Geospatial model of COVID-19 spreading and vaccination with event Gillespie algorithm
Published inNonlinear dynamics, vol. 109, no. 1, p. 239-248
Publication date2022-07
First online date2022-01-22
Abstract
Keywords
- COVID-19
- Contact matrices
- Gillespie algorithm
- Population density
- Spatial epidemic modeling
Research group
Funding
- Swiss National Science Foundation - Coronavirus epidemic in Switzerland: integrating clinical, epidemiological, biological and behaviour with mathematical modelling [31CA30_196270]
- European Commission - EOSCsecretariat.eu [831644]
- Swiss National Science Foundation - Understanding the HIV epidemic in Malawi: integrating quantitative and qualitative data in a mathematical model [PP00P3_163878]
Citation (ISO format)
TEMEREV, Alexander et al. Geospatial model of COVID-19 spreading and vaccination with event Gillespie algorithm. In: Nonlinear dynamics, 2022, vol. 109, n° 1, p. 239–248. doi: 10.1007/s11071-021-07186-5
Main files (1)
Article (Published version)
Identifiers
- PID : unige:164607
- DOI : 10.1007/s11071-021-07186-5
- PMID : 35095197
- PMCID : PMC8783199
ISSN of the journal0924-090X