The outbreak of the 2019 novel coronavirus disease (COVID-19) has infected 4 million people worldwide and has caused more than 300,000 deaths worldwide. With infection and death rates on rise, COVID-19 poses a serious threat to social functioning, human health, economies, and geopolitics. Geographic information systems and big geospatial technologies have come to the forefront in this fight against COVID-19 by playing an important role by integrating multisourced data, enhanced and rapid analytics of mapping services, location analytics, and spatial tracking of confirmed, forecasting transmission trajectories, spatial clustering of risk on epidemiologic levels, public awareness on the elimination of panic spread and decision-making support for the government and research institutions for effective prevention and control of COVID-19 cases. Big geospatial data has turned itself as the major support system for governments in dealing with this global healthcare crisis because of its advanced and innovative technological capabilities from preparation of data to modeling the results with quick and large accessibility to every spatial scale. This robust data-driven system using the accurate and prediction geoanalysis is being widely used by governments and public health institutions interfaced with both health and nonhealth digital data repositories for mining the individual and regional datasets for breaking the transmission chain. Profiling of confirmed cases on the basis of location and temporality and then visualizing them effectively coupled with behavioral and critical geographic variables such as mobility patterns, demographic data, and population density enhance the predictive analytics of big geospatial data. With the intersection of artificial intelligence, geospatial data enables real-time visualization and syndromic surveillance of epidemic data based on spatiotemporal dynamics and the data are then accurately geopositioned. This chapter aims to reflect on the relevance of big geospatial data and health geoinformatics in containing and preventing the further spread of COVID-19 and how countries and research organizations around the world have used it as accurate, fast, and comprehensive dataset in their containing strategy and management of this public health crisis. China and Taiwan are used as case studies as in how these countries have applied the computational architecture of big geospatial data and location analytics surveillance techniques for prediction and monitoring of COVID-19-positive cases.
Role of big geospatial data in the COVID-19 crisis