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Crowdsourcing applications addressing diseases and public health: a perspective on COVID-19 infestation

The spread of the COVID-19 disease with an unprecedented speed into humans, and the global scaleof its occurrence over multiple geographic locations, since December 2019, in Wuhan, China, hassparked off extensive confusion and debate in public health, giving it the status of a pandemic. Theinability of restraining the outbreak in the early stages, has multiplied the disease risk to fatalcomplications. Crowdsourcing technique can conglomerate crowd knowledge for solving problemsrevolutionizing health care by use of internet sources, data mining, e-health trackers, etc. to collectand assess data faster to the rate of spread of infection, directly from a point source (individual-level). The present study provides perspectives on crowdsourcing in alignment with health care andpublic health services by critically comparing strengths and challenges with traditional methods. Forthe same 3 models have been designed by the authors, for improvement in public health care, in thewake of the COVID-19 infestation.