Probability of a large 2019-nCoV outbreak following introduction of cases
This analysis uses a model that incorporates randomness and individual-level variation in transmission (i.e. potential for 'superspreading') to calculate the probability that a given number of independently introduced cases in a new location will eventually lead to a large outbreak. (Source: Lloyd-Smith et al, Nature, 2005). There are two key values to explore: the reproduction number in the new location (i.e. average number of secondary cases generated by a typical infectious individual); and individual-level variation in transmission - do all cases generate similar numbers of secondary cases, or do most generate few and some lots? Infections with more individual-level variation (such as SARS) lead to more fragile initial transmission chains, and hence are overall less likely to spark a large outbreak following an introduced case (although they can lead to rapidly growing outbreaks if by chance transmission does take hold. The random-mixing option in the drop-down menu assumes transmission occurs at random with similar secondary cases from all individuals.
Keywords
Coronavirus, COVID-19, 2019-nCoVItem Type | Dataset |
---|---|
Capture method | Simulation |
Date | 31 January 2020 |
Language(s) of written materials | English |
Creator(s) |
Kucharski, AJ |
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 |
Date Deposited | 22 Apr 2020 15:48 |
Last Modified | 08 Jul 2021 12:52 |
Publisher | Github |
Explore Further
- Early dynamics of transmission and control of COVID-19: a mathematical modelling study (Paper)
- CMMID Interactive Application (Online Data Resource)
No files available. Please consult associated links.
- Early dynamics of transmission and control of COVID-19: a mathematical modelling study (Paper)
- CMMID Interactive Application (Online Data Resource)