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Transmission dynamics of COVID-19 pandemic with combined effects of relapse, reinfection and environmental contribution: A modeling analysis.
Musa, Salihu S; Yusuf, Abdullahi; Zhao, Shi; Abdullahi, Zainab U; Abu-Odah, Hammoda; Saad, Farouk Tijjani; Adamu, Lukman; He, Daihai.
  • Musa SS; Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.
  • Yusuf A; Department of Mathematics, Kano University of Science and Technology, Wudil, Nigeria.
  • Zhao S; Department of Computer Engineering, Biruni University, Istanbul, Turkey.
  • Abdullahi ZU; Department of Mathematics, Science Faculty, Federal University Dutse, Jigawa, Nigeria.
  • Abu-Odah H; JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China.
  • Saad FT; Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China.
  • Adamu L; Department of Biological Sciences, Federal University Dutsin-Ma, Katsina, Nigeria.
  • He D; School of Nursing, Hong Kong Polytechnic University, Hong Kong, China.
Results Phys ; 38: 105653, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-1867748
ABSTRACT
Reinfection and reactivation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have recently raised public health pressing concerns in the fight against the current pandemic globally. In this study, we propose a new dynamic model to study the transmission of the coronavirus disease 2019 (COVID-19) pandemic. The model incorporates possible relapse, reinfection and environmental contribution to assess the combined effects on the overall transmission dynamics of SARS-CoV-2. The model's local asymptotic stability is analyzed qualitatively. We derive the formula for the basic reproduction number ( R 0 ) and final size epidemic relation, which are vital epidemiological quantities that are used to reveal disease transmission status and guide control strategies. Furthermore, the model is validated using the COVID-19 reported situations in Saudi Arabia. Moreover, sensitivity analysis is examined by implementing a partial rank correlation coefficient technique to obtain the ultimate rank model parameters to control or mitigate the pandemic effectively. Finally, we employ a standard Euler technique for numerical simulations of the model to elucidate the influence of some crucial parameters on the overall transmission dynamics. Our results highlight that contact rate, hospitalization rate, and reactivation rate are the fundamental parameters that need particular emphasis for the prevention, mitigation and control.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Qualitative research Language: English Journal: Results Phys Year: 2022 Document Type: Article Affiliation country: J.rinp.2022.105653

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Qualitative research Language: English Journal: Results Phys Year: 2022 Document Type: Article Affiliation country: J.rinp.2022.105653