Abstract
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.
Highlights
The spread of the COVID-19 disease with an unprecedented speed into humans, and the global scale of its occurrence over multiple geographic locations, since December 2019, in Wuhan, China, has sparked off extensive confusion and debate in public health, giving it the status of a pandemic
The present study provides perspectives on crowdsourcing in alignment with health care and public health services by critically comparing strengths and challenges with traditional methods
For the same 3 models have been designed by the authors, for improvement in public health care, in the wake of the COVID-19 infestation
Summary
The COVID-19 disease was first officially declared by WHO1 on December 31st, 2019, citing reference of occurrences of an influenza-like disease in the Hubei province of Wuhan city in China [1]. Crowdsourcing techniques in the era of big data includes participation based internet-surveillance systems for diseases, where disease symptoms are reported by actively participating individuals who voluntarily submit their data through web portals, mobile health trackers, mobile apps, tweets or emails generating a huge pool of real-time data within a short period [12] This was successfully conducted for the influenza outbreak in 2009, and the same if applied in the case of COVID-19 infestation can provide several advantages like increased speed, data size, research utility, data validation and accessibility over traditional disease surveillance measures in public health [13,14,15,16,17]. The fourth stage depicts how the solutions analyzed, will serve as valuable realtime data for conducting health care research aimed
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