Abstract
Abstract. 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.
Highlights
The COVID-19 pandemic has exposed the fragility and vulnerability of health infrastructures globally and the challenges scientific advisors and public health experts face to understand the magnitude and spread of this highly infectious disease
We have identified an urgent need to effectively prepare for countering future threats and safeguard people, by harvesting emerging technologies to forecast, predict and anticipate action at the strategic, operational and local level strengthening the response capacity
Digital disease detection and bio surveillance can be a great added value for early discovery of even weak signals coming from social media, mainly if the medical intelligence (MEDINT) platform is based on the International Press Telecommunications Council (IPTC) Taxonomy, the Medical Subject Heading (MESH) and the SNOMED CT clinical vocabulary readable by computers, wellrecognized healthcare knowledge base, universally used by experts, practitioners, doctors
Summary
The COVID-19 pandemic has exposed the fragility and vulnerability of health infrastructures globally and the challenges scientific advisors and public health experts face to understand the magnitude and spread of this highly infectious disease This is well demonstrated in the time taken to develop COVID-19 vaccines, by which millions of lives succumbed to this dreadful disease. Authors present a novel approach towards medical intelligence (MEDINT) to harvest from usergenerated data, available through Twitter (Prieto, 2014). Results indicate that such approach, exploiting real-time data sharing, provides a promising solution for measuring and tracking the evolution of disease in society, early detection of disease outbreaks and support decisionmaking for appropriate response to medical threats
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