COVID-19 and dengue co-infection in Brazil: optimal control and cost-effectiveness analysis

Omame, Andrew; Rwezaura, H.; Diagne, Mamadou Lamine; Inyama, S. C.; Tchuenche, Jean M.

doi:10.1140/epjp/s13360-021-02030-6

Cited by 36 publications

(18 citation statements)

References 35 publications

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“…The constants for are used for the balancing cost factors, and represents the final time. Due to nonlinear intervention among the population, quadratic objective functional is take into account, for details see references [ 7 , 8 , 15 , 16 ].…”

Section: Optimal Control Problemmentioning

confidence: 99%

“…The purpose of the study was to observe the role of joint implementation of social distance, mask usage, actively screening and testing in curtailing the spreading of COVID-19. Omame et al presented the formulation of a mathematical compartmental model addressing the dynamics of co-infection with COVID-19 in Brazil [ 15 ]. The authors in [ 15 ] studied the optimal control measures coupled with cost-effective analysis to curtail COVID-19 in the selected region.…”

Section: Introductionmentioning

confidence: 99%

“…Omame et al presented the formulation of a mathematical compartmental model addressing the dynamics of co-infection with COVID-19 in Brazil [ 15 ]. The authors in [ 15 ] studied the optimal control measures coupled with cost-effective analysis to curtail COVID-19 in the selected region. A similar mathematical analysis with a case study of Malaysia and Nigeria is conducted by Abidemi et al and Olaniyi et al in [ 16 , 17 ], respectively.…”

Section: Introductionmentioning

confidence: 99%

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Optimal control analysis of COVID-19 vaccine epidemic model: a case study

2022

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The purpose of this research is to explore the complex dynamics and impact of vaccination in controlling COVID-19 outbreak. We formulate the classical epidemic compartmental model by introducing vaccination class. Initially, the proposed mathematical model is analyzed qualitatively. The basic reproductive number is computed and its numerical value is estimated using actual reported data of COVID-19 for Pakistan. The sensitivity analysis is performed to analyze the contribution of model embedded parameters in transmission of the disease. Further, we compute the equilibrium points and discussed its local and global stability. In order to investigate the influence of model key parameters on the transmission and controlling of the disease, we perform numerical simulations describing the impact of various scenarios of vaccine efficacy rate and other controlling measures. Further, on the basis of sensitivity analysis, the proposed model is restructured to obtained optimal control model by introducing time-dependent control variables for isolation, for vaccine efficacy and for treatment enhancement. Using optimal control theory and Pontryagin’s maximum principle, the model is optimized and important optimality conditions are derived. In order to explore the impact of various control measures on the disease dynamics, we considered three different scenarios, i.e., single and couple and threefold controlling interventions. Finally, the graphical interpretation of each case is depicted and discussed in detail. The simulation results revealed that although single and couple scenarios can be implemented for the disease minimization but, the effective case to curtail the disease incidence is the threefold scenario which implements all controlling measures at the same time.

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Section: Optimal Control Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal control analysis of COVID-19 vaccine epidemic model: a case study

2022

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“…The main conclusion of previous research on this topic is the need for public action, involving mobility restrictions, to contain the spread of any viral disease that constitutes a special potential danger for society. A few studies of mobility restrictions and lockdowns in different parts of the world support this conclusion in the case of the Coronavirus [ 1 , 2 , 4 , 6 , 9 , 12 , 19 ]. A considerable number of them analyse countries and regions strongly affected by the pandemic in its initial stages.…”

Section: Introductionmentioning

confidence: 93%

“…Concerning the first group of factors, different authors have analysed the impact of human mobility and economic activity on the spread of viral diseases before the Coronavirus pandemic [ 3 , 18 ] and in its wake [ 4 , 12 , 19 ]. Using datasets from France, Adda [ 3 ] observes a positive relationship between interregional trade and faster spread of a viral disease.…”

Section: Introductionmentioning

confidence: 99%

The heterogeneous regional effect of mobility on Coronavirus spread

Amoedo

Atrio-Lema

Carreira

et al. 2022

Eur. Phys. J. Spec. Top.

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The Coronavirus (COVID-19) pandemic struck global society in 2020. The pandemic required the adoption of public policies to control spread of the virus, underlining the mobility restrictions. Several studies show that these measures have been effective. Within the topic of Coronavirus spread, this original paper analyses the effect of mobility on Coronavirus spread in a heterogeneous regional context. A multiple dynamic regression model is used to control sub-national disparities in the effect of mobility on the spread of the Coronavirus, as well as to measure it at the context of Spanish regions. The model includes other relevant explanatory factors, such as wind speed, sunshine hours, vaccinated population and social awareness. It also develops a new methodology to optimise the use of Google trends data. The results reveal heterogeneity among regions, which has important implications for current and future pandemic containment strategies.

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An optimal control model for COVID‐19, zika, dengue, and chikungunya co‐dynamics with reinfection

Omame

Isah

Abbas

2022

Optim Control Appl Methods

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The co‐circulation of different emerging viral diseases is a big challenge from an epidemiological point of view. The similarity of symptoms, cases of virus co‐infection, and cross‐reaction can mislead in the diagnosis of the disease. In this article, a new mathematical model for COVID‐19, zika, chikungunya, and dengue co‐dynamics is developed and studied to assess the impact of COVID‐19 on zika, dengue, and chikungunya dynamics and vice‐versa. The local and global stability analyses are carried out. The model is shown to undergo a backward bifurcation under a certain condition. Global sensitivity analysis is also performed on the parameters of the model to determine the most dominant parameters. If the zika‐related reproduction number is used as the response function, then important parameters are: the effective contact rate for vector‐to‐human transmission of zika ( , which is positively correlated), the human natural death rate ( , positively correlated), and the vector recruitment rate ( , also positively correlated). In addition, using the class of individuals co‐infected with COVID‐19 and zika ( ) as response function, the most dominant parameters are: the effective contact rate for COVID‐19 transmission ( , positively correlated), the effective contact rate for vector‐to‐human transmission of zika ( , positively correlated). To control the co‐circulation of all the diseases adequately under an endemic setting, time dependent controls in the form of COVID‐19, zika, dengue, and chikungunya preventions are incorporated into the model and analyzed using the Pontryagin's principle. The model is fitted to real COVID‐19, zika, dengue, and chikungunya datasets for Espirito Santo (a city with the co‐circulation of all the diseases), in Brazil and projections made for the cumulative cases of each of the diseases. Through simulations, it is shown that COVID‐19 prevention could greatly reduce the burden of co‐infections with zika, dengue, and chikungunya. The negative impact of the COVID‐19 pandemic on the control of the arbovirus diseases is also highlighted. Furthermore, it is observed that prevention controls for zika, dengue, and chikungunya can significantly reduce the burden of co‐infections with COVID‐19.

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COVID-19 and dengue co-infection in Brazil: optimal control and cost-effectiveness analysis

Cited by 36 publications

References 35 publications

Optimal control analysis of COVID-19 vaccine epidemic model: a case study

Optimal control analysis of COVID-19 vaccine epidemic model: a case study

The heterogeneous regional effect of mobility on Coronavirus spread

An optimal control model for COVID‐19, zika, dengue, and chikungunya co‐dynamics with reinfection

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