[1]
|
K. R. Philipsen, Nonlinear Stochastic Modelling of Antimicrobial resistance in Bacterial Populations, PhD thesis, Technical University of Denmark (DTU), 2010.
|
[2]
|
I. Nåsell, Stochastic models of some endemic infections, Math. Biosci., 179 (2002), 1-19.
|
[3]
|
J. P. Romero-Leiton, E. Ibargüen-Mondragón, L. Esteva, Un modelo matemático sobre bacterias sensibles y resistentes a antibióticos, Matemáticas: Enseñanza Universitaria, 19 (2011), 55-73.
|
[4]
|
J. P. Romero-Leiton, E. Ibargüen-Mondragón, Sobre la resistencia bacteriana hacia antibióticos de acción bactericida y bacteriostática, Revista Integración, 32 (2014), 101-116.
|
[5]
|
E. Ibargüen-Mondragón, S. Mosquera, M. Cerón, E. M. Burbano-Rosero, S. P. Hidalgo-Bonilla, L. Esteva, J. P. Romero-Leiton, Mathematical modeling on bacterial resistance to multiple antibiotics caused by spontaneous mutations, Biosystems, 117 (2014), 60-67.
|
[6]
|
E. Ibargüen-Mondragón, J. P. Romero-Leiton, L. Esteva, E. Burbano, Mathematical modeling of bacterial resistance to antibiotics by mutations and plasmids, J. Biol. Systems, 24 (2016), 129-146.
|
[7]
|
R. A. Weinstein, M. J. Bonten, D. J. Austin, M. Lipsitch, Understanding the spread of antibiotic resistant pathogens in hospitals: mathematical models as tools for control, Clin. Infect. Dis., 33 (2001), 1739-1746.
|
[8]
|
J. Alavez-Ramirez, J. R. A. Castellanos, L. Esteva, J. A. Flores, J. L. Fuentes-Allen, G. GarcíaRamos, G. Gómez, J. López-Estrada, Within-host population dynamics of antibiotic-resistant M. tuberculosis, Math. Med. Biol., 24 (2007), 35-56.
|
[9]
|
D. Austin, R. Anderson, Studies of antibiotic resistance within the patient, hospitals and the community using simple mathematical models, Philos. Trans. R. Soc. Lond. B. Biol. Sci., 354 (1999), 721-738.
|
[10]
|
E. M. D'Agata, P. Magal, D. Olivier, S. Ruan, G. F. Webb, Modeling antibiotic resistance in hospitals: the impact of minimizing treatment duration, J. Theor. Biol., 249 (2007), 487-499.
|
[11]
|
S. Bonhoeffer, M. Lipsitch, B. R. Levin, Evaluating treatment protocols to prevent antibiotic resistance, Proc. Natl. Acad. Sci. USA, 94 (1997), 12106-12111.
|
[12]
|
M. Bootsma, M. van der Horst, T. Guryeva, B. Ter Kuile, O. Diekmann, Modeling non-inherited antibiotic resistance, Bull. Math. Biol., 74 (2012), 1691-1705.
|
[13]
|
E. Massad, M. N. Burattini, F. A. B. Coutinho, An optimization model for antibiotic use, Appl. Math. Comput., 201 (2008), 161-167.
|
[14]
|
F. Hellweger, X. Ruan, S. Sanchez, A simple model of tetracycline antibiotic resistance in the aquatic environment (with application to the Poudre river), Int. J. Environ. Res. Public Health, 8 (2011), 480-497.
|
[15]
|
T. Saha, M. Bandyopadhyay, Dynamical analysis of a delayed ratio-dependent prey-predator model within fluctuating environment, Appl. Math. Comput., 196 (2008), 458-478.
|
[16]
|
S. B. Mortensen, S. Klim, B. Dammann, N. R. Kristensen, H. Madsen, R. V. Overgaard, A Matlab framework for estimation of NLME models using stochastic differential equations, J. Pharmacokinet. Pharmacodyn., 34 (2007), 623-642.
|
[17]
|
S. Klim, S. B. Mortensen, N. R. Kristensen, R. V. Overgaard, H. Madsen, Population stochastic modelling (PSM)-an R package for mixed-effects models based on stochastic differential equations, Comput. Methods Programs Biomed., 94 (2009), 279-289.
|
[18]
|
M. W. Pedersen, D. Righton, U. H. Thygesen, K. H. Andersen, H. Madsen, Geolocation of north sea cod (gadus morhua) using hidden markov models and behavioural switching, Can. J. Fish. Aquat. Sci., 65 (2008), 2367-2377.
