rachaelpung/covid_missed_infections
Pung, R
(2023).
rachaelpung/covid_missed_infections.
[Dataset].
Zenodo.
https://doi.org/10.5281/zenodo.7538046
(2023).
rachaelpung/covid_missed_infections.
[Dataset].
Zenodo.
https://doi.org/10.5281/zenodo.7538046
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.
Alternative Title
Relative role of border restrictions, case finding and contact tracing in controlling SARS-CoV-2 in the presence of undetected transmission
Keywords
COVID-19; SARS-CoV-2; Coronavirus; Pandemic trajectory| Item Type | Dataset |
|---|---|
| Resource Type |
Resource Type Resource Description Software R script |
| Capture method | Simulation |
| Date | 15 January 2023 |
| Language(s) of written materials | English |
| Creator(s) |
Pung, R
|
| 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 | 04 Oct 2021 09:05 |
| Last Modified | 04 Apr 2023 09:04 |
| Publisher | Zenodo |
Explore Further
- Relative role of border restrictions, case finding and contact tracing in controlling SARS-CoV-2 in the presence of undetected transmission.
- Relative role of border restrictions, case finding and contact tracing in controlling SARS-CoV-2 in the presence of undetected transmission: a mathematical modelling study.
No files available. Please consult associated links.
