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Accompanying code for: Kucharski AJ, Russell TW et al. Early dynamics of transmission and control of COVID-19: a mathematical modelling study. Lancet Infectious Diseases, 2020

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adamkucharski/2020-ncov

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2020-ncov

Analysis of the 2019-nCoV outbreak during 2019/20. Note: this is working repository, so code and data are likely to change over time

Guide to files for stoch_model

This is a stochastic SEIR model implemented using Euler-Maruyama, with likelihood estimated using SMC by jointly fitting to cases in Wuhan and exported cases over time in countries with high connectivity to Wuhan.

Data loading and model run script is in scripts/main_model.r. Calls the following R files:

R/load_timeseries.r - Load and format timeseries

R/model_functions.r - Load process model and SMC

R/plotting_functions.r - Plotting functions

outputs_main.R - Run main model outputs

The code and data used for V1 of our pre-print on early transmission dynamics can be found in stoch_model_V1_paper, with same paths as above.

The code and data used for our final Lancet Infectious Diseases paper can be found in stoch_model_V2_paper, with same paths as above.

Reference

Kucharski AJ, Russell TW, Diamond C et al. Early dynamics of transmission and control of 2019-nCoV: a mathematical modelling study. Lancet Infectious Diseases, 2020

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Accompanying code for: Kucharski AJ, Russell TW et al. Early dynamics of transmission and control of COVID-19: a mathematical modelling study. Lancet Infectious Diseases, 2020

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