دانشگاه تبریز
فهرست نشریات دارای اعتبار وزارت علوم، تحقیقات و فناوری
پایگاه استنادی علوم جهان اسلام (ISC)

 آمار

تعداد نشریات45
تعداد شماره‌ها1,405
تعداد مقالات17,234
تعداد مشاهده مقاله55,661,567
تعداد دریافت فایل اصل مقاله17,853,167
Peter, Olumuyiwa James, Babasola, Oluwatosin, Ojo, Mayowa, Omame, Andrew. (1404). Modelling the transmission of Mpox with a case study in Nigeria and the Democratic Republic of the Congo (DRC). سامانه مدیریت نشریات علمی, 13(3), 995-1011. doi: 10.22034/cmde.2024.62086.2711
Olumuyiwa James Peter; Oluwatosin Babasola; Mayowa M. Ojo; Andrew Omame. "Modelling the transmission of Mpox with a case study in Nigeria and the Democratic Republic of the Congo (DRC)". سامانه مدیریت نشریات علمی, 13, 3, 1404, 995-1011. doi: 10.22034/cmde.2024.62086.2711
Peter, Olumuyiwa James, Babasola, Oluwatosin, Ojo, Mayowa, Omame, Andrew. (1404). 'Modelling the transmission of Mpox with a case study in Nigeria and the Democratic Republic of the Congo (DRC)', سامانه مدیریت نشریات علمی, 13(3), pp. 995-1011. doi: 10.22034/cmde.2024.62086.2711
Peter, Olumuyiwa James, Babasola, Oluwatosin, Ojo, Mayowa, Omame, Andrew. Modelling the transmission of Mpox with a case study in Nigeria and the Democratic Republic of the Congo (DRC). سامانه مدیریت نشریات علمی, 1404; 13(3): 995-1011. doi: 10.22034/cmde.2024.62086.2711

Modelling the transmission of Mpox with a case study in Nigeria and the Democratic Republic of the Congo (DRC)

