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10.1098/rsif.2020.0144

http://scihub22266oqcxt.onion/10.1098/rsif.2020.0144
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suck abstract from ncbi


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pmid32693748      J+R+Soc+Interface 2020 ; 17 (168): 20200144
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  • Reconciling early-outbreak estimates of the basic reproductive number and its uncertainty: framework and applications to the novel coronavirus (SARS-CoV-2) outbreak #MMPMID32693748
  • Park SW; Bolker BM; Champredon D; Earn DJD; Li M; Weitz JS; Grenfell BT; Dushoff J
  • J R Soc Interface 2020[Jul]; 17 (168): 20200144 PMID32693748show ga
  • A novel coronavirus (SARS-CoV-2) emerged as a global threat in December 2019. As the epidemic progresses, disease modellers continue to focus on estimating the basic reproductive number [Formula: see text]-the average number of secondary cases caused by a primary case in an otherwise susceptible population. The modelling approaches and resulting estimates of [Formula: see text] during the beginning of the outbreak vary widely, despite relying on similar data sources. Here, we present a statistical framework for comparing and combining different estimates of [Formula: see text] across a wide range of models by decomposing the basic reproductive number into three key quantities: the exponential growth rate, the mean generation interval and the generation-interval dispersion. We apply our framework to early estimates of [Formula: see text] for the SARS-CoV-2 outbreak, showing that many [Formula: see text] estimates are overly confident. Our results emphasize the importance of propagating uncertainties in all components of [Formula: see text], including the shape of the generation-interval distribution, in efforts to estimate [Formula: see text] at the outset of an epidemic.
  • |*Basic Reproduction Number/statistics & numerical data[MESH]
  • |*Betacoronavirus[MESH]
  • |*Disease Outbreaks/statistics & numerical data[MESH]
  • |*Models, Biological[MESH]
  • |Bayes Theorem[MESH]
  • |COVID-19[MESH]
  • |China/epidemiology[MESH]
  • |Coronavirus Infections/*epidemiology/*transmission[MESH]
  • |Epidemics/statistics & numerical data[MESH]
  • |Humans[MESH]
  • |Markov Chains[MESH]
  • |Monte Carlo Method[MESH]
  • |Pandemics[MESH]
  • |Pneumonia, Viral/*epidemiology/*transmission[MESH]
  • |Probability[MESH]
  • |SARS-CoV-2[MESH]


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