Age-structured SEIR model for COVID-19 outbreak in Wuhan, China
                
    
    Prem, K ; Liu, Y
; Liu, Y ; Russell, TW
; Russell, TW ; Kucharski, AJ
; Kucharski, AJ ; Eggo, RM
; Eggo, RM ; Davies, NG
; Davies, NG ; Jit, M
; Jit, M ; Klepac, P
; Klepac, P ; Flasche, S
; Flasche, S ; Clifford, S
; Clifford, S ; Pearson, CAB
; Pearson, CAB ; Munday, JD
; Munday, JD ; Abbott, S
; Abbott, S ; Gibbs, H
; Gibbs, H ; Rosello, A
; Rosello, A ; Quilty, BJ
; Quilty, BJ ; Jombart, T
; Jombart, T ; Sun, F
; Sun, F ; Diamond, C
; Diamond, C ; Gimma, A
; Gimma, A ; Van zandvoort, K
; Van zandvoort, K ; Funk, S
; Funk, S ; Jarvis, CI
; Jarvis, CI ; Edmunds, WJ
; Edmunds, WJ ; Bosse, NI
; Bosse, NI and Hellewell, J
 and Hellewell, J (2020).
Age-structured SEIR model for COVID-19 outbreak in Wuhan, China.
[Dataset].
Github.
      
                  			
           https://github.com/kieshaprem/covid19-agestructureSEIR-wuhan-social-distancing
  
  
(2020).
Age-structured SEIR model for COVID-19 outbreak in Wuhan, China.
[Dataset].
Github.
      
                  			
           https://github.com/kieshaprem/covid19-agestructureSEIR-wuhan-social-distancing
                   			
           
           
       
  
              
            
                  To assess the impact of a range of control measures that reduce social mixing on data from the COVID-19 outbreak in Wuhan, China. Using the best estimates for the epidemiological parameters, we simulate the effects of the control measures using an age-structured, location-specific transmission model. The model uses data on contact patterns. Specifically, we adjust these patterns according to how they change under certain control measures. We then simulate our transmission model under these different scenarios and assess the impact.
                
Keywords
SARS-CoV-2; COVID-19; Coronavirus; SARS-CoV2| Item Type | Dataset | 
|---|---|
| Resource Type | Resource Type Resource Description Software R script | 
| Capture method | Simulation | 
| Date | 18 March 2020 | 
| Language(s) of written materials | English | 
| Creator(s) | Prem, K | 
| LSHTM Faculty/Department | Faculty of Epidemiology and Population Health Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology (-2023) | 
| Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom | 
| Funders | Project Funder Grant Number Funder URI UNSPECIFIED UNSPECIFIED http://dx.doi.org/10.13039/501100000272 | 
| Date Deposited | 26 Mar 2020 20:49 | 
| Last Modified | 20 Aug 2021 14:40 | 
| Publisher | Github | 
Explore Further
- Prem, Kiesha
- Liu, Yang
- Russell, Timothy W.
- Kucharski, Adam
- Eggo, Rosalind M.
- Davies, Nicholas G.
- Jit, Mark
- Klepac, Petra
- Flasche, Stefan
- Clifford, Samuel
- Pearson, Carl A. B.
- Munday, James D.
- Abbott, Sam
- Gibbs, Hamish
- Rosello, Alicia
- Quilty, Billy
- Jombart, Thibaut
- Sun, Fiona
- Diamond, Charlie
- Gimma, Amy
- Van Zandvoort, Kevin
- Funk, Sebastian
- Jarvis, Christopher I.
- Edmunds, John
- Bosse, Nikos I
- Hellewell, Joel
- Bill and Melinda Gates Foundation
- National Institute for Health Research (NIHR)
- Wellcome Trust
- Health Data Research UK
- Github (Online Data Resource)
- Lancet Public Health (Paper)
No files available. Please consult associated links.
- Github (Online Data Resource)
- Lancet Public Health (Paper)
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