Computational Methods for Differential Equations
مقاله 19، دوره 13، شماره 3، مهر 2025، صفحه 995-1011    اصل مقاله (576.33 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22034/cmde.2024.62086.2711
نویسندگان
Olumuyiwa James Peter* 1؛ Oluwatosin Babasola2؛ Mayowa M. Ojo3؛ Andrew Omame4
1Department of Mathematical and Computer Sciences, University of Medical Sciences, Ondo City, Ondo State, Nigeria.
2Center for Ecology of Infectious Diseases, Department of Infectious Diseases, University of Georgia, Athens, Georgia, United States of America.
3Department of Mathematical Sciences, University of South Africa, South Africa.
4Department of Mathematics, Federal University of Technology Owerri, Nigeria.
چکیده
This paper focuses on the dynamics of Mpox, a viral disease, in Nigeria and the Democratic Republic of Congo (DRC) by employing mathematical modeling and parameter estimation techniques. Utilizing optimization methods, the model parameters were calibrated to match the observed Mpox cases and deaths. The basic reproduction number (R0) was calculated for each region, indicating the disease’s transmission potential, and a sensitivity analysis was conducted to identify key parameters influencing disease outcomes. Subsequently, numerical simulations were performed to assess the impact of intervention scenarios on Mpox cases and deaths. The primary goal is to create mathematical methods that can evaluate the risk of Mpox transmission and implement control measures in Nigeria and the DRC, potentially extending the findings to other countries. Results show that reducing parameters related to transmission and progression significantly decreases disease burden, highlighting the importance of preventive measures. These findings provide valuable insights for policymakers and public health officials in designing effective strategies to mitigate Mpox’s impact on human populations.
کلیدواژه‌ها
Non-linear mathematical Mpox model؛ Control measure؛ Effective reproduction number؛ Sensitivity analysis؛ Case and death averted؛ Immunization
مراجع
  • [1] Africa Centres for Disease Control and Prevention (Africa CDC), 2022–2023 Mpox outbreak, https://en. wikipedia.org/wiki/2022.
  • [2] A. Aldurayhim, A. Elsonbaty, W. Adel, and A. El-Mesady, Mathematical modeling and analysis of a novel monkeypox virus spread integrating imperfect vaccination and nonlinear incidence rates, Ain Shams Engineering Journal, 15(3) (2024), 102451.
  • [3] N. Akinwande, F. Oguntolu, and N. Lasisi, Development and exploration of a mathematical model for transmission of monkeypox disease in humans, Mathematical Models in Engineering, 6(1) (2020), 23–33.
  • [4] A. Augustine, O. I. Marcus, and T. Jonathan, A co-infection model for monkeypox and HIV/AIDS: Sensitivity and bifurcation analyses, Journal of Scientific Research and Reports, 30(5) (2024), 351–368.
  • [5] O. Babasola, E. O. Omondi, K. Oshinubi, and N. M. Imbusi, Stochastic delay differential equations: a comprehensive approach for understanding biosystems with application to disease modelling, Applied-Math, 3(4) (2023), 702–721.
  • [6] B. Bolaji, O. A. Godwin, and O. O. Peace, A compartmental deterministic epidemiological model with non-linear differential equations for analyzing the co-infection dynamics between COVID-19, HIV, and monkeypox diseases, Healthcare Analytics, (2024), 100311.
  • [7] C. P. Bhunu, J. Hyman, and S. Mushayabasa, Modelling HIV/AIDS and monkeypox co-infection, Applied Mathematics and Computation, 218(18) (2012), 9504–9518.
  • [8] X. Cai, T. Zhou, W. Shi, Y. Cai, and J. Zhou, Monkeypox virus crosstalk with HIV: An integrated skin transcriptome and machine learning study, ACS Omega, 8(49) (2023), 47283–47294.
  • [9] M. Cavallaro, S. P. Brand, F. Cumming, C. Turner, J. Hilton, I. Florence, L. M. Guzman-Rincon, P. Blomquist, D. J. Nokes, and T. House, The role of vaccination and public awareness in forecasts of mpox incidence in the United Kingdom, Nature Communications, 14(1) (2023), 4100.
  • [10] P. A. Clay, E. D. Pollock, E. M. Saldarriaga, P. Pathela, M. Macaraig, J. R. Zucker, B. Crouch, I. Kracalik, S. O. Aral, and I. H. Spicknall, Modeling the impact of prioritizing first or second vaccine doses during the 2022 mpox outbreak, medRxiv, (2023), 2023–10.
  • [11] C. E. Copen, E. D. Pollock, J. M. Asher, K. P. Delaney, P. A. Clay, D. C. Payne, E. M. Saldarriaga, P. Pathela, B. Crouch, and I. H. Spicknall, Modeling the impact of prioritizing first or second vaccine doses during the 2022 mpox outbreak, medRxiv, (2023), 2023–10.
  • [12] P. A. Clay, J. M. Asher, N. Carnes, C. E. Copen, K. P. Delaney, D. C. Payne, E. D. Pollock, J. Mermin, Y. Nakazawa, W. Still, et al., Modelling the impact of vaccination and sexual behaviour adaptations on mpox cases in the USA during the 2022 outbreak, Sexually Transmitted Infections, 100(2) (2024), 70–76.
  • [13] P. L. Delamater, E. J. Street, T. F. Leslie, Y. T. Yang, and K. H. Jacobsen, Complexity of the basic reproduction number (R0), Emerging Infectious Diseases, 25(1) (2019), 1.
  • [14] O. Diekmann, J. A. P. Heesterbeek, and J. A. Metz, On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations, Journal of Mathematical Biology, 28 (1990), 365–382.
