Author: Arsath Abbasali Ayubali; Sara Roshini Satheesh
Title: On predicting the novel COVID-19 human infections by using Infectious Disease modelling method in the Indian State of Tamil Nadu during 2020 Document date: 2020_4_7
ID: 660ul4fb_38
Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.05.20054593 doi: medRxiv preprint = (4) Where , corresponds to the total population which represents = + + + , indicates (referred to as the effective contact rate) the probability of infection between the susceptible and the latent, which is expressed as = * , where in the latent population daily exposed and is the probability of the pop.....
Document: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.05.20054593 doi: medRxiv preprint = (4) Where , corresponds to the total population which represents = + + + , indicates (referred to as the effective contact rate) the probability of infection between the susceptible and the latent, which is expressed as = * , where in the latent population daily exposed and is the probability of the population being infected , represents the conversion rate of the latent human to the infected human, which is the obtained as the reciprocal of the incubation duration , denotes the recovery rate, which is computed by the reciprocal of number of days the infected human is in treatment.
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