Harvesting social media with artificial intelligence for medical threats mapping and analytics

The COVID-19 pandemic has exposed both national and organizational vulnerabilities to infectious diseases and has impacted, with devastating effects, many business sectors. Authors have identified an urgent need to effectively plan for future threats, by exploiting emerging technologies to forecast, predict and anticipate action at the strategic, operational and local level thus strengthening the capacity of national and international responders. In order to do this, we need an approach to increase awareness of actors involved. The purpose of this study is to investigate how improved medical intelligence, harvesting from big data available from social media, scientific literature and other resources such as local press, can improve situational awareness to take more informed decision in the context of safeguarding and protecting populations from medical threats. This paper focuses on the exploitation of large unstructured data available from microblogging service Twitter for mapping and analytics of health and sentiment situation. Authors tested an explainable artificial intelligence (AI) supported medical intelligence tool on a scenario of a megacity by processing and visualizing tweets on a GIS map. Results indicate that explainable AI provides a promising solution for measuring and tracking the evolution of disease to provide health, sentiment and emotion situational awareness.