BibTex RIS Kaynak Göster
Yıl 2018, Cilt: 67 Sayı: 1, 179 - 197, 01.02.2018
https://doi.org/10.1501/Commua1_0000000841

Öz

Kaynakça

  • Alton, J. The Ebola Survival Handbook. Skyhorse Publishing, New York, 2014.
  • Area, I., H. Batar…, J. Losada, J. J. Nieto, W. Shammakh, A. Torres. On a fractional order Ebola epidemic model, Adv. Diğ erence Equ. 2015 (2015), Art. ID 278, 12 pp.
  • Ariens, D., B. Houska, H. J. Ferreau. ACADO Toolkit User’s Manual, Toolkit for Automatic Control and Dynamic Optimization, 2010. http://www.acadotoolkit.org
  • Atangana, A., E. F. Doungmo Goufo. On the mathematical analysis of Ebola hemorrhagic fever: deathly infection disease in West African countries, BioMed Research International (2014), Art. ID 261383, 7 pp.
  • Barry, M., F. A. Traoré, F. B. Sako, D. O. Kpamy, E. I. Bah, M. Poncin, C. Keita, M. Cisse, A. Touré. Ebola outbreak in Conakry, Guinea: Epidemiological, clinical, and outcome features. Médecine et Maladies Infectieuses 44 (2014), no. 11–12, 491–494.
  • Bartlett, J, J., DeVinney, E. Pudlowski. Mathematical modeling of the 2014/2015 Ebola epidemic in West Africa, SIAM Undergraduate Research Online 9 (2016), 87–102.
  • Bock, H. G., K. J. Pitt. A multiple shooting algorithm for direct solution of optimal control problems. Proc. 9th IFAC World Congress, Budapest, Pergamon Press, 1984, 243–247.
  • Borio L., et al. [Working Group on Civilian Biodefense; Corporate Author]. Hemorrhagic fever viruses as biological weapons: medical and public health management. Journal of the American Medical Association 287 (2002), no. 18, 2391–2405.
  • Boujakjian, H. Modeling the spread of Ebola with SEIR and optimal control, SIAM Under- graduate Research Online 9 (2016), 299–310.
  • Brauer, F., P. D. V. Driessche, J. Wu. Mathematical Epidemiology. Lectures Notes in Math- ematics 1945, Mathematical Biosciences Subseries, 2008.
  • Chapnick, E. K., Ebola Myths & Facts. Wiley & Sons, 2015.
  • Diekmann, O., H. Heesterbeek, T. Britton. Mathematical tools for understanding infectious disease dynamics, Princeton Series in Theoretical and Computational Biology, Princeton Univ. Press, Princeton, NJ, 2013.
  • Diekmann, O., J. A. P. Heesterbeek, J. A. J. Metz. On the de…nition and the computation of the basic reproduction ratio R0in models for infectious diseases in heterogeneous populations. J. Math. Biol. 28 (1990), no. 4, 365–382.
  • Dowell, S. F., R. Mukunu, T. G. Ksiazek, A. S. Khan, P. E. Rollin, C. J. Peters. Transmission of Ebola hemorrhagic fever: a study of risk factors in family members, Kikwit, Democratic Republic of the Congo, 1995. Commission de Lutte contre les Epidémies à Kikwit. J. Infect. Dis. 179 (1999), Suppl. 1, S87–S91.
  • Embaixada da Repşblica Popular da China no Brasil. China terá produção em massa de vacina contra vírus Ebola, 14/Oct/2015. http://br.china-embassy.org/por/szxw/ t1305911.htm
  • Gağ, H., E. Schaefer. Optimal control applied to vaccination and treatment strategies for various epidemiological models. Math. Biosci. Eng. 6 (2009), no. 3, 469–492.
  • Heğernan, J. M., R. J. Smith, L. M. Wahl. Perspectives on the basic reproductive ratio. J. R. Soc. Interface 2 (2005), 281–293.
  • IndexMundi. http://www.indexmundi.com. Kermack, W. O., A. G. McKendrick. Contributions to the mathematical theory of epidemics– I. 1927. Bull Math Biol. 53 (1991), 33–55.
