MATHEMATICAL MODEL OF DENGUE HEMORRHAGIC FEVER SPREAD WITH DIFFERENT LEVELS OF TRANSMISSION RISK

  • Faishal Farrel Herdicho Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia https://orcid.org/0000-0001-8405-7853
  • Nabil Azizul Hakim Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia https://orcid.org/0009-0002-5535-0668
  • Fatmawati Fatmawati Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia https://orcid.org/0000-0002-0418-6629
  • Cicik Alfiniyah Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia https://orcid.org/0000-0002-0022-9732
  • John Olajide Akanni Department of Mathematical and Computing Sciences, Faculty of Applied Sciences, Koladaisi University, Nigeria https://orcid.org/0000-0002-1343-345X
Keywords: Dengue Hemorrhagic Fever, Genetic Algorithm, Mathematical Model, Parameter Estimation, Transmission Risk

Abstract

Dengue Haemorrhagic Fever (DHF) is a vector-borne disease caused by the dengue virus, transmitted to humans through the bite of an infected female Aedes aegypti mosquito. DHF is prevalent in tropical regions, necessitating mathematical modeling to better understand its dynamics and predict its spread. This study develops and analyzes a mathematical model for DHF transmission that incorporates seven compartments to reflect different transmission risk levels. Stability analysis of the disease-free and endemic equilibria was conducted, with the basic reproduction number  used to classify the conditions under which DHF transmission is controlled  or endemic . Key model parameters were estimated using DHF case data from East Java in 2018, employing a genetic algorithm (GA) to optimize the estimation process. The GA approach achieved a mean absolute percentage error (MAPE) of , ensuring high accuracy in parameter values. Furthermore, the basic reproduction number was determined to be , which is greater than one, confirming that DHF remains endemic in East Java. Sensitivity analysis identified the mosquito biting rate , mosquito mortality rate , and transmission rates  as the most critical factors influencing . Numerical simulations demonstrated the effects of these key parameters on both  and the symptomatic human population . An increase in , , or  significantly amplified  and , while a rise in  had the opposite effect, reducing both transmission and infections. These results underscore the critical role of vector control strategies, such as increasing mosquito mortality and reducing breeding sites, in mitigating DHF outbreaks. This study highlights the utility of combining mathematical modeling with genetic algorithm-based parameter estimation to provide accurate insights into disease dynamics and inform effective control measures.

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References

World Health Organization, “DENGUE GUIDELINES, FOR DIAGNOSIS, TREATMENT, PREVENTION AND CONTROL.” Accessed: Sep. 19, 2020. [Online]. Available: https://www.who.int/publications/i/item/9789241547871

D. J. Gubler, “DENGUE AND DENGUE HEMORRHAGIC FEVER,” Clin. Microbiol. Rev., vol. 11, no. 3, pp. 480–496, 1998, https://doi.org/10.1016/B978-0-443-06668-9.50077-6.

A. Wilder-Smith, E. E. Ooi, S. G. Vasudevan, and D. J. Gubler, “UPDATE ON DENGUE: EPIDEMIOLOGY, VIRUS EVOLUTION, ANTIVIRAL DRUGS, AND VACCINE DEVELOPMENT,” Curr. Infect. Dis. Rep., vol. 12, no. 3, pp. 157–164, 2010, https://doi.org/10.1007/s11908-010-0102-7.

World Health Organization, “GLOBAL STRATEGY FOR DENGUE PREVENTION AND CONTROL, 2012–2020.” Accessed: Sep. 19, 2020. [Online]. Available: https://www.who.int/publications/i/item/9789241504034

Health Department of East Java Province Indonesia, “PROFIL KESEHATAN PROVINSI JAWA TIMUR TAHUN 2018,” DINAS KESEHATAN PROVINSI JAWA TIMUR. Accessed: Sep. 19, 2020. [Online]. Available: https://dinkes.jatimprov.go.id/index.php?r=site/file_list&id_file=10&id_berita=8

Ministry of Health of the Republic Indonesia, “PROFIL KESEHATAN INDONESIA TAHUN 2017.” Accessed: Sep. 19, 2020. [Online]. Available: https://www.kemkes.go.id/id/profil-kesehatan-indonesia-2017

E. Bonyah, M. L. Juga, C. W. Chukwu, and Fatmawati, “A FRACTIONAL ORDER DENGUE FEVER MODEL IN THE CONTEXT OF PROTECTED TRAVELERS,” Alexandria Eng. J., vol. 61, no. 1, pp. 927–936, 2022, https://doi.org/10.1016/j.aej.2021.04.070.

D. Handayani, A. U. Gunadi, and R. N. Rachmawati, “MATHEMATICAL MODEL OF REPELLENT EFFECT IN DENGUE TRANSMISSION,” BAREKENG J. Math. Its Appl., vol. 18, no. 2, pp. 1037–1052, May 2024, https://doi.org/10.30598/barekengvol18iss2pp1037-1052.

