Behavioural determinants of testing behaviour during a hypothetical human-to-human avian influenza outbreak: an interview study

BACKGROUND: Avian Influenza (AI) is a potential pandemic threat, specifically when human-to-human transmission occurs. In order to mitigate potential outbreaks amongst humans, testing is essential. l. It is necessary to identify determinants of testing behaviour for AI in an early phase, as current knowledge on testing behaviour is mostly derived from other infectious diseases such as COVID-19. Therefore, this interview study aims to identify a wide range of behavioural determinants of diagnostic testing during a hypothetical human-to-human transmissible AI outbreak. METHODS: Semi-structured in-depth interviews, based on the Theoretical Domains Framework, were carried out between May 2024 and February 2025. Participants were included through purposive and convenience sampling. During the interviews an animation was shown illustrating a hypothetical AI outbreak. Verbatim transcripts were thematically analysed. RESULTS: We included seventeen participants (median age 44, range 20-81; 71% women) with diverse backgrounds in terms of age, gender, educational level and country of birth. Results show that, in this hypothetical setting, having the choice to test increases acceptance of testing, whereas a decreased sense of autonomy discourages testing. Most themes included individual rather than population-level benefits as drivers of testing behaviour. These included protecting loved ones, one's own health and gaining psychological reassurance. External conditions such as being unable to go to work or an event would generally encourage testing behaviour. Lower trust in governmental authorities could hamper testing behaviour. Previous experiences from the COVID-19 pandemic shaped participants' answers about AI testing behaviour. CONCLUSION: Key considerations include balancing people's need for autonomy with the external measures imposed by employers or the government, rebuilding trust in institutions and acknowledging how prior experiences with testing may shape testing behaviour in future AI outbreaks. Further research is needed to determine how these findings can be translated into effective communication and how trust in authorities can be built.