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10.1016/j.chaos.2020.110156

http://scihub22266oqcxt.onion/10.1016/j.chaos.2020.110156
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32834644!7386481!32834644
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suck abstract from ncbi


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pmid32834644      Chaos+Solitons+Fractals 2020 ; 140 (ä): 110156
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  • An epidemic model SIPHERD and its application for prediction of the spread of COVID-19 infection in India #MMPMID32834644
  • Mahajan A; Sivadas NA; Solanki R
  • Chaos Solitons Fractals 2020[Nov]; 140 (ä): 110156 PMID32834644show ga
  • Originating from Wuhan, China, in late 2019, and 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.
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