COVID-19 transmission dynamics and the impact of vaccination: modelling, analysis and simulations

被引:2
作者
Malinzi, Joseph [1 ,2 ]
Juma, Victor Ogesa [3 ]
Madubueze, Chinwendu Emilian [4 ,5 ]
Mwaonanji, John [6 ]
Nkem, Godwin Nwachukwu [7 ]
Mwakilama, Elias [8 ]
Mupedza, Tinashe Victor [9 ]
Chiteri, Vincent Nandwa [10 ]
Bakare, Emmanuel Afolabi [11 ,12 ]
Moyo, Isabel Linda-Zulu [1 ]
Campillo-Funollet, Eduard [13 ]
Nyabadza, Farai [14 ]
Madzvamuse, Anotida [14 ,15 ,16 ]
机构
[1] Univ Eswatini, Fac Sci & Engn, Dept Math, Private Bag 4, Kwaluseni, Eswatini
[2] Durban Univ Technol, Inst Syst Sci, ZA-4000 Durban, South Africa
[3] Univ Zaragoza, Inst Invest Ingn Aragon I3A, Multiscale Mech & Biol Engn M2BE, Zaragoza 50018, Spain
[4] Fed Univ Agr, Dept Math, Makurdi, Nigeria
[5] York Univ, Dept Math & Stat, Toronto, ON, Canada
[6] Malawi Univ Business & Appl Sci, Dept Math Sci, Blantyre, Malawi
[7] Univ Ibadan, Dept Math, Ibadan, Nigeria
[8] Jomo Kenyatta Univ Agr & Technol, Dept Pure & Appl Math, Nairobi, Kenya
[9] Univ Zimbabwe, Dept Math & Computat Sci, Box MP167 Mt Pleasant, Harare, Zimbabwe
[10] Univ Nairobi, Dept Math, Nairobi, Kenya
[11] Fed Univ Oye Ekiti, Int Ctr Appl Math Modelling & Data Analyt, Oye, Ekiti, Nigeria
[12] Fed Univ Oye Ekiti, Dept Math, Oye, Ekiti, Nigeria
[13] Univ Lancaster, Dept Math & Stat, Lancaster LA1 4YR, England
[14] Univ Johannesburg, Dept Math & Appl Math, Auckland Pk, ZA-2006 Johannesburg, South Africa
[15] Univ British Columbia, Math Dept, Room 121,Math Bldg,1984 Math Rd, Vancouver, BC V6T 1Z2, Canada
[16] Univ Sussex, Sch Math & Phys Sci, Dept Math, Brighton BN1 9QH, England
来源
ROYAL SOCIETY OPEN SCIENCE | 2023年 / 10卷 / 07期
基金
美国国家卫生研究院; 加拿大自然科学与工程研究理事会; 英国工程与自然科学研究理事会; 新加坡国家研究基金会;
关键词
COVID-19; vaccinations; mathematical modelling; parameter estimation; sensitivity analysis; bifurcation analysis; SENSITIVITY-ANALYSIS; MATHEMATICAL-MODEL;
D O I
10.1098/rsos.221656
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Despite the lifting of COVID-19 restrictions, the COVID-19 pandemic and its effects remain a global challenge including the sub-Saharan Africa (SSA) region. Knowledge of the COVID-19 dynamics and its potential trends amidst variations in COVID-19 vaccine coverage is therefore crucial for policy makers in the SSA region where vaccine uptake is generally lower than in high-income countries. Using a compartmental epidemiological model, this study aims to forecast the potential COVID-19 trends and determine how long a wave could be, taking into consideration the current vaccination rates. The model is calibrated using South African reported data for the first four waves of COVID-19, and the data for the fifth wave are used to test the validity of the model forecast. The model is qualitatively analysed by determining equilibria and their stability, calculating the basic reproduction number R0 and investigating the local and global sensitivity analysis with respect to R0. The impact of vaccination and control interventions are investigated via a series of numerical simulations. Based on the fitted data and simulations, we observed that massive vaccination would only be beneficial (deaths averting) if a highly effective vaccine is used, particularly in combination with non-pharmaceutical interventions. Furthermore, our forecasts demonstrate that increased vaccination coverage in SSA increases population immunity leading to low daily infection numbers in potential future waves. Our findings could be helpful in guiding policy makers and governments in designing vaccination strategies and the implementation of other COVID-19 mitigation strategies.
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页数:24
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