T. P. Blante, J. Jaharuddin, and E. H. Nugrahani, “SENSITIVITY ANALYSIS OF SI1I2RS MODEL FOR DENGUE FEVER TRANSMISSION,” Jambura J. Biomath., vol. 5, no. 1, pp. 19–26, 2024, https://doi.org/10.37905/jjbm.v5i1.23132.

A. Abidemi, Fatmawati, and O. J. Peter, “AN OPTIMAL CONTROL MODEL FOR DENGUE DYNAMICS WITH ASYMPTOMATIC, ISOLATION, AND VIGILANT COMPARTMENTS,” Decis. Anal. J., vol. 10, no. June 2023, p. 100413, 2024, https://doi.org/10.1016/j.dajour.2024.100413.

F. B. Agusto and M. A. Khan, “OPTIMAL CONTROL STRATEGIES FOR DENGUE TRANSMISSION IN PAKISTAN,” Math. Biosci., vol. 305, no. July, pp. 102–121, 2018, https://doi.org/10.1016/j.mbs.2018.09.007.

R. Jan, M. A. Khan, P. Kumam, and P. Thounthong, “MODELING THE TRANSMISSION OF DENGUE INFECTION THROUGH FRACTIONAL DERIVATIVES,” Chaos, Solitons and Fractals, vol. 127, pp. 189–216, 2019, https://doi.org/10.1016/j.chaos.2019.07.002.

I. Ghosh, P. K. Tiwari, and J. Chattopadhyay, “EFFECT OF ACTIVE CASE FINDING ON DENGUE CONTROL: IMPLICATIONS FROM A MATHEMATICAL MODEL,” J. Theor. Biol., vol. 464, pp. 50–62, 2019, https://doi.org/10.1016/j.jtbi.2018.12.027.

N. Anggriani, H. Tasman, M. Z. Ndii, A. K. Supriatna, E. Soewono, and E. Siregar, “THE EFFECT OF REINFECTION WITH THE SAME SEROTYPE ON DENGUE TRANSMISSION DYNAMICS,” Appl. Math. Comput., vol. 349, pp. 62–80, 2019, https://doi.org/10.1016/j.amc.2018.12.022.

H. Zhang and R. Lui, “RELEASING WOLBACHIA-INFECTED AEDES AEGYPTI TO PREVENT THE SPREAD OF DENGUE VIRUS: A MATHEMATICAL STUDY,” Infect. Dis. Model., vol. 5, pp. 142–160, 2020, https://doi.org/10.1016/j.idm.2019.12.004.

N. Aldawoodi, “AN APPROACH TO DESIGNING AN UNMANNED HELICOPTER AUTOPILOT USING GENETIC ALGORITHMS AND SIMULATED ANNEALING,” University of South Florida, 2008. [Online]. Available: https://www.proquest.com/openview/416ccc976083ba5055b263f0787304e9/1?pq-origsite=gscholar&cbl=18750

Central Bureau of Statistics East Java Province Indonesia, “ANGKA HARAPAN HIDUP (TAHUN), 2017-2019.” Accessed: Sep. 19, 2020. [Online]. Available: https://jatim.bps.go.id/id/statistics-table/2/MjkjMg==/angka-harapan-hidup.html

Central Bureau of Statistics East Java Province Indonesia, “JUMLAH PENDUDUK MENURUT JENIS KELAMIN DAN KABUPATEN/KOTA PROVINSI JAWA TIMUR (JIWA), 2016-2018.” [Online]. Available: https://jatim.bps.go.id/id/statistics-table/2/Mzc1IzI=/jumlah-penduduk-menurut-jenis-kelamin-dan-kabupaten-kota-provinsi-jawa-timur.html

P. Van Den Driessche and J. Watmough, “REPRODUCTION NUMBERS AND SUB-THRESHOLD ENDEMIC EQUILIBRIA FOR COMPARTMENTAL MODELS OF DISEASE TRANSMISSION,” Math. Biosci., vol. 180, no. 1–2, pp. 29–48, 2002, https://doi.org/10.1016/S0025-5564(02)00108-6.

J. P. LaSalle, THE STABILITY OF DYNAMICAL SYSTEMS. Philadelphia: Society for Industrial and Applied Mathematics, 1976.

N. Chitnis, J. M. Hyman, and J. M. Cushing, “DETERMINING IMPORTANT PARAMETERS IN THE SPREAD OF MALARIA THROUGH THE SENSITIVITY ANALYSIS OF A MATHEMATICAL MODEL,” Bull. Math. Biol., vol. 70, no. 5, pp. 1272–1296, 2008, https://doi.org/10.1007/s11538-008-9299-0.

Published
2025-07-01
How to Cite
[1]
F. F. Herdicho, N. A. Hakim, F. Fatmawati, C. Alfiniyah, and J. O. Akanni, “MATHEMATICAL MODEL OF DENGUE HEMORRHAGIC FEVER SPREAD WITH DIFFERENT LEVELS OF TRANSMISSION RISK”, BAREKENG: J. Math. & App., vol. 19, no. 3, pp. 1649-1666, Jul. 2025.