<p><p>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 <math> <mrow> <mrow> <msub><mrow><mi>ℛ</mi></mrow> <mrow><mtext>0Z</mtext></mrow> </msub> </mrow> </mrow> </math> is used as the response function, then important parameters are: the effective contact rate for vector-to-human transmission of zika ( <math> <mrow> <mrow> <msubsup><mrow><mi>β</mi></mrow> <mrow><mn>2</mn></mrow> <mrow><mi>h</mi></mrow> </msubsup> </mrow> </mrow> </math> , which is positively correlated), the human natural death rate ( <math> <mrow> <mrow> <msup><mrow><mi>ϑ</mi></mrow> <mrow><mi>h</mi></mrow> </msup> </mrow> </mrow> </math> , positively correlated), and the vector recruitment rate ( <math> <mrow> <mrow> <msup><mrow><mi>Ψ</mi></mrow> <mrow><mi>v</mi></mrow> </msup> </mrow> </mrow> </math> , also positively correlated). In addition, using the class of individuals co-infected with COVID-19 and zika ( <math> <mrow> <mrow> <msubsup><mrow><mi>ℐ</mi></mrow> <mrow><mtext>CZ</mtext></mrow> <mrow><mi>h</mi></mrow> </msubsup> </mrow> </mrow> </math> ) as response function, the most dominant parameters are: the effective contact rate for COVID-19 transmission ( <math> <mrow> <mrow> <msub><mrow><mi>β</mi></mrow> <mrow><mn>1</mn></mrow> </msub> </mrow> </mrow> </math> , positively correlated), the effective contact rate for vector-to-human transmission of zika ( <math> <mrow> <mrow> <msubsup><mrow><mi>β</mi></mrow> <mrow><mn>2</mn></mrow> <mrow><mi>h</mi></mrow> </msubsup> </mrow> </mrow> </math> , 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 contr
{"title":"An optimal control model for COVID-19, zika, dengue, and chikungunya co-dynamics with reinfection.","authors":"Andrew Omame, Mary Ele Isah, Mujahid Abbas","doi":"10.1002/oca.2936","DOIUrl":"10.1002/oca.2936","url":null,"abstract":"<p><p>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 <math> <mrow> <mrow> <msub><mrow><mi>ℛ</mi></mrow> <mrow><mtext>0Z</mtext></mrow> </msub> </mrow> </mrow> </math> is used as the response function, then important parameters are: the effective contact rate for vector-to-human transmission of zika ( <math> <mrow> <mrow> <msubsup><mrow><mi>β</mi></mrow> <mrow><mn>2</mn></mrow> <mrow><mi>h</mi></mrow> </msubsup> </mrow> </mrow> </math> , which is positively correlated), the human natural death rate ( <math> <mrow> <mrow> <msup><mrow><mi>ϑ</mi></mrow> <mrow><mi>h</mi></mrow> </msup> </mrow> </mrow> </math> , positively correlated), and the vector recruitment rate ( <math> <mrow> <mrow> <msup><mrow><mi>Ψ</mi></mrow> <mrow><mi>v</mi></mrow> </msup> </mrow> </mrow> </math> , also positively correlated). In addition, using the class of individuals co-infected with COVID-19 and zika ( <math> <mrow> <mrow> <msubsup><mrow><mi>ℐ</mi></mrow> <mrow><mtext>CZ</mtext></mrow> <mrow><mi>h</mi></mrow> </msubsup> </mrow> </mrow> </math> ) as response function, the most dominant parameters are: the effective contact rate for COVID-19 transmission ( <math> <mrow> <mrow> <msub><mrow><mi>β</mi></mrow> <mrow><mn>1</mn></mrow> </msub> </mrow> </mrow> </math> , positively correlated), the effective contact rate for vector-to-human transmission of zika ( <math> <mrow> <mrow> <msubsup><mrow><mi>β</mi></mrow> <mrow><mn>2</mn></mrow> <mrow><mi>h</mi></mrow> </msubsup> </mrow> </mrow> </math> , 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 contr","PeriodicalId":54672,"journal":{"name":"Optimal Control Applications & Methods","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9538730/pdf/OCA-9999-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9548692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-01Epub Date: 2021-06-02DOI: 10.1002/oca.2748
Andrew Omame, Ndolane Sene, Ikenna Nometa, Cosmas I Nwakanma, Emmanuel U Nwafor, Nneka O Iheonu, Daniel Okuonghae
