About: Estimation of Undetected Symptomatic and Asymptomatic cases of COVID-19 Infection and prediction of its spread in USA

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Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Estimation of Undetected Symptomatic and Asymptomatic cases of COVID-19 Infection and prediction of its spread in USA
Creator	Mahajan, Ashutosh Sivadas, Namitha Solanki, Ravi
Source	MedRxiv
abstract	The reported COVID-19 cases in the USA have crossed over 2 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 propose a new 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 lockdown 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 also demonstrates the possibility of a second wave of the infection if social distancing regulations are relaxed to a large extent. We estimate that around 12.7 million people are already infected, and in the absence of any vaccine, 17.7 million (range: 16.3-19.2) people, or 5.3% (range: 4.9-5.8) of the population will be infected by when the disease spread ends in the USA. We find the Infection to Fatality Ratio to be 0.93% (range: 0.85-1.01).
has issue date	2020-06-23(xsd:dateTime)
bibo:doi	10.1101/2020.06.21.20136580
has license	medrxiv
sha1sum (hex)	ff2223ee3687525b7beffdf04acabc66a6d86cdd
schema:url	https://doi.org/10.1101/2020.06.21.20136580
resource representing a document's title	Estimation of Undetected Symptomatic and Asymptomatic cases of COVID-19 Infection and prediction of its spread in USA
resource representing a document's body	covid:ff2223ee3687525b7beffdf04acabc66a6d86cdd#body_text
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