Pung, R. 2021. rachaelpung/covid_missed_infections. [Online]. Github. Available from: https://github.com/rachaelpung/covid_missed_infections
Pung, R. rachaelpung/covid_missed_infections [Internet]. Github; 2021. Available from: https://github.com/rachaelpung/covid_missed_infections
Pung, R (2021). rachaelpung/covid_missed_infections. [Data Collection]. Github. https://github.com/rachaelpung/covid_missed_infections
Alternative Title
Relative role of border restrictions, case finding and contact tracing in controlling SARS-CoV-2 in the presence of undetected transmission
Description
This repository contains code and aggregate data to reconstruct the COVID-19 pandemic trajectory in Singapore. For each time period of the pandemic, we simulated the transmissions through a branching process model to compute the expected incidence over time and model outputs were fitted against the daily incidence of linked and unlinked local COVID-19 cases. Model parameters were estimated using a Bayesian MCMC framework.
Keywords
Data capture method | Simulation |
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Date (Published in a 3rd party system) | 5 May 2021 |
Language(s) of written materials | English |
Data Creators | Pung, R |
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LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology |
Research Centre | Centre for the Mathematical Modelling of Infectious Diseases |
Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
Date Deposited | 04 Oct 2021 09:05 |
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Last Modified | 04 Oct 2021 09:06 |
Publisher | Github |