  • Kermack, W. O., A. G. McKendrick. Contributions to the mathematical theory of epidemics– II. The problem of endemicity. 1932. Bull Math Biol. 53 (1991), 57–87.
  • Kretzschmar, M. Ring Vaccination and Smallpox Control. Emerging Infectious Diseases 10 (2004), no. 5, 832–841.
  • Legrand, J., R. F. Grais, P. Y. Boelle, A. J. Valleron, A. Flahault. Understanding the dy- namics of Ebola epidemics. Epidemiol. Infect. 135 (2007), no. 4, 610–621.
  • Longini, Jr. I. M., E. Ackerman. An optimization model for in*uenza A epidemics. Mathe- matical Biosciences 38 (1978), no. 1-2, 141–157.
  • Mamo, D. K., P. R. Koya. Mathematical modeling and simulation study of SEIR disease and data …tting of Ebola epidemic spreading in West Africa, Journal of Multidisciplinary Engineering Science and Technology 2 (2015), no. 1, 106–114.
  • Peters, C. J., J. W. LeDuc. An introduction to Ebola: the virus and the disease. Journal of Infectious Diseases 179 (1999), Suppl. 1, ix–xvi.
  • Rachah, A., D. F. M. Torres. Mathematical modelling, simulation and optimal control of the Ebola outbreak in West Africa. Discrete Dyn. Nat. Soc. 2015 (2015), Art. ID 842792, pp.
  • Rachah, A., D. F. M. Torres. Optimal control strategies for the spread of Ebola in West Africa. J. Math. Anal. 7 (2016), no. 1, 102–114.
  • Rachah, A., D. F. M. Torres. Modeling, dynamics and optimal control of Ebola virus spread. Pure and Applied Functional Analysis 1 (2016), no. 2, 277–289.
  • Rachah, A., D. F. M. Torres. Dynamics and optimal control of Ebola transmission. Math. Comput. Sci. 10 (2016), no. 3, 331–342.
  • Rachah, A., D. F. M. Torres. Predicting and controlling the Ebola infection. Math. Methods Appl. Sci., in press. DOI:10.1002/mma.3841
  • Report of an International Commission. Ebola haemorrhagic fever in Zaire, 1976. Bull. World
  • Health Organ. 56 (1978), no. 2, 271–293.
  • Reuters. Two new trials of Ebola vaccines begin in Africa and Europe, http:// voicesofafrica.co.za/two-new-trials-ebola-vaccines-begin-africa-europe Rodrigues, H. S., M. T. T. Monteiro, D. F. M. Torres. Dynamics of dengue epidemics when using optimal control. Math. Comput. Modelling 52 (2010), no. 9-10, 1667–1673.
  • Rodrigues, H. S., M. T. T. Monteiro, D. F. M. Torres. Vaccination models and optimal control strategies to dengue. Math. Biosci. 247 (2014), no. 1, 1–12.
  • Smith, T. C. Ebola. Deadly Diseases and Epidemics, Chelsea House Publisher, 2006.
  • Smith, T. C. Heymann Ebola and Marburg Virus. Second Edition. Deadly diseases and epi- demics, Chelsea House Publisher, 2010.
  • Uganda Ministry of Health. An outbreak of Ebola in Uganda. Trop. Med. Int. Health. 7 (2002), no. 12, 1068–1075.
  • Wang, X.-S., L. Zhong. Ebola outbreak in West Africa: real-time estimation and multiple- wave prediction. Math. Biosci. Eng. 12 (2015), no. 5, 1055–1063.
  • WHO, World Health Organization. Report of an International Study Team. Ebola haemor- rhagic fever in Sudan 1976. Bull. World Health Organ. 56 (1978), no. 2, 247–270.
  • WHO, World Health Organization. Ebola Situation Reports. http://apps.who.int/ebola/ ebola-situation-reports WHO, World Health Organization. Ebola Data and Statistics. http://apps.who.int/gho/ data/view.ebola-sitrep.ebola-country-LBR. Current address : Amira Rachah: Department of Production Animal Clinical Sciences, Norwe- gian University of Life Sciences, PO Box 8146, NO-0033 Oslo, Norway.

