Estimation of timing of infection from longitudinal SARS-CoV-2 viral load data: mathematical modelling study.

ABSTRACT:

Background

Multiple waves of the COVID-19 epidemic have hit most countries by the end of 2021. Most of those waves are caused by emergence and importation of new variants. To prevent importation of new variants, combination of border control and contact tracing is essential. However, the timing of infection inferred by interview is influenced by recall bias and hinders the contact tracing process.

Methods

We propose a novel approach to infer the timing of infection, by employing a within-host model to capture viral load dynamics after the onset of symptoms. We applied this approach to ascertain secondary transmission which can trigger outbreaks. As a demonstration, the 12 initial reported cases in Singapore, which were considered as imported because of their recent travel hi

SUBMITTER: Ejima K 

PROVIDER: S-EPMC9331019 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature