Shurendar Selva Kumar

Abstract Artificial intelligence (AI)-enabled infectious disease surveillance platforms are expanding rapidly, but their roles within health systems remain poorly characterized. This review examined 20 platforms according to primary data inputs, surveillance function, AI methods, data privacy, geographic scope and pathogen focus. Three archetypes emerged: Early Warning Networks, Situational Awareness Platforms and Integrated Surveillance Platforms.

Average (ratings) Abstract Cardiovascular disease (CVD) accounts for one-third of global mortality, with a disproportionate burden in low- and middle-income countries. These settings face intersecting pressures including under-resourced health systems coupled with rapid urbanisation and environmental shifts. Despite broad global commitments, CVD control has lagged behind historical progress in other health domains, such as HIV, tuberculosis and maternal–child health.

In Brazil, federal authorities and conservation agencies have run joint campaigns urging people to protect primates—key hosts in the yellow fever jungle cycle—explicitly tying prevention and conservation messaging to vaccination and early warning.