ANALYSIS, SIMULATION AND OPTIMAL CONTROL OF A SEIR MODEL FOR EBOLA VIRUS WITH DEMOGRAPHIC EFFECTS

Yıl 2018, Cilt: 67 Sayı: 1, 179 - 197, 01.02.2018
https://doi.org/10.1501/Commua1_0000000841

Öz

Ebola virus is one of the most virulent pathogens for humans. Wepresent a mathematical description of diğerent Susceptible–Exposed–Infectious–Recovered (SEIR) models. By using mathematical modeling and analysis, thelatest major outbreak of Ebola virus in West Africa is described. Our aim is tostudy and discuss the properties of SEIR models with respect to Ebola virus,the information they provide, and when the models make sense. We added tothe basic SEIR model demographic eğects in order to analyze the equilibriawith vital dynamics. Numerical simulations con…rm the theoretical analysis.The control of the propagation of the virus through vaccination is investigatedand the case study of Liberia is discussed in detail

Kaynakça

  • Alton, J. The Ebola Survival Handbook. Skyhorse Publishing, New York, 2014.
  • Area, I., H. Batar…, J. Losada, J. J. Nieto, W. Shammakh, A. Torres. On a fractional order Ebola epidemic model, Adv. Diğ erence Equ. 2015 (2015), Art. ID 278, 12 pp.
  • Ariens, D., B. Houska, H. J. Ferreau. ACADO Toolkit User’s Manual, Toolkit for Automatic Control and Dynamic Optimization, 2010. http://www.acadotoolkit.org
  • Atangana, A., E. F. Doungmo Goufo. On the mathematical analysis of Ebola hemorrhagic fever: deathly infection disease in West African countries, BioMed Research International (2014), Art. ID 261383, 7 pp.
  • Barry, M., F. A. Traoré, F. B. Sako, D. O. Kpamy, E. I. Bah, M. Poncin, C. Keita, M. Cisse, A. Touré. Ebola outbreak in Conakry, Guinea: Epidemiological, clinical, and outcome features. Médecine et Maladies Infectieuses 44 (2014), no. 11–12, 491–494.
  • Bartlett, J, J., DeVinney, E. Pudlowski. Mathematical modeling of the 2014/2015 Ebola epidemic in West Africa, SIAM Undergraduate Research Online 9 (2016), 87–102.
  • Bock, H. G., K. J. Pitt. A multiple shooting algorithm for direct solution of optimal control problems. Proc. 9th IFAC World Congress, Budapest, Pergamon Press, 1984, 243–247.
  • Borio L., et al. [Working Group on Civilian Biodefense; Corporate Author]. Hemorrhagic fever viruses as biological weapons: medical and public health management. Journal of the American Medical Association 287 (2002), no. 18, 2391–2405.
  • Boujakjian, H. Modeling the spread of Ebola with SEIR and optimal control, SIAM Under- graduate Research Online 9 (2016), 299–310.
  • Brauer, F., P. D. V. Driessche, J. Wu. Mathematical Epidemiology. Lectures Notes in Math- ematics 1945, Mathematical Biosciences Subseries, 2008.
  • Chapnick, E. K., Ebola Myths & Facts. Wiley & Sons, 2015.
  • Diekmann, O., H. Heesterbeek, T. Britton. Mathematical tools for understanding infectious disease dynamics, Princeton Series in Theoretical and Computational Biology, Princeton Univ. Press, Princeton, NJ, 2013.
  • Diekmann, O., J. A. P. Heesterbeek, J. A. J. Metz. On the de…nition and the computation of the basic reproduction ratio R0in models for infectious diseases in heterogeneous populations. J. Math. Biol. 28 (1990), no. 4, 365–382.
  • Dowell, S. F., R. Mukunu, T. G. Ksiazek, A. S. Khan, P. E. Rollin, C. J. Peters. Transmission of Ebola hemorrhagic fever: a study of risk factors in family members, Kikwit, Democratic Republic of the Congo, 1995. Commission de Lutte contre les Epidémies à Kikwit. J. Infect. Dis. 179 (1999), Suppl. 1, S87–S91.
  • Embaixada da Repşblica Popular da China no Brasil. China terá produção em massa de vacina contra vírus Ebola, 14/Oct/2015. http://br.china-embassy.org/por/szxw/ t1305911.htm
  • Gağ, H., E. Schaefer. Optimal control applied to vaccination and treatment strategies for various epidemiological models. Math. Biosci. Eng. 6 (2009), no. 3, 469–492.
