Modeling nosocomial infection of COVID-19 transmission dynamics

被引:3
作者
Masandawa, Lemjini [2 ]
Mirau, Silas Steven [2 ]
Mbalawata, Isambi Sailon [1 ]
Paul, James Nicodemus [2 ]
Kreppel, Katharina [2 ]
Msamba, Oscar M. [3 ]
机构
[1] African Inst Math Sci, NEI Globla Secretariat, Rue KG590 ST, Kigali, Rwanda
[2] Nelson Mandela African Inst Sci & Technol, Sch Computat & Commun Sci & Engn, POB 447, Arusha, Tanzania
[3] Arusha Tech Coll, POB 296, Arusha, Tanzania
关键词
Proposed C0VID-19 model; Personal protective equipment; PRCC; Basic reproduction number; Hospital-acquired infection;
D O I
10.1016/j.rinp.2022.105503
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
COVID-19 epidemic has posed an unprecedented threat to global public health. The disease has alarmed the healthcare system with the harm of nosocomial infection. Nosocomial spread of COVID-19 has been discovered and reported globally in different healthcare facilities. Asymptomatic patients and super-spreaders are sough to be among of the source of these infections. Thus, this study contributes to the subject by formulating a SEIHR mathematical model to gain the insight into nosocomial infection for COVID-19 transmission dynamics. The role of personal protective equipment theta is studied in the proposed model. Benefiting the next generation matrix method, R-0 was computed. Routh-Hurwitz criterion and stable Metzler matrix theory revealed that COVID-19-free equilibrium point is locally and globally asymptotically stable whenever R-0 < 1. Lyapunov function depicted that the endemic equilibrium point is globally asymptotically stable when R-0 > 1. Further, the dynamics behavior of R-0 was explored when varying theta. In the absence of theta, the value of R-0 was 8.4584 which implies the expansion of the disease. When theta is introduced in the model, R0 was 0.4229, indicating the decrease of the disease in the community. Numerical solutions were simulated by using Runge-Kutta fourth-order method. Global sensitivity analysis is performed to present the most significant parameter. The numerical results illustrated mathematically that personal protective equipment can minimizes nosocomial infections of COVID-19.
引用
收藏
页数:10
相关论文
共 50 条
[41]   Mathematical analysis of COVID-19 and TB co-infection dynamics with optimal control [J].
Jain, Kshama ;
Bhattacharjee, Anuradha ;
Krishnamurhty, Srikumar .
MODELING EARTH SYSTEMS AND ENVIRONMENT, 2025, 11 (01)
[42]   Nosocomial or not? A combined epidemiological and genomic investigation to understand hospital-acquired COVID-19 infection on an elderly care ward [J].
Wenlock, R. D. ;
Tausan, M. ;
Garr, W. ;
Preston, R. ;
Arnold, A. ;
Hoban, J. ;
Webb, L. ;
Beckett, A. ;
Loveson, K. ;
Glaysher, S. ;
Elliott, S. ;
Malone, C. ;
Cogger, B. ;
Easton, L. ;
Robson, S. C. ;
Hassan-Ibrahim, M. O. ;
Sargent, C. .
INFECTION PREVENTION IN PRACTICE, 2021, 3 (03)
[43]   TRANSMISSION DYNAMICS OF COVID-19 WITH DIABETES IN INDIA: A COST-EFFECTIVE AND OPTIMAL CONTROL ANALYSIS [J].
Tripathi, Jai Prakash ;
Kumawat, Nitesh ;
Tanwar, Komal ;
Palla, Dhanumjaya ;
Martcheva, Maia .
JOURNAL OF BIOLOGICAL SYSTEMS, 2024, 32 (02) :643-681
[44]   A mathematical model of COVID-19 using fractional derivative: outbreak in India with dynamics of transmission and control [J].
Amjad Salim Shaikh ;
Iqbal Najiroddin Shaikh ;
Kottakkaran Sooppy Nisar .
Advances in Difference Equations, 2020
[45]   A mathematical model of COVID-19 using fractional derivative: outbreak in India with dynamics of transmission and control [J].
Shaikh, Amjad Salim ;
Shaikh, Iqbal Najiroddin ;
Nisar, Kottakkaran Sooppy .
ADVANCES IN DIFFERENCE EQUATIONS, 2020, 2020 (01)
[46]   Risk Assessment of Importation and Local Transmission of COVID-19 in South Korea: Statistical Modeling Approach [J].
Lee, Hyojung ;
Kim, Yeahwon ;
Kim, Eunsu ;
Lee, Sunmi .
JMIR PUBLIC HEALTH AND SURVEILLANCE, 2021, 7 (06)
[47]   Modeling the transmission of second-wave COVID-19 caused by imported cases: A case study [J].
Guo, Youming ;
Li, Tingting .
MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2022, 45 (13) :8096-8114
[48]   Global dynamics of a space-age structured covid-19 model coupling within-host infection and between-host transmission [J].
Wu, Peng ;
Feng, Zhaosheng .
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2024, 131
[49]   Impact of Infective Immigrants on COVID-19 Dynamics [J].
Tchoumi, Stephane Yanick ;
Rwezaura, Herieth ;
Diagne, Mamadou Lamine ;
Gonzalez-Parra, Gilberto ;
Tchuenche, Jean .
MATHEMATICAL AND COMPUTATIONAL APPLICATIONS, 2022, 27 (01)
[50]   Modeling and forecasting the COVID-19 pandemic in India [J].
Sarkar, Kankan ;
Khajanchi, Subhas ;
Nieto, Juan J. .
CHAOS SOLITONS & FRACTALS, 2020, 139 (139)