health Sciences, University of Health and Allied Sciences, Ho, Ho-00233, Ghana. lstuglo2012@uhas.edu.gh.
Massimo CiccozziUnit of Medical Statistics and Molecular Epidemiology, University Campus Bio-Medico of Rome, Rome, Italy.
Fabio ScarpaDepartment of Biomedical Sciences, University of Sassari, Sassari, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aims to provide real-time surveillance of epidemiological outbreaks of avian influenza in humans and mammals. The primary objective is to understand and track the dynamics of outbreaks as they develop, facilitating timely interventions and informed public health decisions. The data collection is part of a broader initiative focused on improving preparedness and response capabilities to emerging health threats. DATA DESCRIPTION: The dataset includes comprehensive and up-to-date information on epidemiological patterns, including geographic spread, incidence rates, and demographic factors. Collected through systematic monitoring and reporting systems, this dataset is invaluable to researchers seeking to understand the evolving nature of avian influenza outbreaks in the global context. By sharing these data, we aim to contribute to the collective knowledge base by supporting evidence-based strategies for effective public health management and intervention.

Indexed as

Disease OutbreaksEpidemiological MonitoringInfluenza, HumanInfluenza in BirdsAnimalsBirdsGlobal HealthHumansIncidenceAvian influenzaDisease trackingEpidemiological surveillanceGlobal monitoringOutbreak dynamicsPublic health response

Identifiers

PMID40038819
PMCPMC11881443

What OpenQuestion holds

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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.