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Probabilistic approximation of effective reproduction number of COVID-19 using daily death statistics

journal contribution
posted on 14.09.2020 by J Na, H Tibebu, Varuna De-Silva, Ahmet Kondoz, Michael Caine
© 2020 Elsevier Ltd The effective reproduction number (R) which signifies the number of secondary cases infected by one infectious individual, is an important measure of the spread of an infectious disease. Due to the dynamics of COVID-19 where many infected people are not showing symptoms or showing mild symptoms, and where different countries are employing different testing strategies, it is quite difficult to calculate the R, while the pandemic is still widespread. This paper presents a probabilistic methodology to evaluate the effective reproduction number by considering only the daily death statistics of a given country. The methodology utilizes a linearly constrained Quadratic Programming scheme to estimate the daily new infection cases from the daily death statistics, based on the probability distribution of delays associated with symptom onset and to reporting a death. The proposed methodology is validated in-silico by simulating an infectious disease through a Susceptible-Infectious-Recovered (SIR) model. The results suggest that with a reasonable estimate of distribution of delay to death from the onset of symptoms, the model can provide accurate estimates of R. The proposed method is then used to estimate the R values for two countries.

Funding

MIMIc: Multimodal Imitation Learning in MultI-Agent Environments

Engineering and Physical Sciences Research Council

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History

School

  • Loughborough University London

Published in

Chaos, Solitons and Fractals

Volume

140

Pages

110181

Publisher

Elsevier

Version

AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in the journal Chaos, Solitons and Fractals and the definitive published version is available at https://doi.org/10.1016/j.chaos.2020.110181

Acceptance date

29/07/2020

Publication date

2020-07-30

Copyright date

2020

ISSN

0960-0779

Language

en

Depositor

Dr Varuna De Silva . Deposit date: 10 September 2020

Article number

110181

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