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Scale-free dynamics of COVID-19 in a Brazilian city.
- Source :
-
Applied mathematical modelling [Appl Math Model] 2023 Sep; Vol. 121, pp. 166-184. Date of Electronic Publication: 2023 Apr 21. - Publication Year :
- 2023
-
Abstract
- A common basis to address the dynamics of directly transmitted infectious diseases, such as COVID-19, are compartmental (or SIR) models. SIR models typically assume homogenous population mixing, a simplification that is convenient but unrealistic. Here we validate an existing model of a scale-free fractal infection process using high-resolution data on COVID-19 spread in São Caetano, Brazil. We find that transmission can be described by a network in which each infectious individual has a small number of susceptible contacts, of the order of 2-5. This model parameter correlated tightly with physical distancing measured by mobile phone data, such that in periods of greater distancing the model recovered a lower average number of contacts, and vice versa. We show that the SIR model is a special case of our scale-free fractal process model in which the parameter that reflects population structure is set at unity, indicating homogeneous mixing. Our more general framework better explained the dynamics of COVID-19 in São Caetano, used fewer parameters than a standard SIR model and accounted for geographically localized clusters of disease. Our model requires further validation in other locations and with other directly transmitted infectious agents.<br /> (© 2023 Published by Elsevier Inc.)
Details
- Language :
- English
- ISSN :
- 0307-904X
- Volume :
- 121
- Database :
- MEDLINE
- Journal :
- Applied mathematical modelling
- Publication Type :
- Academic Journal
- Accession number :
- 37151217
- Full Text :
- https://doi.org/10.1016/j.apm.2023.03.039