Abstract
Superspreading phenomenon has been observed in many infectious diseases and contributes significantly to public health burden in many countries. Superspreading events have recently been reported in the transmission of the COVID-19 pandemic. The present study uses a set of nine ordinary differential equations to investigate the impact of superspreading on COVID-19 dynamics. The model developed in this study addresses the heterogeineity in infectiousness by taking into account two forms of transmission rate functions for superspreaders based on clinical (infectivity level) and social or environmental (contact level). The basic reproduction number has been derived and the contribution of each infectious compartment towards the generation of new COVID-19 cases is ascertained. Data fitting was performed and parameter values were estimated within plausible ranges. Numerical simulations performed suggest that control measures that decrease the effective contact radius and increase the transmission rate exponent will be greatly beneficial in the control of COVID-19 in the presence of superspreading phenomena.
| Original language | English |
|---|---|
| Pages (from-to) | 191-209 |
| Number of pages | 19 |
| Journal | International Journal of Mathematical Modelling and Numerical Optimisation |
| Volume | 12 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- COVID-19
- model analysis
- numerical simulations
- superspreaders
ASJC Scopus subject areas
- Numerical Analysis
- Modeling and Simulation
- Applied Mathematics
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