In this work, we develop and analyze a mathematical model for the dynamics of COVID-19 with re-infection in order to assess the impact of prior comorbidity (specifically, diabetes mellitus) on COVID-19 complications. The model is simulated using data relevant to the dynamics of the diseases in Lagos, Nigeria, making predictions for the attainment of peak periods in the presence or absence of comorbidity. The model is shown to undergo the phenomenon of backward bifurcation caused by the parameter accounting for increased susceptibility to COVID-19 infection by comorbid susceptibles as well as the rate of reinfection by those who have recovered from a previous COVID-19 infection. Simulations of the cumulative number of active cases (including those with comorbidity), at different reinfection rates, show infection peaks reducing with decreasing reinfection of those who have recovered from a previous COVID-19 infection. In addition, optimal control and cost-effectiveness analysis of the model reveal that the strategy that prevents COVID-19 infection by comorbid susceptibles is the most cost-effective of all the control strategies for the prevention of COVID-19.
{"title":"Analysis of COVID-19 and comorbidity co-infection model with optimal control.","authors":"Andrew Omame, Ndolane Sene, Ikenna Nometa, Cosmas I Nwakanma, Emmanuel U Nwafor, Nneka O Iheonu, Daniel Okuonghae","doi":"10.1002/oca.2748","DOIUrl":"https://doi.org/10.1002/oca.2748","url":null,"abstract":"<p><p>In this work, we develop and analyze a mathematical model for the dynamics of COVID-19 with re-infection in order to assess the impact of prior comorbidity (specifically, <b>diabetes mellitus</b>) on COVID-19 complications. The model is simulated using data relevant to the dynamics of the diseases in Lagos, Nigeria, making predictions for the attainment of peak periods in the presence or absence of comorbidity. The model is shown to undergo the phenomenon of backward bifurcation caused by the parameter accounting for increased susceptibility to COVID-19 infection by comorbid susceptibles as well as the rate of reinfection by those who have recovered from a previous COVID-19 infection. Simulations of the cumulative number of active cases (including those with comorbidity), at different reinfection rates, show infection peaks reducing with decreasing reinfection of those who have recovered from a previous COVID-19 infection. In addition, optimal control and cost-effectiveness analysis of the model reveal that the strategy that prevents COVID-19 infection by comorbid susceptibles is the most cost-effective of all the control strategies for the prevention of COVID-19.</p>","PeriodicalId":54672,"journal":{"name":"Optimal Control Applications & Methods","volume":"42 6","pages":"1568-1590"},"PeriodicalIF":1.8,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/oca.2748","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39158345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yili Chen, Haoming He, Dakang Liu, Xie Zhang, Jingpei Wang, Yixiao Yang
Novel coronavirus pneumonia (COVID-19) epidemic outbreak at the end of 2019 and threaten global public health, social stability, and economic development, which is characterized by highly contagious and asymptomatic infections. At present, governments around the world are taking decisive action to limit the human and economic impact of COVID-19, but very few interventions have been made to target the transmission of asymptomatic infected individuals. Thus, it is a quite crucial and complex problem to make accurate forecasts of epidemic trends, which many types of research dedicated to deal with it. In this article, we set up a novel COVID-19 transmission model by introducing traditional SEIR (susceptible-exposed-infected-removed) disease transmission models into complex network and propose an effective prediction algorithm based on the traditional machine learning algorithm TrustRank, which can predict asymptomatic infected individuals in a population contact network. Our simulation results show that our method largely outperforms the graph neural network algorithm for new coronary pneumonia prediction and our method is also robust and gives good results even if the network information is incomplete.
