rachaelpung/covid_missed_infections

Pung, RORCID logo (2023). rachaelpung/covid_missed_infections. [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.7538046
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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

COVID-19, SARS-CoV-2, Coronavirus, Pandemic trajectory

Item Type Dataset
Capture method Simulation
Date 15 January 2023
Language(s) of written materials English
Creator(s) Pung, RORCID logo
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

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