CoMix - Age structured contact matrices for 9 key periods of the COVID-19 epidemic in England
, Jarvis, CI, Gimma, A, Wong, KL, van Zandvoort, K, Funk, S and Edmunds, WJ
(2021).
CoMix - Age structured contact matrices for 9 key periods of the COVID-19 epidemic in England.
[Dataset].
Zenodo.
http://doi.org/10.5281/zenodo.4677018
Contact matrices from 9 distinct periods of the UK COVID-19 epidemic: Lockdown 1 = 23rd March - 3rd June 2020; Lockdown 1 easing = 4th June - 29th July 2020; Reduced restrictions = 30th July - 3rd Sep 2020; Schools open = 4th Sept - 26th October 2020; Lockdown 2 = 5th November - 2nd December 2020; Lockdown 2 easing = 3rd December - 19th December 2020; Christmas = 20 December 2020 - 2nd January 2021; Lockdown 3 = 5th January - 8th March 2021; and Lockdown 3 with schools open = 8th March - 16th March 2021. The file: contact_matrices_9_periods.csv contains the mean contact matrices. The nine 'qs' files for the individual periods contain 1000 bootstrap samples of the contact matrix for the relevant period. each column is a different sample. The age-groups are not explicitly detailed, but follow the same order as in the contact_matrices_9_periods.csv file.
Keywords
UK COVID-19, COVID-19, Coronavirus, Contact matrix, SARS-CoV-2, Epidemic| Item Type | Dataset |
|---|---|
| Capture method | Aggregation |
| Date | 9 April 2021 |
| Geographical area covered (offline during plugin upgrade) |
North Latitude East Longitude South Latitude West Longitude 59.3985 1.50679 50.4832 -6.00786 |
| Language(s) of written materials | English |
| Creator(s) |
Munday, JD, Jarvis, CI, Gimma, A, Wong, KL, van Zandvoort, K, Funk, S and Edmunds, WJ
|
| LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology (-2023) |
| Research Centre | Centre for the Mathematical Modelling of Infectious Diseases |
| Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
| Funders |
Project Funder Grant Number Funder URI EpiPose - Epidemic intelligence to minimize 2019-nCoV’s public health, economic and social impact in Europe 101003688 http://dx.doi.org/10.13039/501100000780 Understanding the dynamics and drivers of the COVID-2019 epidemic using real-time outbreak analytics MC_PC_19065 UNSPECIFIED |
| Date Deposited | 20 Apr 2021 08:56 |
| Last Modified | 23 Aug 2021 10:51 |
| Publisher | Zenodo |
No files available. Please consult associated links.
