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. 2020 Dec;75(12):1643-1647.
doi: 10.1111/anae.15151. Epub 2020 Jun 19.

Managing the R0 of COVID-19: mathematics fights back

J J Pandit  1
Affiliations

Managing the R0 of COVID-19: mathematics fights back

J J Pandit. Anaesthesia. 2020 Dec.
No abstract available

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Figures

Figure 1
Figure 1
Three models of population (viral) growth: exponential (Eqn 1; red), logistic (Eqn 2, black) and logistic map (Eqn 3, green). Different values have been used to separate the lines. Note that whereas in exponential, R0 value is constant, it varies for the other two models depending on the time‐point it is measured
Figure 2
Figure 2
Example of an SIR model plot for a hypothetical infectious disease. The green curve is the susceptible population; the red curve is the infected, and the black curve is the recovered. Note the inverse relationship between the susceptible and recovered, with the infected being the balance
Figure 3
Figure 3
Estimate of the proportion of population needed to be immune to achieve herd immunity, as a function of R0. Note that for R0 < 2, the relationship is very steep with < 50% of population needing immunity,
See this image and copyright information in PMC

Comment in

  • Measuring R0.
    Gwinnutt C. Gwinnutt C. Anaesthesia. 2021 Mar;76 Suppl 3:26. doi: 10.1111/anae.15351. Epub 2020 Dec 23. Anaesthesia. 2021. PMID: 33253474 No abstract available.

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