{"title":"Prediction of asymptomatic COVID-19 infections based on complex network.","authors":"Yili Chen, Haoming He, Dakang Liu, Xie Zhang, Jingpei Wang, Yixiao Yang","doi":"10.1002/oca.2806","DOIUrl":"10.1002/oca.2806","url":null,"abstract":"<p><p>Novel coronavirus pneumonia (COVID-19) epidemic outbreak at the end of 2019 and threaten global public health, social stability, and economic development, which is characterized by highly contagious and asymptomatic infections. At present, governments around the world are taking decisive action to limit the human and economic impact of COVID-19, but very few interventions have been made to target the transmission of asymptomatic infected individuals. Thus, it is a quite crucial and complex problem to make accurate forecasts of epidemic trends, which many types of research dedicated to deal with it. In this article, we set up a novel COVID-19 transmission model by introducing traditional SEIR (susceptible-exposed-infected-removed) disease transmission models into complex network and propose an effective prediction algorithm based on the traditional machine learning algorithm TrustRank, which can predict asymptomatic infected individuals in a population contact network. Our simulation results show that our method largely outperforms the graph neural network algorithm for new coronary pneumonia prediction and our method is also robust and gives good results even if the network information is incomplete.</p>","PeriodicalId":54672,"journal":{"name":"Optimal Control Applications & Methods","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8661857/pdf/OCA-9999-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39726336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1007/978-3-030-91029-7_14
L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal
{"title":"Extremals Field Theory","authors":"L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal","doi":"10.1007/978-3-030-91029-7_14","DOIUrl":"https://doi.org/10.1007/978-3-030-91029-7_14","url":null,"abstract":"","PeriodicalId":54672,"journal":{"name":"Optimal Control Applications & Methods","volume":"17 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83245824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1007/978-3-319-49781-5_1
L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal
{"title":"The Subject of Optimal Control","authors":"L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal","doi":"10.1007/978-3-319-49781-5_1","DOIUrl":"https://doi.org/10.1007/978-3-319-49781-5_1","url":null,"abstract":"","PeriodicalId":54672,"journal":{"name":"Optimal Control Applications & Methods","volume":"35 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91346811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1007/978-3-319-49781-5_4
L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal
{"title":"Controllability of Linear Systems","authors":"L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal","doi":"10.1007/978-3-319-49781-5_4","DOIUrl":"https://doi.org/10.1007/978-3-319-49781-5_4","url":null,"abstract":"","PeriodicalId":54672,"journal":{"name":"Optimal Control Applications & Methods","volume":"22 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91082883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1007/978-3-319-49781-5_11
L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal
{"title":"The Simplest Problem of Optimal Control","authors":"L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal","doi":"10.1007/978-3-319-49781-5_11","DOIUrl":"https://doi.org/10.1007/978-3-319-49781-5_11","url":null,"abstract":"","PeriodicalId":54672,"journal":{"name":"Optimal Control Applications & Methods","volume":"15 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76529401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1007/978-3-319-49781-5_5
L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal
{"title":"Minimum Time Problem","authors":"L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal","doi":"10.1007/978-3-319-49781-5_5","DOIUrl":"https://doi.org/10.1007/978-3-319-49781-5_5","url":null,"abstract":"","PeriodicalId":54672,"journal":{"name":"Optimal Control Applications & Methods","volume":"26 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90231477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1007/978-3-319-49781-5_13
L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal
{"title":"Sufficient Optimality Conditions","authors":"L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal","doi":"10.1007/978-3-319-49781-5_13","DOIUrl":"https://doi.org/10.1007/978-3-319-49781-5_13","url":null,"abstract":"","PeriodicalId":54672,"journal":{"name":"Optimal Control Applications & Methods","volume":"41 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73976858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1007/978-3-319-49781-5_12
L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal
{"title":"General Optimal Control Problem","authors":"L. T. Ashchepkov, Dmitriy V. Dolgy, Taekyun Kim, R. Agarwal","doi":"10.1007/978-3-319-49781-5_12","DOIUrl":"https://doi.org/10.1007/978-3-319-49781-5_12","url":null,"abstract":"","PeriodicalId":54672,"journal":{"name":"Optimal Control Applications & Methods","volume":"115 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81622130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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