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Year : 2020  |  Volume : 4  |  Issue : 4  |  Page : 121-126

Monitoring and epidemiological trends of coronavirus disease (COVID-19) around the world

1 Delhi Development Authority, New Delhi, India
2 Department of Civil Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat, India
3 Department of Computer Science Engineering, Indian Institute of Technology, Roorkee, Uttarakhand, India

Correspondence Address:
Er. Arnab Saha
Delhi Development Authority, New Delhi - 110 002
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/MTSM.MTSM_16_20

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Coronavirus disease 2019 (COVID-19) has struck fear into populaces all through the world and shocked the worldwide restorative community, with the World Health Organization pronouncing it a widespread as it were approximately 3 months after the flare-up of the infection. A new different virus (primarily called “novel coronavirus 2019 [nCoV]”) causing severe acute respiratory syndrome (COVID-19) emerged in Wuhan, Hubei Province, China, in December 2019 and rapidly spread to other parts of China and other countries around the world. The outbreak of the nCoV disease (COVID-19) has caused more than 850,000 people infected and approx. 40,000 of deaths in more than 190 countries up to March 2020, extremely affecting economic and social development. Presently, the number of infections and deaths is still increasing rapidly. COVID-19 seriously threatens human health, production, life, social functioning, and international relations. In the fight against COVID-19, geographic information systems (GIS) and big data technologies have played an important role in many aspects. This article describes the usage of practical GIS and mapping dashboards and applications for monitoring the coronavirus epidemic and related activities as they spread around the world. At the fact level, in the generation of massive data, information no longer come on the whole from the authorities but are gathered from greater diverse enterprises. As of now and for a long time in future, the improvement of GIS should be fortified to create a data-driven framework for fast information securing, which implies that GIS ought to be utilized to fortify the social operation parameterization of models and methods, particularly when giving back for social administration.

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