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A quantitative COVID-19 model that incorporates hidden asymptomatic patientsis developed, and an analytic solution in parametric form is given. The modelincorporates the impact of lockdown and resulting spatial migration ofpopulation due to announcement of lockdown. A method is presented forestimating the model parameters from real-world data. It is shown that increaseof infections slows down and herd immunity is achieved when symptomaticpatients are 4-6\% of the population for the European countries we studied,when the total infected fraction is between 50-56 \%. Finally, a method forestimating the number of asymptomatic patients, who have been the key hiddenlink in the spread of the infections, is presented.

Estimating Hidden Asymptomatics, Herd Immunity Threshold and Lockdown Effects using a COVID-19 Specific Model