Mathematical Modeling and Estimation of the Regional Variations in COVID-19 Infections Transmission in Nigeria: A Retrospective Data Analysis

This study estimated the reproduction number, which was used to determine the rate of spread of a communicable disease at sub-national levels in Nigeria and thereby provides state specific information needed to plan public health interventions.A Susceptible-Infectious-Recovered (SIR) model was first formulated from the compartmentalization of the whole disease population, and the SIR parameters for rate of spread of coronavirus (COVID)-19 computed and the reproduction numbers of infection were estimated across states in Nigeria.A log-linear model was also formulated from an exponential growth curve of COVID-19 infection, and thereafter the basic reproduction numbers were as well determined.The SIR analysis yielded the median reproduction number of COVID-19 transmission rate across states in Nigeria of 0.04473, range between 0.00082 and 1.2870, while the log-linear model yielded the median reproduction number of 2.003 ranges between 1.9759 and 2.0262 The results further reveals that there were significant disparities emerged when applying these models to the Nigerian context with notable under-estimation in some states perhaps due to under-reported cases at the early stage.The second approach, log-linear model with time-dependent transmission and removal rates to account for possible random errors across Nigeria states and estimates of reproduction numbers across states are greater than one (), may be due to the specified formula.The predictive ability of the log-linear model may be more suitable for modeling the incidence of COVID-19 and other infectious diseases in both the growth and decay phases, as well as for short-term predictions of the growth (or decay) of the number of new cases when no intervention measures had been recently implemented before the advent of vaccines.The general findings may reflect the effectiveness of virus control strategies and nonpharmaceutical interventions.

Authors

Publication Details

Journal
NIPES Journal of Science and Technology Research
Published
2025-04-25
DOI
https://doi.org/10.37933/nipes/7.1.2025.15
Citations
1
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
1.37
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article

Mathematical Modeling and Estimation of the Regional Variations in COVID-19 Infections Transmission in Nigeria: A Retrospective Data Analysis

Jamiu S. Olumoh, Stephen Oguche, Rasaki Aliu, R. A. Adeyemi
1 citations
NIPES Journal of Science and Technology Research
COVID-19 epidemiological studies
1.37
article

Mathematical Modeling and Estimation of the Regional Variations in COVID-19 Infections Transmission in Nigeria: A Retrospective Data Analysis

Jamiu S. Olumoh, Stephen Oguche, Rasaki Aliu, R. A. Adeyemi
article en
1 citations

Abstract

This study estimated the reproduction number, which was used to determine the rate of spread of a communicable disease at sub-national levels in Nigeria and thereby provides state specific information needed to plan public health interventions.A Susceptible-Infectious-Recovered (SIR) model was first formulated from the compartmentalization of the whole disease population, and the SIR parameters for rate of spread of coronavirus (COVID)-19 computed and the reproduction numbers of infection were estimated across states in Nigeria.A log-linear model was also formulated from an exponential growth curve of COVID-19 infection, and thereafter the basic reproduction numbers were as well determined.The SIR analysis yielded the median reproduction number of COVID-19 transmission rate across states in Nigeria of 0.04473, range between 0.00082 and 1.2870, while the log-linear model yielded the median reproduction number of 2.003 ranges between 1.9759 and 2.0262 The results further reveals that there were significant disparities emerged when applying these models to the Nigerian context with notable under-estimation in some states perhaps due to under-reported cases at the early stage.The second approach, log-linear model with time-dependent transmission and removal rates to account for possible random errors across Nigeria states and estimates of reproduction numbers across states are greater than one (), may be due to the specified formula.The predictive ability of the log-linear model may be more suitable for modeling the incidence of COVID-19 and other infectious diseases in both the growth and decay phases, as well as for short-term predictions of the growth (or decay) of the number of new cases when no intervention measures had been recently implemented before the advent of vaccines.The general findings may reflect the effectiveness of virus control strategies and nonpharmaceutical interventions.

NIPES Journal of Science and Technology ResearchVol. 7(1)
Openalex Percentile: Top 20%
COVID-19 epidemiological studies
1.37
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Mathematical Modeling and Estimation of the Regional Variations in COVID-19 Infections Transmission in Nigeria: A Retrospective Data Analysis — Jamiu S. Olumoh, Stephen Oguche, et al. · NIPES Journal of Science and Technology Research (2025) | TGRS Research Map | TGRS