|
[19]
|
J. L. Jacobsen, H. Madsen, P. Harremoës, A stochastic model for two-station hydraulics exhibiting transient impact, Water Sci. Technol., 36 (1997), 19-26.
|
[20]
|
H. Jonsdottir, H. Madsen, O. P. Palsson, Parameter estimation in stochastic rainfall-runoff models, J. Hydrol., 326 (2006), 379-393.
|
[21]
|
J. U.-M. Nielsen, Price-quality competition in the exports of the central and eastern european countries, Intereconomics, 35 (2000), 94-101.
|
[22]
|
S. U. Acikgoz, U. M. Diwekar, Blood glucose regulation with stochastic optimal control for insulin-dependent diabetic patients, Chem. Eng. Sci., 65 (2010), 1227-1236.
|
[23]
|
P. Grandits, R. M. Kovacevic, V. M. Veliov, Optimal control and the value of information for a stochastic epidemiological SIS-model, J. Math. Anal. Appl., 476 (2019), 665 - 695.
|
[24]
|
P. J. Witbooi, G. E. Muller, G. J. Van Schalkwyk, Vaccination control in a stochastic SVIR epidemic model, Comput. Math. Methods Med., 2015.
|
[25]
|
R. Aboulaich, A. Darouichi, I. Elmouki, A. Jraifi, A stochastic optimal control model for BCG immunotherapy in superficial bladder cancer, Math. Model. Nat. Phenom., 12 (2017), 99-119.
|
[26]
|
J. H. Brown, J. F. Gillooly, A. P. Allen, V. M. Savage, G. B. West, Toward a metabolic theory of ecology, Ecology, 85 (2004), 1771-1789.
|
[27]
|
A. Lahrouz, L. Omari, D. Kiouach, Global analysis of a deterministic and stochastic nonlinear SIRS epidemic model.
|
[28]
|
Y. Zhao, D. Jiang, X. Mao, A. Gray, The threshold of a stochastic SIRS epidemic model in a population with varying size, Discrete Contin. Dyn. Syst. Ser. B, 20 (2015). 1277-1295,
|
[29]
|
X. Mao, Stochastic differential equations and applications, Elsevier, 2007.
|
[30]
|
N. Chehrazi, L. Cipriano, E. Enns, Dynamics of drug resistance: Optimal control of an infectious disease, Available at SSRN, URL http://dx.doi.org/10.2139/ssrn.2927549.
|
[31]
|
N. I. Stilianakis, A. S. Perelson, F. G. Hayden, Emergence of drug resistance during an influenza epidemic: insights from a mathematical model, J. Infect. Dis., 177 (1998), 863-873.
|
[32]
|
K. Leung, M. Lipsitch, K. Y. Yuen, J. T. Wu, Monitoring the fitness of antiviral-resistant influenza strains during an epidemic: A mathematical modelling study, Lancet Infect. Dis., 17 (2017), 339- 347.
|
[33]
|
B. Petrie, R. Barden, B. Kasprzyk-Hordern, A review on emerging contaminants in wastewaters and the environment: Current knowledge, understudied areas and recommendations for future monitoring, Water Res., 72 (2015), 3-27.
|
[34]
|
A. Permatasari, R. Tjahjana, T. Udjiani, Existence and characterization of optimal control in mathematics model of diabetics population, in J. Phys. Conf. Ser., vol. 983, 2018, 1-6.
|
[35]
|
L. S. Pontryagin, V. G. Boltyanskii, R. V. Gamkrelidze, E. F. Mishchenko, The Mathematical Theory of Optimal Processes., New York and London: Interscience Publisher, 1962.
|
[36]
|
S. Lenhart, J. T. Workman, Optimal control applied to biological models, CRC Press, 2007.
|
[37]
|
J. P. Romero-Leiton, E. Ibargüen-Mondragón, Stability analysis and optimal control intervention strategies of a malaria mathematical model, Appl. Sci., 21 (2019), 184-217.
|
[38]
|
J. Yong, X. Y. Zhou, Stochastic controls: Hamiltonian systems and HJB equations, vol. 43, Springer Science & Business Media, 1999.
|
[39]
|
J. Ma, P. Protter, J. Yong, Solving forward-backward stochastic differential equations explicitly-a four step scheme, Probab. Theory Related Fields, 98 (1994), 339-359.
|
[40]
|
G. Milstein, M. V. Tretyakov, Numerical algorithms for forward-backward stochastic differential equations, SIAM J. Sci. Comput., 28 (2006), 561-582.
|