Mathematical modeling for infectious viral disease: The COVID‐19 perspective

• Published date: 01 November 2020
• Author: Hafeez Aderinsayo Adekola,Ibrahim Ayoade Adekunle,Haneefat Olabimpe Egberongbe,Sefiu Adekunle Onitilo,Idris Nasir Abdullahi
• Date: 01 November 2020
• DOI: http://doi.org/10.1002/pa.2306

ACADEMIC PAPER

Mathematical modeling for infectious viral disease:

The COVID-19 perspective

Hafeez Aderinsayo Adekola

1

|Ibrahim Ayoade Adekunle

2

|

Haneefat Olabimpe Egberongbe

1

|Sefiu Adekunle Onitilo

3

|Idris Nasir Abdullahi

4

1

Department of Microbiology, Olabisi

Onabanjo University, Ago-Iwoye, Ogun State,

Nigeria

2

Department of Economics, Olabisi Onabanjo

University, Ago-Iwoye, Ogun State, Nigeria

3

Department of Mathematical Sciences,

Olabisi Onabanjo University, Ago Iwoye, Ogun

State, Nigeria

4

Department of Medical Laboratory Science,

Faculty of Allied Health Sciences, College of

Medical Sciences, Ahmadu Bello University,

Zaria, Nigeria

Correspondence

Ibrahim Ayoade Adekunle, Department of

Economics, Olabisi Onabanjo University, Ago-

Iwoye, Ogun State, Nigeria.

Email: adekunle_ia@yahoo.com

In this study, we examined various forms of mathematical models that are relevant

for the containment, risk analysis, and features of COVID-19. Greater emphasis was

laid on the extension of the Susceptible–Infectious–Recovered (SIR) models for pol-

icy relevance in the time of COVID-19. These mathematical models play a significant

role in the understanding of COVID-19 transmission mechanisms, structures, and

features. Considering that the disease has spread sporadically around the world,

causing large scale socioeconomic disruption unwitnessed in contemporary ages

since World War II, researchers, stakeholders, government, and the society at large

are actively engaged in finding ways to reduce the rate of infection until a cure or

vaccination procedure is established. We advanced argument for the various forms

of the mathematical model of epidemics and highlighted their relevance in the con-

tainment of COVID-19 at the present time. Mathematical models address the need

for understanding the transmission dynamics and other significant factors of the dis-

ease that would aid policymakers to make accurate decisions and reduce the rate of

transmission of the disease.

1|INTRODUCTION

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), a

novel β-coronavirus is the pathogen responsible for the coronavirus

disease 2019 (COVID-19; Li, Geng, Peng, Meng, & Lu, 2020). The

novel coronavirus has spread across the globe with the attendant

consequences felt in about 203 countries. As at the time of writing

(June 18, 2020), there are about 8,061,550 confirmed COVID-19

cases with 440,290 attributable deaths (World Health Organization

[WHO], 2020). The Americas (North and South) account for close to

50% of global cases with values standing at 3,899,859 confirmed

cases and 205,555 deaths. In Europe, there are about 2,452,247 con-

firmed cases with about 189,582 attributable deaths. In the Eastern

Mediterranean region, cases have soared to 817,458 with fatalities

around 18,057. In the Southeastern Asia region, about 503,034 cases

have been recorded with around 15,498 deaths. Down in the west-

ern pacific, there are about 200,586 cases with about 7,239 attribut-

able deaths. Across the African region, the number of confirmed

cases stood at 187,625 with 4,346 deaths (WHO, 2020). Since the

emergence of the virus in Wuhan, China in December 2019, the

aerosolized pathogens have spread exponentially, causing a large

scale and unprecedented socio and economic disruptions, threat to

global public health systems, poverty, undesirable psychological

depression, more considerable uncertainties among many other

deep-rooted issues (Sameni, 2020). The viral genome sequence of

the SARS-CoV-2 suggests the close relatedness to SARS-like bat

CoVs, but most genomic encoded proteins of the SARS-CoV-2 are

similar to the SARS-Covs with differences in two of the non-

structural proteins (NSP2 and NSP3), spike protein and the receptor-

binding domain (RBD; Wu et al., 2020). Studies have shown that the

SARS-CoV-2 is capable of mutation with two types being majorly

classified as the L-type and the S-type (Tang et al., 2020). The S-type

has been reported to have evolved when jumping from animal to

man while the L-type evolved later. Although both are currently

involved in the pandemic, the L-type has been reported to be more

prevalent than the S-type (Guo et al., 2020). How mathematical

models explain these chain reactions and transmission mechanisms

forms the core of the foregoing.

Received: 26 June 2020Revised: 14 July 2020Accepted: 19 July 2020

DOI: 10.1002/pa.2306

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https://doi.org/10.1002/pa.2306