• FluTrackers.com Inc. does not provide medical advice. Information on this web site is collected from various internet resources, and the FluTrackers board of directors makes no warranty to the safety, efficacy, correctness or completeness of the information posted on this site by any author or poster. The information collated here is for instructional and/or discussion purposes only and is NOT intended to diagnose or treat any disease, illness, or other medical condition. Every individual reader or poster should seek advice from their personal physician/healthcare practitioner before considering or using any interventions that are discussed on this website. By continuing to access this website you agree to consult your personal physican before using any interventions posted on this website, and you agree to hold harmless FluTrackers.com Inc., the board of directors, the members, and all authors and posters for any effects from use of any medication, supplement, vitamin or other substance, device, intervention, etc. mentioned in posts on this website, or other internet venues referenced in posts on this website.
  • We are not asking for any donations. Do not donate to any entity who says they are raising funds for us.

Sci Afr . Investigating the Transmission Dynamics of SARS-CoV-2 in Nigeria: A SEIR Modelling Approach

tetano

Editor, Senior Moderator
Sci Afr


. 2022 Feb 7;e01116.
doi: 10.1016/j.sciaf.2022.e01116. Online ahead of print.
Investigating the Transmission Dynamics of SARS-CoV-2 in Nigeria: A SEIR Modelling Approach


Matthew Olayiwola Adewole[SUP] 1 [/SUP], Akinkunmi Paul Okekunle[SUP] 2 3 [/SUP], Ikeola Adejoke Adeoye[SUP] 2 [/SUP], Onoja Matthew Akpa[SUP] 2 4 [/SUP]



Affiliations

Abstract

This study was designed to investigate the transmission dynamics of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to inform policy advisory vital for managing the spread of the virus in Nigeria. We applied the Susceptible-Exposed-Infectious-Recovered (SEIR)-type predictive model to discern the transmission dynamics of SARS-CoV-2 at different stages of the pandemic; incidence, during and after the lockdown from 27th March 2020 to 22nd September 2020 in Nigeria. Our model was calibrated with the COVID-19 data (obtained from the Nigeria Centre for Disease Control) using the "lsqcurvefit" package in MATLAB to fit the "cumulative active cases" and "cumulative death" data. We adopted the Latin hypercube sampling with a partial rank correlation coefficient index to determine the measure of uncertainty in our parameter estimation at a 99% confidence interval (CI). At the incidence of SARS-CoV-2 in Nigeria, the basic reproduction number (R[SUB]0[/SUB] ) was 6.860; 99%CI [6.003, 7.882]. R[SUB]0[/SUB] decreased by half (3.566; 99%CI [3.503, 3.613]) during the lockdown, and R[SUB]0[/SUB] was 1.238; 99%CI [1.215, 1.262] after easing the lockdown. If all parameters are maintained (as in after easing the lockdown), our model forecasted a gradual and perpetual surge through the next 12 months or more. In the light of our results and available data, evidence of human-to-human transmission at higher rates is still very likely. A timely, proactive, and well-articulated effort should help mitigate the transmission of SARS-CoV-2 in Nigeria.

Keywords: COVID-19; Data fitting, LHS/PRCC, Basic reproduction number.
 
Back
Top Bottom