  • Heğernan, J. M., R. J. Smith, L. M. Wahl. Perspectives on the basic reproductive ratio. J. R. Soc. Interface 2 (2005), 281–293.
  • IndexMundi. http://www.indexmundi.com. Kermack, W. O., A. G. McKendrick. Contributions to the mathematical theory of epidemics– I. 1927. Bull Math Biol. 53 (1991), 33–55.
  • Kermack, W. O., A. G. McKendrick. Contributions to the mathematical theory of epidemics– II. The problem of endemicity. 1932. Bull Math Biol. 53 (1991), 57–87.
  • Kretzschmar, M. Ring Vaccination and Smallpox Control. Emerging Infectious Diseases 10 (2004), no. 5, 832–841.
  • Legrand, J., R. F. Grais, P. Y. Boelle, A. J. Valleron, A. Flahault. Understanding the dy- namics of Ebola epidemics. Epidemiol. Infect. 135 (2007), no. 4, 610–621.
  • Longini, Jr. I. M., E. Ackerman. An optimization model for in*uenza A epidemics. Mathe- matical Biosciences 38 (1978), no. 1-2, 141–157.
  • Mamo, D. K., P. R. Koya. Mathematical modeling and simulation study of SEIR disease and data …tting of Ebola epidemic spreading in West Africa, Journal of Multidisciplinary Engineering Science and Technology 2 (2015), no. 1, 106–114.
  • Peters, C. J., J. W. LeDuc. An introduction to Ebola: the virus and the disease. Journal of Infectious Diseases 179 (1999), Suppl. 1, ix–xvi.
  • Rachah, A., D. F. M. Torres. Mathematical modelling, simulation and optimal control of the Ebola outbreak in West Africa. Discrete Dyn. Nat. Soc. 2015 (2015), Art. ID 842792, pp.
  • Rachah, A., D. F. M. Torres. Optimal control strategies for the spread of Ebola in West Africa. J. Math. Anal. 7 (2016), no. 1, 102–114.
  • Rachah, A., D. F. M. Torres. Modeling, dynamics and optimal control of Ebola virus spread. Pure and Applied Functional Analysis 1 (2016), no. 2, 277–289.
  • Rachah, A., D. F. M. Torres. Dynamics and optimal control of Ebola transmission. Math. Comput. Sci. 10 (2016), no. 3, 331–342.
  • Rachah, A., D. F. M. Torres. Predicting and controlling the Ebola infection. Math. Methods Appl. Sci., in press. DOI:10.1002/mma.3841
  • Report of an International Commission. Ebola haemorrhagic fever in Zaire, 1976. Bull. World
  • Health Organ. 56 (1978), no. 2, 271–293.
  • Reuters. Two new trials of Ebola vaccines begin in Africa and Europe, http:// voicesofafrica.co.za/two-new-trials-ebola-vaccines-begin-africa-europe Rodrigues, H. S., M. T. T. Monteiro, D. F. M. Torres. Dynamics of dengue epidemics when using optimal control. Math. Comput. Modelling 52 (2010), no. 9-10, 1667–1673.
  • Rodrigues, H. S., M. T. T. Monteiro, D. F. M. Torres. Vaccination models and optimal control strategies to dengue. Math. Biosci. 247 (2014), no. 1, 1–12.
  • Smith, T. C. Ebola. Deadly Diseases and Epidemics, Chelsea House Publisher, 2006.
  • Smith, T. C. Heymann Ebola and Marburg Virus. Second Edition. Deadly diseases and epi- demics, Chelsea House Publisher, 2010.
  • Uganda Ministry of Health. An outbreak of Ebola in Uganda. Trop. Med. Int. Health. 7 (2002), no. 12, 1068–1075.
  • Wang, X.-S., L. Zhong. Ebola outbreak in West Africa: real-time estimation and multiple- wave prediction. Math. Biosci. Eng. 12 (2015), no. 5, 1055–1063.
  • WHO, World Health Organization. Report of an International Study Team. Ebola haemor- rhagic fever in Sudan 1976. Bull. World Health Organ. 56 (1978), no. 2, 247–270.
  • WHO, World Health Organization. Ebola Situation Reports. http://apps.who.int/ebola/ ebola-situation-reports WHO, World Health Organization. Ebola Data and Statistics. http://apps.who.int/gho/ data/view.ebola-sitrep.ebola-country-LBR. Current address : Amira Rachah: Department of Production Animal Clinical Sciences, Norwe- gian University of Life Sciences, PO Box 8146, NO-0033 Oslo, Norway.
Toplam 39 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Research Article
Yazarlar

