Memoire Online - Dynamics of covid-19 pandemic in cameroon : impacts of social distanciation and face mask wearing

Lethality is the percentage of the death toll among confirmed virus cases. The first fatality assessment was released on 14 February by the Chinese Center for Disease Control and Prevention (Chinese CDC), among the first 44, 672 confirmed cases it was then estimated at (2.3%) .

Lethality varies according to the conditions in which patients are treated and their access to hospital services. It is different from one country to another. Globally the WHO has estimated it to be around 3.4 % (the 3 March 2020).

With the increase in cases of the disease worldwide, WHO estimates the percentage of death rate from COVID- 19 to 2.2% as of 17 December 2020.

If it seemed spared for a long time or almost, the African continent is now affected like the rest of the world, even if the number of cases remains limited. The first case of COVID- 19 in Africa appeared in February 2020 in Egypt. A sudden increase in the number of cases is observed in July

Master's thesis II * Molecular Atomic Physics and Biophysics Laboratory-UYI * YAMENI STEINLEN DONAT D (c)2021

and August, then the contaminations slowed down again. The following table presents the results of the pandemic in some African countries during the period of August 31, 2021 [14, 15].

Countries	N.Cas	healing Cas	N.death	Lethality%
Soudan	37699	3163	2831	6.2
Egypte	288162	238580	16727	5.5
Liberia	5459	2715	148	4.4
Cameroon	82064	80433	1354	1.7

In this chapter, we were talking about generalities about the Coronavirus disease. COVID-19 is a newly identified highly infectious disease originating in Wuhan, China, December 2019, which quickly spread like wildfire causing death and devastation around the world. In order to limit the spread of the pandemic, the States will organize the response. The need therefore arises in the next chapter to build a compartmental model to predict the possible scenarios of transmission and spread of the disease.

Infectious disease models are increasingly used to predict a range of future possibilities to aid and support knowledge development and decision making at the scientific, medical and health levels.

In this chapter, we present the actual calculation of the reproduction rate with control measures R_c, which is an important quantity to characterize epidemic diseases, through the stability analysis.

2.2 Formulation of the model

The fundamental tool in the study of COVID-19 dynamics is the mathematical model in that it allows for a better understanding of the impacts of various non-pharmaceutical control measures (governmental and personal) on the population dynamics of the new COVID-19 disease.

Master's thesis II * Molecular Atomic Physics and Biophysics Laboratory-UYI * YAMENI STEINLEN DONAT D (c)2021

À	Recruitment of sensitive individuals
/31	Transmission rate of undetected infected
/32	Transmission rate of detected infected
cf	Containment rate of sensitive individuals
ä	Incubation rate
p	Fraction of exposures that become infected undetected
u	Disease-induced mortality rate
€	Quarantine rate of detected infectious
a	Quarantine rate of undetected infectious
a1	Recovery rate of undetected infectious
a2	Recovery rate of quarantined individuals
O	Represents the fraction of the total population that uses a face mask
ø	proportion of the population that maintains the minimum distance required to prevent infection

The total human population at time (t), denoted Nh(t) is divided into a mutually exclusive subgroup of susceptible individuals S(t), exposed individuals E(t), undetected infectious individuals I_nd(t), detected infectious individuals Id(t), quarantined individuals Q(t), recovered individuals R(t).

The model of the transmission dynamics of COVID-19 in a population is given by the following

system of deterministic nonlinear differential equations in (2-1) built by Nkamba et al [5],

Eÿ = (â1Ind + â2Id)S - äE, ^ÿInd = päE - (ó1 + á + u)I_nd, ^ÿId = (1 - p)äE - (å + u)Id, Qÿ = åId + áInd - (ó2 + u)Q,

with the table describing the state associated variables and parameters in the model(2-1) while figure (2-1) gives the schematic diagram of the model(2-1).

Mathematical models without demographic parameters (i.e. birth and natural death) in equations (2-1) have been widely used to study the dynamics of epidemics [16, 17, 19]. Demographic parameters, including natural births and deaths, can be excluded when dynamically exchanging an epidemic that occurs within weeks or months [18, 19, 20, 21, 22]. If we introduce parameters used by Okuonghae and Omame [23], that represent social distancing and use of face masks of infection from the basic model (2-1), in which a new parameter ø represents the proportion of the population that maintains the minimum distance required to prevent infection (at least 1 meter apart), and another parameter è represents the fraction of the population that use face masks (where it is assumed that face masks are effectively high whenever they are in public, so that 0 < è < 1), the basic model (2-1) now becomes.

???????????????? ?

?????????????????

S^ÿ= ë - (1 - è)(1 - ø)(â1Ind + â2Id)S - CfS, E^ÿ= (1 - è)(1 - ø)(â1Ind + â2Id)S - äE,

^ÿInd = päE - (ó1 + á + u)I_nd, (2.2)

^ÿId = (1 - p)äE - (å + u)Id,

Qÿ = åId + áInd - (ó2 + u)Q, R^ÿ= ó1Ind + ó2Q.

It is imperative to specify that in the framework envisaged in this work, the strict adoption of the use of face masks has been encouraged well into the current outbreaks in Cameroon, particularly

Dynamics of covid-19 pandemic in cameroon : impacts of social distanciation and face mask wearing

1.12 Lethality

2.2 Formulation of the model