Evidence map›Paper›PMID 42797817›Full record

ArticleViruses2026

Public Information Demand During the 2026 Bundibugyo Virus Outbreak: A Dual Infodemiology Analysis Across Six Ebola Virus Disease Outbreaks.

Hakkı Öztürk, Berrak Itır Aylı

Abstract read
In one paragraph

Article in Viruses, 2026. 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

2 authors.

Hakkı ÖztürkAfyonkarahisar Provincial Health Services Directorate, Afyonkarahisar 03200, Türkiye.
Berrak Itır AylıFaculty of Life Sciences, University of Westminster, London W1B 2HW, UK.ORCID 0000-0002-0834-900X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The 2026 Bundibugyo virus disease outbreak in the Democratic Republic of the Congo and Uganda, the first Ebola-related PHEIC caused by a species lacking a licensed vaccine, has been accompanied by an information crisis marked by conspiracy-driven violence against response teams and destruction of treatment centres. Understanding what populations actually seek to know during such events is essential for designing effective communication strategies, yet the content of public information demand during Ebola outbreaks has not been systematically characterised. We combined Google Autocomplete query extraction (7347 unique queries from 83 seed terms in English and French) with Google Trends temporal analysis across six Ebola outbreaks (2014-2026). The autocomplete suggestion landscape was dominated by risk quantification and transmission concerns. Google Trends temporal analysis showed moderate to strong co-movement between misinformation-related search terms and overall Ebola search interest (Spearman ρ = 0.359-0.697, nominal

Indexed as

Disease OutbreaksHemorrhagic Fever, EbolaDemocratic Republic of the CongoEbolavirusHumansInfodemicInformation DisseminationInternetUgandaBundibugyo ebolavirusCentral Africadisease outbreaksEbola virusGoogle AutocompleteGoogle Trendsinfodemicmisinformation

Identifiers

PMID42797817
PMCPMC13611964

What OpenQuestion holds

Textmetadata
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.