Amira Rachah Bu kişi benim

M. Torres Delfim F. Bu kişi benim

Yayımlanma Tarihi 1 Şubat 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 67 Sayı: 1

Kaynak Göster

APA Rachah, A., & Torres Delfim F., M. (2018). ANALYSIS, SIMULATION AND OPTIMAL CONTROL OF A SEIR MODEL FOR EBOLA VIRUS WITH DEMOGRAPHIC EFFECTS. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 67(1), 179-197. https://doi.org/10.1501/Commua1_0000000841
AMA Rachah A, Torres Delfim F. M. ANALYSIS, SIMULATION AND OPTIMAL CONTROL OF A SEIR MODEL FOR EBOLA VIRUS WITH DEMOGRAPHIC EFFECTS. Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat. Şubat 2018;67(1):179-197. doi:10.1501/Commua1_0000000841
Chicago Rachah, Amira, ve M. Torres Delfim F. “ANALYSIS, SIMULATION AND OPTIMAL CONTROL OF A SEIR MODEL FOR EBOLA VIRUS WITH DEMOGRAPHIC EFFECTS”. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 67, sy. 1 (Şubat 2018): 179-97. https://doi.org/10.1501/Commua1_0000000841.
EndNote Rachah A, Torres Delfim F. M (01 Şubat 2018) ANALYSIS, SIMULATION AND OPTIMAL CONTROL OF A SEIR MODEL FOR EBOLA VIRUS WITH DEMOGRAPHIC EFFECTS. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 67 1 179–197.
IEEE A. Rachah ve M. Torres Delfim F., “ANALYSIS, SIMULATION AND OPTIMAL CONTROL OF A SEIR MODEL FOR EBOLA VIRUS WITH DEMOGRAPHIC EFFECTS”, Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat., c. 67, sy. 1, ss. 179–197, 2018, doi: 10.1501/Commua1_0000000841.
ISNAD Rachah, Amira - Torres Delfim F., M. “ANALYSIS, SIMULATION AND OPTIMAL CONTROL OF A SEIR MODEL FOR EBOLA VIRUS WITH DEMOGRAPHIC EFFECTS”. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 67/1 (Şubat 2018), 179-197. https://doi.org/10.1501/Commua1_0000000841.
JAMA Rachah A, Torres Delfim F. M. ANALYSIS, SIMULATION AND OPTIMAL CONTROL OF A SEIR MODEL FOR EBOLA VIRUS WITH DEMOGRAPHIC EFFECTS. Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat. 2018;67:179–197.
MLA Rachah, Amira ve M. Torres Delfim F. “ANALYSIS, SIMULATION AND OPTIMAL CONTROL OF A SEIR MODEL FOR EBOLA VIRUS WITH DEMOGRAPHIC EFFECTS”. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, c. 67, sy. 1, 2018, ss. 179-97, doi:10.1501/Commua1_0000000841.
Vancouver Rachah A, Torres Delfim F. M. ANALYSIS, SIMULATION AND OPTIMAL CONTROL OF A SEIR MODEL FOR EBOLA VIRUS WITH DEMOGRAPHIC EFFECTS. Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat. 2018;67(1):179-97.

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Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics.

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