lwyakob/COVIDsaturates
Yakob, L
and Nightingale, E
(2020).
lwyakob/COVIDsaturates.
[Dataset].
Github.
https://github.com/lwyakob/COVIDsaturates
and Nightingale, E
(2020).
lwyakob/COVIDsaturates.
[Dataset].
Github.
https://github.com/lwyakob/COVIDsaturates
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
SARS-CoV-2; COVID-19; Coronavirus; Density dependence| Item Type | Dataset |
|---|---|
| Resource Type |
Resource Type Resource Description Software Jupyter notebook |
| Capture method | Simulation |
| Date | 21 September 2020 |
| Language(s) of written materials | English |
| Creator(s) |
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 |
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