Estimating  the Basic Reproductive Number of COVID-19 Cases in Ghana

Otoo, Dominic; Donkoh, Elvis K.; Kessie, Justice Amenyo

doi:10.29020/nybg.ejpam.v14i1.3850

Cited by 5 publications

(5 citation statements)

References 13 publications

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“…Numerous models have been developed to estimate the basic reproduction number of COVID-19 across the world [45][46][47][48][49][50][51][52][53]. In [53], logistic growth curves were fitted to the daily reported cases of COVID-19 for 58 countries across the world.…”

Section: Introductionmentioning

confidence: 99%

The basic reproduction number of COVID-19 across Africa

et al. 2022

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The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) took the world by surprise. Following the first outbreak of COVID-19 in December 2019, several models have been developed to study and understand its transmission dynamics. Although the spread of COVID-19 is being slowed down by vaccination and other interventions, there is still a need to have a clear understanding of the evolution of the pandemic across countries, states and communities. To this end, there is a need to have a clearer picture of the initial spread of the disease in different regions. In this project, we used a simple SEIR model and a Bayesian inference framework to estimate the basic reproduction number of COVID-19 across Africa. Our estimates vary between 1.98 (Sudan) and 9.66 (Mauritius), with a median of 3.67 (90% CrI: 3.31–4.12). The estimates provided in this paper will help to inform COVID-19 modeling in the respective countries/regions.

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Section: Introductionmentioning

confidence: 99%

The basic reproduction number of COVID-19 across Africa

et al. 2022

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“…According to the Routh-Hurwitz stability criterion [41][42][43][44], all the eigenvalues of the characteristic Equation (30) have negative real part if and only if R 0 < 1 such that the following conditions hold: q j > 0, j = 1, ⋯, 5 q 1 q 2 − q 3 > 0 q 3 q 1 q 2 − q 3 + q 1 q 5 − q 1 q 4 > 0 q 1 q 2 − q 3 q 4 q 3 − q 2 q 5 − q 5 − q 1 q 4 2 > 0 Theorem 5. The DFE of the system ((1)) is locally asymptotically stable if R 0 < 1 and the conditions ((1))-((4)) above are satisfied.…”

Section: S Hn+τ T − S Hn T ≤ 〠mentioning

confidence: 99%

Modeling the Transmission Routes of Hepatitis E Virus as a Zoonotic Disease Using Fractional-Order Derivative

Osman,

Lassong,

Dasumani

et al. 2024

Journal of Applied Mathematics

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Hepatitis E virus (HEV) is one of the emerging zoonotic diseases in Sub-Saharan Africa. Domestic pigs are considered to be the main reservoir for this infectious disease. A third of the world’s population is thought to have been exposed to the virus. The zoonotic transmission of the HEV raises serious zoonotic and food safety concerns for the general public. This is a major public health issue in both developed and developing countries. The World Health Organization (WHO) estimated that 44,000 people died in 2015 as a result of HEV infection. East and South Asia have the highest prevalence of this disease overall. In this study, we proposed, developed, and analyzed the transmission routes of the infection using a fractional-order derivative approach. The existence, stability, and uniqueness of solutions were established using the approach and concept in Banach space. Local and global stability was determined using the Hyers–Ulam (HU) stability approach. Numerical simulation was conducted using existing parameter values, and it was established that, as the susceptible human population declines, the number of infected human populations rises with a change in fractional order θ^. When the susceptible pig population increases, the number of infected pig populations rises with a change in θ^. It was observed that a few variations in the fractional derivative order did not alter the function’s overall behavior with the results of numerical simulations. Moreover, as the number of recovered human populations increases, there is a corresponding increase in the population of recovered pigs with a change in θ^. The exponential increase in the infected pig population can be controlled by treatment of the infected pigs and prevention of the susceptible pigs. The authors recommend policymakers, and stakeholders prioritize the fight against the virus by enforcing the prevention of humans and treatment of infected pigs. The model can be extended to optimal control and cost-effectiveness analysis to determine the most effective control strategy that comes with less cost in the combat of the disease.

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“…For the COVID-19, one can find estimates of the basic reproduction number based on different approaches. There are contributions that rely on the classical compartmental models by direct analysis of the models [31,32], or by applying the next generation matrix approach [33][34][35]. In the non-Markovian setting, there can be found works that use the mean and variance of the generation interval distribution [36], or the serial interval distribution as its proxy [37][38][39] and so on.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the basic reproduction number of COVID-19 from the incubation period distribution

Basnarkov

Tomovski

Avram

2022

Eur. Phys. J. Spec. Top.

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The estimates of the future course of spreading of the SARS-CoV-2 virus are frequently based on Markovian models in which the duration of residence in any compartment is exponentially distributed. Accordingly, the basic reproduction number R0 is also determined from formulae where it is related to the parameters of such models. The observations show that the start of infectivity of an individual appears nearly at the same time as the onset of symptoms, while the distribution of the incubation period is not an exponential. Therefore, we propose a method for estimation of R0 for COVID-19 based on the empirical incubation period distribution and assumed very short infectivity period that lasts only few days around the onset of symptoms. We illustrate this venerable approach to estimate R0 for six major European countries in the first wave of the epidemic. The calculations show that even if the infectivity starts 2 days before the onset of symptoms and stops instantly when they appear (immediate isolation), the value of R0 is larger than that from the classical, SIR model. For more realistic cases, when only individuals with mild symptoms spread the virus for few days after onset of symptoms, the respective values are even larger. This implies that calculations of R0 and other characteristics of spreading of COVID-19 based on the classical, Markovian approaches should be taken very cautiously.

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Estimating the Basic Reproductive Number of COVID-19 Cases in Ghana

Cited by 5 publications

References 13 publications

The basic reproduction number of COVID-19 across Africa

The basic reproduction number of COVID-19 across Africa

Modeling the Transmission Routes of Hepatitis E Virus as a Zoonotic Disease Using Fractional-Order Derivative

Estimation of the basic reproduction number of COVID-19 from the incubation period distribution

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