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 |
|---|---|
| Date (Published in a 3rd party system) | 5 May 2021 |
| Language(s) of written materials | English |
| Data Creators | Pung, R |
|---|---|
| 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 |
|---|---|
| Last Modified | 04 Oct 2021 09:06 |
| Publisher | Github |