  • [15] O. Diekmann, J. Heesterbeek, and M. G. Roberts, The construction of next-generation matrices for compartmental epidemic models, Journal of the Royal Society Interface, 7(47) (2010), 873–885.
  • [16] K. N. Durski, A. Khalakdina, M. G. Reynolds, I. K. Damon, S. Briand, Y. Nakazawa, M. H. Djingarey, V. Olson, and A. M. McCollum, Emergence of monkeypox—west and central africa, 1970–2017, Morbidity and Mortality Weekly Report, 67(10) (2018), 306.
  • [17] A. El-Mesady, W. Adel, A. Elsadany, and A. Elsonbaty, Stability analysis and optimal control strategies of a fractional-order monkeypox virus infection model, Physica Scripta, 98(9) (2023), 095256.
  • [18] A. Elsonbaty, A. Aldurayhim, W. Adel, and A. El-Mesady, Investigating the dynamics of a novel fractional-order monkeypox epidemic model with optimal control, Alexandria Engineering Journal, 73 (2023), 519–542.
  • [19] B. Liu, M. Altanji, R. Nawaz, S. Farid, S. Ullah, and S. Wondimagegnhu Teklu, Mathematical assessment of monkeypox disease with the impact of vaccination using a fractional epidemiological modeling approach, Scientific Reports, 13(1) (2023), 13550.
  • [20] J. Mermin, P. A. Clay, E. D. Pollock, J. M. Asher, N. Carnes, C. E. Copen, and K. P. Delaney, Modelling the impact of vaccination and sexual behaviour adaptations on mpox cases in the USA during the 2022 outbreak, Sexually Transmitted Infections, 100(2) (2024), 70–76.
  • [21] Nigeria Centre for Disease Control, Mpox Monkeypox outbreak situation report, https://ncdc.gov.ng/report/, (2023). [Online; Accessed on August 23, 2023].
  • [22] A. Omame, Q. Han, S. A. Iyaniwura, E. Adeniyi, N. L. Bragazzi, X. Wang, J. D. Kong, and W. A. Woldegerima, Understanding the impact of HIV on mpox transmission in an MSM population: a mathematical modeling study, Available at SSRN 4762707, (2024).
  • [23] O. J. Peter, A. Abidemi, M. M. Ojo, and T. A. Ayoola, Mathematical model and analysis of monkeypox with control strategies, The European Physical Journal Plus, 138(3) (2023), 242.
  • [24] O. J. Peter, S. Kumar, N. Kumari, F. A. Oguntolu, K. Oshinubi, and R. Musa, Transmission dynamics of Monkeypox virus: a mathematical modelling approach, Modeling Earth Systems and Environment, (2022), 1–12.
  • [25] O. J. Peter, C. E. Madubueze, F. A. Oguntolu, M. M. Ojo, and T. A. Ayoola, Modeling and optimal control of monkeypox with cost-effective strategies, Modeling Earth Systems and Environment, 9(2) (2023), 1989–2007.
  • [26] E. M. Tag-Eldin, F. Allehiany, M. A. Khan, M. H. DarAssi, and I. Ahmad, Mathematical modeling and backward bifurcation in monkeypox disease under real observed data, Results in Physics, 50 (2023), 106557.
  • [27] M. Rabiu, E. J. Dansu, O. A. Mogbojuri, I. O. Idisi, M. M. Yahaya, P. Chiwira, R. T. Abah, and A. A. Adeniji, Modeling the sexual transmission dynamics of mpox in the United States of America, The European Physical Journal Plus, 139(3) (2024), 1–20.
  • [28] P. Van den Driessche, Reproduction numbers of infectious disease models, Infectious Disease Modelling, 2(3) (2017), 288–303.
  • [29] World Health Organization, Mpox (monkeypox Newsroom), https://www.who.int/news-room/ questions-and-answers/item/monkeypox, (2023). [Online; Accessed on August 13, 2023].
  • [30] World Health Organization, Mpox (monkeypox Fact sheets), https://www.who.int/news-room/fact-sheets/ detail/monkeypox, (2023). [Online; Accessed on August 13, 2023].
  • [31] World Bank, Population, total - Nigeria, https://data.worldbank.org/indicator/SP.POP.TOTL?locations= NG, (2023). [Online; Accessed on August 18, 2023].
  • [32] World Health Organization, Health data overview for the Federal Republic of Nigeria, https://data.who.int/ countries/566, (2023). [Online; Accessed on August 18, 2023].
  • [33] World Health Organization, Africa Region, Emergency Preparedness and Response, https://www.afro.who. int/, (2023). [Online; Accessed on August 25, 2023].
  • [34] World Bank, Population, total - Congo, Dem. Rep., https://data.worldbank.org/indicator/SP.POP.TOTL? locations=CD, (2023). [Online; Accessed on August 18, 2023].
  • [35] World Health Organization, Health data overview for the Democratic Republic of the Congo, https://data.who. int/countries/180, (2023). [Online; Accessed on August 18, 2023].
  • [36] M. Xiridou, F. Miura, P. Adam, E. O. de Coul, J. de Wit, and J. Wallinga, The fading of the mpox outbreak among men who have sex with men: a mathematical modelling study, The Journal of Infectious Diseases, (2024), jiad414.
  • [37] S. Yang, X. Guo, Y. Zhao, Z. Zhao, T. Chen, H. Wei, Y. Wang, J. Rui, and W. Song, Possibility of mpox viral transmission and control from high-risk to the general population: a modeling study, BMC Infectious Diseases, 23(1) (2023), 119.
  • [38] N. Zhang, E. Addai, L. Zhang, M. Ngungu, E. Marinda, and A. JKK, Fractional modeling and numerical simulation for unfolding Marburg–monkeypox virus co-infection transmission, Fractals, 31(7) (2023), 2350086.
آمار
تعداد مشاهده مقاله: 729
تعداد دریافت فایل اصل مقاله: 694


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب