tetano
Editor, Senior Moderator
J Med Virol
. 2021 Feb 23.
doi: 10.1002/jmv.26897. Online ahead of print.
Estimation of Undetected Symptomatic and Asymptomatic cases of COVID-19 Infection and prediction of its spread in USA
Ashutosh Mahajan[SUP] 1 [/SUP], Ravi Solanki[SUP] 2 [/SUP], Namitha Sivadas[SUP] 1 [/SUP]
Affiliations
Abstract
The reported COVID-19 cases in the USA have crossed over 10 million, and a large number of infected cases are undetected whose estimation can be done if country-wide antibody testing is performed. In this work, we estimate this undetected fraction of the population by modeling and simulation approach. We employ an epidemic model SIPHERD in which three categories of infection carriers Symptomatic, Purely Asymptomatic, and Exposed are considered with different transmission rates that are taken dependent on the social distancing conditions, and the detection rate of the infected carriers is taken dependent on the tests done per day. The model is first validated for Germany and South Korea and then applied for prediction of total number of confirmed, active and death, and daily new positive cases in the United States. Our study predicts the possible outcomes of the infection if social distancing conditions are relaxed or kept stringent. We estimate that around 30.1 million people are already infected, and in the absence of any vaccine, 66.2 million (range: 64.3-68.0) people, or 20% (range: 19.4-20.5) of the population will be infected by Mid Feb' 21 if social distancing conditions are not made stringent. We find the Infection to Fatality Ratio to be 0.65% (range: 0.63-0.67). This article is protected by copyright. All rights reserved.
Keywords: Computer Modeling; Coronavirus; Epidemiology; Pandemics.
. 2021 Feb 23.
doi: 10.1002/jmv.26897. Online ahead of print.
Estimation of Undetected Symptomatic and Asymptomatic cases of COVID-19 Infection and prediction of its spread in USA
Ashutosh Mahajan[SUP] 1 [/SUP], Ravi Solanki[SUP] 2 [/SUP], Namitha Sivadas[SUP] 1 [/SUP]
Affiliations
- PMID: 33620096
- DOI: 10.1002/jmv.26897
Abstract
The reported COVID-19 cases in the USA have crossed over 10 million, and a large number of infected cases are undetected whose estimation can be done if country-wide antibody testing is performed. In this work, we estimate this undetected fraction of the population by modeling and simulation approach. We employ an epidemic model SIPHERD in which three categories of infection carriers Symptomatic, Purely Asymptomatic, and Exposed are considered with different transmission rates that are taken dependent on the social distancing conditions, and the detection rate of the infected carriers is taken dependent on the tests done per day. The model is first validated for Germany and South Korea and then applied for prediction of total number of confirmed, active and death, and daily new positive cases in the United States. Our study predicts the possible outcomes of the infection if social distancing conditions are relaxed or kept stringent. We estimate that around 30.1 million people are already infected, and in the absence of any vaccine, 66.2 million (range: 64.3-68.0) people, or 20% (range: 19.4-20.5) of the population will be infected by Mid Feb' 21 if social distancing conditions are not made stringent. We find the Infection to Fatality Ratio to be 0.65% (range: 0.63-0.67). This article is protected by copyright. All rights reserved.
Keywords: Computer Modeling; Coronavirus; Epidemiology; Pandemics.