Yakob, L and Nightingale, E. 2020. lwyakob/COVIDsaturates. [Online]. Github. Available from: https://github.com/lwyakob/COVIDsaturates
Yakob, L and Nightingale, E. lwyakob/COVIDsaturates [Internet]. Github; 2020. Available from: https://github.com/lwyakob/COVIDsaturates
Yakob, L and Nightingale, E (2020). lwyakob/COVIDsaturates. [Data Collection]. Github. https://github.com/lwyakob/COVIDsaturates
Description
Contact rates between people within a population increase with human density, up until a saturating level. Using COVID-19 associated mortality data from England, we inferred the shape of this saturating contact-rate curve. We then included this saturating contact rate in a mathematical model of SARS-CoV-2 transmission, and compared projections with standard density-independent and density-dependent models. This item contains code to accompany "The importance of saturating density dependence for predicting SARS-CoV-2 resurgence" authored by Emily Nightingale, Oliver Brady & Laith Yakob.
Keywords
| Data capture method | Simulation |
|---|---|
| Date (Published in a 3rd party system) | 21 September 2020 |
| Language(s) of written materials | English |
| Data Creators | Yakob, L and Nightingale, E |
|---|---|
| LSHTM Faculty/Department | Faculty of Infectious and Tropical Diseases > Dept of Disease Control Faculty of Public Health and Policy > Dept of Global Health and Development |
| Research Centre | Antimicrobial Resistance Centre (AMR) Centre for Statistical Methodology Centre for the Mathematical Modelling of Infectious Diseases Malaria Centre |
| Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
| Date Deposited | 15 Apr 2021 10:08 |
|---|---|
| Last Modified | 08 Jul 2021 12:51 |
| Publisher | Github |
