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10.3390/ijerph17124568

http://scihub22266oqcxt.onion/10.3390/ijerph17124568
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32630363!7344859!32630363
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suck abstract from ncbi


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pmid32630363      Int+J+Environ+Res+Public+Health 2020 ; 17 (12): ä
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  • Predicting the Epidemiological Outbreak of the Coronavirus Disease 2019 (COVID-19) in Saudi Arabia #MMPMID32630363
  • Alboaneen D; Pranggono B; Alshammari D; Alqahtani N; Alyaffer R
  • Int J Environ Res Public Health 2020[Jun]; 17 (12): ä PMID32630363show ga
  • The coronavirus diseases 2019 (COVID-19) outbreak continues to spread rapidly across the world and has been declared as pandemic by World Health Organization (WHO). Saudi Arabia was among the countries that was affected by the deadly and contagious virus. Using a real-time data from 2 March 2020 to 15 May 2020 collected from Saudi Ministry of Health, we aimed to give a local prediction of the epidemic in Saudi Arabia. We used two models: the Logistic Growth and the Susceptible-Infected-Recovered for real-time forecasting the confirmed cases of COVID-19 across Saudi Arabia. Our models predicted that the epidemics of COVID-19 will have total cases of 69,000 to 79,000 cases. The simulations also predicted that the outbreak will entering the final-phase by end of June 2020.
  • |*Forecasting[MESH]
  • |*Pandemics[MESH]
  • |Betacoronavirus/pathogenicity[MESH]
  • |COVID-19[MESH]
  • |Coronavirus Infections/*epidemiology/virology[MESH]
  • |Health Surveys[MESH]
  • |Humans[MESH]
  • |Models, Biological[MESH]
  • |Pneumonia, Viral/*epidemiology/virology[MESH]
  • |SARS-CoV-2[MESH]


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