Global dynamics and optimal control in a brucellosis transmission model with distributed incubation delays

Xiaodong Wang , Lei Wang , Kai Wang , Zhidong Teng

Electronic Research Archive ›› 2026, Vol. 34 ›› Issue (12) : 8850 -8895.

PDF (9897KB)
Electronic Research Archive ›› 2026, Vol. 34 ›› Issue (12) :8850 -8895. DOI: 10.3934/era.2026373
Research article
research-article
Global dynamics and optimal control in a brucellosis transmission model with distributed incubation delays
Author information +
History +
PDF (9897KB)

Abstract

In this paper, the global dynamics and optimal control strategies in a brucellosis transmission model with distribution incubation delays were investigated. The basic reproduction number of the model was first calculated, and then the threshold criteria for the global asymptotic stability of disease-free and endemic equilibria were established. Furthermore, the several effective measures for controlling the spread of diseases are introduced, and then an optimal control model that incorporates these measures was proposed. By providing a reasonable objective function, some optimal control strategies were established. Through numerical simulation of these optimal control strategies, reasonable prevention, control, and treatment measures for brucellosis were proposed.

Keywords

brucellosis model / global dynamics / optimal control strategy / distribution delay / latency

Cite this article

Download citation ▾
Xiaodong Wang, Lei Wang, Kai Wang, Zhidong Teng. Global dynamics and optimal control in a brucellosis transmission model with distributed incubation delays. Electronic Research Archive, 2026, 34 (12) : 8850-8895 DOI:10.3934/era.2026373

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

J. Ariza, M. Bosilkovski, A. Cascio, J. D. Colmenero, M. J. Corbel, M. E. Falagas, et al., Prospectives for the treatment of brucellosis in the 21st century: The Ioannina recommendations, PLoS Med., 4 (2007), e317. https://doi.org/10.1371/journal.pmed.0040317

[2]

M. Corbel, Brucellosis in Humans and Animals: FAO, OIE, WHO. 2006.

[3]

F. Roth, J. Zinsstag, D. Orkhon, G. Chimed-Ochir, G. HuttonI, O. Cosivi, Human health benefits from livestock vaccination for brucellosis: Case study, Bull. World Health Organ., 81 (2003), 867-876.

[4]

G. Pappas, N. Akritidis, M. Bosilkovski, E. Tsianos, Brucellosis, N. Engl. J. Med., 352 (2005) 2325-2336. https://doi.org/10.1056/NEJMra050570

[5]

X. Ma, G. Sun, Global dynamics of a periodic brucellosis model with time delay and environmental factors, Appl. Math. Modell., 130 (2024), 288-309. https://doi.org/10.1016/j.apm.2024.03.002

[6]

Q. Hou, H. Qin, Global dynamics of a multi-stage brucellosis model with distributed delays and indirect transmission, Math. Biosci. Eng., 16 (2019), 3111-3129.

[7]

Q. Hou, X. Sun, J. Zhang, Y. Liu, Y. Wang, Zhen Jin, Modeling the transmission dynamics of sheep brucellosis in Inner Mongolia Autonomous Region, China, Math. Biosci., 242 (2013), 51-58. https://doi.org/10.1016/j.mbs.2012.11.012

[8]

M. Li, G. Sun, W. Zhang, Z. Jin, Model-based evaluation of strategies to control brucellosis in China, Int. J. Environ. Res. Public Health, 14 (2017), 295. https://doi.org/10.3390/ijerph14030295

[9]

M. Li, X. Pei, J. Zhang, L. Li, Asymptotic analysis of endemic equilibrium to a brucellosis model, Math. Biosci. Eng., 16 (2019), 5836-5850. https://doi.org/10.3934/mbe.2019291

[10]

P. O. Lolika, S. Mushayabasa, C. P. Bhunu, C. Modnak, J. Wang, Modeling and analyzing the effects of seasonality on brucellosis infection, Chaos Solitons Fractals, 104 (2017), 338-349. https://doi.org/10.1016/j.chaos.2017.08.027

[11]

J. Yang, R. Xu, H. Sun, Dynamics of a seasonal brucellosis disease model with nonlocal transmission and spatial diffusion, Commun. Nonlinear Sci. Numer. Simul., 94 (2021), 105551. https://doi.org/10.1016/j.cnsns.2020.105551

[12]

Z. Zhang, J. Zhang, L. Li, Z. Guo, Z. Zhang, G Sun, Quantifying the effectiveness of brucellosis control strategies in northern China using a mechanistic and data-driven model, Chaos Solitons Fractals, 185 (2024), 115121. https://doi.org/10.1016/j.chaos.2024.115121

[13]

X. Wang, K. Wang, L. Wang, Z. Teng, Dynamics of a stochastic brucellosis model with vaccination and environmental pollution transmission, Qual. Theory Dyn. Syst., 23 (2024), 299. https://doi.org/10.1007/s12346-024-01158-x

[14]

G. J. Kang, L. Gunaseelan, K. M. Abbas, Epidemiological modeling of bovine brucellosis in India, in 2014 IEEE International Conference on Big Data, IEEE, (2014), 6-10. https://doi.org/10.7490/f1000research.1111710.1

[15]

J. Nie, G. Sun, X. Sun, J. Zhang, N. Wang, Y. Wang, et al., Modeling the transmission dynamics of dairy cattle brucellosis in Jilin province, China, J. Biol. Syst., 22 (2014), 533-554. https://doi.org/10.1142/S021833901450020X

[16]

J. Zhang, Z. Jin, L. Li, X. Sun, Cost assessment of control measure for brucellosis in Jilin province, China, Chaos Solitons Fractals, 104 (2017), 798-805. https://doi.org/10.1016/j.chaos.2017.09.004

[17]

