{"title":"2-DG药物抑制SARS-CoV-2感染的临床效果:分数阶最优对照研究","authors":"Piu Samui, Jayanta Mondal, Bashir Ahmad, Amar Nath Chatterjee","doi":"10.1007/s10867-022-09617-9","DOIUrl":null,"url":null,"abstract":"<div><p>Fractional calculus is very convenient tool in modeling of an emergent infectious disease system comprising previous disease states, memory of disease patterns, profile of genetic variation etc. Significant complex behaviors of a disease system could be calibrated in a proficient manner through fractional order derivatives making the disease system more realistic than integer order model. In this study, a fractional order differential equation model is developed in micro level to gain perceptions regarding the effects of host immunological memory in dynamics of SARS-CoV-2 infection. Additionally, the possible optimal control of the infection with the help of an antiviral drug, viz. 2-DG, has been exemplified here. The fractional order optimal control would enable to employ the proper administration of the drug minimizing its systematic cost which will assist the health policy makers in generating better therapeutic measures against SARS-CoV-2 infection. Numerical simulations have advantages to visualize the dynamical effects of the immunological memory and optimal control inputs in the epidemic system.</p></div>","PeriodicalId":612,"journal":{"name":"Journal of Biological Physics","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10867-022-09617-9.pdf","citationCount":"3","resultStr":"{\"title\":\"Clinical effects of 2-DG drug restraining SARS-CoV-2 infection: A fractional order optimal control study\",\"authors\":\"Piu Samui, Jayanta Mondal, Bashir Ahmad, Amar Nath Chatterjee\",\"doi\":\"10.1007/s10867-022-09617-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Fractional calculus is very convenient tool in modeling of an emergent infectious disease system comprising previous disease states, memory of disease patterns, profile of genetic variation etc. Significant complex behaviors of a disease system could be calibrated in a proficient manner through fractional order derivatives making the disease system more realistic than integer order model. In this study, a fractional order differential equation model is developed in micro level to gain perceptions regarding the effects of host immunological memory in dynamics of SARS-CoV-2 infection. Additionally, the possible optimal control of the infection with the help of an antiviral drug, viz. 2-DG, has been exemplified here. The fractional order optimal control would enable to employ the proper administration of the drug minimizing its systematic cost which will assist the health policy makers in generating better therapeutic measures against SARS-CoV-2 infection. Numerical simulations have advantages to visualize the dynamical effects of the immunological memory and optimal control inputs in the epidemic system.</p></div>\",\"PeriodicalId\":612,\"journal\":{\"name\":\"Journal of Biological Physics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2022-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s10867-022-09617-9.pdf\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Biological Physics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10867-022-09617-9\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biological Physics","FirstCategoryId":"99","ListUrlMain":"https://link.springer.com/article/10.1007/s10867-022-09617-9","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOPHYSICS","Score":null,"Total":0}
Clinical effects of 2-DG drug restraining SARS-CoV-2 infection: A fractional order optimal control study
Fractional calculus is very convenient tool in modeling of an emergent infectious disease system comprising previous disease states, memory of disease patterns, profile of genetic variation etc. Significant complex behaviors of a disease system could be calibrated in a proficient manner through fractional order derivatives making the disease system more realistic than integer order model. In this study, a fractional order differential equation model is developed in micro level to gain perceptions regarding the effects of host immunological memory in dynamics of SARS-CoV-2 infection. Additionally, the possible optimal control of the infection with the help of an antiviral drug, viz. 2-DG, has been exemplified here. The fractional order optimal control would enable to employ the proper administration of the drug minimizing its systematic cost which will assist the health policy makers in generating better therapeutic measures against SARS-CoV-2 infection. Numerical simulations have advantages to visualize the dynamical effects of the immunological memory and optimal control inputs in the epidemic system.
期刊介绍:
Many physicists are turning their attention to domains that were not traditionally part of physics and are applying the sophisticated tools of theoretical, computational and experimental physics to investigate biological processes, systems and materials.
The Journal of Biological Physics provides a medium where this growing community of scientists can publish its results and discuss its aims and methods. It welcomes papers which use the tools of physics in an innovative way to study biological problems, as well as research aimed at providing a better understanding of the physical principles underlying biological processes.