Assessing the potential impact of immunity waning on the dynamics of COVID-19 in South Africa: an endemic model of COVID-19

Rabiu, Musa; Iyaniwura, Sarafa A.

doi:10.1007/s11071-022-07225-9

Cited by 15 publications

(6 citation statements)

References 71 publications

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“…In this study, we developed a deterministic compartmental model of COVID-19 stratified by infection status and vaccination status to describe the impact of an imperfect vaccine on the transmission dynamics of the disease. The proposed model is a modification of a previously developed compartmental model [36] where vaccination was incorporated in the COVID-19 model as a pharmaceutical intervention strategy in South Africa. The mathematical model comprises eight epidemiological states depending on the individual's health and vaccination status.…”

Section: Model Formulationmentioning

confidence: 99%

“…Thus, infections for the vaccinated can occur but at a reduced rate compared to that of the unvaccinated susceptible individuals. (iii) Both vaccine-derived and natural immunity may wane over time in individuals, implying that individuals rejoin the fully susceptible class after a certain period [36][37][38]. (iv) We assume that there is homogeneous mixing among the population, which means that every individual in the community is equally likely to mix and acquire infections from each member when they make contact.…”

Section: Model Formulationmentioning

confidence: 99%

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Assessing the Impact of Vaccination on the Dynamics of COVID-19 in Africa: A Mathematical Modeling Study

et al. 2023

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Several effective COVID-19 vaccines are administered to combat the COVID-19 pandemic globally. In most African countries, there is a comparatively limited deployment of vaccination programs. In this work, we develop a mathematical compartmental model to assess the impact of vaccination programs on curtailing the burden of COVID-19 in eight African countries considering SARS-CoV-2 cumulative case data for each country for the third wave of the COVID-19 pandemic. The model stratifies the total population into two subgroups based on individual vaccination status. We use the detection and death rates ratios between vaccinated and unvaccinated individuals to quantify the vaccine’s effectiveness in reducing new COVID-19 infections and death, respectively. Additionally, we perform a numerical sensitivity analysis to assess the combined impact of vaccination and reduction in the SARS-CoV-2 transmission due to control measures on the control reproduction number (Rc). Our results reveal that on average, at least 60% of the population in each considered African country should be vaccinated to curtail the pandemic (lower the Rc below one). Moreover, lower values of Rc are possible even when there is a low (10%) or moderate (30%) reduction in the SARS-CoV-2 transmission rate due to NPIs. Combining vaccination programs with various levels of reduction in the transmission rate due to NPI aids in curtailing the pandemic. Additionally, this study shows that vaccination significantly reduces the severity of the disease and death rates despite low efficacy against COVID-19 infections. The African governments need to design vaccination strategies that increase vaccine uptake, such as an incentive-based approach.

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Section: Model Formulationmentioning

confidence: 99%

Section: Model Formulationmentioning

confidence: 99%

Assessing the Impact of Vaccination on the Dynamics of COVID-19 in Africa: A Mathematical Modeling Study

et al. 2023

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“…Rabiu and Iyaniwura [12] have developed an endemic model for COVID-19 in-order to study the impact of vaccination and waning of immunity on the dynamics of COVID-19 disease. Based on the model, authors have suggested that waning of vaccine-related immunity has more effect on the disease compared to the post-recovery based immunity which has a direct impact on the eradication of COVID-19.…”

Section: B Waning Immunitymentioning

confidence: 99%

A Proposed Quantitative Model for the Computation and Analysis of Waning Immunity for COVID-19 Virus among Human Population

Rubini

Choudhary

2022

2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)

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Waning Immunity is an important and relevant concept during these days as the COVID-19 pandemic is expected to become endemic in the coming months. By definition, Waning Immunity is the loss of protective antibodies over time and hence necessitates booster shots at regular intervals of time. This quantitative study is on proposition of a model for computing a newly defined metric called Waning Immunity Index (WII). The model takes into account the three group of people namely, susceptible, infected and recovered individuals from the COVID-19 infections. The required data can be collected from the Kaggle repository that contains information on infections, recovery, vaccination and booster doses given on the human population while considering a geographical location. The proposed model and its implementation have thrown light on the spread, control and effect of COVID-19 virus. Results of the proposed model and the measurement can help health officials to seamlessly plan the duration of booster doses administered on vaccinated population. A sample data has been prepared for testing the model and the application of the proposed metrics. Based on the results, it is found that vulnerability of the Waning Immunity increases steeply at some duration and gradually steadies in time.

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“…The effort to control the multiple COVID-19 strains is the demand for more restrictive measures [11]. The SEIR model with vaccination and pre-symptomatic populations shows that the waning of vaccineinduced immunity significantly impacts the disease spreading [12]. Contact tracing, national-scale social restriction, wearing face masks, and case detection and treatment are the most effective scenarios to control the spreading of COVID-19 in Indonesia [13].…”

mentioning

confidence: 99%

A mathematical model of tuberculosis and COVID-19 coinfection with the effect of isolation and treatment

Inayaturohmat

Beay

Supriatna

2022

Front. Appl. Math. Stat.

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In this research, we developed a coinfection model of tuberculosis and COVID-19 with the effect of isolation and treatment. We obtained two equilibria, namely, disease-free equilibrium and endemic equilibrium. Disease-free equilibrium is a state in which no infection of tuberculosis and COVID-19 occurs. Endemic equilibrium is a state in which there occurs not only the infection of tuberculosis and COVID-19 but also the coinfection of tuberculosis and COVID-19. We assumed that the parameters follow the uniform distribution, and then, we took 1,000 samples of each parameter using Latin hypercube sampling (LHS). Next, the samples were sorted by ranking. Finally, we used the partial rank correlation coefficient (PRCC) to find the correlation between the parameters with compartments. We analyzed the PRCC for three compartments, namely, individuals infected with COVID-19, individuals infected with tuberculosis, and individuals coinfected with COVID-19 and tuberculosis. The most sensitive parameters are the recovery rate and the infection rate of each COVID-19 and tuberculosis. We performed the optimal control in the form of prevention for COVID-19 and tuberculosis. The numerical simulation shows that these controls effectively reduce the infected population. We also concluded that the effect of isolation has an immediate impact on reducing the number of COVID-19 infections, while the effect of treatment has an impact that tends to take a longer time.

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Assessing the potential impact of immunity waning on the dynamics of COVID-19 in South Africa: an endemic model of COVID-19

Cited by 15 publications

References 71 publications

Assessing the Impact of Vaccination on the Dynamics of COVID-19 in Africa: A Mathematical Modeling Study

Assessing the Impact of Vaccination on the Dynamics of COVID-19 in Africa: A Mathematical Modeling Study

A Proposed Quantitative Model for the Computation and Analysis of Waning Immunity for COVID-19 Virus among Human Population

A mathematical model of tuberculosis and COVID-19 coinfection with the effect of isolation and treatment

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