Hakkı Öztürk, Berrak Itır Aylı
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 p < 0.001). Substantial differences emerged between the English-language and French-language suggestion sets: French-language suggestions contained six times more misinformation and conspiracy content (4.9% vs. 0.8%) and nearly nine times more fear-related content (3.5% vs. 0.4%) than English-language suggestions. These findings demonstrate that infodemic management strategies designed in Anglophone contexts are inadequate for the populations most at risk and should inform linguistically adapted interventions for the ongoing response.