Modelling the impacts of lockdown and isolation on the eradication of COVID-19

Abstract

A model describing the dynamics of COVID-19 is formulated and examined. The model is meant to address the impacts of lockdown and social isolation as strategies for the eradication of the pandemic. Local stability analysis indicate that the equilibria are locally-asymptotically stable for R0<1 and R_0>1 for the disease-free equilibrium and the endemic equilibrium respectively. Numerical simulations of the model equations show that lockdown is a more effective strategy in the eradication of the disease than social isolation. However, strict enforcement of both strategies is the most effective means that could end the disease within a shorter period of time.

Mathematical Modelling and Control of COVID-19 Transmission in the Presence of Exposed Immigrants

“…The impact of quarantine strategy at point of entry as demonstrated in Figure 4 actually limits the spread of COVID-19 cases compared to the scenario where the exposed immigrants enter the community without being screened. This result conforms to the works of [13], [18] that suggested that lockdown and border closure will help to curtail the spread of COVID-19. In a similar fashion, it is noted in Figure 5 that strong body immune system has an encouraging response towards the mitigating of the pandemic.…”

“…Some works focus on testing and detection [13]. Some implements the use of vaccines [14] and others focus on influence of infective immigrants [15], quarantine and education ( [16], [17]), lockdown, contact tracing and isolation ( [18], [19]). Research in these areas have presented novel results on preventive and curable steps to contain the pandemic and have reported better outcomes in terms of completing time estimation for contact tracing.…”

Mathematical assessment of the role of denial on COVID-19 transmission with non-linear incidence and treatment functions

“…In this study, we propose a mathematical framework of generic SEIR model for COVID-19 transmission dynamics using the Beddington-De Angelis functional response and Holling type II treatment as applied in [15] , [16] on infectious model. The derivation of the differential equations is as a result of the under listed assumptions: The total population, N at any time, t, is divided into five classes: Susceptible people, S (who are under risk of contracting COVID-19), Exposed people, E (who are in close contact with infected people, but not yet infected), Asymptomatic people, A (who harbour the corona virus without clinical symptoms but capable of transmitting the disease), Symptomatic people, I (who are infected with the corona virus with clinical symptoms and capable of transmitting the disease), Hospitalized people, H (infectious people who are isolated for treatment) and Recovered people, R (who survived the COVID-19 infection).…”

“…Non-linear incidence and treatment functions have been reported by several authors [13] , [14] , [15] to be invaluable tool used to reduce the spread of diseases, not limited to measles and tuberculosis. In epidemiological modelling of COVID-19, mass action function of the kind , where is the infection rate was applied in model of [16] and a saturated incidence rate, was found in the models of [17] , [18] . On the other hand, the application of Beddington-De Angelis incidence rate of type was adopted in the works of [19] , [20] , [21] , [22] , [23] for non-COVID-19 models.…”

“… [24] and Daniel [18] used a constant rate and Holling type II, respectively as treatment functions, in corona virus transmission models. Other controls such as lock down strategy, social isolation on corona virus have been deliberated upon in the work of Ndam [16] without denial effect. A dual-purpose wheelchair was developed for containment of COVID-19 in paraplegic patients in Lagos, Nigeria [25] , and knowledge and attitudinal behaviour among Sudanese population was also observed to be key in eradicating the pandemic [26] .…”