Algorithmic health: AI chatbots, climate-linked disease communication, and governance conditions for trust in public health systems - a comparative documentary study of Africa and the Global North

Climate change is reshaping disease epidemiology, particularly through the expansion of vector-borne diseases into previously unaffected regions. In parallel, artificial intelligence-powered chatbots have emerged as critical intermediaries in public health communication systems AI-powered chatbots have emerged as new intermediaries in public health communication. This qualitative comparative documentary study examines how AI chatbots influence climate-related disease risk perception, trust formation, and preventive health behaviors the governance conditions under which AI-mediated climate-linked disease communication is more or less likely to generate public trust across five countries: Nigeria, Kenya, and South Africa representing the African context, and Germany and South Korea representing the Global North. Drawing on a corpus of 47 publicly available documents - national digital health policies, data-protection legislation, disease-surveillance and climate–health communication materials, and chatbot-related technical and operational documentation - the study analyses deployment logics, regulatory architectures, climate–health integration, community mediation arrangements, and digital inequality patterns. The findings are governance-level inferences, not direct evidence of user attitudes or behaviour. Findings demonstrate indicate that Global North implementations are embedded within robust digital infrastructure and regulatory frameworks, while African deployments compensate for health-workforce shortages but operate under constraints of digital literacy, language diversity, and infrastructure. The study contributes to digital public health scholarship by showing how sociocultural contexts, institutional legitimacy, and technological design jointly shape the conditions for trust in shape the effectiveness of algorithmic health communication in climate-sensitive disease prevention. Recommendations emphasise context-adaptive AI design, multilingual capabilities, community co-creation processes, and regulatory frameworks that prioritize health equity over technological determinism.