Z. Liu, H. Wang, M. Wang, Z. Li, Investigation of the molecular epizootiological characteristics and tracking of the geographical origins of brucella canis strains in China, Transbound. Emerg. Dis., 67 (2020), 834-843. https://doi.org/10.1111/tbed.13404

[18]

D. Wu, W. Zhang, Y. Ma, Y. Zheng, H. Li, G. Hu, Investigation on risk factors of brucellosis outbreak caused by occupational exposure in a dairy farm (in Chinese), Dis. Surveill., 34 (2019), 473-476. https://doi.org/10.3784/j.issn.1003-9961.2019.05.022

[19]

Z. Bian, L. Zhu, Y. Feng, S. Sun, Y. Qin, J. Ding, Epidemiological trend and characteristics of brucellosis in aborted dairy herds in China from 2013 to 2017 (in Chinese), Microbiol. China, 46 (2019), 618-623. https://doi.org/10.13344/j.microbiol.china.180390

[20]

F. F. Tuon, R. B. Gondolfo, N. Cerchiari, Human-to-human transmission of Brucella a systematic review, Trop. Med. Int. Health, 22 (2017), 539-546. https://doi.org/10.1111/tmi.12856

[21]

H. Wu, W. Chen, N. Wang, L. Zhang, H. Li, Z. Teng, A delayed stage-structure brucellosis model with interaction among seasonality, time-varying incubation and density-dependent growth, Inter. J. Biomath., 16 (2023), 2250114. https://doi.org/10.1142/s1793524522501145

[22]

Q. Hou, F. Zhang, Global dynamics of a general brucellosis model with discrete delay, J. Appl. Anal. Comput., 6 (2016), 227-241. https://www.jaac-online.com/article/doi/10.11948/2016019

[23]

M. Wu, X. Abdurahman, Z. Teng, Optimal control strategy analysis for an human- animal brucellosis infection model with multiple delays, Heliyon, 8 (2022), e12274. https://doi.org/10.1016/j.heliyon.2022.e12274

[24]

Q. Hou, L. Zhang, M. Liu, Mathematical analysis of a time-delayed model on brucellosis transmission with disease testing information, Inter. J. Biomath., 13 (2020), 2050039. https://doi.org/10.1142/s1793524520500394

[25]

A. Ma, J. Hu, X. Li, X. Xu, Q. Zhang, Hopf bifurcation and optimal control of a delayed reaction-diffusion brucellosis disease model, Int. J. Biomath., 19 (2024), 2450060. https://doi.org/10.1142/s1793524524500608

[26]

X. He, T. Lv, J. Liu, L. Zhou, M. Fan, Dynamical modeling and optimal control of brucellosis with mixed delays and environmental transmission, Int. J. Biomath., 14 (2025), 2550136. https://doi.org/10.1142/s1793524525501360

[27]

J. Lai, X. Zou, Modeling HIV-1 virus dynamics with both virus-to-cell infection and cell-to-cell transmission, SIAM J. Appl. Math. 74 (2014), 898-917. https://doi.org/10.1137/130930145

[28]

Y. Hinon, S. Murakami, T. Naito, Functional Differential Equations with Infinite Delay , Lecture Notes in Mathematics 1473, Springer-Verlag, Berlin Heidelberg, 1991. https://doi.org/10.1007/bfb0084432

[29]

X. Q. Zhao, The linear stability and basic reproduction number for autonomous FDEs, Disc. Cont. Dyn. Sys. S, 17 (2024), 708-719. https://doi.org/10.3934/dcdss.2023082

[30]

J. P. LaSalle, The Stability of Dynamical Systems , Regional Conference Series in Applied Mathematics, SIAM, Philadelphia, 1976. https://doi.org/10.1137/1.9781611970432

[31]

S. Lenhart, J. T. Workman, Optimal Control Applied to Biological Models , Chapman and Hall/CRC, 2007. https://doi.org/10.1201/9781420011418

[32]

J. Danane, A. Meskaf, K. Allali, Optimal control of a delayed hepatitis B viral infection model with HBV DNA-containing capsids and CTL immune response, Optim. Control Appl. Methods, 39 (2018), 1262-1272. https://doi.org/10.1002/oca.2407

[33]

S. Nababan, A Filippov-type lemma for functions involving delays and its application to time-delayed optimal control problems, J. Optim. Theory Appl., 27 (1979), 357-376. https://doi.org/10.1007/BF00933030

[34]

L. Gollmann, D. Kern, H. Maurer, Optimal control problems with delays in state and control variables subject to mixed control-state constraints, Optim. Control Appl. Methods, 30 (2009), 341-365. https://doi.org/10.1002/oca.843

[35]

E. B. M. Bashier, K. C. Patidar, Optimal control of an epidemiological model with multiple time delays, Appl. Math. Comput., 292 (2017), 47-56. https://doi.org/10.1016/j.amc.2016.07.009

[36]

H. Muhtar, H. He, X. Tai, X. Chen, S. Tong, Z. Wang, Analysis of surveillance data and epidemic situation of human brucellosis in Xinjiang, 2013 (in Chinese), Chin. J. Vect. Biol. Control, 26 (2015), 86-88. https://doi.org/10.11853/j.issn.1003.4692.2015.01.024

[37]

P. Lou, L. Wang, X. Zhang, J. Xu, K. Wang, Modelling seasonal Brucellosis epidemics in Bayingolin Mongol Autonomous Prefecture of Xinjiang, China, 2010-2014, Bio. Med Res. Inter., 2016 (2016), 5103718. https://doi.org/10.1155/2016/5103718

[38]

C. Sun, H. Ma, S. Yin, Brucellosis (in Chinese), Ningxia Peoples Press, 1985.

PDF (9897KB)

0

Accesses

0

Citation

Detail

Sections
Recommended

/

〈 〉