Is Nigeria really on top of COVID-19? Message from effective reproduction number
Adekunle, A.I., Adegboye, O.A., Gayawan, E., and McBryde, E.S. (2020) Is Nigeria really on top of COVID-19? Message from effective reproduction number. Epidemiology and Infection, 148. e166.
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Abstract
Following the importation of coronavirus disease (COVID-19) into Nigeria on 27 February 2020 and then the outbreak, the question is: How do we anticipate the progression of the ongoing epidemic following all the intervention measures put in place? This kind of question is appropriate for public health responses and it will depend on the early estimates of the key epidemiological parameters of the virus in a defined population.
In this study, we combined a likelihood-based method using a Bayesian framework and compartmental model of the epidemic of COVID-19 in Nigeria to estimate the effective reproduction number (R(t)) and basic reproduction number (R0) – this also enables us to estimate the initial daily transmission rate (β0). We further estimate the reported fraction of symptomatic cases. The models are applied to the NCDC data on COVID-19 symptomatic and death cases from 27 February 2020 and 7 May 2020.
In this period, the effective reproduction number is estimated with a minimum value of 0.18 and a maximum value of 2.29. Most importantly, the R(t) is strictly greater than one from 13 April till 7 May 2020. The R0 is estimated to be 2.42 with credible interval: (2.37–2.47). Comparing this with the R(t) shows that control measures are working but not effective enough to keep R(t) below 1. Also, the estimated fraction of reported symptomatic cases is between 10 and 50%.
Our analysis has shown evidence that the existing control measures are not enough to end the epidemic and more stringent measures are needed.
Item ID: | 64227 |
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Item Type: | Article (Research - C1) |
ISSN: | 1469-4409 |
Keywords: | Basic reproduction number; COVID-19; effective reproductive number; imported cases; Nigeria |
Copyright Information: | COPYRIGHT: © The Author(s), 2020. Published by Cambridge University Press This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Date Deposited: | 02 Sep 2020 00:06 |
FoR Codes: | 49 MATHEMATICAL SCIENCES > 4903 Numerical and computational mathematics > 490303 Numerical solution of differential and integral equations @ 50% 42 HEALTH SCIENCES > 4202 Epidemiology > 420202 Disease surveillance @ 50% |
SEO Codes: | 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920109 Infectious Diseases @ 50% 97 EXPANDING KNOWLEDGE > 970101 Expanding Knowledge in the Mathematical Sciences @ 50% |
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