About: An Epidemic Model SIPHERD and its application for prediction of the spread of COVID-19 infection in India

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Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	An Epidemic Model SIPHERD and its application for prediction of the spread of COVID-19 infection in India
Creator	Mahajan, Ashutosh Sivadas, Namitha Solanki, Ravi
Source	MedRxiv
abstract	After originating from Wuhan, China, in late 2019, with a gradual spread in the last few months, COVID-19 has become a pandemic crossing 9 million confirmed positive cases and 450 thousand deaths. India is not only an overpopulated country but has a high population density as well, and at present, a high-risk nation where COVID-19 infection can go out of control. In this paper, we employ a compartmental epidemic model SIPHERD for COVID-19 and predict the total number of confirmed, active and death cases, and daily new cases. We analyze the impact of lockdown and the number of tests conducted per day on the prediction and bring out the scenarios in which the infection can be controlled faster. Our findings indicate that increasing the tests per day at a rapid pace (10k per day increase), stringent measures on social-distancing for the coming months and strict lockdown in the month of July all have a significant impact on the disease spread.
has issue date	2020-06-26(xsd:dateTime)
bibo:doi	10.1101/2020.06.25.20139782
has license	medrxiv
sha1sum (hex)	8605d2a5736eb7690f7d171e82160b0467a641c9
schema:url	https://doi.org/10.1101/2020.06.25.20139782
resource representing a document's title	An Epidemic Model SIPHERD and its application for prediction of the spread of COVID-19 infection in India
resource representing a document's body	covid:8605d2a5736eb7690f7d171e82160b0467a641c9#body_text
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